diff --git a/Afni_proc_through_nipype/_subject_id_001/afni_proc/_0x40130b82c0418a5dc016fe0334a2c8f6_unfinished.json b/Afni_proc_through_nipype/_subject_id_001/afni_proc/_0x40130b82c0418a5dc016fe0334a2c8f6_unfinished.json new file mode 100644 index 00000000..d8d42f93 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_001/afni_proc/_0x40130b82c0418a5dc016fe0334a2c8f6_unfinished.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "001" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_001/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_001/afni_proc/_inputs.pklz new file mode 100644 index 00000000..42e4c420 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_001/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_001/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_001/afni_proc/_node.pklz new file mode 100644 index 00000000..4899f6e6 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_001/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_001/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_001/afni_proc/_report/report.rst new file mode 100644 index 00000000..a49e065e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_001/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a070 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 001 + diff --git a/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_0x4b88c28a232fe352aaa3991b95b3cbfc.json b/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_0x4b88c28a232fe352aaa3991b95b3cbfc.json new file mode 100644 index 00000000..bbc63a18 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_0x4b88c28a232fe352aaa3991b95b3cbfc.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "001" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..22262718 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_node.pklz new file mode 100644 index 00000000..36e77078 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_report/report.rst new file mode 100644 index 00000000..8825c171 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a070 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 001 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 001 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012201 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_001/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_001/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_001/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..fffed5ad Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_001/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_002/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_002/afni_proc/_inputs.pklz new file mode 100644 index 00000000..4c40389a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_002/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_002/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_002/afni_proc/_node.pklz new file mode 100644 index 00000000..7bb6f902 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_002/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_002/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_002/afni_proc/_report/report.rst new file mode 100644 index 00000000..d58070f0 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_002/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a005 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 002 + diff --git a/Afni_proc_through_nipype/_subject_id_002/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_002/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..6b38ac0c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_002/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_0x828dba5362000ae4a98c5e5894950bc2.json b/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_0x828dba5362000ae4a98c5e5894950bc2.json new file mode 100644 index 00000000..f75c36a1 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_0x828dba5362000ae4a98c5e5894950bc2.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "002" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..7f66aa46 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_node.pklz new file mode 100644 index 00000000..fb4ce447 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_report/report.rst new file mode 100644 index 00000000..7047fcb1 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a005 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 002 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 002 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.013305 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_002/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_002/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_002/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..fead5cfc Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_002/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_003/afni_proc/_0x1672a71e029a1fae37c7d82d60d10354.json b/Afni_proc_through_nipype/_subject_id_003/afni_proc/_0x1672a71e029a1fae37c7d82d60d10354.json new file mode 100644 index 00000000..af1bd2ce --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_003/afni_proc/_0x1672a71e029a1fae37c7d82d60d10354.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "003" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_003/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_003/afni_proc/_inputs.pklz new file mode 100644 index 00000000..735b6b7f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_003/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_003/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_003/afni_proc/_node.pklz new file mode 100644 index 00000000..a4addf7e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_003/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_003/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_003/afni_proc/_report/report.rst new file mode 100644 index 00000000..a25b8855 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_003/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a023 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 003 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 003 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.073517 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_003/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_003/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_003/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..3da72079 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_003/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_0xf39e16cd9b4e465ab9a6df01d1bca5e0.json b/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_0xf39e16cd9b4e465ab9a6df01d1bca5e0.json new file mode 100644 index 00000000..375955b7 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_0xf39e16cd9b4e465ab9a6df01d1bca5e0.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "003" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..17739e4d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_node.pklz new file mode 100644 index 00000000..f4b91392 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_report/report.rst new file mode 100644 index 00000000..70ffa24d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a023 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 003 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 003 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012411 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_003/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_003/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_003/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..bd549147 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_003/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_004/afni_proc/_0x7bd12589dcfbb82daba15bb9e5b941b8.json b/Afni_proc_through_nipype/_subject_id_004/afni_proc/_0x7bd12589dcfbb82daba15bb9e5b941b8.json new file mode 100644 index 00000000..a1728169 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_004/afni_proc/_0x7bd12589dcfbb82daba15bb9e5b941b8.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "004" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_004/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_004/afni_proc/_inputs.pklz new file mode 100644 index 00000000..584aec8b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_004/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_004/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_004/afni_proc/_node.pklz new file mode 100644 index 00000000..c218319d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_004/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_004/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_004/afni_proc/_report/report.rst new file mode 100644 index 00000000..85eb56c0 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_004/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a004 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 004 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 004 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072937 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_004/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_004/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_004/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..7a1328bc Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_004/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_0x332b1c6e5d406505a41b9862da82d3af.json b/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_0x332b1c6e5d406505a41b9862da82d3af.json new file mode 100644 index 00000000..2c2a4c80 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_0x332b1c6e5d406505a41b9862da82d3af.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "004" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..61a0f010 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_node.pklz new file mode 100644 index 00000000..cd4c22d0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_report/report.rst new file mode 100644 index 00000000..87f3d3d5 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a004 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 004 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 004 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012438 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_004/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_004/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_004/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..f5501d76 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_004/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_005/afni_proc/_0x66adc730aec8306bd719310c7f023b50.json b/Afni_proc_through_nipype/_subject_id_005/afni_proc/_0x66adc730aec8306bd719310c7f023b50.json new file mode 100644 index 00000000..badef56e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_005/afni_proc/_0x66adc730aec8306bd719310c7f023b50.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "005" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_005/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_005/afni_proc/_inputs.pklz new file mode 100644 index 00000000..7ad6f5ec Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_005/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_005/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_005/afni_proc/_node.pklz new file mode 100644 index 00000000..4217fa62 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_005/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_005/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_005/afni_proc/_report/report.rst new file mode 100644 index 00000000..5f94458c --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_005/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a030 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 005 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 005 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.074299 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_005/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_005/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_005/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..09cfeb60 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_005/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_0x53e9f2ab37b004ea8655a036430b95db.json b/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_0x53e9f2ab37b004ea8655a036430b95db.json new file mode 100644 index 00000000..d4685f49 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_0x53e9f2ab37b004ea8655a036430b95db.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "005" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..5c388f31 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_node.pklz new file mode 100644 index 00000000..9999581a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_report/report.rst new file mode 100644 index 00000000..5391108f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a030 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 005 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 005 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012852 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_005/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_005/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_005/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..94147f7d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_005/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_0x21ebbfe5fc586de50f78d96b027cb04e.json b/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_0x21ebbfe5fc586de50f78d96b027cb04e.json new file mode 100644 index 00000000..bd2febf7 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_0x21ebbfe5fc586de50f78d96b027cb04e.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "006" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..ef9e5318 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_node.pklz new file mode 100644 index 00000000..d2e2869b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_report/report.rst new file mode 100644 index 00000000..97dda78f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a100 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 006 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 006 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.053228 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_006/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_006/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_006/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..a474be54 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_006/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_008/afni_proc/_0x082381b5999def21113ab7bd5970f444.json b/Afni_proc_through_nipype/_subject_id_008/afni_proc/_0x082381b5999def21113ab7bd5970f444.json new file mode 100644 index 00000000..43d9dfbe --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_008/afni_proc/_0x082381b5999def21113ab7bd5970f444.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "008" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_008/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_008/afni_proc/_inputs.pklz new file mode 100644 index 00000000..ad788f88 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_008/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_008/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_008/afni_proc/_node.pklz new file mode 100644 index 00000000..09eb0869 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_008/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_008/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_008/afni_proc/_report/report.rst new file mode 100644 index 00000000..371a4495 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_008/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a014 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 008 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 008 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.073152 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_008/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_008/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_008/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..d0d87021 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_008/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_0x2e8468cb3d727bd5c1802195995c0551.json b/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_0x2e8468cb3d727bd5c1802195995c0551.json new file mode 100644 index 00000000..8f95fdf6 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_0x2e8468cb3d727bd5c1802195995c0551.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "008" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..a4c82700 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_node.pklz new file mode 100644 index 00000000..69d42001 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_report/report.rst new file mode 100644 index 00000000..283ad610 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a014 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 008 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 008 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012371 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_008/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_008/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_008/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..59eb1d6d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_008/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_0xcfdc4c461ca3e89691c0a1b184ef4a41.json b/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_0xcfdc4c461ca3e89691c0a1b184ef4a41.json new file mode 100644 index 00000000..2adaf507 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_0xcfdc4c461ca3e89691c0a1b184ef4a41.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "009" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..5c16e0b2 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_node.pklz new file mode 100644 index 00000000..63af2468 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_report/report.rst new file mode 100644 index 00000000..9b848d97 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a081 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 009 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 009 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012112 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_009/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_009/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_009/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..3ab23453 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_009/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_010/afni_proc/_0xdc77add13a0e2b01bd236484f756ff9f.json b/Afni_proc_through_nipype/_subject_id_010/afni_proc/_0xdc77add13a0e2b01bd236484f756ff9f.json new file mode 100644 index 00000000..8ad91cbf --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_010/afni_proc/_0xdc77add13a0e2b01bd236484f756ff9f.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "010" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_010/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_010/afni_proc/_inputs.pklz new file mode 100644 index 00000000..3ba64e6e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_010/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_010/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_010/afni_proc/_node.pklz new file mode 100644 index 00000000..15045659 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_010/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_010/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_010/afni_proc/_report/report.rst new file mode 100644 index 00000000..02dc001b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_010/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a024 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 010 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 010 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.071658 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_010/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_010/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_010/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..3c19e219 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_010/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_0xc7bcfd952bdeda6f1ac3267d3fe40efe.json b/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_0xc7bcfd952bdeda6f1ac3267d3fe40efe.json new file mode 100644 index 00000000..222a48cb --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_0xc7bcfd952bdeda6f1ac3267d3fe40efe.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "010" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..b4db3a46 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_node.pklz new file mode 100644 index 00000000..754afdb3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_report/report.rst new file mode 100644 index 00000000..83ecefcb --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a024 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 010 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 010 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012319 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_010/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_010/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_010/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..f6653753 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_010/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_011/afni_proc/_0xcb98c1c3f8ba2766789a33a20180999b.json b/Afni_proc_through_nipype/_subject_id_011/afni_proc/_0xcb98c1c3f8ba2766789a33a20180999b.json new file mode 100644 index 00000000..2cf70a88 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_011/afni_proc/_0xcb98c1c3f8ba2766789a33a20180999b.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "011" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_011/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_011/afni_proc/_inputs.pklz new file mode 100644 index 00000000..f9585387 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_011/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_011/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_011/afni_proc/_node.pklz new file mode 100644 index 00000000..815083f3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_011/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_011/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_011/afni_proc/_report/report.rst new file mode 100644 index 00000000..f0897c4e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_011/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a016 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 011 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 011 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.07176 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_011/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_011/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_011/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..55941305 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_011/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_0x562dae15b2074b2c0630186f6a706e0a.json b/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_0x562dae15b2074b2c0630186f6a706e0a.json new file mode 100644 index 00000000..2c07b8ca --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_0x562dae15b2074b2c0630186f6a706e0a.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "011" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..a1cdbb06 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_node.pklz new file mode 100644 index 00000000..d2944a5e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_report/report.rst new file mode 100644 index 00000000..24532a78 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a016 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 011 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 011 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012644 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_011/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_011/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_011/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..2b9e14f7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_011/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_013/afni_proc/_0x78ea16f74f40a91d4904afe87bb2cb05.json b/Afni_proc_through_nipype/_subject_id_013/afni_proc/_0x78ea16f74f40a91d4904afe87bb2cb05.json new file mode 100644 index 00000000..29668348 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_013/afni_proc/_0x78ea16f74f40a91d4904afe87bb2cb05.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "013" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_013/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_013/afni_proc/_inputs.pklz new file mode 100644 index 00000000..aadddd0a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_013/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_013/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_013/afni_proc/_node.pklz new file mode 100644 index 00000000..1b2c3c56 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_013/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_013/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_013/afni_proc/_report/report.rst new file mode 100644 index 00000000..a2fc2602 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_013/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a001 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 013 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 013 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.075128 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_013/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_013/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_013/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..4adf7c0f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_013/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_0xdef586efabfbe19760f7ee91bc0fdaea.json b/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_0xdef586efabfbe19760f7ee91bc0fdaea.json new file mode 100644 index 00000000..386f27d1 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_0xdef586efabfbe19760f7ee91bc0fdaea.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "013" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..7e9f6982 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_node.pklz new file mode 100644 index 00000000..d7c5e071 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_report/report.rst new file mode 100644 index 00000000..575005ec --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a001 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 013 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 013 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.013223 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_013/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_013/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_013/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..d9bb04a7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_013/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_0x803ed4427ac75dd2491e4cb41b84f2c2.json b/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_0x803ed4427ac75dd2491e4cb41b84f2c2.json new file mode 100644 index 00000000..0d249d33 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_0x803ed4427ac75dd2491e4cb41b84f2c2.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "014" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..75bd9256 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_node.pklz new file mode 100644 index 00000000..861c33a3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_report/report.rst new file mode 100644 index 00000000..daf40dd1 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a102 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 014 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 014 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012347 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_014/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_014/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_014/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..0f4b3926 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_014/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_0xe09c3b6f1c6fa35a9899bf0bfc04377e.json b/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_0xe09c3b6f1c6fa35a9899bf0bfc04377e.json new file mode 100644 index 00000000..bb9ca7e6 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_0xe09c3b6f1c6fa35a9899bf0bfc04377e.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "015" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..e79b582b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_node.pklz new file mode 100644 index 00000000..5dff36b2 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_report/report.rst new file mode 100644 index 00000000..a9d43847 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a074 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 015 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 015 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012287 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_015/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_015/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_015/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..f5b30d9e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_015/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_016/afni_proc/_0xf78a12fdff76772b70f5f757c88ec718.json b/Afni_proc_through_nipype/_subject_id_016/afni_proc/_0xf78a12fdff76772b70f5f757c88ec718.json new file mode 100644 index 00000000..67b63ec7 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_016/afni_proc/_0xf78a12fdff76772b70f5f757c88ec718.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "016" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_016/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_016/afni_proc/_inputs.pklz new file mode 100644 index 00000000..0d062df2 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_016/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_016/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_016/afni_proc/_node.pklz new file mode 100644 index 00000000..260d0bc0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_016/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_016/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_016/afni_proc/_report/report.rst new file mode 100644 index 00000000..c1e7d76e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_016/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a015 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 016 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 016 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072374 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_016/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_016/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_016/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..fdef552d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_016/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_0x4506aaa53352c49a81e65aa0d9ecb066.json b/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_0x4506aaa53352c49a81e65aa0d9ecb066.json new file mode 100644 index 00000000..f212a5fd --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_0x4506aaa53352c49a81e65aa0d9ecb066.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "016" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..aec6e5dc Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_node.pklz new file mode 100644 index 00000000..a6cdcab8 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_report/report.rst new file mode 100644 index 00000000..bf9e11d8 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a015 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 016 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 016 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.01247 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_016/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_016/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_016/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..61af3d9a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_016/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_017/afni_proc/_0x75135d983f2d910c596b1534afaa6e07.json b/Afni_proc_through_nipype/_subject_id_017/afni_proc/_0x75135d983f2d910c596b1534afaa6e07.json new file mode 100644 index 00000000..4c0f456d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_017/afni_proc/_0x75135d983f2d910c596b1534afaa6e07.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "017" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_017/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_017/afni_proc/_inputs.pklz new file mode 100644 index 00000000..39e13dc0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_017/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_017/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_017/afni_proc/_node.pklz new file mode 100644 index 00000000..8a94c8f8 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_017/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_017/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_017/afni_proc/_report/report.rst new file mode 100644 index 00000000..2ba3b7fd --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_017/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a056 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 017 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 017 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.074692 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_017/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_017/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_017/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..b276705d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_017/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_0xe07660d4ef5ef0a4815e084218fc7a84.json b/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_0xe07660d4ef5ef0a4815e084218fc7a84.json new file mode 100644 index 00000000..84a15384 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_0xe07660d4ef5ef0a4815e084218fc7a84.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "017" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..ba67ebb1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_node.pklz new file mode 100644 index 00000000..139fb843 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_report/report.rst new file mode 100644 index 00000000..9c0926b5 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a056 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 017 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 017 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012476 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_017/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_017/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_017/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..46434112 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_017/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_018/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_018/afni_proc/_inputs.pklz new file mode 100644 index 00000000..5d486a60 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_018/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_018/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_018/afni_proc/_node.pklz new file mode 100644 index 00000000..a0b7ab71 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_018/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_018/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_018/afni_proc/_report/report.rst new file mode 100644 index 00000000..3ff187a8 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_018/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a027 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 018 + diff --git a/Afni_proc_through_nipype/_subject_id_018/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_018/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..ca9c349e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_018/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_0x96527a62190622c3c36f1d18057ebd4a.json b/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_0x96527a62190622c3c36f1d18057ebd4a.json new file mode 100644 index 00000000..45646bc2 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_0x96527a62190622c3c36f1d18057ebd4a.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "018" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..a94d2486 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_node.pklz new file mode 100644 index 00000000..d3f9b117 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_report/report.rst new file mode 100644 index 00000000..59ff0d36 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a027 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 018 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 018 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012447 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_018/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_018/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_018/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..e5a5ff00 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_018/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_019/afni_proc/_0x3ed5fc939177982773f4a3de7aade6e2.json b/Afni_proc_through_nipype/_subject_id_019/afni_proc/_0x3ed5fc939177982773f4a3de7aade6e2.json new file mode 100644 index 00000000..af77e2a0 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_019/afni_proc/_0x3ed5fc939177982773f4a3de7aade6e2.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "019" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_019/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_019/afni_proc/_inputs.pklz new file mode 100644 index 00000000..3277261a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_019/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_019/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_019/afni_proc/_node.pklz new file mode 100644 index 00000000..8c1a3e88 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_019/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_019/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_019/afni_proc/_report/report.rst new file mode 100644 index 00000000..e766714d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_019/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a059 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 019 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 019 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072389 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_019/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_019/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_019/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..597ef697 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_019/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_0xefa4ecc73cd1207b7a19ccf8c641bc92.json b/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_0xefa4ecc73cd1207b7a19ccf8c641bc92.json new file mode 100644 index 00000000..3b381254 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_0xefa4ecc73cd1207b7a19ccf8c641bc92.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "019" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..298bb5d5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_node.pklz new file mode 100644 index 00000000..1b8fddd3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_report/report.rst new file mode 100644 index 00000000..6e2e346b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a059 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 019 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 019 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012463 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_019/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_019/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_019/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..da92dbdd Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_019/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_020/afni_proc/_0xf15640574a5fa3ee862867dd48258cc4.json b/Afni_proc_through_nipype/_subject_id_020/afni_proc/_0xf15640574a5fa3ee862867dd48258cc4.json new file mode 100644 index 00000000..b1796105 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_020/afni_proc/_0xf15640574a5fa3ee862867dd48258cc4.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "020" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_020/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_020/afni_proc/_inputs.pklz new file mode 100644 index 00000000..01816ed5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_020/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_020/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_020/afni_proc/_node.pklz new file mode 100644 index 00000000..e9a4db4b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_020/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_020/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_020/afni_proc/_report/report.rst new file mode 100644 index 00000000..97469604 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_020/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a046 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 020 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 020 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.073318 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_020/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_020/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_020/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..57e57e41 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_020/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_0x87f22be45611d46a5e5253005a5c607a.json b/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_0x87f22be45611d46a5e5253005a5c607a.json new file mode 100644 index 00000000..c02a0aba --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_0x87f22be45611d46a5e5253005a5c607a.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "020" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..f18ba2e8 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_node.pklz new file mode 100644 index 00000000..29b8f1ab Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_report/report.rst new file mode 100644 index 00000000..0a8c5e69 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a046 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 020 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 020 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012684 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_020/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_020/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_020/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..2b03155f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_020/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_021/afni_proc/_0x842d0ffe2f7891e4fcd9c15e70ad76dd.json b/Afni_proc_through_nipype/_subject_id_021/afni_proc/_0x842d0ffe2f7891e4fcd9c15e70ad76dd.json new file mode 100644 index 00000000..b87bc4ce --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_021/afni_proc/_0x842d0ffe2f7891e4fcd9c15e70ad76dd.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "021" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_021/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_021/afni_proc/_inputs.pklz new file mode 100644 index 00000000..e35a3981 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_021/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_021/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_021/afni_proc/_node.pklz new file mode 100644 index 00000000..33c2bc4c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_021/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_021/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_021/afni_proc/_report/report.rst new file mode 100644 index 00000000..5c660344 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_021/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a002 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 021 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 021 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072532 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_021/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_021/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_021/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..5ba11803 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_021/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_0x2035f23ddf2da6815786e483128949d6.json b/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_0x2035f23ddf2da6815786e483128949d6.json new file mode 100644 index 00000000..6a0652c4 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_0x2035f23ddf2da6815786e483128949d6.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "021" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..b7cf5ca7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_node.pklz new file mode 100644 index 00000000..91ff342e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_report/report.rst new file mode 100644 index 00000000..61923d55 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a002 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 021 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 021 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.013108 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_021/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_021/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_021/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..348e3718 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_021/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_022/afni_proc/_0x034759bf09ede3f732a354f3b1727e10.json b/Afni_proc_through_nipype/_subject_id_022/afni_proc/_0x034759bf09ede3f732a354f3b1727e10.json new file mode 100644 index 00000000..c1937c61 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_022/afni_proc/_0x034759bf09ede3f732a354f3b1727e10.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "022" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_022/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_022/afni_proc/_inputs.pklz new file mode 100644 index 00000000..900d57f7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_022/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_022/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_022/afni_proc/_node.pklz new file mode 100644 index 00000000..1f5ca9e0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_022/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_022/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_022/afni_proc/_report/report.rst new file mode 100644 index 00000000..f30725e6 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_022/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a060 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 022 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 022 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072042 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_022/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_022/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_022/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..5737acdf Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_022/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_0x27d39a75b3df3dee233986845c0d00be.json b/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_0x27d39a75b3df3dee233986845c0d00be.json new file mode 100644 index 00000000..54aac9f4 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_0x27d39a75b3df3dee233986845c0d00be.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "022" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..ad53b2a4 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_node.pklz new file mode 100644 index 00000000..f8855640 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_report/report.rst new file mode 100644 index 00000000..a4174f7f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a060 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 022 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 022 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012485 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_022/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_022/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_022/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..1e5d284b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_022/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_024/afni_proc/_0xae2900a421e5ae12940c8a7d83be362e.json b/Afni_proc_through_nipype/_subject_id_024/afni_proc/_0xae2900a421e5ae12940c8a7d83be362e.json new file mode 100644 index 00000000..778bec82 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_024/afni_proc/_0xae2900a421e5ae12940c8a7d83be362e.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "024" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_024/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_024/afni_proc/_inputs.pklz new file mode 100644 index 00000000..cdb865d9 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_024/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_024/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_024/afni_proc/_node.pklz new file mode 100644 index 00000000..2f05005e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_024/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_024/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_024/afni_proc/_report/report.rst new file mode 100644 index 00000000..22cb8608 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_024/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a061 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 024 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 024 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072252 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_024/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_024/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_024/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..24a4cd97 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_024/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_0x79dfe99ab4a5e6f1d1e008e0b6056d0b.json b/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_0x79dfe99ab4a5e6f1d1e008e0b6056d0b.json new file mode 100644 index 00000000..1ec53d36 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_0x79dfe99ab4a5e6f1d1e008e0b6056d0b.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "024" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..a68468e1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_node.pklz new file mode 100644 index 00000000..5ca28b99 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_report/report.rst new file mode 100644 index 00000000..c24014c0 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a061 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 024 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 024 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012228 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_024/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_024/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_024/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..bb543512 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_024/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_0x9e31053bcf1e12b25fec06cca8b3f6ca.json b/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_0x9e31053bcf1e12b25fec06cca8b3f6ca.json new file mode 100644 index 00000000..8e544add --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_0x9e31053bcf1e12b25fec06cca8b3f6ca.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "025" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..b825fb76 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_node.pklz new file mode 100644 index 00000000..44382b04 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_report/report.rst new file mode 100644 index 00000000..7cd16449 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a079 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 025 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 025 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012355 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_025/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_025/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_025/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..66c33667 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_025/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_026/afni_proc/_0x0f44349e272f010e5b6386c8c9482953.json b/Afni_proc_through_nipype/_subject_id_026/afni_proc/_0x0f44349e272f010e5b6386c8c9482953.json new file mode 100644 index 00000000..a81ec9e1 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_026/afni_proc/_0x0f44349e272f010e5b6386c8c9482953.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "026" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_026/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_026/afni_proc/_inputs.pklz new file mode 100644 index 00000000..a9a8b7ff Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_026/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_026/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_026/afni_proc/_node.pklz new file mode 100644 index 00000000..630998b4 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_026/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_026/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_026/afni_proc/_report/report.rst new file mode 100644 index 00000000..be52b85e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_026/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a028 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 026 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 026 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.073277 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_026/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_026/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_026/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..3071db18 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_026/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_0xb821996742c1404f35791ed54fd21605.json b/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_0xb821996742c1404f35791ed54fd21605.json new file mode 100644 index 00000000..af735340 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_0xb821996742c1404f35791ed54fd21605.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "026" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..ec651c02 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_node.pklz new file mode 100644 index 00000000..5c8e490c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_report/report.rst new file mode 100644 index 00000000..b1f18c81 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a028 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 026 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 026 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012667 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_026/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_026/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_026/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..f707742a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_026/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_0x8535316d7b3edd0392f612e06a6f297b.json b/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_0x8535316d7b3edd0392f612e06a6f297b.json new file mode 100644 index 00000000..60443c3f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_0x8535316d7b3edd0392f612e06a6f297b.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "027" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..df0a3f6c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_node.pklz new file mode 100644 index 00000000..f2ef39c6 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_report/report.rst new file mode 100644 index 00000000..1622ed0b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a084 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 027 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 027 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012305 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_027/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_027/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_027/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..50a509ee Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_027/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_029/afni_proc/_0xe48364c65e06397ae3b8a04b1740225f.json b/Afni_proc_through_nipype/_subject_id_029/afni_proc/_0xe48364c65e06397ae3b8a04b1740225f.json new file mode 100644 index 00000000..df792181 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_029/afni_proc/_0xe48364c65e06397ae3b8a04b1740225f.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "029" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_029/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_029/afni_proc/_inputs.pklz new file mode 100644 index 00000000..86746a87 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_029/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_029/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_029/afni_proc/_node.pklz new file mode 100644 index 00000000..fd722edc Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_029/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_029/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_029/afni_proc/_report/report.rst new file mode 100644 index 00000000..a7aa7a5e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_029/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a010 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 029 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 029 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.073317 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_029/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_029/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_029/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..c0ae14b3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_029/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_0xcdd8a1e9a8f4f233f0947d5ed7419b67.json b/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_0xcdd8a1e9a8f4f233f0947d5ed7419b67.json new file mode 100644 index 00000000..697ce466 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_0xcdd8a1e9a8f4f233f0947d5ed7419b67.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "029" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..69e9373c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_node.pklz new file mode 100644 index 00000000..83a93893 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_report/report.rst new file mode 100644 index 00000000..13fed95b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a010 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 029 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 029 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012369 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_029/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_029/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_029/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..96f19592 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_029/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_030/afni_proc/_0x946474cb872f3497e0a44b107f0aeecf.json b/Afni_proc_through_nipype/_subject_id_030/afni_proc/_0x946474cb872f3497e0a44b107f0aeecf.json new file mode 100644 index 00000000..eed9e673 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_030/afni_proc/_0x946474cb872f3497e0a44b107f0aeecf.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "030" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_030/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_030/afni_proc/_inputs.pklz new file mode 100644 index 00000000..dd23f2e4 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_030/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_030/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_030/afni_proc/_node.pklz new file mode 100644 index 00000000..646f229b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_030/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_030/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_030/afni_proc/_report/report.rst new file mode 100644 index 00000000..cd137b4c --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_030/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a068 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 030 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 030 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.07302 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_030/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_030/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_030/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..7e103cbe Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_030/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_0x8f5cb2646fc2fa8424e53b22f26bb048.json b/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_0x8f5cb2646fc2fa8424e53b22f26bb048.json new file mode 100644 index 00000000..7d73c797 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_0x8f5cb2646fc2fa8424e53b22f26bb048.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "030" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..d64b84aa Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_node.pklz new file mode 100644 index 00000000..5bcf7fe0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_report/report.rst new file mode 100644 index 00000000..03b13f27 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a068 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 030 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 030 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012212 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_030/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_030/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_030/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..ffc6f2b1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_030/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_0xe5d7c01301c9bbcd5164eceded2c27f3.json b/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_0xe5d7c01301c9bbcd5164eceded2c27f3.json new file mode 100644 index 00000000..6778b0b4 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_0xe5d7c01301c9bbcd5164eceded2c27f3.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "032" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..be77c3a2 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_node.pklz new file mode 100644 index 00000000..1b269e4b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_report/report.rst new file mode 100644 index 00000000..24de76cf --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a072 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 032 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 032 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012368 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_032/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_032/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_032/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..b580f0fc Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_032/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_033/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_033/afni_proc/_inputs.pklz new file mode 100644 index 00000000..69953100 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_033/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_033/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_033/afni_proc/_node.pklz new file mode 100644 index 00000000..4de4a2f7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_033/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_033/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_033/afni_proc/_report/report.rst new file mode 100644 index 00000000..f6b7b83d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_033/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a041 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 033 + diff --git a/Afni_proc_through_nipype/_subject_id_033/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_033/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..ec76e82e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_033/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_0x6c9baf9c6d70dfe0158fb11e86d9d85f.json b/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_0x6c9baf9c6d70dfe0158fb11e86d9d85f.json new file mode 100644 index 00000000..cc200805 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_0x6c9baf9c6d70dfe0158fb11e86d9d85f.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "033" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..0a99af6a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_node.pklz new file mode 100644 index 00000000..6146f70b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_report/report.rst new file mode 100644 index 00000000..44aa1cde --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a041 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 033 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 033 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012844 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_033/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_033/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_033/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..e6afdefd Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_033/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_0x60ea3b92aac3c9ed6c62016a8b7c7fe5.json b/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_0x60ea3b92aac3c9ed6c62016a8b7c7fe5.json new file mode 100644 index 00000000..d63cf67c --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_0x60ea3b92aac3c9ed6c62016a8b7c7fe5.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "035" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..11c5ef09 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_node.pklz new file mode 100644 index 00000000..7c4c449a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_report/report.rst new file mode 100644 index 00000000..170a1014 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a094 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 035 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 035 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012362 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_035/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_035/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_035/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..cb0a4402 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_035/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_0x992d4ff2428428edc7b2ca38bb86dc65.json b/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_0x992d4ff2428428edc7b2ca38bb86dc65.json new file mode 100644 index 00000000..f16ff0f7 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_0x992d4ff2428428edc7b2ca38bb86dc65.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "036" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..19714462 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_node.pklz new file mode 100644 index 00000000..aa1fb35e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_report/report.rst new file mode 100644 index 00000000..b7175d91 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a099 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 036 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 036 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012482 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_036/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_036/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_036/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..b16bae2f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_036/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_0xcc21dffa6fe1cce80b5314a60c3ff5e6.json b/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_0xcc21dffa6fe1cce80b5314a60c3ff5e6.json new file mode 100644 index 00000000..8fd5a34a --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_0xcc21dffa6fe1cce80b5314a60c3ff5e6.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "037" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..a579c7be Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_node.pklz new file mode 100644 index 00000000..b102d2fe Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_report/report.rst new file mode 100644 index 00000000..13c82a89 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a088 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 037 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 037 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012266 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_037/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_037/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_037/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..fe0771b2 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_037/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_038/afni_proc/_0x9f1fb559a7f70b06e79e2ceeed7c7503.json b/Afni_proc_through_nipype/_subject_id_038/afni_proc/_0x9f1fb559a7f70b06e79e2ceeed7c7503.json new file mode 100644 index 00000000..e225112d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_038/afni_proc/_0x9f1fb559a7f70b06e79e2ceeed7c7503.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "038" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_038/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_038/afni_proc/_inputs.pklz new file mode 100644 index 00000000..10b65b4a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_038/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_038/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_038/afni_proc/_node.pklz new file mode 100644 index 00000000..8a3887e3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_038/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_038/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_038/afni_proc/_report/report.rst new file mode 100644 index 00000000..0c8985f4 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_038/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a008 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 038 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 038 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.073271 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_038/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_038/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_038/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..caf9d05c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_038/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_0x8020b887b800fb3211deeaa3d63de33d.json b/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_0x8020b887b800fb3211deeaa3d63de33d.json new file mode 100644 index 00000000..c84b641b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_0x8020b887b800fb3211deeaa3d63de33d.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "038" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..d51cd9c3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_node.pklz new file mode 100644 index 00000000..1da1cccd Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_report/report.rst new file mode 100644 index 00000000..7093a954 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a008 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 038 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 038 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.01271 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_038/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_038/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_038/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..43958494 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_038/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_039/afni_proc/_0xab1371e1988d24b472db63e18ff73eb2.json b/Afni_proc_through_nipype/_subject_id_039/afni_proc/_0xab1371e1988d24b472db63e18ff73eb2.json new file mode 100644 index 00000000..354588bd --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_039/afni_proc/_0xab1371e1988d24b472db63e18ff73eb2.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "039" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_039/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_039/afni_proc/_inputs.pklz new file mode 100644 index 00000000..39004e52 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_039/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_039/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_039/afni_proc/_node.pklz new file mode 100644 index 00000000..b18beed8 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_039/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_039/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_039/afni_proc/_report/report.rst new file mode 100644 index 00000000..56fd4159 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_039/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a066 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 039 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 039 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072638 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_039/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_039/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_039/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..ad24dba2 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_039/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_0xc0ecaca3746a356c8aab463303ba4948.json b/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_0xc0ecaca3746a356c8aab463303ba4948.json new file mode 100644 index 00000000..85015f4b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_0xc0ecaca3746a356c8aab463303ba4948.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "039" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..e8d1fd1b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_node.pklz new file mode 100644 index 00000000..a29d618b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_report/report.rst new file mode 100644 index 00000000..fc930186 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a066 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 039 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 039 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.01236 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_039/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_039/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_039/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..42e8804c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_039/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_040/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_040/afni_proc/_inputs.pklz new file mode 100644 index 00000000..695206fc Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_040/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_040/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_040/afni_proc/_node.pklz new file mode 100644 index 00000000..58b6e602 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_040/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_040/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_040/afni_proc/_report/report.rst new file mode 100644 index 00000000..0e56a9fc --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_040/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a038 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 040 + diff --git a/Afni_proc_through_nipype/_subject_id_040/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_040/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..31a47003 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_040/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_0x067613127eb9873042069b2d00551fe0.json b/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_0x067613127eb9873042069b2d00551fe0.json new file mode 100644 index 00000000..09e24fea --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_0x067613127eb9873042069b2d00551fe0.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "040" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..33aeb5ad Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_node.pklz new file mode 100644 index 00000000..c0629f78 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_report/report.rst new file mode 100644 index 00000000..7b5265e7 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a038 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 040 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 040 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.01229 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_040/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_040/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_040/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..94437914 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_040/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_041/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_041/afni_proc/_inputs.pklz new file mode 100644 index 00000000..95fc336c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_041/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_041/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_041/afni_proc/_node.pklz new file mode 100644 index 00000000..1c4015cf Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_041/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_041/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_041/afni_proc/_report/report.rst new file mode 100644 index 00000000..55a8841c --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_041/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a032 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 041 + diff --git a/Afni_proc_through_nipype/_subject_id_041/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_041/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..56e5f15f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_041/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_0xa892d02df6f04aa55c6f92705c256a0d.json b/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_0xa892d02df6f04aa55c6f92705c256a0d.json new file mode 100644 index 00000000..3a0a6033 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_0xa892d02df6f04aa55c6f92705c256a0d.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "041" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..953d9b68 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_node.pklz new file mode 100644 index 00000000..63caff2a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_report/report.rst new file mode 100644 index 00000000..9fff31de --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a032 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 041 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 041 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012978 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_041/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_041/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_041/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..057e1f02 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_041/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_043/afni_proc/_0x8b492afad08c3518e645a7f19af0f63e.json b/Afni_proc_through_nipype/_subject_id_043/afni_proc/_0x8b492afad08c3518e645a7f19af0f63e.json new file mode 100644 index 00000000..48128f82 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_043/afni_proc/_0x8b492afad08c3518e645a7f19af0f63e.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "043" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_043/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_043/afni_proc/_inputs.pklz new file mode 100644 index 00000000..ad3e82a8 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_043/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_043/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_043/afni_proc/_node.pklz new file mode 100644 index 00000000..5fe8c326 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_043/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_043/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_043/afni_proc/_report/report.rst new file mode 100644 index 00000000..a1861cf9 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_043/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a007 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 043 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 043 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.074271 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_043/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_043/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_043/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..2d3a0f5f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_043/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_0x381748b44ca3771052bbcf37e8afe6cc.json b/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_0x381748b44ca3771052bbcf37e8afe6cc.json new file mode 100644 index 00000000..e3860d13 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_0x381748b44ca3771052bbcf37e8afe6cc.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "043" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..c60cc563 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_node.pklz new file mode 100644 index 00000000..056a4bd6 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_report/report.rst new file mode 100644 index 00000000..78d1b355 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a007 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 043 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 043 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.013179 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_043/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_043/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_043/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..e910b9f0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_043/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_044/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_044/afni_proc/_inputs.pklz new file mode 100644 index 00000000..fd4bfaa7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_044/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_044/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_044/afni_proc/_node.pklz new file mode 100644 index 00000000..826ffe39 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_044/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_044/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_044/afni_proc/_report/report.rst new file mode 100644 index 00000000..3a7756c2 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_044/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a050 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 044 + diff --git a/Afni_proc_through_nipype/_subject_id_044/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_044/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..72324921 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_044/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_0xe3f0a878664684a99c6ad6ba1be4cca3.json b/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_0xe3f0a878664684a99c6ad6ba1be4cca3.json new file mode 100644 index 00000000..bbf13ecd --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_0xe3f0a878664684a99c6ad6ba1be4cca3.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "044" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..6744ce7e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_node.pklz new file mode 100644 index 00000000..73cd621f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_report/report.rst new file mode 100644 index 00000000..47d74938 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a050 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 044 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 044 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012737 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_044/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_044/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_044/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..e5172b12 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_044/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_0x6354c94b8fafad0a2d0ea01316084569.json b/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_0x6354c94b8fafad0a2d0ea01316084569.json new file mode 100644 index 00000000..7902f73d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_0x6354c94b8fafad0a2d0ea01316084569.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "045" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..d87c3941 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_node.pklz new file mode 100644 index 00000000..07925429 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_report/report.rst new file mode 100644 index 00000000..9ca54cd7 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a076 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 045 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 045 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012441 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_045/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_045/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_045/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..71e15478 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_045/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_046/afni_proc/_0x1d4c51e53416d8b82b13a96333580f82.json b/Afni_proc_through_nipype/_subject_id_046/afni_proc/_0x1d4c51e53416d8b82b13a96333580f82.json new file mode 100644 index 00000000..2d18d0f4 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_046/afni_proc/_0x1d4c51e53416d8b82b13a96333580f82.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "046" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_046/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_046/afni_proc/_inputs.pklz new file mode 100644 index 00000000..07a480b5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_046/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_046/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_046/afni_proc/_node.pklz new file mode 100644 index 00000000..f7f2d6b4 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_046/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_046/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_046/afni_proc/_report/report.rst new file mode 100644 index 00000000..c2767b58 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_046/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a006 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 046 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 046 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.122185 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_046/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_046/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_046/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..4adef684 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_046/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_0x5f43c7f735c08a981e581d35b508cae6.json b/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_0x5f43c7f735c08a981e581d35b508cae6.json new file mode 100644 index 00000000..abe90023 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_0x5f43c7f735c08a981e581d35b508cae6.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "046" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..e05894aa Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_node.pklz new file mode 100644 index 00000000..1cf129c9 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_report/report.rst new file mode 100644 index 00000000..d7927803 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a006 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 046 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 046 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012248 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_046/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_046/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_046/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..e1445f4a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_046/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_047/afni_proc/_0x6717d3cf6657c70372ad1f0df71c7481.json b/Afni_proc_through_nipype/_subject_id_047/afni_proc/_0x6717d3cf6657c70372ad1f0df71c7481.json new file mode 100644 index 00000000..3346a999 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_047/afni_proc/_0x6717d3cf6657c70372ad1f0df71c7481.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "047" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_047/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_047/afni_proc/_inputs.pklz new file mode 100644 index 00000000..7c8163ef Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_047/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_047/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_047/afni_proc/_node.pklz new file mode 100644 index 00000000..c0c5eb15 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_047/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_047/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_047/afni_proc/_report/report.rst new file mode 100644 index 00000000..849eb040 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_047/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a039 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 047 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 047 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.073904 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_047/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_047/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_047/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..7b47a6a6 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_047/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_0x856ccca4ca2e5938d06df03b1cde90b2.json b/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_0x856ccca4ca2e5938d06df03b1cde90b2.json new file mode 100644 index 00000000..f22a4d2d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_0x856ccca4ca2e5938d06df03b1cde90b2.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "047" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..5b7a48d0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_node.pklz new file mode 100644 index 00000000..800be10a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_report/report.rst new file mode 100644 index 00000000..3045f66c --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a039 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 047 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 047 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012221 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_047/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_047/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_047/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..956be7bf Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_047/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_049/afni_proc/_0xe463d38146f4daeb17f42c78a43f4970.json b/Afni_proc_through_nipype/_subject_id_049/afni_proc/_0xe463d38146f4daeb17f42c78a43f4970.json new file mode 100644 index 00000000..44a89fc6 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_049/afni_proc/_0xe463d38146f4daeb17f42c78a43f4970.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "049" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_049/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_049/afni_proc/_inputs.pklz new file mode 100644 index 00000000..b749bbdd Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_049/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_049/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_049/afni_proc/_node.pklz new file mode 100644 index 00000000..a060558a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_049/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_049/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_049/afni_proc/_report/report.rst new file mode 100644 index 00000000..77d0fc09 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_049/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a034 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 049 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 049 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072226 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_049/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_049/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_049/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..03c95390 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_049/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_0x5c9bb7ddb1134a0503ef16fb2591e367.json b/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_0x5c9bb7ddb1134a0503ef16fb2591e367.json new file mode 100644 index 00000000..dab957b2 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_0x5c9bb7ddb1134a0503ef16fb2591e367.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "049" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..b3f3a4a7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_node.pklz new file mode 100644 index 00000000..f5a33b0c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_report/report.rst new file mode 100644 index 00000000..a44f9d22 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a034 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 049 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 049 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012481 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_049/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_049/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_049/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..33e661ce Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_049/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_050/afni_proc/_0xf629673497638fc1be530fc0419613ea.json b/Afni_proc_through_nipype/_subject_id_050/afni_proc/_0xf629673497638fc1be530fc0419613ea.json new file mode 100644 index 00000000..775b1600 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_050/afni_proc/_0xf629673497638fc1be530fc0419613ea.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "050" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_050/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_050/afni_proc/_inputs.pklz new file mode 100644 index 00000000..ce003f01 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_050/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_050/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_050/afni_proc/_node.pklz new file mode 100644 index 00000000..44dbd980 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_050/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_050/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_050/afni_proc/_report/report.rst new file mode 100644 index 00000000..0ad397e5 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_050/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a069 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 050 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 050 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072965 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_050/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_050/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_050/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..a79fbc2b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_050/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_0xc20abc29a7f2cfb3c129121baaa625bb.json b/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_0xc20abc29a7f2cfb3c129121baaa625bb.json new file mode 100644 index 00000000..29ba639e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_0xc20abc29a7f2cfb3c129121baaa625bb.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "050" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..4cec6494 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_node.pklz new file mode 100644 index 00000000..25286d68 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_report/report.rst new file mode 100644 index 00000000..17a2c41e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a069 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 050 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 050 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012405 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_050/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_050/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_050/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..cafd0457 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_050/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_0xb010da99a8c5ba299100258ce16f9ffe.json b/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_0xb010da99a8c5ba299100258ce16f9ffe.json new file mode 100644 index 00000000..73473abb --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_0xb010da99a8c5ba299100258ce16f9ffe.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "051" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..2d62e142 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_node.pklz new file mode 100644 index 00000000..80d248c0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_report/report.rst new file mode 100644 index 00000000..180d8805 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a089 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 051 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 051 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012498 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_051/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_051/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_051/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..4a73800a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_051/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_0x6b31a6173b7df71090af96acd2f6c8a1.json b/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_0x6b31a6173b7df71090af96acd2f6c8a1.json new file mode 100644 index 00000000..160b4f94 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_0x6b31a6173b7df71090af96acd2f6c8a1.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "052" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..620290eb Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_node.pklz new file mode 100644 index 00000000..c65e23fa Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_report/report.rst new file mode 100644 index 00000000..2a6395d4 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a091 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 052 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 052 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012609 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_052/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_052/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_052/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..4e202515 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_052/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_053/afni_proc/_0xd3fc95320172f7d63d16ee61a28a0d7d.json b/Afni_proc_through_nipype/_subject_id_053/afni_proc/_0xd3fc95320172f7d63d16ee61a28a0d7d.json new file mode 100644 index 00000000..a3278f03 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_053/afni_proc/_0xd3fc95320172f7d63d16ee61a28a0d7d.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "053" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_053/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_053/afni_proc/_inputs.pklz new file mode 100644 index 00000000..929d9c4d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_053/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_053/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_053/afni_proc/_node.pklz new file mode 100644 index 00000000..48fb41a8 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_053/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_053/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_053/afni_proc/_report/report.rst new file mode 100644 index 00000000..73299fa5 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_053/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a012 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 053 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 053 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.073039 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_053/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_053/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_053/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..6b66cd44 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_053/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_0xa8b26774dc1bbda1ac991b50707e62e8.json b/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_0xa8b26774dc1bbda1ac991b50707e62e8.json new file mode 100644 index 00000000..b63d1416 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_0xa8b26774dc1bbda1ac991b50707e62e8.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "053" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..9a9a8d8d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_node.pklz new file mode 100644 index 00000000..ecffd114 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_report/report.rst new file mode 100644 index 00000000..d066c13a --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a012 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 053 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 053 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012302 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_053/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_053/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_053/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..dfb73f88 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_053/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_0x5d692952cbd51d3bee4eaff23316a6fc.json b/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_0x5d692952cbd51d3bee4eaff23316a6fc.json new file mode 100644 index 00000000..43bea763 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_0x5d692952cbd51d3bee4eaff23316a6fc.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "054" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..754c751c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_node.pklz new file mode 100644 index 00000000..8f054354 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_report/report.rst new file mode 100644 index 00000000..5e16c65a --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a106 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 054 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 054 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.013562 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_054/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_054/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_054/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..288f5e6b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_054/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_055/afni_proc/_0xadf9a5388032e433d0e4c62c11ec1c67.json b/Afni_proc_through_nipype/_subject_id_055/afni_proc/_0xadf9a5388032e433d0e4c62c11ec1c67.json new file mode 100644 index 00000000..6aaec569 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_055/afni_proc/_0xadf9a5388032e433d0e4c62c11ec1c67.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "055" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_055/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_055/afni_proc/_inputs.pklz new file mode 100644 index 00000000..d6f0876d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_055/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_055/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_055/afni_proc/_node.pklz new file mode 100644 index 00000000..f966fd91 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_055/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_055/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_055/afni_proc/_report/report.rst new file mode 100644 index 00000000..5c3db00d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_055/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a026 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 055 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 055 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.071081 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_055/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_055/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_055/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..47f0e367 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_055/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_0x452ae5708964c457e7513fb29c2053d3.json b/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_0x452ae5708964c457e7513fb29c2053d3.json new file mode 100644 index 00000000..57ce4945 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_0x452ae5708964c457e7513fb29c2053d3.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "055" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..652c02cc Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_node.pklz new file mode 100644 index 00000000..67973fba Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_report/report.rst new file mode 100644 index 00000000..6814650e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a026 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 055 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 055 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012851 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_055/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_055/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_055/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..b356e5ec Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_055/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_056/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_056/afni_proc/_inputs.pklz new file mode 100644 index 00000000..ee4feb0e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_056/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_056/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_056/afni_proc/_node.pklz new file mode 100644 index 00000000..b0243fbc Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_056/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_056/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_056/afni_proc/_report/report.rst new file mode 100644 index 00000000..45a01cb8 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_056/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a058 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 056 + diff --git a/Afni_proc_through_nipype/_subject_id_056/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_056/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..67037bd9 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_056/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_0x3b6c30cc71f9ad366c822496fb589718.json b/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_0x3b6c30cc71f9ad366c822496fb589718.json new file mode 100644 index 00000000..d2e81da9 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_0x3b6c30cc71f9ad366c822496fb589718.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "056" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..dfbc2328 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_node.pklz new file mode 100644 index 00000000..72b188c1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_report/report.rst new file mode 100644 index 00000000..58f189a8 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a058 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 056 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 056 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012266 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_056/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_056/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_056/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..337852fd Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_056/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_057/afni_proc/_0x9c05bb27deb8f33f64413d4465ea4ef8.json b/Afni_proc_through_nipype/_subject_id_057/afni_proc/_0x9c05bb27deb8f33f64413d4465ea4ef8.json new file mode 100644 index 00000000..da157b5b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_057/afni_proc/_0x9c05bb27deb8f33f64413d4465ea4ef8.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "057" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_057/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_057/afni_proc/_inputs.pklz new file mode 100644 index 00000000..9c696abb Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_057/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_057/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_057/afni_proc/_node.pklz new file mode 100644 index 00000000..ea17f980 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_057/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_057/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_057/afni_proc/_report/report.rst new file mode 100644 index 00000000..5ab467a0 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_057/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a036 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 057 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 057 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072067 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_057/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_057/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_057/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..0b072cb8 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_057/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_0xfb31361957b77b916fbab80d8fec6def.json b/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_0xfb31361957b77b916fbab80d8fec6def.json new file mode 100644 index 00000000..c831cd7b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_0xfb31361957b77b916fbab80d8fec6def.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "057" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..24ef9a35 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_node.pklz new file mode 100644 index 00000000..64a7ae39 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_report/report.rst new file mode 100644 index 00000000..4f4293ae --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a036 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 057 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 057 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012327 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_057/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_057/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_057/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..025b9936 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_057/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_058/afni_proc/_0x09c1f3168e2d72b072ca0e01a947a58e.json b/Afni_proc_through_nipype/_subject_id_058/afni_proc/_0x09c1f3168e2d72b072ca0e01a947a58e.json new file mode 100644 index 00000000..99112c56 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_058/afni_proc/_0x09c1f3168e2d72b072ca0e01a947a58e.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "058" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_058/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_058/afni_proc/_inputs.pklz new file mode 100644 index 00000000..85c1c712 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_058/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_058/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_058/afni_proc/_node.pklz new file mode 100644 index 00000000..485acf8d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_058/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_058/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_058/afni_proc/_report/report.rst new file mode 100644 index 00000000..05c37e85 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_058/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a018 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 058 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 058 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072004 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_058/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_058/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_058/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..ba5babc3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_058/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_0x01e5b8dd24756ed0c0fe3629cc71eb3c.json b/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_0x01e5b8dd24756ed0c0fe3629cc71eb3c.json new file mode 100644 index 00000000..998f5ce5 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_0x01e5b8dd24756ed0c0fe3629cc71eb3c.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "058" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..c6887b49 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_node.pklz new file mode 100644 index 00000000..f13323cf Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_report/report.rst new file mode 100644 index 00000000..3984d89b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a018 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 058 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 058 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012335 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_058/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_058/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_058/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..9092b05f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_058/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_0x09b6f0379631039b0ae4fbfc242d4d59.json b/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_0x09b6f0379631039b0ae4fbfc242d4d59.json new file mode 100644 index 00000000..f5dc84a3 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_0x09b6f0379631039b0ae4fbfc242d4d59.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "059" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..18712241 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_node.pklz new file mode 100644 index 00000000..d6fb77d0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_report/report.rst new file mode 100644 index 00000000..61f1f860 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a078 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 059 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 059 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012781 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_059/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_059/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_059/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..ce1a6abd Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_059/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_0xbc6ff409e7a11a5e715e4ba53677c9c8.json b/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_0xbc6ff409e7a11a5e715e4ba53677c9c8.json new file mode 100644 index 00000000..2739af83 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_0xbc6ff409e7a11a5e715e4ba53677c9c8.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "060" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..a452af40 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_node.pklz new file mode 100644 index 00000000..d9d2472c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_report/report.rst new file mode 100644 index 00000000..83d68508 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a093 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 060 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 060 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012353 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_060/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_060/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_060/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..a749e921 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_060/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_061/afni_proc/_0xb2f2d7a9a1dc7b5068b97008ab38a8cd.json b/Afni_proc_through_nipype/_subject_id_061/afni_proc/_0xb2f2d7a9a1dc7b5068b97008ab38a8cd.json new file mode 100644 index 00000000..75612d93 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_061/afni_proc/_0xb2f2d7a9a1dc7b5068b97008ab38a8cd.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "061" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_061/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_061/afni_proc/_inputs.pklz new file mode 100644 index 00000000..88424db8 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_061/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_061/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_061/afni_proc/_node.pklz new file mode 100644 index 00000000..8d77a915 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_061/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_061/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_061/afni_proc/_report/report.rst new file mode 100644 index 00000000..dd1861ed --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_061/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a029 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 061 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 061 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.07261 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_061/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_061/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_061/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..58318db8 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_061/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_0x8266e658cbe0fdf32e3a7879b8073bec.json b/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_0x8266e658cbe0fdf32e3a7879b8073bec.json new file mode 100644 index 00000000..94269c7f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_0x8266e658cbe0fdf32e3a7879b8073bec.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "061" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..ac441018 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_node.pklz new file mode 100644 index 00000000..c99a8d0b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_report/report.rst new file mode 100644 index 00000000..b4ab39b1 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a029 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 061 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 061 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012638 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_061/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_061/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_061/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..1e924443 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_061/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_0x0e1aaf13355ed7c82bf254acf616f31c.json b/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_0x0e1aaf13355ed7c82bf254acf616f31c.json new file mode 100644 index 00000000..87439393 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_0x0e1aaf13355ed7c82bf254acf616f31c.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "062" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..15f813e5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_node.pklz new file mode 100644 index 00000000..4fa438ef Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_report/report.rst new file mode 100644 index 00000000..ca4bfb9b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a103 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 062 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 062 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012282 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_062/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_062/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_062/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..9c260b97 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_062/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_063/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_063/afni_proc/_inputs.pklz new file mode 100644 index 00000000..c3738dbe Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_063/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_063/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_063/afni_proc/_node.pklz new file mode 100644 index 00000000..d7f9da6c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_063/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_063/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_063/afni_proc/_report/report.rst new file mode 100644 index 00000000..c1ace05d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_063/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a055 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 063 + diff --git a/Afni_proc_through_nipype/_subject_id_063/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_063/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..9ceceeca Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_063/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_0x4586828376765da3dcebbcc65842752d.json b/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_0x4586828376765da3dcebbcc65842752d.json new file mode 100644 index 00000000..e6fa91cb --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_0x4586828376765da3dcebbcc65842752d.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "063" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..be8afb0e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_node.pklz new file mode 100644 index 00000000..d679292d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_report/report.rst new file mode 100644 index 00000000..be1d7a3b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a055 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 063 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 063 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.01242 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_063/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_063/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_063/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..1925ef72 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_063/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_064/afni_proc/_0x837b611046fbaed0402751086c5c5aea.json b/Afni_proc_through_nipype/_subject_id_064/afni_proc/_0x837b611046fbaed0402751086c5c5aea.json new file mode 100644 index 00000000..d91fcfc1 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_064/afni_proc/_0x837b611046fbaed0402751086c5c5aea.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "064" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_064/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_064/afni_proc/_inputs.pklz new file mode 100644 index 00000000..8bcca192 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_064/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_064/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_064/afni_proc/_node.pklz new file mode 100644 index 00000000..25cf52ab Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_064/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_064/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_064/afni_proc/_report/report.rst new file mode 100644 index 00000000..7abf13a5 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_064/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a054 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 064 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 064 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.07284 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_064/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_064/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_064/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..57b31e7b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_064/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_0xf50a88c8bfa3bb40af29bdfe600ac624.json b/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_0xf50a88c8bfa3bb40af29bdfe600ac624.json new file mode 100644 index 00000000..4c4ba305 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_0xf50a88c8bfa3bb40af29bdfe600ac624.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "064" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..d8d5856e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_node.pklz new file mode 100644 index 00000000..6cb484f5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_report/report.rst new file mode 100644 index 00000000..738a11ac --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a054 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 064 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 064 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012346 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_064/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_064/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_064/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..75071ec4 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_064/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_066/afni_proc/_0xec90c9e1a19cc00398bb60732b469df3.json b/Afni_proc_through_nipype/_subject_id_066/afni_proc/_0xec90c9e1a19cc00398bb60732b469df3.json new file mode 100644 index 00000000..48f1930e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_066/afni_proc/_0xec90c9e1a19cc00398bb60732b469df3.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "066" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_066/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_066/afni_proc/_inputs.pklz new file mode 100644 index 00000000..278cbd1b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_066/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_066/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_066/afni_proc/_node.pklz new file mode 100644 index 00000000..18180193 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_066/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_066/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_066/afni_proc/_report/report.rst new file mode 100644 index 00000000..21b163e2 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_066/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a045 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 066 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 066 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.078029 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_066/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_066/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_066/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..7e600008 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_066/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_0x639864a150a788e88be80d083aa4c3d6.json b/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_0x639864a150a788e88be80d083aa4c3d6.json new file mode 100644 index 00000000..688743ba --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_0x639864a150a788e88be80d083aa4c3d6.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "066" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..1e2913f1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_node.pklz new file mode 100644 index 00000000..a09d2984 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_report/report.rst new file mode 100644 index 00000000..7c8eef83 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a045 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 066 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 066 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012534 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_066/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_066/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_066/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..d70666d6 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_066/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_067/afni_proc/_0xca08fca9eef2190364b7897d017f5a89.json b/Afni_proc_through_nipype/_subject_id_067/afni_proc/_0xca08fca9eef2190364b7897d017f5a89.json new file mode 100644 index 00000000..31c65451 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_067/afni_proc/_0xca08fca9eef2190364b7897d017f5a89.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "067" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_067/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_067/afni_proc/_inputs.pklz new file mode 100644 index 00000000..01d1ab9e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_067/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_067/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_067/afni_proc/_node.pklz new file mode 100644 index 00000000..8f0e8628 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_067/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_067/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_067/afni_proc/_report/report.rst new file mode 100644 index 00000000..9004f766 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_067/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a064 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 067 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 067 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.071166 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_067/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_067/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_067/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..0cb9afef Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_067/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_0x1b348cdf1acb0096519c9f5817e06914.json b/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_0x1b348cdf1acb0096519c9f5817e06914.json new file mode 100644 index 00000000..e17dc569 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_0x1b348cdf1acb0096519c9f5817e06914.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "067" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..aafc4e4b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_node.pklz new file mode 100644 index 00000000..6ec8d44d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_report/report.rst new file mode 100644 index 00000000..d69cfb46 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a064 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 067 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 067 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012619 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_067/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_067/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_067/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..c2d083c0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_067/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_0xf538d8cfc972c0815c68dcb386dd89bf.json b/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_0xf538d8cfc972c0815c68dcb386dd89bf.json new file mode 100644 index 00000000..d165856f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_0xf538d8cfc972c0815c68dcb386dd89bf.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "068" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..cc8d21b5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_node.pklz new file mode 100644 index 00000000..c7495ad1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_report/report.rst new file mode 100644 index 00000000..774c8f38 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a105 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 068 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 068 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.01222 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_068/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_068/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_068/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..8ad3bf59 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_068/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_069/afni_proc/_0x7ad651e4ef4b8a2561b0678e31d87d06.json b/Afni_proc_through_nipype/_subject_id_069/afni_proc/_0x7ad651e4ef4b8a2561b0678e31d87d06.json new file mode 100644 index 00000000..e27ffd33 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_069/afni_proc/_0x7ad651e4ef4b8a2561b0678e31d87d06.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "069" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_069/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_069/afni_proc/_inputs.pklz new file mode 100644 index 00000000..15d6970c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_069/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_069/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_069/afni_proc/_node.pklz new file mode 100644 index 00000000..cdcbf104 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_069/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_069/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_069/afni_proc/_report/report.rst new file mode 100644 index 00000000..c5360238 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_069/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a019 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 069 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 069 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072596 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_069/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_069/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_069/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..4644bd92 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_069/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_0x4011380c8797270139dcfa391ddc1920.json b/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_0x4011380c8797270139dcfa391ddc1920.json new file mode 100644 index 00000000..c681a820 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_0x4011380c8797270139dcfa391ddc1920.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "069" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..78751f7a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_node.pklz new file mode 100644 index 00000000..7c49dd84 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_report/report.rst new file mode 100644 index 00000000..273cf997 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a019 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 069 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 069 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012344 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_069/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_069/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_069/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..f079a43b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_069/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_0x53c58d1052ca19c53a1a5d2dc8c0789c.json b/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_0x53c58d1052ca19c53a1a5d2dc8c0789c.json new file mode 100644 index 00000000..5219c0bb --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_0x53c58d1052ca19c53a1a5d2dc8c0789c.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "070" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..e46928aa Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_node.pklz new file mode 100644 index 00000000..a6ef5a78 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_report/report.rst new file mode 100644 index 00000000..6d10f85b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a095 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 070 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 070 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012456 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_070/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_070/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_070/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..4448c359 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_070/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_071/afni_proc/_0x7220a6c614588a2c502e01d3a022546e.json b/Afni_proc_through_nipype/_subject_id_071/afni_proc/_0x7220a6c614588a2c502e01d3a022546e.json new file mode 100644 index 00000000..cb72a075 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_071/afni_proc/_0x7220a6c614588a2c502e01d3a022546e.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "071" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_071/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_071/afni_proc/_inputs.pklz new file mode 100644 index 00000000..6b7fd440 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_071/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_071/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_071/afni_proc/_node.pklz new file mode 100644 index 00000000..e577eed8 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_071/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_071/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_071/afni_proc/_report/report.rst new file mode 100644 index 00000000..ae9c88da --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_071/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a022 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 071 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 071 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.07362 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_071/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_071/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_071/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..6e563b0d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_071/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_0x30489087666fd986fe613b7429f795d9.json b/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_0x30489087666fd986fe613b7429f795d9.json new file mode 100644 index 00000000..920c4496 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_0x30489087666fd986fe613b7429f795d9.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "071" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..6da32c01 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_node.pklz new file mode 100644 index 00000000..467053c5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_report/report.rst new file mode 100644 index 00000000..0feaa371 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a022 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 071 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 071 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012329 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_071/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_071/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_071/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..2c0752a7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_071/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_072/afni_proc/_0xc25390419459295f01a587c0773f1ae2.json b/Afni_proc_through_nipype/_subject_id_072/afni_proc/_0xc25390419459295f01a587c0773f1ae2.json new file mode 100644 index 00000000..02af7fc9 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_072/afni_proc/_0xc25390419459295f01a587c0773f1ae2.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "072" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_072/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_072/afni_proc/_inputs.pklz new file mode 100644 index 00000000..9f814bf8 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_072/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_072/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_072/afni_proc/_node.pklz new file mode 100644 index 00000000..96cbd9c0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_072/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_072/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_072/afni_proc/_report/report.rst new file mode 100644 index 00000000..179379b5 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_072/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a049 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 072 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 072 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.071506 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_072/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_072/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_072/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..2794c55d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_072/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_0x872aa0df8d52bd94b041223c012cad7b.json b/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_0x872aa0df8d52bd94b041223c012cad7b.json new file mode 100644 index 00000000..e9c0b935 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_0x872aa0df8d52bd94b041223c012cad7b.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "072" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..735a47d2 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_node.pklz new file mode 100644 index 00000000..abaec127 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_report/report.rst new file mode 100644 index 00000000..e930254a --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a049 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 072 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 072 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012177 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_072/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_072/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_072/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..6c9582a0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_072/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_0xb7da0429e0ae8a66567720eeedb35ffd.json b/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_0xb7da0429e0ae8a66567720eeedb35ffd.json new file mode 100644 index 00000000..4b529e4a --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_0xb7da0429e0ae8a66567720eeedb35ffd.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "073" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..f9bfbb12 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_node.pklz new file mode 100644 index 00000000..2caccbed Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_report/report.rst new file mode 100644 index 00000000..35e7b9d4 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a083 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 073 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 073 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012405 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_073/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_073/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_073/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..823dc77e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_073/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_074/afni_proc/_0x03f26d04b517fbd5a4d2062ff3f2f68d.json b/Afni_proc_through_nipype/_subject_id_074/afni_proc/_0x03f26d04b517fbd5a4d2062ff3f2f68d.json new file mode 100644 index 00000000..4501ec74 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_074/afni_proc/_0x03f26d04b517fbd5a4d2062ff3f2f68d.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "074" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_074/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_074/afni_proc/_inputs.pklz new file mode 100644 index 00000000..159388a7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_074/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_074/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_074/afni_proc/_node.pklz new file mode 100644 index 00000000..c201fd4c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_074/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_074/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_074/afni_proc/_report/report.rst new file mode 100644 index 00000000..464fcac4 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_074/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a067 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 074 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 074 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.071973 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_074/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_074/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_074/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..46b53477 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_074/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_0x9ea914ea3a56de0871a6f0ae454e0e86.json b/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_0x9ea914ea3a56de0871a6f0ae454e0e86.json new file mode 100644 index 00000000..64daeb24 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_0x9ea914ea3a56de0871a6f0ae454e0e86.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "074" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..157a5c75 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_node.pklz new file mode 100644 index 00000000..edd9923e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_report/report.rst new file mode 100644 index 00000000..c469b9b7 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a067 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 074 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 074 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012461 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_074/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_074/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_074/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..e034d8cf Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_074/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_075/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_075/afni_proc/_inputs.pklz new file mode 100644 index 00000000..bf8a05df Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_075/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_075/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_075/afni_proc/_node.pklz new file mode 100644 index 00000000..df1422d3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_075/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_075/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_075/afni_proc/_report/report.rst new file mode 100644 index 00000000..9f7d86a5 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_075/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a047 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 075 + diff --git a/Afni_proc_through_nipype/_subject_id_075/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_075/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..eca5a47f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_075/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_0x92d10bedb7ed8b1ff89fc77bbe5b3151.json b/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_0x92d10bedb7ed8b1ff89fc77bbe5b3151.json new file mode 100644 index 00000000..d51dc92b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_0x92d10bedb7ed8b1ff89fc77bbe5b3151.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "075" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..0d579383 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_node.pklz new file mode 100644 index 00000000..8dab4bf6 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_report/report.rst new file mode 100644 index 00000000..bf591100 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a047 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 075 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 075 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012409 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_075/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_075/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_075/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..da3e8fa2 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_075/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_076/afni_proc/_0x6c2e0e4f62dacc80e585410e422ba89f.json b/Afni_proc_through_nipype/_subject_id_076/afni_proc/_0x6c2e0e4f62dacc80e585410e422ba89f.json new file mode 100644 index 00000000..d0bc0e04 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_076/afni_proc/_0x6c2e0e4f62dacc80e585410e422ba89f.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "076" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_076/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_076/afni_proc/_inputs.pklz new file mode 100644 index 00000000..55f52949 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_076/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_076/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_076/afni_proc/_node.pklz new file mode 100644 index 00000000..7a886206 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_076/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_076/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_076/afni_proc/_report/report.rst new file mode 100644 index 00000000..0a99650d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_076/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a021 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 076 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 076 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.0755 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_076/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_076/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_076/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..f5ebed9e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_076/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_0x1db59509511bb4dca10d238592ee3904.json b/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_0x1db59509511bb4dca10d238592ee3904.json new file mode 100644 index 00000000..a6132ae8 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_0x1db59509511bb4dca10d238592ee3904.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "076" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..98791499 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_node.pklz new file mode 100644 index 00000000..9c23f044 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_report/report.rst new file mode 100644 index 00000000..a27505b3 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a021 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 076 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 076 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012387 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_076/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_076/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_076/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..dfa30f5f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_076/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_077/afni_proc/_0x657a66eb55c9e5fe22b6facadb30a0cd.json b/Afni_proc_through_nipype/_subject_id_077/afni_proc/_0x657a66eb55c9e5fe22b6facadb30a0cd.json new file mode 100644 index 00000000..a9e19034 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_077/afni_proc/_0x657a66eb55c9e5fe22b6facadb30a0cd.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "077" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_077/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_077/afni_proc/_inputs.pklz new file mode 100644 index 00000000..d2b43048 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_077/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_077/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_077/afni_proc/_node.pklz new file mode 100644 index 00000000..a723e4f6 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_077/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_077/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_077/afni_proc/_report/report.rst new file mode 100644 index 00000000..57364524 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_077/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a013 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 077 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 077 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.076068 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_077/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_077/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_077/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..055c5a27 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_077/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_0x739c4a8b07a5681b1aaad919d61e986f.json b/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_0x739c4a8b07a5681b1aaad919d61e986f.json new file mode 100644 index 00000000..cec6e98c --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_0x739c4a8b07a5681b1aaad919d61e986f.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "077" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..0dd450c1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_node.pklz new file mode 100644 index 00000000..48fbcc64 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_report/report.rst new file mode 100644 index 00000000..012e26d3 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a013 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 077 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 077 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012433 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_077/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_077/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_077/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..f2d7f0c5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_077/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_079/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_079/afni_proc/_inputs.pklz new file mode 100644 index 00000000..2f87b506 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_079/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_079/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_079/afni_proc/_node.pklz new file mode 100644 index 00000000..938ab3b1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_079/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_079/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_079/afni_proc/_report/report.rst new file mode 100644 index 00000000..61d69226 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_079/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a035 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 079 + diff --git a/Afni_proc_through_nipype/_subject_id_079/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_079/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..06e4a159 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_079/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_0x29b01735ef28de5158cd338cee9a79f8.json b/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_0x29b01735ef28de5158cd338cee9a79f8.json new file mode 100644 index 00000000..dc3b8167 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_0x29b01735ef28de5158cd338cee9a79f8.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "079" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..da47a388 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_node.pklz new file mode 100644 index 00000000..c93eee07 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_report/report.rst new file mode 100644 index 00000000..70b979bc --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a035 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 079 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 079 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012417 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_079/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_079/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_079/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..ba79a8e5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_079/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_0xdb296635772377fd94ba947dc3481ed2.json b/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_0xdb296635772377fd94ba947dc3481ed2.json new file mode 100644 index 00000000..41005e50 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_0xdb296635772377fd94ba947dc3481ed2.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "080" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..3dbcc11f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_node.pklz new file mode 100644 index 00000000..fea258e6 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_report/report.rst new file mode 100644 index 00000000..a3c27acd --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a107 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 080 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 080 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012766 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_080/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_080/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_080/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..8ed8f53b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_080/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_0x2ecd40acf1d2ffaab543eba174346124.json b/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_0x2ecd40acf1d2ffaab543eba174346124.json new file mode 100644 index 00000000..21aff7bd --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_0x2ecd40acf1d2ffaab543eba174346124.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "081" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..883b7253 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_node.pklz new file mode 100644 index 00000000..17ac0c11 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_report/report.rst new file mode 100644 index 00000000..0a23fb68 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a096 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 081 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 081 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012443 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_081/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_081/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_081/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..eb397c52 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_081/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_082/afni_proc/_0xc1967b2724737b5b13288083144788cc.json b/Afni_proc_through_nipype/_subject_id_082/afni_proc/_0xc1967b2724737b5b13288083144788cc.json new file mode 100644 index 00000000..78a9c13f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_082/afni_proc/_0xc1967b2724737b5b13288083144788cc.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "082" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_082/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_082/afni_proc/_inputs.pklz new file mode 100644 index 00000000..c45aef90 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_082/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_082/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_082/afni_proc/_node.pklz new file mode 100644 index 00000000..41cc6ec9 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_082/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_082/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_082/afni_proc/_report/report.rst new file mode 100644 index 00000000..563e0d38 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_082/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a000 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 082 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 082 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.094263 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_082/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_082/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_082/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..56fcd33e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_082/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_0xa4f037b6d5ff386c5e97b1d3eb987752.json b/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_0xa4f037b6d5ff386c5e97b1d3eb987752.json new file mode 100644 index 00000000..1fd196b7 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_0xa4f037b6d5ff386c5e97b1d3eb987752.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "082" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..45d4c877 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_node.pklz new file mode 100644 index 00000000..7ec3ba50 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_report/report.rst new file mode 100644 index 00000000..81d75cff --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a000 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 082 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 082 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.195395 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_082/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_082/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_082/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..aee76829 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_082/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_0x687396ea1d6055ecb97495311aab5d55.json b/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_0x687396ea1d6055ecb97495311aab5d55.json new file mode 100644 index 00000000..1ac38097 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_0x687396ea1d6055ecb97495311aab5d55.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "083" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..2c8301c7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_node.pklz new file mode 100644 index 00000000..585e4ba0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_report/report.rst new file mode 100644 index 00000000..1ce2fb38 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a086 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 083 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 083 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012327 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_083/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_083/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_083/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..9e9c3106 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_083/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_0xcb97cba9ad63b78165ba4bc4bad657ca.json b/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_0xcb97cba9ad63b78165ba4bc4bad657ca.json new file mode 100644 index 00000000..5d64fd43 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_0xcb97cba9ad63b78165ba4bc4bad657ca.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "084" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..6b99cb09 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_node.pklz new file mode 100644 index 00000000..62b2fe07 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_report/report.rst new file mode 100644 index 00000000..fc6fa55c --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a077 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 084 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 084 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012555 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_084/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_084/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_084/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..e02a33c0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_084/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_085/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_085/afni_proc/_inputs.pklz new file mode 100644 index 00000000..b1c05c02 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_085/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_085/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_085/afni_proc/_node.pklz new file mode 100644 index 00000000..7973ca80 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_085/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_085/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_085/afni_proc/_report/report.rst new file mode 100644 index 00000000..fbf1276e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_085/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a044 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 085 + diff --git a/Afni_proc_through_nipype/_subject_id_085/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_085/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..c5e420dc Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_085/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_0x2015bbef96c8d3d0f1c59f9265af3cf2.json b/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_0x2015bbef96c8d3d0f1c59f9265af3cf2.json new file mode 100644 index 00000000..f8350f5e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_0x2015bbef96c8d3d0f1c59f9265af3cf2.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "085" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..3aeec521 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_node.pklz new file mode 100644 index 00000000..60b0e73b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_report/report.rst new file mode 100644 index 00000000..5a30ed92 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a044 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 085 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 085 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.01371 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_085/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_085/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_085/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..c6952c10 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_085/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_0x00af9c0f332e31cd809361e68391cfc0.json b/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_0x00af9c0f332e31cd809361e68391cfc0.json new file mode 100644 index 00000000..46415b55 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_0x00af9c0f332e31cd809361e68391cfc0.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "087" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..06777e7d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_node.pklz new file mode 100644 index 00000000..f1bbcc84 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_report/report.rst new file mode 100644 index 00000000..3a87cbdb --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a092 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 087 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 087 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012249 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_087/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_087/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_087/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..f7b02ebe Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_087/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_088/afni_proc/_0x6239e773ba053e07c01ae230d943aed1.json b/Afni_proc_through_nipype/_subject_id_088/afni_proc/_0x6239e773ba053e07c01ae230d943aed1.json new file mode 100644 index 00000000..4f8e0fe9 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_088/afni_proc/_0x6239e773ba053e07c01ae230d943aed1.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "088" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_088/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_088/afni_proc/_inputs.pklz new file mode 100644 index 00000000..40115df3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_088/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_088/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_088/afni_proc/_node.pklz new file mode 100644 index 00000000..0e69d7b6 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_088/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_088/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_088/afni_proc/_report/report.rst new file mode 100644 index 00000000..784673df --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_088/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a053 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 088 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 088 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.074487 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_088/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_088/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_088/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..457fa1ad Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_088/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_0x31b145bec7847e96e89836fbdbbd870e.json b/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_0x31b145bec7847e96e89836fbdbbd870e.json new file mode 100644 index 00000000..4bdb7bf5 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_0x31b145bec7847e96e89836fbdbbd870e.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "088" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..484704b1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_node.pklz new file mode 100644 index 00000000..ee911653 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_report/report.rst new file mode 100644 index 00000000..d79ff186 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a053 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 088 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 088 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012223 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_088/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_088/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_088/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..8e07bd7b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_088/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_089/afni_proc/_0x425675644f506c856820345a1fa543f9.json b/Afni_proc_through_nipype/_subject_id_089/afni_proc/_0x425675644f506c856820345a1fa543f9.json new file mode 100644 index 00000000..5e738c30 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_089/afni_proc/_0x425675644f506c856820345a1fa543f9.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "089" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_089/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_089/afni_proc/_inputs.pklz new file mode 100644 index 00000000..0830f6e6 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_089/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_089/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_089/afni_proc/_node.pklz new file mode 100644 index 00000000..792eaf8d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_089/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_089/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_089/afni_proc/_report/report.rst new file mode 100644 index 00000000..37f38fb5 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_089/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a003 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 089 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 089 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.071698 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_089/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_089/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_089/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..8c3428bc Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_089/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_0xbf025bdf197385a2ca47bfa077d18083.json b/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_0xbf025bdf197385a2ca47bfa077d18083.json new file mode 100644 index 00000000..6dd1e8fd --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_0xbf025bdf197385a2ca47bfa077d18083.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "089" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..77aba165 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_node.pklz new file mode 100644 index 00000000..6a0118d1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_report/report.rst new file mode 100644 index 00000000..f0e50dae --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a003 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 089 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 089 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.013129 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_089/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_089/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_089/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..7f15a838 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_089/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_090/afni_proc/_0x7867e20b31553dc34b16dea33cbb86b4.json b/Afni_proc_through_nipype/_subject_id_090/afni_proc/_0x7867e20b31553dc34b16dea33cbb86b4.json new file mode 100644 index 00000000..711ddc75 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_090/afni_proc/_0x7867e20b31553dc34b16dea33cbb86b4.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "090" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_090/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_090/afni_proc/_inputs.pklz new file mode 100644 index 00000000..522591fb Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_090/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_090/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_090/afni_proc/_node.pklz new file mode 100644 index 00000000..ec41a1bd Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_090/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_090/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_090/afni_proc/_report/report.rst new file mode 100644 index 00000000..a9c221f7 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_090/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a062 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 090 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 090 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.073215 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_090/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_090/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_090/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..c9abab5d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_090/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_0xfc610037c834d75e2eaf02a6b1596ead.json b/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_0xfc610037c834d75e2eaf02a6b1596ead.json new file mode 100644 index 00000000..3e5f3d52 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_0xfc610037c834d75e2eaf02a6b1596ead.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "090" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..91c99cf7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_node.pklz new file mode 100644 index 00000000..e633e48b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_report/report.rst new file mode 100644 index 00000000..92ec7c1b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a062 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 090 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 090 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012333 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_090/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_090/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_090/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..322eb2a7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_090/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_092/afni_proc/_0x34ff581aaf00c780350576c6aceaff5d.json b/Afni_proc_through_nipype/_subject_id_092/afni_proc/_0x34ff581aaf00c780350576c6aceaff5d.json new file mode 100644 index 00000000..e673ea78 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_092/afni_proc/_0x34ff581aaf00c780350576c6aceaff5d.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "092" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_092/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_092/afni_proc/_inputs.pklz new file mode 100644 index 00000000..14a30777 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_092/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_092/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_092/afni_proc/_node.pklz new file mode 100644 index 00000000..c760d977 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_092/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_092/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_092/afni_proc/_report/report.rst new file mode 100644 index 00000000..c07fc37f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_092/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a009 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 092 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 092 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.074907 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_092/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_092/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_092/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..618d1e08 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_092/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_0x579e7ac5e81b39521c2b1429535304b1.json b/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_0x579e7ac5e81b39521c2b1429535304b1.json new file mode 100644 index 00000000..d67a4bae --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_0x579e7ac5e81b39521c2b1429535304b1.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "092" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..552d7958 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_node.pklz new file mode 100644 index 00000000..6f87dd10 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_report/report.rst new file mode 100644 index 00000000..7150d4f4 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a009 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 092 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 092 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.01263 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_092/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_092/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_092/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..8f20f7c4 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_092/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_093/afni_proc/_0x961cbfc6874517fad8958d745b394e73.json b/Afni_proc_through_nipype/_subject_id_093/afni_proc/_0x961cbfc6874517fad8958d745b394e73.json new file mode 100644 index 00000000..93c3c88d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_093/afni_proc/_0x961cbfc6874517fad8958d745b394e73.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "093" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_093/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_093/afni_proc/_inputs.pklz new file mode 100644 index 00000000..eab096a5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_093/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_093/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_093/afni_proc/_node.pklz new file mode 100644 index 00000000..50a6c052 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_093/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_093/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_093/afni_proc/_report/report.rst new file mode 100644 index 00000000..ee7f7129 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_093/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a020 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 093 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 093 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.073071 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_093/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_093/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_093/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..232d614e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_093/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_0x8b5c06294f57b8f33422e05c63ff2512.json b/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_0x8b5c06294f57b8f33422e05c63ff2512.json new file mode 100644 index 00000000..195bece6 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_0x8b5c06294f57b8f33422e05c63ff2512.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "093" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..8d79a9b1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_node.pklz new file mode 100644 index 00000000..47e78310 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_report/report.rst new file mode 100644 index 00000000..d9486116 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a020 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 093 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 093 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012393 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_093/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_093/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_093/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..72512f4e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_093/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_094/afni_proc/_0xe0ea2ce9cc1dbca353cfdd4d67e2f049.json b/Afni_proc_through_nipype/_subject_id_094/afni_proc/_0xe0ea2ce9cc1dbca353cfdd4d67e2f049.json new file mode 100644 index 00000000..ec6952c0 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_094/afni_proc/_0xe0ea2ce9cc1dbca353cfdd4d67e2f049.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "094" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_094/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_094/afni_proc/_inputs.pklz new file mode 100644 index 00000000..189b9483 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_094/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_094/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_094/afni_proc/_node.pklz new file mode 100644 index 00000000..5c9287a2 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_094/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_094/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_094/afni_proc/_report/report.rst new file mode 100644 index 00000000..eef4e121 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_094/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a065 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 094 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 094 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072011 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_094/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_094/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_094/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..52dd3d7a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_094/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_0x22dcd2ff2021e1007fe03333f333bcbd.json b/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_0x22dcd2ff2021e1007fe03333f333bcbd.json new file mode 100644 index 00000000..3b07aebe --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_0x22dcd2ff2021e1007fe03333f333bcbd.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "094" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..83fee9e9 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_node.pklz new file mode 100644 index 00000000..4cb0111e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_report/report.rst new file mode 100644 index 00000000..4c1327ba --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a065 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 094 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 094 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012521 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_094/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_094/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_094/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..cb661a83 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_094/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_0x17cd4e6d0f884c5d89823ded883720b8.json b/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_0x17cd4e6d0f884c5d89823ded883720b8.json new file mode 100644 index 00000000..9b003529 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_0x17cd4e6d0f884c5d89823ded883720b8.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "095" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..4fd07039 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_node.pklz new file mode 100644 index 00000000..676f65a4 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_report/report.rst new file mode 100644 index 00000000..440587bf --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a087 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 095 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 095 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012164 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_095/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_095/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_095/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..7a209bfb Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_095/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_096/afni_proc/_0x117cf771f80206fefd91d4112830f527.json b/Afni_proc_through_nipype/_subject_id_096/afni_proc/_0x117cf771f80206fefd91d4112830f527.json new file mode 100644 index 00000000..3ae1e4b2 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_096/afni_proc/_0x117cf771f80206fefd91d4112830f527.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "096" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_096/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_096/afni_proc/_inputs.pklz new file mode 100644 index 00000000..801323e9 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_096/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_096/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_096/afni_proc/_node.pklz new file mode 100644 index 00000000..3c6a0dca Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_096/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_096/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_096/afni_proc/_report/report.rst new file mode 100644 index 00000000..c59151c1 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_096/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a025 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 096 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 096 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.07204 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_096/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_096/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_096/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..a285602b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_096/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_0x95c4c5a44021b703ade418ad1eed8292.json b/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_0x95c4c5a44021b703ade418ad1eed8292.json new file mode 100644 index 00000000..39b2b32f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_0x95c4c5a44021b703ade418ad1eed8292.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "096" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..08440ad1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_node.pklz new file mode 100644 index 00000000..1c4cfa34 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_report/report.rst new file mode 100644 index 00000000..bfd03f6a --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a025 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 096 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 096 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012373 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_096/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_096/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_096/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..a1b4fbb1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_096/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_0xd66bdde67324ae3081f10b2b8a34f33f.json b/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_0xd66bdde67324ae3081f10b2b8a34f33f.json new file mode 100644 index 00000000..451a121c --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_0xd66bdde67324ae3081f10b2b8a34f33f.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "098" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..6c0c8d0a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_node.pklz new file mode 100644 index 00000000..ce951455 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_report/report.rst new file mode 100644 index 00000000..d63b62f4 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a101 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 098 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 098 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012997 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_098/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_098/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_098/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..e7d9dcd5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_098/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_099/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_099/afni_proc/_inputs.pklz new file mode 100644 index 00000000..2e2530ef Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_099/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_099/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_099/afni_proc/_node.pklz new file mode 100644 index 00000000..dcf1b449 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_099/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_099/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_099/afni_proc/_report/report.rst new file mode 100644 index 00000000..b477dcc9 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_099/afni_proc/_report/report.rst @@ -0,0 +1,23 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a052 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 099 + diff --git a/Afni_proc_through_nipype/_subject_id_099/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_099/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..8ebb3cfe Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_099/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_0x53700f75572a6db12ddbea0609d825d6.json b/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_0x53700f75572a6db12ddbea0609d825d6.json new file mode 100644 index 00000000..f2e0ffa2 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_0x53700f75572a6db12ddbea0609d825d6.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "099" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..fcbf141f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_node.pklz new file mode 100644 index 00000000..435790eb Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_report/report.rst new file mode 100644 index 00000000..77fc65ed --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a052 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 099 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 099 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012344 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_099/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_099/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_099/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..7354ef32 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_099/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_0xb8e8a189322147b9c4aacdaf1278ddf1.json b/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_0xb8e8a189322147b9c4aacdaf1278ddf1.json new file mode 100644 index 00000000..2841c38d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_0xb8e8a189322147b9c4aacdaf1278ddf1.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "100" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..307a34af Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_node.pklz new file mode 100644 index 00000000..e1222a1a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_report/report.rst new file mode 100644 index 00000000..c2956956 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a073 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 100 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 100 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012565 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_100/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_100/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_100/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..ed0610ef Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_100/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_102/afni_proc/_0x7b397c40bfa713e8b0f26723621040bc.json b/Afni_proc_through_nipype/_subject_id_102/afni_proc/_0x7b397c40bfa713e8b0f26723621040bc.json new file mode 100644 index 00000000..e2002310 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_102/afni_proc/_0x7b397c40bfa713e8b0f26723621040bc.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "102" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_102/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_102/afni_proc/_inputs.pklz new file mode 100644 index 00000000..42376f9a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_102/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_102/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_102/afni_proc/_node.pklz new file mode 100644 index 00000000..f76caf5f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_102/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_102/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_102/afni_proc/_report/report.rst new file mode 100644 index 00000000..c444e66f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_102/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a051 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 102 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 102 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072565 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_102/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_102/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_102/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..759a9613 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_102/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_0xdd8761564040ddbfdd0333c88f5b5d04.json b/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_0xdd8761564040ddbfdd0333c88f5b5d04.json new file mode 100644 index 00000000..9b31e018 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_0xdd8761564040ddbfdd0333c88f5b5d04.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "102" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..340f0b3e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_node.pklz new file mode 100644 index 00000000..3f4fb4ab Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_report/report.rst new file mode 100644 index 00000000..3476501a --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a051 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 102 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 102 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.035142 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_102/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_102/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_102/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..8f8cd79c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_102/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_0xda419de82cabb6ff026179518fc7254d.json b/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_0xda419de82cabb6ff026179518fc7254d.json new file mode 100644 index 00000000..6f78feae --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_0xda419de82cabb6ff026179518fc7254d.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "103" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..6e708c22 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_node.pklz new file mode 100644 index 00000000..49c95a29 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_report/report.rst new file mode 100644 index 00000000..2c1ec44c --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a075 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 103 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 103 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012406 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_103/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_103/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_103/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..ff81321f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_103/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_0x13cd2b39c9e9fcc85b70577da7095809.json b/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_0x13cd2b39c9e9fcc85b70577da7095809.json new file mode 100644 index 00000000..b4384d6d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_0x13cd2b39c9e9fcc85b70577da7095809.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "104" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..839d5ff9 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_node.pklz new file mode 100644 index 00000000..8f5af748 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_report/report.rst new file mode 100644 index 00000000..9485445f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a085 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 104 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 104 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.0124 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_104/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_104/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_104/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..cfc6e666 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_104/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_105/afni_proc/_0xb89f0009728fded185114954fd09be0a.json b/Afni_proc_through_nipype/_subject_id_105/afni_proc/_0xb89f0009728fded185114954fd09be0a.json new file mode 100644 index 00000000..53d59566 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_105/afni_proc/_0xb89f0009728fded185114954fd09be0a.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "105" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_105/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_105/afni_proc/_inputs.pklz new file mode 100644 index 00000000..8cfea29c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_105/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_105/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_105/afni_proc/_node.pklz new file mode 100644 index 00000000..223c4e92 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_105/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_105/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_105/afni_proc/_report/report.rst new file mode 100644 index 00000000..c740dfd8 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_105/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a043 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 105 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 105 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.073479 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_105/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_105/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_105/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..321172e0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_105/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_0x9cef5ee9021e53deb1d17133128bf8cc.json b/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_0x9cef5ee9021e53deb1d17133128bf8cc.json new file mode 100644 index 00000000..dd70a914 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_0x9cef5ee9021e53deb1d17133128bf8cc.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "105" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..a8d1d2ae Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_node.pklz new file mode 100644 index 00000000..495af99e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_report/report.rst new file mode 100644 index 00000000..72c172ea --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a043 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 105 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 105 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012343 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_105/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_105/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_105/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..ad61dba9 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_105/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_106/afni_proc/_0x4408790cf3576eba1e3b44649c35a937.json b/Afni_proc_through_nipype/_subject_id_106/afni_proc/_0x4408790cf3576eba1e3b44649c35a937.json new file mode 100644 index 00000000..e61b5c6e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_106/afni_proc/_0x4408790cf3576eba1e3b44649c35a937.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "106" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_106/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_106/afni_proc/_inputs.pklz new file mode 100644 index 00000000..e3d37a9d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_106/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_106/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_106/afni_proc/_node.pklz new file mode 100644 index 00000000..ee94595a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_106/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_106/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_106/afni_proc/_report/report.rst new file mode 100644 index 00000000..37ca688a --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_106/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a040 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 106 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 106 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.071412 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_106/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_106/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_106/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..f4bbbab8 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_106/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_0xba6330f8e2e17d9e85d982abbabef116.json b/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_0xba6330f8e2e17d9e85d982abbabef116.json new file mode 100644 index 00000000..5006c2eb --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_0xba6330f8e2e17d9e85d982abbabef116.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "106" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..23c60cd9 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_node.pklz new file mode 100644 index 00000000..f15051d1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_report/report.rst new file mode 100644 index 00000000..5f0eae47 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a040 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 106 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 106 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.033148 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_106/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_106/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_106/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..24d0744a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_106/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_0xd9baabf70b64b42e1bfcb798316eecbd.json b/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_0xd9baabf70b64b42e1bfcb798316eecbd.json new file mode 100644 index 00000000..9c86c950 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_0xd9baabf70b64b42e1bfcb798316eecbd.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "107" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..8aaf4201 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_node.pklz new file mode 100644 index 00000000..d6ad851d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_report/report.rst new file mode 100644 index 00000000..c140507a --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a090 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 107 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 107 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012309 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_107/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_107/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_107/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..4532d8d9 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_107/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_108/afni_proc/_0xa8ba560a0952ffc6c987bc252f5e8f2a.json b/Afni_proc_through_nipype/_subject_id_108/afni_proc/_0xa8ba560a0952ffc6c987bc252f5e8f2a.json new file mode 100644 index 00000000..8f176022 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_108/afni_proc/_0xa8ba560a0952ffc6c987bc252f5e8f2a.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "108" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_108/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_108/afni_proc/_inputs.pklz new file mode 100644 index 00000000..a5b2eb8d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_108/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_108/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_108/afni_proc/_node.pklz new file mode 100644 index 00000000..c6b9bc05 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_108/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_108/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_108/afni_proc/_report/report.rst new file mode 100644 index 00000000..519c8f4f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_108/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a037 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 108 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 108 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.07052 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_108/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_108/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_108/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..dc81f347 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_108/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_0x3a145b4551094625dab75161caa45066.json b/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_0x3a145b4551094625dab75161caa45066.json new file mode 100644 index 00000000..93590d7e --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_0x3a145b4551094625dab75161caa45066.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "108" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..485b21f3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_node.pklz new file mode 100644 index 00000000..d42769bf Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_report/report.rst new file mode 100644 index 00000000..795a7621 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a037 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 108 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 108 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012491 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_108/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_108/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_108/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..5bcaf100 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_108/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_0xf27743b314f96b86ce4efaf7648fb89c.json b/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_0xf27743b314f96b86ce4efaf7648fb89c.json new file mode 100644 index 00000000..cccd06a3 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_0xf27743b314f96b86ce4efaf7648fb89c.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "109" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..06fc8c6a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_node.pklz new file mode 100644 index 00000000..e2abb70d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_report/report.rst new file mode 100644 index 00000000..5f9aac27 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a098 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 109 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 109 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012314 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_109/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_109/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_109/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..2a85063b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_109/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_110/afni_proc/_0x36f70ce00573a8177152ee0dba3978ce.json b/Afni_proc_through_nipype/_subject_id_110/afni_proc/_0x36f70ce00573a8177152ee0dba3978ce.json new file mode 100644 index 00000000..b1a0c1b7 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_110/afni_proc/_0x36f70ce00573a8177152ee0dba3978ce.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "110" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_110/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_110/afni_proc/_inputs.pklz new file mode 100644 index 00000000..342ac140 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_110/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_110/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_110/afni_proc/_node.pklz new file mode 100644 index 00000000..8ab5e751 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_110/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_110/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_110/afni_proc/_report/report.rst new file mode 100644 index 00000000..60e67285 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_110/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a033 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 110 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 110 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.074748 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_110/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_110/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_110/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..e0e7b0e2 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_110/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_0x2802425b9e54b64f9e9b7f212d420d57.json b/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_0x2802425b9e54b64f9e9b7f212d420d57.json new file mode 100644 index 00000000..7746d650 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_0x2802425b9e54b64f9e9b7f212d420d57.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "110" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..0c4eb2a2 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_node.pklz new file mode 100644 index 00000000..616d5881 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_report/report.rst new file mode 100644 index 00000000..cbb45827 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a033 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 110 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 110 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012674 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_110/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_110/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_110/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..3d5fac44 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_110/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_0xb9602c990271f2cc01017ccaf6130fe9.json b/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_0xb9602c990271f2cc01017ccaf6130fe9.json new file mode 100644 index 00000000..a6556864 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_0xb9602c990271f2cc01017ccaf6130fe9.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "112" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..1706298b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_node.pklz new file mode 100644 index 00000000..7afbf9a5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_report/report.rst new file mode 100644 index 00000000..c939605b --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a080 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 112 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 112 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012405 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_112/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_112/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_112/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..cc4394aa Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_112/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_0x8028ec2ab171cdb4a3620d5c50235bdc.json b/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_0x8028ec2ab171cdb4a3620d5c50235bdc.json new file mode 100644 index 00000000..e1de856f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_0x8028ec2ab171cdb4a3620d5c50235bdc.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "113" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..b8795e21 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_node.pklz new file mode 100644 index 00000000..548777c2 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_report/report.rst new file mode 100644 index 00000000..b913822f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a104 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 113 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 113 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012502 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_113/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_113/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_113/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..9b319105 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_113/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_114/afni_proc/_0x91d700cee6ab9eb414550298de7d1f22.json b/Afni_proc_through_nipype/_subject_id_114/afni_proc/_0x91d700cee6ab9eb414550298de7d1f22.json new file mode 100644 index 00000000..908d5da0 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_114/afni_proc/_0x91d700cee6ab9eb414550298de7d1f22.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "114" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_114/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_114/afni_proc/_inputs.pklz new file mode 100644 index 00000000..20485b64 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_114/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_114/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_114/afni_proc/_node.pklz new file mode 100644 index 00000000..19796827 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_114/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_114/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_114/afni_proc/_report/report.rst new file mode 100644 index 00000000..6693a0c8 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_114/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a048 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 114 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 114 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.071345 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_114/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_114/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_114/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..43f1a813 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_114/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_0x1405a9ce75d4c39543fff51cd4d9506f.json b/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_0x1405a9ce75d4c39543fff51cd4d9506f.json new file mode 100644 index 00000000..a57ebe72 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_0x1405a9ce75d4c39543fff51cd4d9506f.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "114" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..88f0dd96 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_node.pklz new file mode 100644 index 00000000..9d15286a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_report/report.rst new file mode 100644 index 00000000..66663356 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a048 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 114 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 114 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012435 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_114/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_114/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_114/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..2435915d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_114/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_0x5127709ab3ac7067acf4cf436c3a5c49.json b/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_0x5127709ab3ac7067acf4cf436c3a5c49.json new file mode 100644 index 00000000..2b1774b7 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_0x5127709ab3ac7067acf4cf436c3a5c49.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "115" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..aceab530 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_node.pklz new file mode 100644 index 00000000..d64c407a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_report/report.rst new file mode 100644 index 00000000..791153c5 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a082 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 115 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 115 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012539 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_115/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_115/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_115/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..d5ce1167 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_115/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_116/afni_proc/_0xe5cb75ed33128b68ebee5635ff6f015a.json b/Afni_proc_through_nipype/_subject_id_116/afni_proc/_0xe5cb75ed33128b68ebee5635ff6f015a.json new file mode 100644 index 00000000..bfa86b24 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_116/afni_proc/_0xe5cb75ed33128b68ebee5635ff6f015a.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "116" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_116/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_116/afni_proc/_inputs.pklz new file mode 100644 index 00000000..851da6c1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_116/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_116/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_116/afni_proc/_node.pklz new file mode 100644 index 00000000..ff1baf89 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_116/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_116/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_116/afni_proc/_report/report.rst new file mode 100644 index 00000000..a8ce0c5d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_116/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a042 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 116 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 116 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.071015 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_116/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_116/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_116/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..9f7f4d13 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_116/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_0x4a7a13e3b7048a4a83a1b10792ee22ec.json b/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_0x4a7a13e3b7048a4a83a1b10792ee22ec.json new file mode 100644 index 00000000..e4a0d720 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_0x4a7a13e3b7048a4a83a1b10792ee22ec.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "116" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..000dfb5b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_node.pklz new file mode 100644 index 00000000..9a65a54a Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_report/report.rst new file mode 100644 index 00000000..3b7dcf31 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a042 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 116 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 116 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.013775 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_116/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_116/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_116/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..abed59fc Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_116/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_117/afni_proc/_0x8acf8af6343b6f4763a526b0a5a3ad6a.json b/Afni_proc_through_nipype/_subject_id_117/afni_proc/_0x8acf8af6343b6f4763a526b0a5a3ad6a.json new file mode 100644 index 00000000..ae435551 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_117/afni_proc/_0x8acf8af6343b6f4763a526b0a5a3ad6a.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "117" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_117/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_117/afni_proc/_inputs.pklz new file mode 100644 index 00000000..d837cfa6 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_117/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_117/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_117/afni_proc/_node.pklz new file mode 100644 index 00000000..3c3a579e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_117/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_117/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_117/afni_proc/_report/report.rst new file mode 100644 index 00000000..219508a6 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_117/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a057 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 117 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 117 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.071836 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_117/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_117/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_117/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..393b989c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_117/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_0xbb6302e2f4b1767c0bfe70340f1011d9.json b/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_0xbb6302e2f4b1767c0bfe70340f1011d9.json new file mode 100644 index 00000000..69bcf607 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_0xbb6302e2f4b1767c0bfe70340f1011d9.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "117" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..4bcb93a1 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_node.pklz new file mode 100644 index 00000000..2ab52d93 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_report/report.rst new file mode 100644 index 00000000..36cc32e2 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a057 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 117 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 117 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012418 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_117/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_117/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_117/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..a658c2c0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_117/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_118/afni_proc/_0xd09e0416cae08054579506f039eb5147.json b/Afni_proc_through_nipype/_subject_id_118/afni_proc/_0xd09e0416cae08054579506f039eb5147.json new file mode 100644 index 00000000..245c0cb9 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_118/afni_proc/_0xd09e0416cae08054579506f039eb5147.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "118" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_118/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_118/afni_proc/_inputs.pklz new file mode 100644 index 00000000..7ef7428e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_118/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_118/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_118/afni_proc/_node.pklz new file mode 100644 index 00000000..197ba03c Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_118/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_118/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_118/afni_proc/_report/report.rst new file mode 100644 index 00000000..c02671c6 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_118/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a011 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 118 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 118 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.073461 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_118/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_118/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_118/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..31a417f9 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_118/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_0x23d3092dcbeb29c96a57146dbeb92b8a.json b/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_0x23d3092dcbeb29c96a57146dbeb92b8a.json new file mode 100644 index 00000000..df8fba29 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_0x23d3092dcbeb29c96a57146dbeb92b8a.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "118" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..df72b5c5 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_node.pklz new file mode 100644 index 00000000..76346352 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_report/report.rst new file mode 100644 index 00000000..dd42c6b1 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a011 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 118 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 118 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012219 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_118/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_118/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_118/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..2ce7ad4e Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_118/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_0x486e06042423a9b68aa41826c53f617b.json b/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_0x486e06042423a9b68aa41826c53f617b.json new file mode 100644 index 00000000..ee08ce36 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_0x486e06042423a9b68aa41826c53f617b.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "119" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..6dd36354 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_node.pklz new file mode 100644 index 00000000..b0e84f98 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_report/report.rst new file mode 100644 index 00000000..b449d661 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a071 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 119 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 119 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012327 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_119/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_119/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_119/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..3e9bb851 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_119/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_0x9d907e30c3d4ff576d4f61ea2c308b47.json b/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_0x9d907e30c3d4ff576d4f61ea2c308b47.json new file mode 100644 index 00000000..540d6b30 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_0x9d907e30c3d4ff576d4f61ea2c308b47.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "120" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..d66f9e27 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_node.pklz new file mode 100644 index 00000000..22eafe1b Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_report/report.rst new file mode 100644 index 00000000..46d64acc --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a097 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 120 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 120 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012304 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_120/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_120/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_120/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..2f6c6ee7 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_120/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_121/afni_proc/_0xf66976ca0b247e935b8418ba04bfb86a.json b/Afni_proc_through_nipype/_subject_id_121/afni_proc/_0xf66976ca0b247e935b8418ba04bfb86a.json new file mode 100644 index 00000000..9528ab25 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_121/afni_proc/_0xf66976ca0b247e935b8418ba04bfb86a.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "121" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_121/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_121/afni_proc/_inputs.pklz new file mode 100644 index 00000000..2af413bc Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_121/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_121/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_121/afni_proc/_node.pklz new file mode 100644 index 00000000..3d132640 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_121/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_121/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_121/afni_proc/_report/report.rst new file mode 100644 index 00000000..090166bc --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_121/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a031 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 121 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 121 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.076281 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_121/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_121/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_121/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..5c20ba52 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_121/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_0x27bc88a639010f6e9d6db14931ddb7e3.json b/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_0x27bc88a639010f6e9d6db14931ddb7e3.json new file mode 100644 index 00000000..dbd7c60d --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_0x27bc88a639010f6e9d6db14931ddb7e3.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "121" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..8acbd857 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_node.pklz new file mode 100644 index 00000000..bd1c8d3d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_report/report.rst new file mode 100644 index 00000000..6abf0263 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a031 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 121 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 121 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012563 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_121/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_121/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_121/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..fd91ad5f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_121/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_123/afni_proc/_0x07d961123977aad61a90906a23f8a450.json b/Afni_proc_through_nipype/_subject_id_123/afni_proc/_0x07d961123977aad61a90906a23f8a450.json new file mode 100644 index 00000000..9a2ca45a --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_123/afni_proc/_0x07d961123977aad61a90906a23f8a450.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "123" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_123/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_123/afni_proc/_inputs.pklz new file mode 100644 index 00000000..9bf4f9e3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_123/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_123/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_123/afni_proc/_node.pklz new file mode 100644 index 00000000..4ae0f78d Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_123/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_123/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_123/afni_proc/_report/report.rst new file mode 100644 index 00000000..d39c875a --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_123/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a017 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 123 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 123 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072011 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_123/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_123/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_123/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..e2b7c604 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_123/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_0x1d7429d15d8dc8bc366cef6fdca6e0ba.json b/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_0x1d7429d15d8dc8bc366cef6fdca6e0ba.json new file mode 100644 index 00000000..39c8e7e7 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_0x1d7429d15d8dc8bc366cef6fdca6e0ba.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "123" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..8f416ad0 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_node.pklz new file mode 100644 index 00000000..e842648f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_report/report.rst new file mode 100644 index 00000000..570a0d5f --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a017 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 123 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 123 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012011 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_123/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_123/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_123/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..ddca115f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_123/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_124/afni_proc/_0x5cb1fba445e30746c5a1ddba11ddaaca.json b/Afni_proc_through_nipype/_subject_id_124/afni_proc/_0x5cb1fba445e30746c5a1ddba11ddaaca.json new file mode 100644 index 00000000..6d99fcfa --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_124/afni_proc/_0x5cb1fba445e30746c5a1ddba11ddaaca.json @@ -0,0 +1,25 @@ +[ + [ + "command", + [ + "/home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel", + "d24bc0377b166d70c1e7e74f97b48e4b" + ] + ], + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def run(command, results_dir, subject, data_dir):\n import subprocess\n subject= \"sub-{}\".format(subject)\n subprocess.run([command, results_dir, subject, data_dir])\n print(\"Done\")\n" + ], + [ + "results_dir", + "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + ], + [ + "subject", + "124" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_124/afni_proc/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_124/afni_proc/_inputs.pklz new file mode 100644 index 00000000..6819994f Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_124/afni_proc/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_124/afni_proc/_node.pklz b/Afni_proc_through_nipype/_subject_id_124/afni_proc/_node.pklz new file mode 100644 index 00000000..ddb2f350 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_124/afni_proc/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_124/afni_proc/_report/report.rst b/Afni_proc_through_nipype/_subject_id_124/afni_proc/_report/report.rst new file mode 100644 index 00000000..9123d459 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_124/afni_proc/_report/report.rst @@ -0,0 +1,126 @@ +Node: afni_proc (utility) +========================= + + + Hierarchy : Afni_proc_through_nipype.afni_proc + Exec ID : afni_proc.a063 + + +Original Inputs +--------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 124 + + +Execution Inputs +---------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +* results_dir : /home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/ +* subject : 124 + + +Execution Outputs +----------------- + + +* Adni_1stLevel : None + + +Runtime info +------------ + + +* duration : 0.072925 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_124/afni_proc + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_124/afni_proc/result_afni_proc.pklz b/Afni_proc_through_nipype/_subject_id_124/afni_proc/result_afni_proc.pklz new file mode 100644 index 00000000..4909d341 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_124/afni_proc/result_afni_proc.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_0xee20d4b7506c6a5d86c5f408e9250c9f.json b/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_0xee20d4b7506c6a5d86c5f408e9250c9f.json new file mode 100644 index 00000000..79ff6304 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_0xee20d4b7506c6a5d86c5f408e9250c9f.json @@ -0,0 +1,14 @@ +[ + [ + "data_dir", + "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" + ], + [ + "function_str", + "def create_stimuli_file(subject, data_dir):\n # create 1D stimuli file :\n import pandas as pd \n from os.path import join as opj\n df_run1 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-01_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run1 = df_run1[[\"onset\", \"gain\", \"loss\"]].T\n df_run2 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-02_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run2 = df_run2[[\"onset\", \"gain\", \"loss\"]].T\n df_run3 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-03_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run3 = df_run3[[\"onset\", \"gain\", \"loss\"]].T\n df_run4 = pd.read_csv(opj(data_dir, \"sub-{}/func/sub-{}_task-MGT_run-04_events.tsv\".format(subject, subject)), sep=\"\\t\")\n df_run4 = df_run4[[\"onset\", \"gain\", \"loss\"]].T\n\n df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_gain.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)]\n df_gain.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)]\n df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64))\n df_loss.loc[0] = [\"{}*{}\".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[1] = [\"{}*{}\".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[2] = [\"{}*{}\".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)]\n df_loss.loc[3] = [\"{}*{}\".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)]\n\n df_gain.to_csv(opj(data_dir, \"sub-{}/func/times+gain.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n df_loss.to_csv(opj(data_dir, \"sub-{}/func/times+loss.1D\".format(subject)), \n sep='\\t', index=False, header=False)\n print(\"Done\")\n" + ], + [ + "subject", + "124" + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_inputs.pklz b/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_inputs.pklz new file mode 100644 index 00000000..e1e3e2a3 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_node.pklz b/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_node.pklz new file mode 100644 index 00000000..3536c080 Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_node.pklz differ diff --git a/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_report/report.rst b/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_report/report.rst new file mode 100644 index 00000000..6a4e7db9 --- /dev/null +++ b/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_report/report.rst @@ -0,0 +1,170 @@ +Node: create_stimuli (utility) +============================== + + + Hierarchy : Afni_proc_through_nipype.create_stimuli + Exec ID : create_stimuli.a063 + + +Original Inputs +--------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 124 + + +Execution Inputs +---------------- + + +* data_dir : /home/jlefortb/narps_open_pipelines/data/original/ds001734/ +* function_str : def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +* subject : 124 + + +Execution Outputs +----------------- + + +* Stimuli : None + + +Runtime info +------------ + + +* duration : 0.012064 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_124/create_stimuli + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/_subject_id_124/create_stimuli/result_create_stimuli.pklz b/Afni_proc_through_nipype/_subject_id_124/create_stimuli/result_create_stimuli.pklz new file mode 100644 index 00000000..862c94cb Binary files /dev/null and b/Afni_proc_through_nipype/_subject_id_124/create_stimuli/result_create_stimuli.pklz differ diff --git a/Afni_proc_through_nipype/d3.js b/Afni_proc_through_nipype/d3.js new file mode 100644 index 00000000..e1ddb037 --- /dev/null +++ b/Afni_proc_through_nipype/d3.js @@ -0,0 +1,9255 @@ +!function() { + var d3 = { + version: "3.4.8" + }; + if (!Date.now) Date.now = function() { + return +new Date(); + }; + var d3_arraySlice = [].slice, d3_array = function(list) { + return d3_arraySlice.call(list); + }; + var d3_document = document, d3_documentElement = d3_document.documentElement, d3_window = window; + try { + d3_array(d3_documentElement.childNodes)[0].nodeType; + } catch (e) { + d3_array = function(list) { + var i = list.length, array = new Array(i); + while (i--) array[i] = list[i]; + return array; + }; + } + try { + d3_document.createElement("div").style.setProperty("opacity", 0, ""); + } catch (error) { + var d3_element_prototype = d3_window.Element.prototype, d3_element_setAttribute = d3_element_prototype.setAttribute, d3_element_setAttributeNS = d3_element_prototype.setAttributeNS, d3_style_prototype = d3_window.CSSStyleDeclaration.prototype, d3_style_setProperty = d3_style_prototype.setProperty; + d3_element_prototype.setAttribute = function(name, value) { + d3_element_setAttribute.call(this, name, value + ""); + }; + d3_element_prototype.setAttributeNS = function(space, local, value) { + d3_element_setAttributeNS.call(this, space, local, value + ""); + }; + d3_style_prototype.setProperty = function(name, value, priority) { + d3_style_setProperty.call(this, name, value + "", priority); + }; + } + d3.ascending = d3_ascending; + function d3_ascending(a, b) { + return a < b ? -1 : a > b ? 1 : a >= b ? 0 : NaN; + } + d3.descending = function(a, b) { + return b < a ? -1 : b > a ? 1 : b >= a ? 0 : NaN; + }; + d3.min = function(array, f) { + var i = -1, n = array.length, a, b; + if (arguments.length === 1) { + while (++i < n && !((a = array[i]) != null && a <= a)) a = undefined; + while (++i < n) if ((b = array[i]) != null && a > b) a = b; + } else { + while (++i < n && !((a = f.call(array, array[i], i)) != null && a <= a)) a = undefined; + while (++i < n) if ((b = f.call(array, array[i], i)) != null && a > b) a = b; + } + return a; + }; + d3.max = function(array, f) { + var i = -1, n = array.length, a, b; + if (arguments.length === 1) { + while (++i < n && !((a = array[i]) != null && a <= a)) a = undefined; + while (++i < n) if ((b = array[i]) != null && b > a) a = b; + } else { + while (++i < n && !((a = f.call(array, array[i], i)) != null && a <= a)) a = undefined; + while (++i < n) if ((b = f.call(array, array[i], i)) != null && b > a) a = b; + } + return a; + }; + d3.extent = function(array, f) { + var i = -1, n = array.length, a, b, c; + if (arguments.length === 1) { + while (++i < n && !((a = c = array[i]) != null && a <= a)) a = c = undefined; + while (++i < n) if ((b = array[i]) != null) { + if (a > b) a = b; + if (c < b) c = b; + } + } else { + while (++i < n && !((a = c = f.call(array, array[i], i)) != null && a <= a)) a = undefined; + while (++i < n) if ((b = f.call(array, array[i], i)) != null) { + if (a > b) a = b; + if (c < b) c = b; + } + } + return [ a, c ]; + }; + d3.sum = function(array, f) { + var s = 0, n = array.length, a, i = -1; + if (arguments.length === 1) { + while (++i < n) if (!isNaN(a = +array[i])) s += a; + } else { + while (++i < n) if (!isNaN(a = +f.call(array, array[i], i))) s += a; + } + return s; + }; + function d3_number(x) { + return x != null && !isNaN(x); + } + d3.mean = function(array, f) { + var s = 0, n = array.length, a, i = -1, j = n; + if (arguments.length === 1) { + while (++i < n) if (d3_number(a = array[i])) s += a; else --j; + } else { + while (++i < n) if (d3_number(a = f.call(array, array[i], i))) s += a; else --j; + } + return j ? s / j : undefined; + }; + d3.quantile = function(values, p) { + var H = (values.length - 1) * p + 1, h = Math.floor(H), v = +values[h - 1], e = H - h; + return e ? v + e * (values[h] - v) : v; + }; + d3.median = function(array, f) { + if (arguments.length > 1) array = array.map(f); + array = array.filter(d3_number); + return array.length ? d3.quantile(array.sort(d3_ascending), .5) : undefined; + }; + function d3_bisector(compare) { + return { + left: function(a, x, lo, hi) { + if (arguments.length < 3) lo = 0; + if (arguments.length < 4) hi = a.length; + while (lo < hi) { + var mid = lo + hi >>> 1; + if (compare(a[mid], x) < 0) lo = mid + 1; else hi = mid; + } + return lo; + }, + right: function(a, x, lo, hi) { + if (arguments.length < 3) lo = 0; + if (arguments.length < 4) hi = a.length; + while (lo < hi) { + var mid = lo + hi >>> 1; + if (compare(a[mid], x) > 0) hi = mid; else lo = mid + 1; + } + return lo; + } + }; + } + var d3_bisect = d3_bisector(d3_ascending); + d3.bisectLeft = d3_bisect.left; + d3.bisect = d3.bisectRight = d3_bisect.right; + d3.bisector = function(f) { + return d3_bisector(f.length === 1 ? function(d, x) { + return d3_ascending(f(d), x); + } : f); + }; + d3.shuffle = function(array) { + var m = array.length, t, i; + while (m) { + i = Math.random() * m-- | 0; + t = array[m], array[m] = array[i], array[i] = t; + } + return array; + }; + d3.permute = function(array, indexes) { + var i = indexes.length, permutes = new Array(i); + while (i--) permutes[i] = array[indexes[i]]; + return permutes; + }; + d3.pairs = function(array) { + var i = 0, n = array.length - 1, p0, p1 = array[0], pairs = new Array(n < 0 ? 0 : n); + while (i < n) pairs[i] = [ p0 = p1, p1 = array[++i] ]; + return pairs; + }; + d3.zip = function() { + if (!(n = arguments.length)) return []; + for (var i = -1, m = d3.min(arguments, d3_zipLength), zips = new Array(m); ++i < m; ) { + for (var j = -1, n, zip = zips[i] = new Array(n); ++j < n; ) { + zip[j] = arguments[j][i]; + } + } + return zips; + }; + function d3_zipLength(d) { + return d.length; + } + d3.transpose = function(matrix) { + return d3.zip.apply(d3, matrix); + }; + d3.keys = function(map) { + var keys = []; + for (var key in map) keys.push(key); + return keys; + }; + d3.values = function(map) { + var values = []; + for (var key in map) values.push(map[key]); + return values; + }; + d3.entries = function(map) { + var entries = []; + for (var key in map) entries.push({ + key: key, + value: map[key] + }); + return entries; + }; + d3.merge = function(arrays) { + var n = arrays.length, m, i = -1, j = 0, merged, array; + while (++i < n) j += arrays[i].length; + merged = new Array(j); + while (--n >= 0) { + array = arrays[n]; + m = array.length; + while (--m >= 0) { + merged[--j] = array[m]; + } + } + return merged; + }; + var abs = Math.abs; + d3.range = function(start, stop, step) { + if (arguments.length < 3) { + step = 1; + if (arguments.length < 2) { + stop = start; + start = 0; + } + } + if ((stop - start) / step === Infinity) throw new Error("infinite range"); + var range = [], k = d3_range_integerScale(abs(step)), i = -1, j; + start *= k, stop *= k, step *= k; + if (step < 0) while ((j = start + step * ++i) > stop) range.push(j / k); else while ((j = start + step * ++i) < stop) range.push(j / k); + return range; + }; + function d3_range_integerScale(x) { + var k = 1; + while (x * k % 1) k *= 10; + return k; + } + function d3_class(ctor, properties) { + try { + for (var key in properties) { + Object.defineProperty(ctor.prototype, key, { + value: properties[key], + enumerable: false + }); + } + } catch (e) { + ctor.prototype = properties; + } + } + d3.map = function(object) { + var map = new d3_Map(); + if (object instanceof d3_Map) object.forEach(function(key, value) { + map.set(key, value); + }); else for (var key in object) map.set(key, object[key]); + return map; + }; + function d3_Map() {} + d3_class(d3_Map, { + has: d3_map_has, + get: function(key) { + return this[d3_map_prefix + key]; + }, + set: function(key, value) { + return this[d3_map_prefix + key] = value; + }, + remove: d3_map_remove, + keys: d3_map_keys, + values: function() { + var values = []; + this.forEach(function(key, value) { + values.push(value); + }); + return values; + }, + entries: function() { + var entries = []; + this.forEach(function(key, value) { + entries.push({ + key: key, + value: value + }); + }); + return entries; + }, + size: d3_map_size, + empty: d3_map_empty, + forEach: function(f) { + for (var key in this) if (key.charCodeAt(0) === d3_map_prefixCode) f.call(this, key.substring(1), this[key]); + } + }); + var d3_map_prefix = "\x00", d3_map_prefixCode = d3_map_prefix.charCodeAt(0); + function d3_map_has(key) { + return d3_map_prefix + key in this; + } + function d3_map_remove(key) { + key = d3_map_prefix + key; + return key in this && delete this[key]; + } + function d3_map_keys() { + var keys = []; + this.forEach(function(key) { + keys.push(key); + }); + return keys; + } + function d3_map_size() { + var size = 0; + for (var key in this) if (key.charCodeAt(0) === d3_map_prefixCode) ++size; + return size; + } + function d3_map_empty() { + for (var key in this) if (key.charCodeAt(0) === d3_map_prefixCode) return false; + return true; + } + d3.nest = function() { + var nest = {}, keys = [], sortKeys = [], sortValues, rollup; + function map(mapType, array, depth) { + if (depth >= keys.length) return rollup ? rollup.call(nest, array) : sortValues ? array.sort(sortValues) : array; + var i = -1, n = array.length, key = keys[depth++], keyValue, object, setter, valuesByKey = new d3_Map(), values; + while (++i < n) { + if (values = valuesByKey.get(keyValue = key(object = array[i]))) { + values.push(object); + } else { + valuesByKey.set(keyValue, [ object ]); + } + } + if (mapType) { + object = mapType(); + setter = function(keyValue, values) { + object.set(keyValue, map(mapType, values, depth)); + }; + } else { + object = {}; + setter = function(keyValue, values) { + object[keyValue] = map(mapType, values, depth); + }; + } + valuesByKey.forEach(setter); + return object; + } + function entries(map, depth) { + if (depth >= keys.length) return map; + var array = [], sortKey = sortKeys[depth++]; + map.forEach(function(key, keyMap) { + array.push({ + key: key, + values: entries(keyMap, depth) + }); + }); + return sortKey ? array.sort(function(a, b) { + return sortKey(a.key, b.key); + }) : array; + } + nest.map = function(array, mapType) { + return map(mapType, array, 0); + }; + nest.entries = function(array) { + return entries(map(d3.map, array, 0), 0); + }; + nest.key = function(d) { + keys.push(d); + return nest; + }; + nest.sortKeys = function(order) { + sortKeys[keys.length - 1] = order; + return nest; + }; + nest.sortValues = function(order) { + sortValues = order; + return nest; + }; + nest.rollup = function(f) { + rollup = f; + return nest; + }; + return nest; + }; + d3.set = function(array) { + var set = new d3_Set(); + if (array) for (var i = 0, n = array.length; i < n; ++i) set.add(array[i]); + return set; + }; + function d3_Set() {} + d3_class(d3_Set, { + has: d3_map_has, + add: function(value) { + this[d3_map_prefix + value] = true; + return value; + }, + remove: function(value) { + value = d3_map_prefix + value; + return value in this && delete this[value]; + }, + values: d3_map_keys, + size: d3_map_size, + empty: d3_map_empty, + forEach: function(f) { + for (var value in this) if (value.charCodeAt(0) === d3_map_prefixCode) f.call(this, value.substring(1)); + } + }); + d3.behavior = {}; + d3.rebind = function(target, source) { + var i = 1, n = arguments.length, method; + while (++i < n) target[method = arguments[i]] = d3_rebind(target, source, source[method]); + return target; + }; + function d3_rebind(target, source, method) { + return function() { + var value = method.apply(source, arguments); + return value === source ? target : value; + }; + } + function d3_vendorSymbol(object, name) { + if (name in object) return name; + name = name.charAt(0).toUpperCase() + name.substring(1); + for (var i = 0, n = d3_vendorPrefixes.length; i < n; ++i) { + var prefixName = d3_vendorPrefixes[i] + name; + if (prefixName in object) return prefixName; + } + } + var d3_vendorPrefixes = [ "webkit", "ms", "moz", "Moz", "o", "O" ]; + function d3_noop() {} + d3.dispatch = function() { + var dispatch = new d3_dispatch(), i = -1, n = arguments.length; + while (++i < n) dispatch[arguments[i]] = d3_dispatch_event(dispatch); + return dispatch; + }; + function d3_dispatch() {} + d3_dispatch.prototype.on = function(type, listener) { + var i = type.indexOf("."), name = ""; + if (i >= 0) { + name = type.substring(i + 1); + type = type.substring(0, i); + } + if (type) return arguments.length < 2 ? this[type].on(name) : this[type].on(name, listener); + if (arguments.length === 2) { + if (listener == null) for (type in this) { + if (this.hasOwnProperty(type)) this[type].on(name, null); + } + return this; + } + }; + function d3_dispatch_event(dispatch) { + var listeners = [], listenerByName = new d3_Map(); + function event() { + var z = listeners, i = -1, n = z.length, l; + while (++i < n) if (l = z[i].on) l.apply(this, arguments); + return dispatch; + } + event.on = function(name, listener) { + var l = listenerByName.get(name), i; + if (arguments.length < 2) return l && l.on; + if (l) { + l.on = null; + listeners = listeners.slice(0, i = listeners.indexOf(l)).concat(listeners.slice(i + 1)); + listenerByName.remove(name); + } + if (listener) listeners.push(listenerByName.set(name, { + on: listener + })); + return dispatch; + }; + return event; + } + d3.event = null; + function d3_eventPreventDefault() { + d3.event.preventDefault(); + } + function d3_eventSource() { + var e = d3.event, s; + while (s = e.sourceEvent) e = s; + return e; + } + function d3_eventDispatch(target) { + var dispatch = new d3_dispatch(), i = 0, n = arguments.length; + while (++i < n) dispatch[arguments[i]] = d3_dispatch_event(dispatch); + dispatch.of = function(thiz, argumentz) { + return function(e1) { + try { + var e0 = e1.sourceEvent = d3.event; + e1.target = target; + d3.event = e1; + dispatch[e1.type].apply(thiz, argumentz); + } finally { + d3.event = e0; + } + }; + }; + return dispatch; + } + d3.requote = function(s) { + return s.replace(d3_requote_re, "\\$&"); + }; + var d3_requote_re = /[\\\^\$\*\+\?\|\[\]\(\)\.\{\}]/g; + var d3_subclass = {}.__proto__ ? function(object, prototype) { + object.__proto__ = prototype; + } : function(object, prototype) { + for (var property in prototype) object[property] = prototype[property]; + }; + function d3_selection(groups) { + d3_subclass(groups, d3_selectionPrototype); + return groups; + } + var d3_select = function(s, n) { + return n.querySelector(s); + }, d3_selectAll = function(s, n) { + return n.querySelectorAll(s); + }, d3_selectMatcher = d3_documentElement[d3_vendorSymbol(d3_documentElement, "matchesSelector")], d3_selectMatches = function(n, s) { + return d3_selectMatcher.call(n, s); + }; + if (typeof Sizzle === "function") { + d3_select = function(s, n) { + return Sizzle(s, n)[0] || null; + }; + d3_selectAll = Sizzle; + d3_selectMatches = Sizzle.matchesSelector; + } + d3.selection = function() { + return d3_selectionRoot; + }; + var d3_selectionPrototype = d3.selection.prototype = []; + d3_selectionPrototype.select = function(selector) { + var subgroups = [], subgroup, subnode, group, node; + selector = d3_selection_selector(selector); + for (var j = -1, m = this.length; ++j < m; ) { + subgroups.push(subgroup = []); + subgroup.parentNode = (group = this[j]).parentNode; + for (var i = -1, n = group.length; ++i < n; ) { + if (node = group[i]) { + subgroup.push(subnode = selector.call(node, node.__data__, i, j)); + if (subnode && "__data__" in node) subnode.__data__ = node.__data__; + } else { + subgroup.push(null); + } + } + } + return d3_selection(subgroups); + }; + function d3_selection_selector(selector) { + return typeof selector === "function" ? selector : function() { + return d3_select(selector, this); + }; + } + d3_selectionPrototype.selectAll = function(selector) { + var subgroups = [], subgroup, node; + selector = d3_selection_selectorAll(selector); + for (var j = -1, m = this.length; ++j < m; ) { + for (var group = this[j], i = -1, n = group.length; ++i < n; ) { + if (node = group[i]) { + subgroups.push(subgroup = d3_array(selector.call(node, node.__data__, i, j))); + subgroup.parentNode = node; + } + } + } + return d3_selection(subgroups); + }; + function d3_selection_selectorAll(selector) { + return typeof selector === "function" ? selector : function() { + return d3_selectAll(selector, this); + }; + } + var d3_nsPrefix = { + svg: "http://www.w3.org/2000/svg", + xhtml: "http://www.w3.org/1999/xhtml", + xlink: "http://www.w3.org/1999/xlink", + xml: "http://www.w3.org/XML/1998/namespace", + xmlns: "http://www.w3.org/2000/xmlns/" + }; + d3.ns = { + prefix: d3_nsPrefix, + qualify: function(name) { + var i = name.indexOf(":"), prefix = name; + if (i >= 0) { + prefix = name.substring(0, i); + name = name.substring(i + 1); + } + return d3_nsPrefix.hasOwnProperty(prefix) ? { + space: d3_nsPrefix[prefix], + local: name + } : name; + } + }; + d3_selectionPrototype.attr = function(name, value) { + if (arguments.length < 2) { + if (typeof name === "string") { + var node = this.node(); + name = d3.ns.qualify(name); + return name.local ? node.getAttributeNS(name.space, name.local) : node.getAttribute(name); + } + for (value in name) this.each(d3_selection_attr(value, name[value])); + return this; + } + return this.each(d3_selection_attr(name, value)); + }; + function d3_selection_attr(name, value) { + name = d3.ns.qualify(name); + function attrNull() { + this.removeAttribute(name); + } + function attrNullNS() { + this.removeAttributeNS(name.space, name.local); + } + function attrConstant() { + this.setAttribute(name, value); + } + function attrConstantNS() { + this.setAttributeNS(name.space, name.local, value); + } + function attrFunction() { + var x = value.apply(this, arguments); + if (x == null) this.removeAttribute(name); else this.setAttribute(name, x); + } + function attrFunctionNS() { + var x = value.apply(this, arguments); + if (x == null) this.removeAttributeNS(name.space, name.local); else this.setAttributeNS(name.space, name.local, x); + } + return value == null ? name.local ? attrNullNS : attrNull : typeof value === "function" ? name.local ? attrFunctionNS : attrFunction : name.local ? attrConstantNS : attrConstant; + } + function d3_collapse(s) { + return s.trim().replace(/\s+/g, " "); + } + d3_selectionPrototype.classed = function(name, value) { + if (arguments.length < 2) { + if (typeof name === "string") { + var node = this.node(), n = (name = d3_selection_classes(name)).length, i = -1; + if (value = node.classList) { + while (++i < n) if (!value.contains(name[i])) return false; + } else { + value = node.getAttribute("class"); + while (++i < n) if (!d3_selection_classedRe(name[i]).test(value)) return false; + } + return true; + } + for (value in name) this.each(d3_selection_classed(value, name[value])); + return this; + } + return this.each(d3_selection_classed(name, value)); + }; + function d3_selection_classedRe(name) { + return new RegExp("(?:^|\\s+)" + d3.requote(name) + "(?:\\s+|$)", "g"); + } + function d3_selection_classes(name) { + return name.trim().split(/^|\s+/); + } + function d3_selection_classed(name, value) { + name = d3_selection_classes(name).map(d3_selection_classedName); + var n = name.length; + function classedConstant() { + var i = -1; + while (++i < n) name[i](this, value); + } + function classedFunction() { + var i = -1, x = value.apply(this, arguments); + while (++i < n) name[i](this, x); + } + return typeof value === "function" ? classedFunction : classedConstant; + } + function d3_selection_classedName(name) { + var re = d3_selection_classedRe(name); + return function(node, value) { + if (c = node.classList) return value ? c.add(name) : c.remove(name); + var c = node.getAttribute("class") || ""; + if (value) { + re.lastIndex = 0; + if (!re.test(c)) node.setAttribute("class", d3_collapse(c + " " + name)); + } else { + node.setAttribute("class", d3_collapse(c.replace(re, " "))); + } + }; + } + d3_selectionPrototype.style = function(name, value, priority) { + var n = arguments.length; + if (n < 3) { + if (typeof name !== "string") { + if (n < 2) value = ""; + for (priority in name) this.each(d3_selection_style(priority, name[priority], value)); + return this; + } + if (n < 2) return d3_window.getComputedStyle(this.node(), null).getPropertyValue(name); + priority = ""; + } + return this.each(d3_selection_style(name, value, priority)); + }; + function d3_selection_style(name, value, priority) { + function styleNull() { + this.style.removeProperty(name); + } + function styleConstant() { + this.style.setProperty(name, value, priority); + } + function styleFunction() { + var x = value.apply(this, arguments); + if (x == null) this.style.removeProperty(name); else this.style.setProperty(name, x, priority); + } + return value == null ? styleNull : typeof value === "function" ? styleFunction : styleConstant; + } + d3_selectionPrototype.property = function(name, value) { + if (arguments.length < 2) { + if (typeof name === "string") return this.node()[name]; + for (value in name) this.each(d3_selection_property(value, name[value])); + return this; + } + return this.each(d3_selection_property(name, value)); + }; + function d3_selection_property(name, value) { + function propertyNull() { + delete this[name]; + } + function propertyConstant() { + this[name] = value; + } + function propertyFunction() { + var x = value.apply(this, arguments); + if (x == null) delete this[name]; else this[name] = x; + } + return value == null ? propertyNull : typeof value === "function" ? propertyFunction : propertyConstant; + } + d3_selectionPrototype.text = function(value) { + return arguments.length ? this.each(typeof value === "function" ? function() { + var v = value.apply(this, arguments); + this.textContent = v == null ? "" : v; + } : value == null ? function() { + this.textContent = ""; + } : function() { + this.textContent = value; + }) : this.node().textContent; + }; + d3_selectionPrototype.html = function(value) { + return arguments.length ? this.each(typeof value === "function" ? function() { + var v = value.apply(this, arguments); + this.innerHTML = v == null ? "" : v; + } : value == null ? function() { + this.innerHTML = ""; + } : function() { + this.innerHTML = value; + }) : this.node().innerHTML; + }; + d3_selectionPrototype.append = function(name) { + name = d3_selection_creator(name); + return this.select(function() { + return this.appendChild(name.apply(this, arguments)); + }); + }; + function d3_selection_creator(name) { + return typeof name === "function" ? name : (name = d3.ns.qualify(name)).local ? function() { + return this.ownerDocument.createElementNS(name.space, name.local); + } : function() { + return this.ownerDocument.createElementNS(this.namespaceURI, name); + }; + } + d3_selectionPrototype.insert = function(name, before) { + name = d3_selection_creator(name); + before = d3_selection_selector(before); + return this.select(function() { + return this.insertBefore(name.apply(this, arguments), before.apply(this, arguments) || null); + }); + }; + d3_selectionPrototype.remove = function() { + return this.each(function() { + var parent = this.parentNode; + if (parent) parent.removeChild(this); + }); + }; + d3_selectionPrototype.data = function(value, key) { + var i = -1, n = this.length, group, node; + if (!arguments.length) { + value = new Array(n = (group = this[0]).length); + while (++i < n) { + if (node = group[i]) { + value[i] = node.__data__; + } + } + return value; + } + function bind(group, groupData) { + var i, n = group.length, m = groupData.length, n0 = Math.min(n, m), updateNodes = new Array(m), enterNodes = new Array(m), exitNodes = new Array(n), node, nodeData; + if (key) { + var nodeByKeyValue = new d3_Map(), dataByKeyValue = new d3_Map(), keyValues = [], keyValue; + for (i = -1; ++i < n; ) { + keyValue = key.call(node = group[i], node.__data__, i); + if (nodeByKeyValue.has(keyValue)) { + exitNodes[i] = node; + } else { + nodeByKeyValue.set(keyValue, node); + } + keyValues.push(keyValue); + } + for (i = -1; ++i < m; ) { + keyValue = key.call(groupData, nodeData = groupData[i], i); + if (node = nodeByKeyValue.get(keyValue)) { + updateNodes[i] = node; + node.__data__ = nodeData; + } else if (!dataByKeyValue.has(keyValue)) { + enterNodes[i] = d3_selection_dataNode(nodeData); + } + dataByKeyValue.set(keyValue, nodeData); + nodeByKeyValue.remove(keyValue); + } + for (i = -1; ++i < n; ) { + if (nodeByKeyValue.has(keyValues[i])) { + exitNodes[i] = group[i]; + } + } + } else { + for (i = -1; ++i < n0; ) { + node = group[i]; + nodeData = groupData[i]; + if (node) { + node.__data__ = nodeData; + updateNodes[i] = node; + } else { + enterNodes[i] = d3_selection_dataNode(nodeData); + } + } + for (;i < m; ++i) { + enterNodes[i] = d3_selection_dataNode(groupData[i]); + } + for (;i < n; ++i) { + exitNodes[i] = group[i]; + } + } + enterNodes.update = updateNodes; + enterNodes.parentNode = updateNodes.parentNode = exitNodes.parentNode = group.parentNode; + enter.push(enterNodes); + update.push(updateNodes); + exit.push(exitNodes); + } + var enter = d3_selection_enter([]), update = d3_selection([]), exit = d3_selection([]); + if (typeof value === "function") { + while (++i < n) { + bind(group = this[i], value.call(group, group.parentNode.__data__, i)); + } + } else { + while (++i < n) { + bind(group = this[i], value); + } + } + update.enter = function() { + return enter; + }; + update.exit = function() { + return exit; + }; + return update; + }; + function d3_selection_dataNode(data) { + return { + __data__: data + }; + } + d3_selectionPrototype.datum = function(value) { + return arguments.length ? this.property("__data__", value) : this.property("__data__"); + }; + d3_selectionPrototype.filter = function(filter) { + var subgroups = [], subgroup, group, node; + if (typeof filter !== "function") filter = d3_selection_filter(filter); + for (var j = 0, m = this.length; j < m; j++) { + subgroups.push(subgroup = []); + subgroup.parentNode = (group = this[j]).parentNode; + for (var i = 0, n = group.length; i < n; i++) { + if ((node = group[i]) && filter.call(node, node.__data__, i, j)) { + subgroup.push(node); + } + } + } + return d3_selection(subgroups); + }; + function d3_selection_filter(selector) { + return function() { + return d3_selectMatches(this, selector); + }; + } + d3_selectionPrototype.order = function() { + for (var j = -1, m = this.length; ++j < m; ) { + for (var group = this[j], i = group.length - 1, next = group[i], node; --i >= 0; ) { + if (node = group[i]) { + if (next && next !== node.nextSibling) next.parentNode.insertBefore(node, next); + next = node; + } + } + } + return this; + }; + d3_selectionPrototype.sort = function(comparator) { + comparator = d3_selection_sortComparator.apply(this, arguments); + for (var j = -1, m = this.length; ++j < m; ) this[j].sort(comparator); + return this.order(); + }; + function d3_selection_sortComparator(comparator) { + if (!arguments.length) comparator = d3_ascending; + return function(a, b) { + return a && b ? comparator(a.__data__, b.__data__) : !a - !b; + }; + } + d3_selectionPrototype.each = function(callback) { + return d3_selection_each(this, function(node, i, j) { + callback.call(node, node.__data__, i, j); + }); + }; + function d3_selection_each(groups, callback) { + for (var j = 0, m = groups.length; j < m; j++) { + for (var group = groups[j], i = 0, n = group.length, node; i < n; i++) { + if (node = group[i]) callback(node, i, j); + } + } + return groups; + } + d3_selectionPrototype.call = function(callback) { + var args = d3_array(arguments); + callback.apply(args[0] = this, args); + return this; + }; + d3_selectionPrototype.empty = function() { + return !this.node(); + }; + d3_selectionPrototype.node = function() { + for (var j = 0, m = this.length; j < m; j++) { + for (var group = this[j], i = 0, n = group.length; i < n; i++) { + var node = group[i]; + if (node) return node; + } + } + return null; + }; + d3_selectionPrototype.size = function() { + var n = 0; + this.each(function() { + ++n; + }); + return n; + }; + function d3_selection_enter(selection) { + d3_subclass(selection, d3_selection_enterPrototype); + return selection; + } + var d3_selection_enterPrototype = []; + d3.selection.enter = d3_selection_enter; + d3.selection.enter.prototype = d3_selection_enterPrototype; + d3_selection_enterPrototype.append = d3_selectionPrototype.append; + d3_selection_enterPrototype.empty = d3_selectionPrototype.empty; + d3_selection_enterPrototype.node = d3_selectionPrototype.node; + d3_selection_enterPrototype.call = d3_selectionPrototype.call; + d3_selection_enterPrototype.size = d3_selectionPrototype.size; + d3_selection_enterPrototype.select = function(selector) { + var subgroups = [], subgroup, subnode, upgroup, group, node; + for (var j = -1, m = this.length; ++j < m; ) { + upgroup = (group = this[j]).update; + subgroups.push(subgroup = []); + subgroup.parentNode = group.parentNode; + for (var i = -1, n = group.length; ++i < n; ) { + if (node = group[i]) { + subgroup.push(upgroup[i] = subnode = selector.call(group.parentNode, node.__data__, i, j)); + subnode.__data__ = node.__data__; + } else { + subgroup.push(null); + } + } + } + return d3_selection(subgroups); + }; + d3_selection_enterPrototype.insert = function(name, before) { + if (arguments.length < 2) before = d3_selection_enterInsertBefore(this); + return d3_selectionPrototype.insert.call(this, name, before); + }; + function d3_selection_enterInsertBefore(enter) { + var i0, j0; + return function(d, i, j) { + var group = enter[j].update, n = group.length, node; + if (j != j0) j0 = j, i0 = 0; + if (i >= i0) i0 = i + 1; + while (!(node = group[i0]) && ++i0 < n) ; + return node; + }; + } + d3_selectionPrototype.transition = function() { + var id = d3_transitionInheritId || ++d3_transitionId, subgroups = [], subgroup, node, transition = d3_transitionInherit || { + time: Date.now(), + ease: d3_ease_cubicInOut, + delay: 0, + duration: 250 + }; + for (var j = -1, m = this.length; ++j < m; ) { + subgroups.push(subgroup = []); + for (var group = this[j], i = -1, n = group.length; ++i < n; ) { + if (node = group[i]) d3_transitionNode(node, i, id, transition); + subgroup.push(node); + } + } + return d3_transition(subgroups, id); + }; + d3_selectionPrototype.interrupt = function() { + return this.each(d3_selection_interrupt); + }; + function d3_selection_interrupt() { + var lock = this.__transition__; + if (lock) ++lock.active; + } + d3.select = function(node) { + var group = [ typeof node === "string" ? d3_select(node, d3_document) : node ]; + group.parentNode = d3_documentElement; + return d3_selection([ group ]); + }; + d3.selectAll = function(nodes) { + var group = d3_array(typeof nodes === "string" ? d3_selectAll(nodes, d3_document) : nodes); + group.parentNode = d3_documentElement; + return d3_selection([ group ]); + }; + var d3_selectionRoot = d3.select(d3_documentElement); + d3_selectionPrototype.on = function(type, listener, capture) { + var n = arguments.length; + if (n < 3) { + if (typeof type !== "string") { + if (n < 2) listener = false; + for (capture in type) this.each(d3_selection_on(capture, type[capture], listener)); + return this; + } + if (n < 2) return (n = this.node()["__on" + type]) && n._; + capture = false; + } + return this.each(d3_selection_on(type, listener, capture)); + }; + function d3_selection_on(type, listener, capture) { + var name = "__on" + type, i = type.indexOf("."), wrap = d3_selection_onListener; + if (i > 0) type = type.substring(0, i); + var filter = d3_selection_onFilters.get(type); + if (filter) type = filter, wrap = d3_selection_onFilter; + function onRemove() { + var l = this[name]; + if (l) { + this.removeEventListener(type, l, l.$); + delete this[name]; + } + } + function onAdd() { + var l = wrap(listener, d3_array(arguments)); + onRemove.call(this); + this.addEventListener(type, this[name] = l, l.$ = capture); + l._ = listener; + } + function removeAll() { + var re = new RegExp("^__on([^.]+)" + d3.requote(type) + "$"), match; + for (var name in this) { + if (match = name.match(re)) { + var l = this[name]; + this.removeEventListener(match[1], l, l.$); + delete this[name]; + } + } + } + return i ? listener ? onAdd : onRemove : listener ? d3_noop : removeAll; + } + var d3_selection_onFilters = d3.map({ + mouseenter: "mouseover", + mouseleave: "mouseout" + }); + d3_selection_onFilters.forEach(function(k) { + if ("on" + k in d3_document) d3_selection_onFilters.remove(k); + }); + function d3_selection_onListener(listener, argumentz) { + return function(e) { + var o = d3.event; + d3.event = e; + argumentz[0] = this.__data__; + try { + listener.apply(this, argumentz); + } finally { + d3.event = o; + } + }; + } + function d3_selection_onFilter(listener, argumentz) { + var l = d3_selection_onListener(listener, argumentz); + return function(e) { + var target = this, related = e.relatedTarget; + if (!related || related !== target && !(related.compareDocumentPosition(target) & 8)) { + l.call(target, e); + } + }; + } + var d3_event_dragSelect = "onselectstart" in d3_document ? null : d3_vendorSymbol(d3_documentElement.style, "userSelect"), d3_event_dragId = 0; + function d3_event_dragSuppress() { + var name = ".dragsuppress-" + ++d3_event_dragId, click = "click" + name, w = d3.select(d3_window).on("touchmove" + name, d3_eventPreventDefault).on("dragstart" + name, d3_eventPreventDefault).on("selectstart" + name, d3_eventPreventDefault); + if (d3_event_dragSelect) { + var style = d3_documentElement.style, select = style[d3_event_dragSelect]; + style[d3_event_dragSelect] = "none"; + } + return function(suppressClick) { + w.on(name, null); + if (d3_event_dragSelect) style[d3_event_dragSelect] = select; + if (suppressClick) { + function off() { + w.on(click, null); + } + w.on(click, function() { + d3_eventPreventDefault(); + off(); + }, true); + setTimeout(off, 0); + } + }; + } + d3.mouse = function(container) { + return d3_mousePoint(container, d3_eventSource()); + }; + function d3_mousePoint(container, e) { + if (e.changedTouches) e = e.changedTouches[0]; + var svg = container.ownerSVGElement || container; + if (svg.createSVGPoint) { + var point = svg.createSVGPoint(); + point.x = e.clientX, point.y = e.clientY; + point = point.matrixTransform(container.getScreenCTM().inverse()); + return [ point.x, point.y ]; + } + var rect = container.getBoundingClientRect(); + return [ e.clientX - rect.left - container.clientLeft, e.clientY - rect.top - container.clientTop ]; + } + d3.touches = function(container, touches) { + if (arguments.length < 2) touches = d3_eventSource().touches; + return touches ? d3_array(touches).map(function(touch) { + var point = d3_mousePoint(container, touch); + point.identifier = touch.identifier; + return point; + }) : []; + }; + d3.behavior.drag = function() { + var event = d3_eventDispatch(drag, "drag", "dragstart", "dragend"), origin = null, mousedown = dragstart(d3_noop, d3.mouse, d3_behavior_dragMouseSubject, "mousemove", "mouseup"), touchstart = dragstart(d3_behavior_dragTouchId, d3.touch, d3_behavior_dragTouchSubject, "touchmove", "touchend"); + function drag() { + this.on("mousedown.drag", mousedown).on("touchstart.drag", touchstart); + } + function dragstart(id, position, subject, move, end) { + return function() { + var that = this, target = d3.event.target, parent = that.parentNode, dispatch = event.of(that, arguments), dragged = 0, dragId = id(), dragName = ".drag" + (dragId == null ? "" : "-" + dragId), dragOffset, dragSubject = d3.select(subject()).on(move + dragName, moved).on(end + dragName, ended), dragRestore = d3_event_dragSuppress(), position0 = position(parent, dragId); + if (origin) { + dragOffset = origin.apply(that, arguments); + dragOffset = [ dragOffset.x - position0[0], dragOffset.y - position0[1] ]; + } else { + dragOffset = [ 0, 0 ]; + } + dispatch({ + type: "dragstart" + }); + function moved() { + var position1 = position(parent, dragId), dx, dy; + if (!position1) return; + dx = position1[0] - position0[0]; + dy = position1[1] - position0[1]; + dragged |= dx | dy; + position0 = position1; + dispatch({ + type: "drag", + x: position1[0] + dragOffset[0], + y: position1[1] + dragOffset[1], + dx: dx, + dy: dy + }); + } + function ended() { + if (!position(parent, dragId)) return; + dragSubject.on(move + dragName, null).on(end + dragName, null); + dragRestore(dragged && d3.event.target === target); + dispatch({ + type: "dragend" + }); + } + }; + } + drag.origin = function(x) { + if (!arguments.length) return origin; + origin = x; + return drag; + }; + return d3.rebind(drag, event, "on"); + }; + function d3_behavior_dragTouchId() { + return d3.event.changedTouches[0].identifier; + } + function d3_behavior_dragTouchSubject() { + return d3.event.target; + } + function d3_behavior_dragMouseSubject() { + return d3_window; + } + var π = Math.PI, τ = 2 * π, halfπ = π / 2, ε = 1e-6, ε2 = ε * ε, d3_radians = π / 180, d3_degrees = 180 / π; + function d3_sgn(x) { + return x > 0 ? 1 : x < 0 ? -1 : 0; + } + function d3_cross2d(a, b, c) { + return (b[0] - a[0]) * (c[1] - a[1]) - (b[1] - a[1]) * (c[0] - a[0]); + } + function d3_acos(x) { + return x > 1 ? 0 : x < -1 ? π : Math.acos(x); + } + function d3_asin(x) { + return x > 1 ? halfπ : x < -1 ? -halfπ : Math.asin(x); + } + function d3_sinh(x) { + return ((x = Math.exp(x)) - 1 / x) / 2; + } + function d3_cosh(x) { + return ((x = Math.exp(x)) + 1 / x) / 2; + } + function d3_tanh(x) { + return ((x = Math.exp(2 * x)) - 1) / (x + 1); + } + function d3_haversin(x) { + return (x = Math.sin(x / 2)) * x; + } + var ρ = Math.SQRT2, ρ2 = 2, ρ4 = 4; + d3.interpolateZoom = function(p0, p1) { + var ux0 = p0[0], uy0 = p0[1], w0 = p0[2], ux1 = p1[0], uy1 = p1[1], w1 = p1[2]; + var dx = ux1 - ux0, dy = uy1 - uy0, d2 = dx * dx + dy * dy, d1 = Math.sqrt(d2), b0 = (w1 * w1 - w0 * w0 + ρ4 * d2) / (2 * w0 * ρ2 * d1), b1 = (w1 * w1 - w0 * w0 - ρ4 * d2) / (2 * w1 * ρ2 * d1), r0 = Math.log(Math.sqrt(b0 * b0 + 1) - b0), r1 = Math.log(Math.sqrt(b1 * b1 + 1) - b1), dr = r1 - r0, S = (dr || Math.log(w1 / w0)) / ρ; + function interpolate(t) { + var s = t * S; + if (dr) { + var coshr0 = d3_cosh(r0), u = w0 / (ρ2 * d1) * (coshr0 * d3_tanh(ρ * s + r0) - d3_sinh(r0)); + return [ ux0 + u * dx, uy0 + u * dy, w0 * coshr0 / d3_cosh(ρ * s + r0) ]; + } + return [ ux0 + t * dx, uy0 + t * dy, w0 * Math.exp(ρ * s) ]; + } + interpolate.duration = S * 1e3; + return interpolate; + }; + d3.behavior.zoom = function() { + var view = { + x: 0, + y: 0, + k: 1 + }, translate0, center, size = [ 960, 500 ], scaleExtent = d3_behavior_zoomInfinity, mousedown = "mousedown.zoom", mousemove = "mousemove.zoom", mouseup = "mouseup.zoom", mousewheelTimer, touchstart = "touchstart.zoom", touchtime, event = d3_eventDispatch(zoom, "zoomstart", "zoom", "zoomend"), x0, x1, y0, y1; + function zoom(g) { + g.on(mousedown, mousedowned).on(d3_behavior_zoomWheel + ".zoom", mousewheeled).on(mousemove, mousewheelreset).on("dblclick.zoom", dblclicked).on(touchstart, touchstarted); + } + zoom.event = function(g) { + g.each(function() { + var dispatch = event.of(this, arguments), view1 = view; + if (d3_transitionInheritId) { + d3.select(this).transition().each("start.zoom", function() { + view = this.__chart__ || { + x: 0, + y: 0, + k: 1 + }; + zoomstarted(dispatch); + }).tween("zoom:zoom", function() { + var dx = size[0], dy = size[1], cx = dx / 2, cy = dy / 2, i = d3.interpolateZoom([ (cx - view.x) / view.k, (cy - view.y) / view.k, dx / view.k ], [ (cx - view1.x) / view1.k, (cy - view1.y) / view1.k, dx / view1.k ]); + return function(t) { + var l = i(t), k = dx / l[2]; + this.__chart__ = view = { + x: cx - l[0] * k, + y: cy - l[1] * k, + k: k + }; + zoomed(dispatch); + }; + }).each("end.zoom", function() { + zoomended(dispatch); + }); + } else { + this.__chart__ = view; + zoomstarted(dispatch); + zoomed(dispatch); + zoomended(dispatch); + } + }); + }; + zoom.translate = function(_) { + if (!arguments.length) return [ view.x, view.y ]; + view = { + x: +_[0], + y: +_[1], + k: view.k + }; + rescale(); + return zoom; + }; + zoom.scale = function(_) { + if (!arguments.length) return view.k; + view = { + x: view.x, + y: view.y, + k: +_ + }; + rescale(); + return zoom; + }; + zoom.scaleExtent = function(_) { + if (!arguments.length) return scaleExtent; + scaleExtent = _ == null ? d3_behavior_zoomInfinity : [ +_[0], +_[1] ]; + return zoom; + }; + zoom.center = function(_) { + if (!arguments.length) return center; + center = _ && [ +_[0], +_[1] ]; + return zoom; + }; + zoom.size = function(_) { + if (!arguments.length) return size; + size = _ && [ +_[0], +_[1] ]; + return zoom; + }; + zoom.x = function(z) { + if (!arguments.length) return x1; + x1 = z; + x0 = z.copy(); + view = { + x: 0, + y: 0, + k: 1 + }; + return zoom; + }; + zoom.y = function(z) { + if (!arguments.length) return y1; + y1 = z; + y0 = z.copy(); + view = { + x: 0, + y: 0, + k: 1 + }; + return zoom; + }; + function location(p) { + return [ (p[0] - view.x) / view.k, (p[1] - view.y) / view.k ]; + } + function point(l) { + return [ l[0] * view.k + view.x, l[1] * view.k + view.y ]; + } + function scaleTo(s) { + view.k = Math.max(scaleExtent[0], Math.min(scaleExtent[1], s)); + } + function translateTo(p, l) { + l = point(l); + view.x += p[0] - l[0]; + view.y += p[1] - l[1]; + } + function rescale() { + if (x1) x1.domain(x0.range().map(function(x) { + return (x - view.x) / view.k; + }).map(x0.invert)); + if (y1) y1.domain(y0.range().map(function(y) { + return (y - view.y) / view.k; + }).map(y0.invert)); + } + function zoomstarted(dispatch) { + dispatch({ + type: "zoomstart" + }); + } + function zoomed(dispatch) { + rescale(); + dispatch({ + type: "zoom", + scale: view.k, + translate: [ view.x, view.y ] + }); + } + function zoomended(dispatch) { + dispatch({ + type: "zoomend" + }); + } + function mousedowned() { + var that = this, target = d3.event.target, dispatch = event.of(that, arguments), dragged = 0, subject = d3.select(d3_window).on(mousemove, moved).on(mouseup, ended), location0 = location(d3.mouse(that)), dragRestore = d3_event_dragSuppress(); + d3_selection_interrupt.call(that); + zoomstarted(dispatch); + function moved() { + dragged = 1; + translateTo(d3.mouse(that), location0); + zoomed(dispatch); + } + function ended() { + subject.on(mousemove, d3_window === that ? mousewheelreset : null).on(mouseup, null); + dragRestore(dragged && d3.event.target === target); + zoomended(dispatch); + } + } + function touchstarted() { + var that = this, dispatch = event.of(that, arguments), locations0 = {}, distance0 = 0, scale0, zoomName = ".zoom-" + d3.event.changedTouches[0].identifier, touchmove = "touchmove" + zoomName, touchend = "touchend" + zoomName, targets = [], subject = d3.select(that).on(mousedown, null).on(touchstart, started), dragRestore = d3_event_dragSuppress(); + d3_selection_interrupt.call(that); + started(); + zoomstarted(dispatch); + function relocate() { + var touches = d3.touches(that); + scale0 = view.k; + touches.forEach(function(t) { + if (t.identifier in locations0) locations0[t.identifier] = location(t); + }); + return touches; + } + function started() { + var target = d3.event.target; + d3.select(target).on(touchmove, moved).on(touchend, ended); + targets.push(target); + var changed = d3.event.changedTouches; + for (var i = 0, n = changed.length; i < n; ++i) { + locations0[changed[i].identifier] = null; + } + var touches = relocate(), now = Date.now(); + if (touches.length === 1) { + if (now - touchtime < 500) { + var p = touches[0], l = locations0[p.identifier]; + scaleTo(view.k * 2); + translateTo(p, l); + d3_eventPreventDefault(); + zoomed(dispatch); + } + touchtime = now; + } else if (touches.length > 1) { + var p = touches[0], q = touches[1], dx = p[0] - q[0], dy = p[1] - q[1]; + distance0 = dx * dx + dy * dy; + } + } + function moved() { + var touches = d3.touches(that), p0, l0, p1, l1; + for (var i = 0, n = touches.length; i < n; ++i, l1 = null) { + p1 = touches[i]; + if (l1 = locations0[p1.identifier]) { + if (l0) break; + p0 = p1, l0 = l1; + } + } + if (l1) { + var distance1 = (distance1 = p1[0] - p0[0]) * distance1 + (distance1 = p1[1] - p0[1]) * distance1, scale1 = distance0 && Math.sqrt(distance1 / distance0); + p0 = [ (p0[0] + p1[0]) / 2, (p0[1] + p1[1]) / 2 ]; + l0 = [ (l0[0] + l1[0]) / 2, (l0[1] + l1[1]) / 2 ]; + scaleTo(scale1 * scale0); + } + touchtime = null; + translateTo(p0, l0); + zoomed(dispatch); + } + function ended() { + if (d3.event.touches.length) { + var changed = d3.event.changedTouches; + for (var i = 0, n = changed.length; i < n; ++i) { + delete locations0[changed[i].identifier]; + } + for (var identifier in locations0) { + return void relocate(); + } + } + d3.selectAll(targets).on(zoomName, null); + subject.on(mousedown, mousedowned).on(touchstart, touchstarted); + dragRestore(); + zoomended(dispatch); + } + } + function mousewheeled() { + var dispatch = event.of(this, arguments); + if (mousewheelTimer) clearTimeout(mousewheelTimer); else d3_selection_interrupt.call(this), + zoomstarted(dispatch); + mousewheelTimer = setTimeout(function() { + mousewheelTimer = null; + zoomended(dispatch); + }, 50); + d3_eventPreventDefault(); + var point = center || d3.mouse(this); + if (!translate0) translate0 = location(point); + scaleTo(Math.pow(2, d3_behavior_zoomDelta() * .002) * view.k); + translateTo(point, translate0); + zoomed(dispatch); + } + function mousewheelreset() { + translate0 = null; + } + function dblclicked() { + var dispatch = event.of(this, arguments), p = d3.mouse(this), l = location(p), k = Math.log(view.k) / Math.LN2; + zoomstarted(dispatch); + scaleTo(Math.pow(2, d3.event.shiftKey ? Math.ceil(k) - 1 : Math.floor(k) + 1)); + translateTo(p, l); + zoomed(dispatch); + zoomended(dispatch); + } + return d3.rebind(zoom, event, "on"); + }; + var d3_behavior_zoomInfinity = [ 0, Infinity ]; + var d3_behavior_zoomDelta, d3_behavior_zoomWheel = "onwheel" in d3_document ? (d3_behavior_zoomDelta = function() { + return -d3.event.deltaY * (d3.event.deltaMode ? 120 : 1); + }, "wheel") : "onmousewheel" in d3_document ? (d3_behavior_zoomDelta = function() { + return d3.event.wheelDelta; + }, "mousewheel") : (d3_behavior_zoomDelta = function() { + return -d3.event.detail; + }, "MozMousePixelScroll"); + function d3_Color() {} + d3_Color.prototype.toString = function() { + return this.rgb() + ""; + }; + d3.hsl = function(h, s, l) { + return arguments.length === 1 ? h instanceof d3_Hsl ? d3_hsl(h.h, h.s, h.l) : d3_rgb_parse("" + h, d3_rgb_hsl, d3_hsl) : d3_hsl(+h, +s, +l); + }; + function d3_hsl(h, s, l) { + return new d3_Hsl(h, s, l); + } + function d3_Hsl(h, s, l) { + this.h = h; + this.s = s; + this.l = l; + } + var d3_hslPrototype = d3_Hsl.prototype = new d3_Color(); + d3_hslPrototype.brighter = function(k) { + k = Math.pow(.7, arguments.length ? k : 1); + return d3_hsl(this.h, this.s, this.l / k); + }; + d3_hslPrototype.darker = function(k) { + k = Math.pow(.7, arguments.length ? k : 1); + return d3_hsl(this.h, this.s, k * this.l); + }; + d3_hslPrototype.rgb = function() { + return d3_hsl_rgb(this.h, this.s, this.l); + }; + function d3_hsl_rgb(h, s, l) { + var m1, m2; + h = isNaN(h) ? 0 : (h %= 360) < 0 ? h + 360 : h; + s = isNaN(s) ? 0 : s < 0 ? 0 : s > 1 ? 1 : s; + l = l < 0 ? 0 : l > 1 ? 1 : l; + m2 = l <= .5 ? l * (1 + s) : l + s - l * s; + m1 = 2 * l - m2; + function v(h) { + if (h > 360) h -= 360; else if (h < 0) h += 360; + if (h < 60) return m1 + (m2 - m1) * h / 60; + if (h < 180) return m2; + if (h < 240) return m1 + (m2 - m1) * (240 - h) / 60; + return m1; + } + function vv(h) { + return Math.round(v(h) * 255); + } + return d3_rgb(vv(h + 120), vv(h), vv(h - 120)); + } + d3.hcl = function(h, c, l) { + return arguments.length === 1 ? h instanceof d3_Hcl ? d3_hcl(h.h, h.c, h.l) : h instanceof d3_Lab ? d3_lab_hcl(h.l, h.a, h.b) : d3_lab_hcl((h = d3_rgb_lab((h = d3.rgb(h)).r, h.g, h.b)).l, h.a, h.b) : d3_hcl(+h, +c, +l); + }; + function d3_hcl(h, c, l) { + return new d3_Hcl(h, c, l); + } + function d3_Hcl(h, c, l) { + this.h = h; + this.c = c; + this.l = l; + } + var d3_hclPrototype = d3_Hcl.prototype = new d3_Color(); + d3_hclPrototype.brighter = function(k) { + return d3_hcl(this.h, this.c, Math.min(100, this.l + d3_lab_K * (arguments.length ? k : 1))); + }; + d3_hclPrototype.darker = function(k) { + return d3_hcl(this.h, this.c, Math.max(0, this.l - d3_lab_K * (arguments.length ? k : 1))); + }; + d3_hclPrototype.rgb = function() { + return d3_hcl_lab(this.h, this.c, this.l).rgb(); + }; + function d3_hcl_lab(h, c, l) { + if (isNaN(h)) h = 0; + if (isNaN(c)) c = 0; + return d3_lab(l, Math.cos(h *= d3_radians) * c, Math.sin(h) * c); + } + d3.lab = function(l, a, b) { + return arguments.length === 1 ? l instanceof d3_Lab ? d3_lab(l.l, l.a, l.b) : l instanceof d3_Hcl ? d3_hcl_lab(l.l, l.c, l.h) : d3_rgb_lab((l = d3.rgb(l)).r, l.g, l.b) : d3_lab(+l, +a, +b); + }; + function d3_lab(l, a, b) { + return new d3_Lab(l, a, b); + } + function d3_Lab(l, a, b) { + this.l = l; + this.a = a; + this.b = b; + } + var d3_lab_K = 18; + var d3_lab_X = .95047, d3_lab_Y = 1, d3_lab_Z = 1.08883; + var d3_labPrototype = d3_Lab.prototype = new d3_Color(); + d3_labPrototype.brighter = function(k) { + return d3_lab(Math.min(100, this.l + d3_lab_K * (arguments.length ? k : 1)), this.a, this.b); + }; + d3_labPrototype.darker = function(k) { + return d3_lab(Math.max(0, this.l - d3_lab_K * (arguments.length ? k : 1)), this.a, this.b); + }; + d3_labPrototype.rgb = function() { + return d3_lab_rgb(this.l, this.a, this.b); + }; + function d3_lab_rgb(l, a, b) { + var y = (l + 16) / 116, x = y + a / 500, z = y - b / 200; + x = d3_lab_xyz(x) * d3_lab_X; + y = d3_lab_xyz(y) * d3_lab_Y; + z = d3_lab_xyz(z) * d3_lab_Z; + return d3_rgb(d3_xyz_rgb(3.2404542 * x - 1.5371385 * y - .4985314 * z), d3_xyz_rgb(-.969266 * x + 1.8760108 * y + .041556 * z), d3_xyz_rgb(.0556434 * x - .2040259 * y + 1.0572252 * z)); + } + function d3_lab_hcl(l, a, b) { + return l > 0 ? d3_hcl(Math.atan2(b, a) * d3_degrees, Math.sqrt(a * a + b * b), l) : d3_hcl(NaN, NaN, l); + } + function d3_lab_xyz(x) { + return x > .206893034 ? x * x * x : (x - 4 / 29) / 7.787037; + } + function d3_xyz_lab(x) { + return x > .008856 ? Math.pow(x, 1 / 3) : 7.787037 * x + 4 / 29; + } + function d3_xyz_rgb(r) { + return Math.round(255 * (r <= .00304 ? 12.92 * r : 1.055 * Math.pow(r, 1 / 2.4) - .055)); + } + d3.rgb = function(r, g, b) { + return arguments.length === 1 ? r instanceof d3_Rgb ? d3_rgb(r.r, r.g, r.b) : d3_rgb_parse("" + r, d3_rgb, d3_hsl_rgb) : d3_rgb(~~r, ~~g, ~~b); + }; + function d3_rgbNumber(value) { + return d3_rgb(value >> 16, value >> 8 & 255, value & 255); + } + function d3_rgbString(value) { + return d3_rgbNumber(value) + ""; + } + function d3_rgb(r, g, b) { + return new d3_Rgb(r, g, b); + } + function d3_Rgb(r, g, b) { + this.r = r; + this.g = g; + this.b = b; + } + var d3_rgbPrototype = d3_Rgb.prototype = new d3_Color(); + d3_rgbPrototype.brighter = function(k) { + k = Math.pow(.7, arguments.length ? k : 1); + var r = this.r, g = this.g, b = this.b, i = 30; + if (!r && !g && !b) return d3_rgb(i, i, i); + if (r && r < i) r = i; + if (g && g < i) g = i; + if (b && b < i) b = i; + return d3_rgb(Math.min(255, ~~(r / k)), Math.min(255, ~~(g / k)), Math.min(255, ~~(b / k))); + }; + d3_rgbPrototype.darker = function(k) { + k = Math.pow(.7, arguments.length ? k : 1); + return d3_rgb(~~(k * this.r), ~~(k * this.g), ~~(k * this.b)); + }; + d3_rgbPrototype.hsl = function() { + return d3_rgb_hsl(this.r, this.g, this.b); + }; + d3_rgbPrototype.toString = function() { + return "#" + d3_rgb_hex(this.r) + d3_rgb_hex(this.g) + d3_rgb_hex(this.b); + }; + function d3_rgb_hex(v) { + return v < 16 ? "0" + Math.max(0, v).toString(16) : Math.min(255, v).toString(16); + } + function d3_rgb_parse(format, rgb, hsl) { + var r = 0, g = 0, b = 0, m1, m2, color; + m1 = /([a-z]+)\((.*)\)/i.exec(format); + if (m1) { + m2 = m1[2].split(","); + switch (m1[1]) { + case "hsl": + { + return hsl(parseFloat(m2[0]), parseFloat(m2[1]) / 100, parseFloat(m2[2]) / 100); + } + + case "rgb": + { + return rgb(d3_rgb_parseNumber(m2[0]), d3_rgb_parseNumber(m2[1]), d3_rgb_parseNumber(m2[2])); + } + } + } + if (color = d3_rgb_names.get(format)) return rgb(color.r, color.g, color.b); + if (format != null && format.charAt(0) === "#" && !isNaN(color = parseInt(format.substring(1), 16))) { + if (format.length === 4) { + r = (color & 3840) >> 4; + r = r >> 4 | r; + g = color & 240; + g = g >> 4 | g; + b = color & 15; + b = b << 4 | b; + } else if (format.length === 7) { + r = (color & 16711680) >> 16; + g = (color & 65280) >> 8; + b = color & 255; + } + } + return rgb(r, g, b); + } + function d3_rgb_hsl(r, g, b) { + var min = Math.min(r /= 255, g /= 255, b /= 255), max = Math.max(r, g, b), d = max - min, h, s, l = (max + min) / 2; + if (d) { + s = l < .5 ? d / (max + min) : d / (2 - max - min); + if (r == max) h = (g - b) / d + (g < b ? 6 : 0); else if (g == max) h = (b - r) / d + 2; else h = (r - g) / d + 4; + h *= 60; + } else { + h = NaN; + s = l > 0 && l < 1 ? 0 : h; + } + return d3_hsl(h, s, l); + } + function d3_rgb_lab(r, g, b) { + r = d3_rgb_xyz(r); + g = d3_rgb_xyz(g); + b = d3_rgb_xyz(b); + var x = d3_xyz_lab((.4124564 * r + .3575761 * g + .1804375 * b) / d3_lab_X), y = d3_xyz_lab((.2126729 * r + .7151522 * g + .072175 * b) / d3_lab_Y), z = d3_xyz_lab((.0193339 * r + .119192 * g + .9503041 * b) / d3_lab_Z); + return d3_lab(116 * y - 16, 500 * (x - y), 200 * (y - z)); + } + function d3_rgb_xyz(r) { + return (r /= 255) <= .04045 ? r / 12.92 : Math.pow((r + .055) / 1.055, 2.4); + } + function d3_rgb_parseNumber(c) { + var f = parseFloat(c); + return c.charAt(c.length - 1) === "%" ? Math.round(f * 2.55) : f; + } + var d3_rgb_names = d3.map({ + aliceblue: 15792383, + antiquewhite: 16444375, + aqua: 65535, + aquamarine: 8388564, + azure: 15794175, + beige: 16119260, + bisque: 16770244, + black: 0, + blanchedalmond: 16772045, + blue: 255, + blueviolet: 9055202, + brown: 10824234, + burlywood: 14596231, + cadetblue: 6266528, + chartreuse: 8388352, + chocolate: 13789470, + coral: 16744272, + cornflowerblue: 6591981, + cornsilk: 16775388, + crimson: 14423100, + cyan: 65535, + darkblue: 139, + darkcyan: 35723, + darkgoldenrod: 12092939, + darkgray: 11119017, + darkgreen: 25600, + darkgrey: 11119017, + darkkhaki: 12433259, + darkmagenta: 9109643, + darkolivegreen: 5597999, + darkorange: 16747520, + darkorchid: 10040012, + darkred: 9109504, + darksalmon: 15308410, + darkseagreen: 9419919, + darkslateblue: 4734347, + darkslategray: 3100495, + darkslategrey: 3100495, + darkturquoise: 52945, + darkviolet: 9699539, + deeppink: 16716947, + deepskyblue: 49151, + dimgray: 6908265, + dimgrey: 6908265, + dodgerblue: 2003199, + firebrick: 11674146, + floralwhite: 16775920, + forestgreen: 2263842, + fuchsia: 16711935, + gainsboro: 14474460, + ghostwhite: 16316671, + gold: 16766720, + goldenrod: 14329120, + gray: 8421504, + green: 32768, + greenyellow: 11403055, + grey: 8421504, + honeydew: 15794160, + hotpink: 16738740, + indianred: 13458524, + indigo: 4915330, + ivory: 16777200, + khaki: 15787660, + lavender: 15132410, + lavenderblush: 16773365, + lawngreen: 8190976, + lemonchiffon: 16775885, + lightblue: 11393254, + lightcoral: 15761536, + lightcyan: 14745599, + lightgoldenrodyellow: 16448210, + lightgray: 13882323, + lightgreen: 9498256, + lightgrey: 13882323, + lightpink: 16758465, + lightsalmon: 16752762, + lightseagreen: 2142890, + lightskyblue: 8900346, + lightslategray: 7833753, + lightslategrey: 7833753, + lightsteelblue: 11584734, + lightyellow: 16777184, + lime: 65280, + limegreen: 3329330, + linen: 16445670, + magenta: 16711935, + maroon: 8388608, + mediumaquamarine: 6737322, + mediumblue: 205, + mediumorchid: 12211667, + mediumpurple: 9662683, + mediumseagreen: 3978097, + mediumslateblue: 8087790, + mediumspringgreen: 64154, + mediumturquoise: 4772300, + mediumvioletred: 13047173, + midnightblue: 1644912, + mintcream: 16121850, + mistyrose: 16770273, + moccasin: 16770229, + navajowhite: 16768685, + navy: 128, + oldlace: 16643558, + olive: 8421376, + olivedrab: 7048739, + orange: 16753920, + orangered: 16729344, + orchid: 14315734, + palegoldenrod: 15657130, + palegreen: 10025880, + paleturquoise: 11529966, + palevioletred: 14381203, + papayawhip: 16773077, + peachpuff: 16767673, + peru: 13468991, + pink: 16761035, + plum: 14524637, + powderblue: 11591910, + purple: 8388736, + red: 16711680, + rosybrown: 12357519, + royalblue: 4286945, + saddlebrown: 9127187, + salmon: 16416882, + sandybrown: 16032864, + seagreen: 3050327, + seashell: 16774638, + sienna: 10506797, + silver: 12632256, + skyblue: 8900331, + slateblue: 6970061, + slategray: 7372944, + slategrey: 7372944, + snow: 16775930, + springgreen: 65407, + steelblue: 4620980, + tan: 13808780, + teal: 32896, + thistle: 14204888, + tomato: 16737095, + turquoise: 4251856, + violet: 15631086, + wheat: 16113331, + white: 16777215, + whitesmoke: 16119285, + yellow: 16776960, + yellowgreen: 10145074 + }); + d3_rgb_names.forEach(function(key, value) { + d3_rgb_names.set(key, d3_rgbNumber(value)); + }); + function d3_functor(v) { + return typeof v === "function" ? v : function() { + return v; + }; + } + d3.functor = d3_functor; + function d3_identity(d) { + return d; + } + d3.xhr = d3_xhrType(d3_identity); + function d3_xhrType(response) { + return function(url, mimeType, callback) { + if (arguments.length === 2 && typeof mimeType === "function") callback = mimeType, + mimeType = null; + return d3_xhr(url, mimeType, response, callback); + }; + } + function d3_xhr(url, mimeType, response, callback) { + var xhr = {}, dispatch = d3.dispatch("beforesend", "progress", "load", "error"), headers = {}, request = new XMLHttpRequest(), responseType = null; + if (d3_window.XDomainRequest && !("withCredentials" in request) && /^(http(s)?:)?\/\//.test(url)) request = new XDomainRequest(); + "onload" in request ? request.onload = request.onerror = respond : request.onreadystatechange = function() { + request.readyState > 3 && respond(); + }; + function respond() { + var status = request.status, result; + if (!status && request.responseText || status >= 200 && status < 300 || status === 304) { + try { + result = response.call(xhr, request); + } catch (e) { + dispatch.error.call(xhr, e); + return; + } + dispatch.load.call(xhr, result); + } else { + dispatch.error.call(xhr, request); + } + } + request.onprogress = function(event) { + var o = d3.event; + d3.event = event; + try { + dispatch.progress.call(xhr, request); + } finally { + d3.event = o; + } + }; + xhr.header = function(name, value) { + name = (name + "").toLowerCase(); + if (arguments.length < 2) return headers[name]; + if (value == null) delete headers[name]; else headers[name] = value + ""; + return xhr; + }; + xhr.mimeType = function(value) { + if (!arguments.length) return mimeType; + mimeType = value == null ? null : value + ""; + return xhr; + }; + xhr.responseType = function(value) { + if (!arguments.length) return responseType; + responseType = value; + return xhr; + }; + xhr.response = function(value) { + response = value; + return xhr; + }; + [ "get", "post" ].forEach(function(method) { + xhr[method] = function() { + return xhr.send.apply(xhr, [ method ].concat(d3_array(arguments))); + }; + }); + xhr.send = function(method, data, callback) { + if (arguments.length === 2 && typeof data === "function") callback = data, data = null; + request.open(method, url, true); + if (mimeType != null && !("accept" in headers)) headers["accept"] = mimeType + ",*/*"; + if (request.setRequestHeader) for (var name in headers) request.setRequestHeader(name, headers[name]); + if (mimeType != null && request.overrideMimeType) request.overrideMimeType(mimeType); + if (responseType != null) request.responseType = responseType; + if (callback != null) xhr.on("error", callback).on("load", function(request) { + callback(null, request); + }); + dispatch.beforesend.call(xhr, request); + request.send(data == null ? null : data); + return xhr; + }; + xhr.abort = function() { + request.abort(); + return xhr; + }; + d3.rebind(xhr, dispatch, "on"); + return callback == null ? xhr : xhr.get(d3_xhr_fixCallback(callback)); + } + function d3_xhr_fixCallback(callback) { + return callback.length === 1 ? function(error, request) { + callback(error == null ? request : null); + } : callback; + } + d3.dsv = function(delimiter, mimeType) { + var reFormat = new RegExp('["' + delimiter + "\n]"), delimiterCode = delimiter.charCodeAt(0); + function dsv(url, row, callback) { + if (arguments.length < 3) callback = row, row = null; + var xhr = d3_xhr(url, mimeType, row == null ? response : typedResponse(row), callback); + xhr.row = function(_) { + return arguments.length ? xhr.response((row = _) == null ? response : typedResponse(_)) : row; + }; + return xhr; + } + function response(request) { + return dsv.parse(request.responseText); + } + function typedResponse(f) { + return function(request) { + return dsv.parse(request.responseText, f); + }; + } + dsv.parse = function(text, f) { + var o; + return dsv.parseRows(text, function(row, i) { + if (o) return o(row, i - 1); + var a = new Function("d", "return {" + row.map(function(name, i) { + return JSON.stringify(name) + ": d[" + i + "]"; + }).join(",") + "}"); + o = f ? function(row, i) { + return f(a(row), i); + } : a; + }); + }; + dsv.parseRows = function(text, f) { + var EOL = {}, EOF = {}, rows = [], N = text.length, I = 0, n = 0, t, eol; + function token() { + if (I >= N) return EOF; + if (eol) return eol = false, EOL; + var j = I; + if (text.charCodeAt(j) === 34) { + var i = j; + while (i++ < N) { + if (text.charCodeAt(i) === 34) { + if (text.charCodeAt(i + 1) !== 34) break; + ++i; + } + } + I = i + 2; + var c = text.charCodeAt(i + 1); + if (c === 13) { + eol = true; + if (text.charCodeAt(i + 2) === 10) ++I; + } else if (c === 10) { + eol = true; + } + return text.substring(j + 1, i).replace(/""/g, '"'); + } + while (I < N) { + var c = text.charCodeAt(I++), k = 1; + if (c === 10) eol = true; else if (c === 13) { + eol = true; + if (text.charCodeAt(I) === 10) ++I, ++k; + } else if (c !== delimiterCode) continue; + return text.substring(j, I - k); + } + return text.substring(j); + } + while ((t = token()) !== EOF) { + var a = []; + while (t !== EOL && t !== EOF) { + a.push(t); + t = token(); + } + if (f && !(a = f(a, n++))) continue; + rows.push(a); + } + return rows; + }; + dsv.format = function(rows) { + if (Array.isArray(rows[0])) return dsv.formatRows(rows); + var fieldSet = new d3_Set(), fields = []; + rows.forEach(function(row) { + for (var field in row) { + if (!fieldSet.has(field)) { + fields.push(fieldSet.add(field)); + } + } + }); + return [ fields.map(formatValue).join(delimiter) ].concat(rows.map(function(row) { + return fields.map(function(field) { + return formatValue(row[field]); + }).join(delimiter); + })).join("\n"); + }; + dsv.formatRows = function(rows) { + return rows.map(formatRow).join("\n"); + }; + function formatRow(row) { + return row.map(formatValue).join(delimiter); + } + function formatValue(text) { + return reFormat.test(text) ? '"' + text.replace(/\"/g, '""') + '"' : text; + } + return dsv; + }; + d3.csv = d3.dsv(",", "text/csv"); + d3.tsv = d3.dsv(" ", "text/tab-separated-values"); + d3.touch = function(container, touches, identifier) { + if (arguments.length < 3) identifier = touches, touches = d3_eventSource().changedTouches; + if (touches) for (var i = 0, n = touches.length, touch; i < n; ++i) { + if ((touch = touches[i]).identifier === identifier) { + return d3_mousePoint(container, touch); + } + } + }; + var d3_timer_queueHead, d3_timer_queueTail, d3_timer_interval, d3_timer_timeout, d3_timer_active, d3_timer_frame = d3_window[d3_vendorSymbol(d3_window, "requestAnimationFrame")] || function(callback) { + setTimeout(callback, 17); + }; + d3.timer = function(callback, delay, then) { + var n = arguments.length; + if (n < 2) delay = 0; + if (n < 3) then = Date.now(); + var time = then + delay, timer = { + c: callback, + t: time, + f: false, + n: null + }; + if (d3_timer_queueTail) d3_timer_queueTail.n = timer; else d3_timer_queueHead = timer; + d3_timer_queueTail = timer; + if (!d3_timer_interval) { + d3_timer_timeout = clearTimeout(d3_timer_timeout); + d3_timer_interval = 1; + d3_timer_frame(d3_timer_step); + } + }; + function d3_timer_step() { + var now = d3_timer_mark(), delay = d3_timer_sweep() - now; + if (delay > 24) { + if (isFinite(delay)) { + clearTimeout(d3_timer_timeout); + d3_timer_timeout = setTimeout(d3_timer_step, delay); + } + d3_timer_interval = 0; + } else { + d3_timer_interval = 1; + d3_timer_frame(d3_timer_step); + } + } + d3.timer.flush = function() { + d3_timer_mark(); + d3_timer_sweep(); + }; + function d3_timer_mark() { + var now = Date.now(); + d3_timer_active = d3_timer_queueHead; + while (d3_timer_active) { + if (now >= d3_timer_active.t) d3_timer_active.f = d3_timer_active.c(now - d3_timer_active.t); + d3_timer_active = d3_timer_active.n; + } + return now; + } + function d3_timer_sweep() { + var t0, t1 = d3_timer_queueHead, time = Infinity; + while (t1) { + if (t1.f) { + t1 = t0 ? t0.n = t1.n : d3_timer_queueHead = t1.n; + } else { + if (t1.t < time) time = t1.t; + t1 = (t0 = t1).n; + } + } + d3_timer_queueTail = t0; + return time; + } + function d3_format_precision(x, p) { + return p - (x ? Math.ceil(Math.log(x) / Math.LN10) : 1); + } + d3.round = function(x, n) { + return n ? Math.round(x * (n = Math.pow(10, n))) / n : Math.round(x); + }; + var d3_formatPrefixes = [ "y", "z", "a", "f", "p", "n", "µ", "m", "", "k", "M", "G", "T", "P", "E", "Z", "Y" ].map(d3_formatPrefix); + d3.formatPrefix = function(value, precision) { + var i = 0; + if (value) { + if (value < 0) value *= -1; + if (precision) value = d3.round(value, d3_format_precision(value, precision)); + i = 1 + Math.floor(1e-12 + Math.log(value) / Math.LN10); + i = Math.max(-24, Math.min(24, Math.floor((i - 1) / 3) * 3)); + } + return d3_formatPrefixes[8 + i / 3]; + }; + function d3_formatPrefix(d, i) { + var k = Math.pow(10, abs(8 - i) * 3); + return { + scale: i > 8 ? function(d) { + return d / k; + } : function(d) { + return d * k; + }, + symbol: d + }; + } + function d3_locale_numberFormat(locale) { + var locale_decimal = locale.decimal, locale_thousands = locale.thousands, locale_grouping = locale.grouping, locale_currency = locale.currency, formatGroup = locale_grouping ? function(value) { + var i = value.length, t = [], j = 0, g = locale_grouping[0]; + while (i > 0 && g > 0) { + t.push(value.substring(i -= g, i + g)); + g = locale_grouping[j = (j + 1) % locale_grouping.length]; + } + return t.reverse().join(locale_thousands); + } : d3_identity; + return function(specifier) { + var match = d3_format_re.exec(specifier), fill = match[1] || " ", align = match[2] || ">", sign = match[3] || "", symbol = match[4] || "", zfill = match[5], width = +match[6], comma = match[7], precision = match[8], type = match[9], scale = 1, prefix = "", suffix = "", integer = false; + if (precision) precision = +precision.substring(1); + if (zfill || fill === "0" && align === "=") { + zfill = fill = "0"; + align = "="; + if (comma) width -= Math.floor((width - 1) / 4); + } + switch (type) { + case "n": + comma = true; + type = "g"; + break; + + case "%": + scale = 100; + suffix = "%"; + type = "f"; + break; + + case "p": + scale = 100; + suffix = "%"; + type = "r"; + break; + + case "b": + case "o": + case "x": + case "X": + if (symbol === "#") prefix = "0" + type.toLowerCase(); + + case "c": + case "d": + integer = true; + precision = 0; + break; + + case "s": + scale = -1; + type = "r"; + break; + } + if (symbol === "$") prefix = locale_currency[0], suffix = locale_currency[1]; + if (type == "r" && !precision) type = "g"; + if (precision != null) { + if (type == "g") precision = Math.max(1, Math.min(21, precision)); else if (type == "e" || type == "f") precision = Math.max(0, Math.min(20, precision)); + } + type = d3_format_types.get(type) || d3_format_typeDefault; + var zcomma = zfill && comma; + return function(value) { + var fullSuffix = suffix; + if (integer && value % 1) return ""; + var negative = value < 0 || value === 0 && 1 / value < 0 ? (value = -value, "-") : sign; + if (scale < 0) { + var unit = d3.formatPrefix(value, precision); + value = unit.scale(value); + fullSuffix = unit.symbol + suffix; + } else { + value *= scale; + } + value = type(value, precision); + var i = value.lastIndexOf("."), before = i < 0 ? value : value.substring(0, i), after = i < 0 ? "" : locale_decimal + value.substring(i + 1); + if (!zfill && comma) before = formatGroup(before); + var length = prefix.length + before.length + after.length + (zcomma ? 0 : negative.length), padding = length < width ? new Array(length = width - length + 1).join(fill) : ""; + if (zcomma) before = formatGroup(padding + before); + negative += prefix; + value = before + after; + return (align === "<" ? negative + value + padding : align === ">" ? padding + negative + value : align === "^" ? padding.substring(0, length >>= 1) + negative + value + padding.substring(length) : negative + (zcomma ? value : padding + value)) + fullSuffix; + }; + }; + } + var d3_format_re = /(?:([^{])?([<>=^]))?([+\- ])?([$#])?(0)?(\d+)?(,)?(\.-?\d+)?([a-z%])?/i; + var d3_format_types = d3.map({ + b: function(x) { + return x.toString(2); + }, + c: function(x) { + return String.fromCharCode(x); + }, + o: function(x) { + return x.toString(8); + }, + x: function(x) { + return x.toString(16); + }, + X: function(x) { + return x.toString(16).toUpperCase(); + }, + g: function(x, p) { + return x.toPrecision(p); + }, + e: function(x, p) { + return x.toExponential(p); + }, + f: function(x, p) { + return x.toFixed(p); + }, + r: function(x, p) { + return (x = d3.round(x, d3_format_precision(x, p))).toFixed(Math.max(0, Math.min(20, d3_format_precision(x * (1 + 1e-15), p)))); + } + }); + function d3_format_typeDefault(x) { + return x + ""; + } + var d3_time = d3.time = {}, d3_date = Date; + function d3_date_utc() { + this._ = new Date(arguments.length > 1 ? Date.UTC.apply(this, arguments) : arguments[0]); + } + d3_date_utc.prototype = { + getDate: function() { + return this._.getUTCDate(); + }, + getDay: function() { + return this._.getUTCDay(); + }, + getFullYear: function() { + return this._.getUTCFullYear(); + }, + getHours: function() { + return this._.getUTCHours(); + }, + getMilliseconds: function() { + return this._.getUTCMilliseconds(); + }, + getMinutes: function() { + return this._.getUTCMinutes(); + }, + getMonth: function() { + return this._.getUTCMonth(); + }, + getSeconds: function() { + return this._.getUTCSeconds(); + }, + getTime: function() { + return this._.getTime(); + }, + getTimezoneOffset: function() { + return 0; + }, + valueOf: function() { + return this._.valueOf(); + }, + setDate: function() { + d3_time_prototype.setUTCDate.apply(this._, arguments); + }, + setDay: function() { + d3_time_prototype.setUTCDay.apply(this._, arguments); + }, + setFullYear: function() { + d3_time_prototype.setUTCFullYear.apply(this._, arguments); + }, + setHours: function() { + d3_time_prototype.setUTCHours.apply(this._, arguments); + }, + setMilliseconds: function() { + d3_time_prototype.setUTCMilliseconds.apply(this._, arguments); + }, + setMinutes: function() { + d3_time_prototype.setUTCMinutes.apply(this._, arguments); + }, + setMonth: function() { + d3_time_prototype.setUTCMonth.apply(this._, arguments); + }, + setSeconds: function() { + d3_time_prototype.setUTCSeconds.apply(this._, arguments); + }, + setTime: function() { + d3_time_prototype.setTime.apply(this._, arguments); + } + }; + var d3_time_prototype = Date.prototype; + function d3_time_interval(local, step, number) { + function round(date) { + var d0 = local(date), d1 = offset(d0, 1); + return date - d0 < d1 - date ? d0 : d1; + } + function ceil(date) { + step(date = local(new d3_date(date - 1)), 1); + return date; + } + function offset(date, k) { + step(date = new d3_date(+date), k); + return date; + } + function range(t0, t1, dt) { + var time = ceil(t0), times = []; + if (dt > 1) { + while (time < t1) { + if (!(number(time) % dt)) times.push(new Date(+time)); + step(time, 1); + } + } else { + while (time < t1) times.push(new Date(+time)), step(time, 1); + } + return times; + } + function range_utc(t0, t1, dt) { + try { + d3_date = d3_date_utc; + var utc = new d3_date_utc(); + utc._ = t0; + return range(utc, t1, dt); + } finally { + d3_date = Date; + } + } + local.floor = local; + local.round = round; + local.ceil = ceil; + local.offset = offset; + local.range = range; + var utc = local.utc = d3_time_interval_utc(local); + utc.floor = utc; + utc.round = d3_time_interval_utc(round); + utc.ceil = d3_time_interval_utc(ceil); + utc.offset = d3_time_interval_utc(offset); + utc.range = range_utc; + return local; + } + function d3_time_interval_utc(method) { + return function(date, k) { + try { + d3_date = d3_date_utc; + var utc = new d3_date_utc(); + utc._ = date; + return method(utc, k)._; + } finally { + d3_date = Date; + } + }; + } + d3_time.year = d3_time_interval(function(date) { + date = d3_time.day(date); + date.setMonth(0, 1); + return date; + }, function(date, offset) { + date.setFullYear(date.getFullYear() + offset); + }, function(date) { + return date.getFullYear(); + }); + d3_time.years = d3_time.year.range; + d3_time.years.utc = d3_time.year.utc.range; + d3_time.day = d3_time_interval(function(date) { + var day = new d3_date(2e3, 0); + day.setFullYear(date.getFullYear(), date.getMonth(), date.getDate()); + return day; + }, function(date, offset) { + date.setDate(date.getDate() + offset); + }, function(date) { + return date.getDate() - 1; + }); + d3_time.days = d3_time.day.range; + d3_time.days.utc = d3_time.day.utc.range; + d3_time.dayOfYear = function(date) { + var year = d3_time.year(date); + return Math.floor((date - year - (date.getTimezoneOffset() - year.getTimezoneOffset()) * 6e4) / 864e5); + }; + [ "sunday", "monday", "tuesday", "wednesday", "thursday", "friday", "saturday" ].forEach(function(day, i) { + i = 7 - i; + var interval = d3_time[day] = d3_time_interval(function(date) { + (date = d3_time.day(date)).setDate(date.getDate() - (date.getDay() + i) % 7); + return date; + }, function(date, offset) { + date.setDate(date.getDate() + Math.floor(offset) * 7); + }, function(date) { + var day = d3_time.year(date).getDay(); + return Math.floor((d3_time.dayOfYear(date) + (day + i) % 7) / 7) - (day !== i); + }); + d3_time[day + "s"] = interval.range; + d3_time[day + "s"].utc = interval.utc.range; + d3_time[day + "OfYear"] = function(date) { + var day = d3_time.year(date).getDay(); + return Math.floor((d3_time.dayOfYear(date) + (day + i) % 7) / 7); + }; + }); + d3_time.week = d3_time.sunday; + d3_time.weeks = d3_time.sunday.range; + d3_time.weeks.utc = d3_time.sunday.utc.range; + d3_time.weekOfYear = d3_time.sundayOfYear; + function d3_locale_timeFormat(locale) { + var locale_dateTime = locale.dateTime, locale_date = locale.date, locale_time = locale.time, locale_periods = locale.periods, locale_days = locale.days, locale_shortDays = locale.shortDays, locale_months = locale.months, locale_shortMonths = locale.shortMonths; + function d3_time_format(template) { + var n = template.length; + function format(date) { + var string = [], i = -1, j = 0, c, p, f; + while (++i < n) { + if (template.charCodeAt(i) === 37) { + string.push(template.substring(j, i)); + if ((p = d3_time_formatPads[c = template.charAt(++i)]) != null) c = template.charAt(++i); + if (f = d3_time_formats[c]) c = f(date, p == null ? c === "e" ? " " : "0" : p); + string.push(c); + j = i + 1; + } + } + string.push(template.substring(j, i)); + return string.join(""); + } + format.parse = function(string) { + var d = { + y: 1900, + m: 0, + d: 1, + H: 0, + M: 0, + S: 0, + L: 0, + Z: null + }, i = d3_time_parse(d, template, string, 0); + if (i != string.length) return null; + if ("p" in d) d.H = d.H % 12 + d.p * 12; + var localZ = d.Z != null && d3_date !== d3_date_utc, date = new (localZ ? d3_date_utc : d3_date)(); + if ("j" in d) date.setFullYear(d.y, 0, d.j); else if ("w" in d && ("W" in d || "U" in d)) { + date.setFullYear(d.y, 0, 1); + date.setFullYear(d.y, 0, "W" in d ? (d.w + 6) % 7 + d.W * 7 - (date.getDay() + 5) % 7 : d.w + d.U * 7 - (date.getDay() + 6) % 7); + } else date.setFullYear(d.y, d.m, d.d); + date.setHours(d.H + Math.floor(d.Z / 100), d.M + d.Z % 100, d.S, d.L); + return localZ ? date._ : date; + }; + format.toString = function() { + return template; + }; + return format; + } + function d3_time_parse(date, template, string, j) { + var c, p, t, i = 0, n = template.length, m = string.length; + while (i < n) { + if (j >= m) return -1; + c = template.charCodeAt(i++); + if (c === 37) { + t = template.charAt(i++); + p = d3_time_parsers[t in d3_time_formatPads ? template.charAt(i++) : t]; + if (!p || (j = p(date, string, j)) < 0) return -1; + } else if (c != string.charCodeAt(j++)) { + return -1; + } + } + return j; + } + d3_time_format.utc = function(template) { + var local = d3_time_format(template); + function format(date) { + try { + d3_date = d3_date_utc; + var utc = new d3_date(); + utc._ = date; + return local(utc); + } finally { + d3_date = Date; + } + } + format.parse = function(string) { + try { + d3_date = d3_date_utc; + var date = local.parse(string); + return date && date._; + } finally { + d3_date = Date; + } + }; + format.toString = local.toString; + return format; + }; + d3_time_format.multi = d3_time_format.utc.multi = d3_time_formatMulti; + var d3_time_periodLookup = d3.map(), d3_time_dayRe = d3_time_formatRe(locale_days), d3_time_dayLookup = d3_time_formatLookup(locale_days), d3_time_dayAbbrevRe = d3_time_formatRe(locale_shortDays), d3_time_dayAbbrevLookup = d3_time_formatLookup(locale_shortDays), d3_time_monthRe = d3_time_formatRe(locale_months), d3_time_monthLookup = d3_time_formatLookup(locale_months), d3_time_monthAbbrevRe = d3_time_formatRe(locale_shortMonths), d3_time_monthAbbrevLookup = d3_time_formatLookup(locale_shortMonths); + locale_periods.forEach(function(p, i) { + d3_time_periodLookup.set(p.toLowerCase(), i); + }); + var d3_time_formats = { + a: function(d) { + return locale_shortDays[d.getDay()]; + }, + A: function(d) { + return locale_days[d.getDay()]; + }, + b: function(d) { + return locale_shortMonths[d.getMonth()]; + }, + B: function(d) { + return locale_months[d.getMonth()]; + }, + c: d3_time_format(locale_dateTime), + d: function(d, p) { + return d3_time_formatPad(d.getDate(), p, 2); + }, + e: function(d, p) { + return d3_time_formatPad(d.getDate(), p, 2); + }, + H: function(d, p) { + return d3_time_formatPad(d.getHours(), p, 2); + }, + I: function(d, p) { + return d3_time_formatPad(d.getHours() % 12 || 12, p, 2); + }, + j: function(d, p) { + return d3_time_formatPad(1 + d3_time.dayOfYear(d), p, 3); + }, + L: function(d, p) { + return d3_time_formatPad(d.getMilliseconds(), p, 3); + }, + m: function(d, p) { + return d3_time_formatPad(d.getMonth() + 1, p, 2); + }, + M: function(d, p) { + return d3_time_formatPad(d.getMinutes(), p, 2); + }, + p: function(d) { + return locale_periods[+(d.getHours() >= 12)]; + }, + S: function(d, p) { + return d3_time_formatPad(d.getSeconds(), p, 2); + }, + U: function(d, p) { + return d3_time_formatPad(d3_time.sundayOfYear(d), p, 2); + }, + w: function(d) { + return d.getDay(); + }, + W: function(d, p) { + return d3_time_formatPad(d3_time.mondayOfYear(d), p, 2); + }, + x: d3_time_format(locale_date), + X: d3_time_format(locale_time), + y: function(d, p) { + return d3_time_formatPad(d.getFullYear() % 100, p, 2); + }, + Y: function(d, p) { + return d3_time_formatPad(d.getFullYear() % 1e4, p, 4); + }, + Z: d3_time_zone, + "%": function() { + return "%"; + } + }; + var d3_time_parsers = { + a: d3_time_parseWeekdayAbbrev, + A: d3_time_parseWeekday, + b: d3_time_parseMonthAbbrev, + B: d3_time_parseMonth, + c: d3_time_parseLocaleFull, + d: d3_time_parseDay, + e: d3_time_parseDay, + H: d3_time_parseHour24, + I: d3_time_parseHour24, + j: d3_time_parseDayOfYear, + L: d3_time_parseMilliseconds, + m: d3_time_parseMonthNumber, + M: d3_time_parseMinutes, + p: d3_time_parseAmPm, + S: d3_time_parseSeconds, + U: d3_time_parseWeekNumberSunday, + w: d3_time_parseWeekdayNumber, + W: d3_time_parseWeekNumberMonday, + x: d3_time_parseLocaleDate, + X: d3_time_parseLocaleTime, + y: d3_time_parseYear, + Y: d3_time_parseFullYear, + Z: d3_time_parseZone, + "%": d3_time_parseLiteralPercent + }; + function d3_time_parseWeekdayAbbrev(date, string, i) { + d3_time_dayAbbrevRe.lastIndex = 0; + var n = d3_time_dayAbbrevRe.exec(string.substring(i)); + return n ? (date.w = d3_time_dayAbbrevLookup.get(n[0].toLowerCase()), i + n[0].length) : -1; + } + function d3_time_parseWeekday(date, string, i) { + d3_time_dayRe.lastIndex = 0; + var n = d3_time_dayRe.exec(string.substring(i)); + return n ? (date.w = d3_time_dayLookup.get(n[0].toLowerCase()), i + n[0].length) : -1; + } + function d3_time_parseMonthAbbrev(date, string, i) { + d3_time_monthAbbrevRe.lastIndex = 0; + var n = d3_time_monthAbbrevRe.exec(string.substring(i)); + return n ? (date.m = d3_time_monthAbbrevLookup.get(n[0].toLowerCase()), i + n[0].length) : -1; + } + function d3_time_parseMonth(date, string, i) { + d3_time_monthRe.lastIndex = 0; + var n = d3_time_monthRe.exec(string.substring(i)); + return n ? (date.m = d3_time_monthLookup.get(n[0].toLowerCase()), i + n[0].length) : -1; + } + function d3_time_parseLocaleFull(date, string, i) { + return d3_time_parse(date, d3_time_formats.c.toString(), string, i); + } + function d3_time_parseLocaleDate(date, string, i) { + return d3_time_parse(date, d3_time_formats.x.toString(), string, i); + } + function d3_time_parseLocaleTime(date, string, i) { + return d3_time_parse(date, d3_time_formats.X.toString(), string, i); + } + function d3_time_parseAmPm(date, string, i) { + var n = d3_time_periodLookup.get(string.substring(i, i += 2).toLowerCase()); + return n == null ? -1 : (date.p = n, i); + } + return d3_time_format; + } + var d3_time_formatPads = { + "-": "", + _: " ", + "0": "0" + }, d3_time_numberRe = /^\s*\d+/, d3_time_percentRe = /^%/; + function d3_time_formatPad(value, fill, width) { + var sign = value < 0 ? "-" : "", string = (sign ? -value : value) + "", length = string.length; + return sign + (length < width ? new Array(width - length + 1).join(fill) + string : string); + } + function d3_time_formatRe(names) { + return new RegExp("^(?:" + names.map(d3.requote).join("|") + ")", "i"); + } + function d3_time_formatLookup(names) { + var map = new d3_Map(), i = -1, n = names.length; + while (++i < n) map.set(names[i].toLowerCase(), i); + return map; + } + function d3_time_parseWeekdayNumber(date, string, i) { + d3_time_numberRe.lastIndex = 0; + var n = d3_time_numberRe.exec(string.substring(i, i + 1)); + return n ? (date.w = +n[0], i + n[0].length) : -1; + } + function d3_time_parseWeekNumberSunday(date, string, i) { + d3_time_numberRe.lastIndex = 0; + var n = d3_time_numberRe.exec(string.substring(i)); + return n ? (date.U = +n[0], i + n[0].length) : -1; + } + function d3_time_parseWeekNumberMonday(date, string, i) { + d3_time_numberRe.lastIndex = 0; + var n = d3_time_numberRe.exec(string.substring(i)); + return n ? (date.W = +n[0], i + n[0].length) : -1; + } + function d3_time_parseFullYear(date, string, i) { + d3_time_numberRe.lastIndex = 0; + var n = d3_time_numberRe.exec(string.substring(i, i + 4)); + return n ? (date.y = +n[0], i + n[0].length) : -1; + } + function d3_time_parseYear(date, string, i) { + d3_time_numberRe.lastIndex = 0; + var n = d3_time_numberRe.exec(string.substring(i, i + 2)); + return n ? (date.y = d3_time_expandYear(+n[0]), i + n[0].length) : -1; + } + function d3_time_parseZone(date, string, i) { + return /^[+-]\d{4}$/.test(string = string.substring(i, i + 5)) ? (date.Z = -string, + i + 5) : -1; + } + function d3_time_expandYear(d) { + return d + (d > 68 ? 1900 : 2e3); + } + function d3_time_parseMonthNumber(date, string, i) { + d3_time_numberRe.lastIndex = 0; + var n = d3_time_numberRe.exec(string.substring(i, i + 2)); + return n ? (date.m = n[0] - 1, i + n[0].length) : -1; + } + function d3_time_parseDay(date, string, i) { + d3_time_numberRe.lastIndex = 0; + var n = d3_time_numberRe.exec(string.substring(i, i + 2)); + return n ? (date.d = +n[0], i + n[0].length) : -1; + } + function d3_time_parseDayOfYear(date, string, i) { + d3_time_numberRe.lastIndex = 0; + var n = d3_time_numberRe.exec(string.substring(i, i + 3)); + return n ? (date.j = +n[0], i + n[0].length) : -1; + } + function d3_time_parseHour24(date, string, i) { + d3_time_numberRe.lastIndex = 0; + var n = d3_time_numberRe.exec(string.substring(i, i + 2)); + return n ? (date.H = +n[0], i + n[0].length) : -1; + } + function d3_time_parseMinutes(date, string, i) { + d3_time_numberRe.lastIndex = 0; + var n = d3_time_numberRe.exec(string.substring(i, i + 2)); + return n ? (date.M = +n[0], i + n[0].length) : -1; + } + function d3_time_parseSeconds(date, string, i) { + d3_time_numberRe.lastIndex = 0; + var n = d3_time_numberRe.exec(string.substring(i, i + 2)); + return n ? (date.S = +n[0], i + n[0].length) : -1; + } + function d3_time_parseMilliseconds(date, string, i) { + d3_time_numberRe.lastIndex = 0; + var n = d3_time_numberRe.exec(string.substring(i, i + 3)); + return n ? (date.L = +n[0], i + n[0].length) : -1; + } + function d3_time_zone(d) { + var z = d.getTimezoneOffset(), zs = z > 0 ? "-" : "+", zh = ~~(abs(z) / 60), zm = abs(z) % 60; + return zs + d3_time_formatPad(zh, "0", 2) + d3_time_formatPad(zm, "0", 2); + } + function d3_time_parseLiteralPercent(date, string, i) { + d3_time_percentRe.lastIndex = 0; + var n = d3_time_percentRe.exec(string.substring(i, i + 1)); + return n ? i + n[0].length : -1; + } + function d3_time_formatMulti(formats) { + var n = formats.length, i = -1; + while (++i < n) formats[i][0] = this(formats[i][0]); + return function(date) { + var i = 0, f = formats[i]; + while (!f[1](date)) f = formats[++i]; + return f[0](date); + }; + } + d3.locale = function(locale) { + return { + numberFormat: d3_locale_numberFormat(locale), + timeFormat: d3_locale_timeFormat(locale) + }; + }; + var d3_locale_enUS = d3.locale({ + decimal: ".", + thousands: ",", + grouping: [ 3 ], + currency: [ "$", "" ], + dateTime: "%a %b %e %X %Y", + date: "%m/%d/%Y", + time: "%H:%M:%S", + periods: [ "AM", "PM" ], + days: [ "Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday" ], + shortDays: [ "Sun", "Mon", "Tue", "Wed", "Thu", "Fri", "Sat" ], + months: [ "January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December" ], + shortMonths: [ "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec" ] + }); + d3.format = d3_locale_enUS.numberFormat; + d3.geo = {}; + function d3_adder() {} + d3_adder.prototype = { + s: 0, + t: 0, + add: function(y) { + d3_adderSum(y, this.t, d3_adderTemp); + d3_adderSum(d3_adderTemp.s, this.s, this); + if (this.s) this.t += d3_adderTemp.t; else this.s = d3_adderTemp.t; + }, + reset: function() { + this.s = this.t = 0; + }, + valueOf: function() { + return this.s; + } + }; + var d3_adderTemp = new d3_adder(); + function d3_adderSum(a, b, o) { + var x = o.s = a + b, bv = x - a, av = x - bv; + o.t = a - av + (b - bv); + } + d3.geo.stream = function(object, listener) { + if (object && d3_geo_streamObjectType.hasOwnProperty(object.type)) { + d3_geo_streamObjectType[object.type](object, listener); + } else { + d3_geo_streamGeometry(object, listener); + } + }; + function d3_geo_streamGeometry(geometry, listener) { + if (geometry && d3_geo_streamGeometryType.hasOwnProperty(geometry.type)) { + d3_geo_streamGeometryType[geometry.type](geometry, listener); + } + } + var d3_geo_streamObjectType = { + Feature: function(feature, listener) { + d3_geo_streamGeometry(feature.geometry, listener); + }, + FeatureCollection: function(object, listener) { + var features = object.features, i = -1, n = features.length; + while (++i < n) d3_geo_streamGeometry(features[i].geometry, listener); + } + }; + var d3_geo_streamGeometryType = { + Sphere: function(object, listener) { + listener.sphere(); + }, + Point: function(object, listener) { + object = object.coordinates; + listener.point(object[0], object[1], object[2]); + }, + MultiPoint: function(object, listener) { + var coordinates = object.coordinates, i = -1, n = coordinates.length; + while (++i < n) object = coordinates[i], listener.point(object[0], object[1], object[2]); + }, + LineString: function(object, listener) { + d3_geo_streamLine(object.coordinates, listener, 0); + }, + MultiLineString: function(object, listener) { + var coordinates = object.coordinates, i = -1, n = coordinates.length; + while (++i < n) d3_geo_streamLine(coordinates[i], listener, 0); + }, + Polygon: function(object, listener) { + d3_geo_streamPolygon(object.coordinates, listener); + }, + MultiPolygon: function(object, listener) { + var coordinates = object.coordinates, i = -1, n = coordinates.length; + while (++i < n) d3_geo_streamPolygon(coordinates[i], listener); + }, + GeometryCollection: function(object, listener) { + var geometries = object.geometries, i = -1, n = geometries.length; + while (++i < n) d3_geo_streamGeometry(geometries[i], listener); + } + }; + function d3_geo_streamLine(coordinates, listener, closed) { + var i = -1, n = coordinates.length - closed, coordinate; + listener.lineStart(); + while (++i < n) coordinate = coordinates[i], listener.point(coordinate[0], coordinate[1], coordinate[2]); + listener.lineEnd(); + } + function d3_geo_streamPolygon(coordinates, listener) { + var i = -1, n = coordinates.length; + listener.polygonStart(); + while (++i < n) d3_geo_streamLine(coordinates[i], listener, 1); + listener.polygonEnd(); + } + d3.geo.area = function(object) { + d3_geo_areaSum = 0; + d3.geo.stream(object, d3_geo_area); + return d3_geo_areaSum; + }; + var d3_geo_areaSum, d3_geo_areaRingSum = new d3_adder(); + var d3_geo_area = { + sphere: function() { + d3_geo_areaSum += 4 * π; + }, + point: d3_noop, + lineStart: d3_noop, + lineEnd: d3_noop, + polygonStart: function() { + d3_geo_areaRingSum.reset(); + d3_geo_area.lineStart = d3_geo_areaRingStart; + }, + polygonEnd: function() { + var area = 2 * d3_geo_areaRingSum; + d3_geo_areaSum += area < 0 ? 4 * π + area : area; + d3_geo_area.lineStart = d3_geo_area.lineEnd = d3_geo_area.point = d3_noop; + } + }; + function d3_geo_areaRingStart() { + var λ00, φ00, λ0, cosφ0, sinφ0; + d3_geo_area.point = function(λ, φ) { + d3_geo_area.point = nextPoint; + λ0 = (λ00 = λ) * d3_radians, cosφ0 = Math.cos(φ = (φ00 = φ) * d3_radians / 2 + π / 4), + sinφ0 = Math.sin(φ); + }; + function nextPoint(λ, φ) { + λ *= d3_radians; + φ = φ * d3_radians / 2 + π / 4; + var dλ = λ - λ0, sdλ = dλ >= 0 ? 1 : -1, adλ = sdλ * dλ, cosφ = Math.cos(φ), sinφ = Math.sin(φ), k = sinφ0 * sinφ, u = cosφ0 * cosφ + k * Math.cos(adλ), v = k * sdλ * Math.sin(adλ); + d3_geo_areaRingSum.add(Math.atan2(v, u)); + λ0 = λ, cosφ0 = cosφ, sinφ0 = sinφ; + } + d3_geo_area.lineEnd = function() { + nextPoint(λ00, φ00); + }; + } + function d3_geo_cartesian(spherical) { + var λ = spherical[0], φ = spherical[1], cosφ = Math.cos(φ); + return [ cosφ * Math.cos(λ), cosφ * Math.sin(λ), Math.sin(φ) ]; + } + function d3_geo_cartesianDot(a, b) { + return a[0] * b[0] + a[1] * b[1] + a[2] * b[2]; + } + function d3_geo_cartesianCross(a, b) { + return [ a[1] * b[2] - a[2] * b[1], a[2] * b[0] - a[0] * b[2], a[0] * b[1] - a[1] * b[0] ]; + } + function d3_geo_cartesianAdd(a, b) { + a[0] += b[0]; + a[1] += b[1]; + a[2] += b[2]; + } + function d3_geo_cartesianScale(vector, k) { + return [ vector[0] * k, vector[1] * k, vector[2] * k ]; + } + function d3_geo_cartesianNormalize(d) { + var l = Math.sqrt(d[0] * d[0] + d[1] * d[1] + d[2] * d[2]); + d[0] /= l; + d[1] /= l; + d[2] /= l; + } + function d3_geo_spherical(cartesian) { + return [ Math.atan2(cartesian[1], cartesian[0]), d3_asin(cartesian[2]) ]; + } + function d3_geo_sphericalEqual(a, b) { + return abs(a[0] - b[0]) < ε && abs(a[1] - b[1]) < ε; + } + d3.geo.bounds = function() { + var λ0, φ0, λ1, φ1, λ_, λ__, φ__, p0, dλSum, ranges, range; + var bound = { + point: point, + lineStart: lineStart, + lineEnd: lineEnd, + polygonStart: function() { + bound.point = ringPoint; + bound.lineStart = ringStart; + bound.lineEnd = ringEnd; + dλSum = 0; + d3_geo_area.polygonStart(); + }, + polygonEnd: function() { + d3_geo_area.polygonEnd(); + bound.point = point; + bound.lineStart = lineStart; + bound.lineEnd = lineEnd; + if (d3_geo_areaRingSum < 0) λ0 = -(λ1 = 180), φ0 = -(φ1 = 90); else if (dλSum > ε) φ1 = 90; else if (dλSum < -ε) φ0 = -90; + range[0] = λ0, range[1] = λ1; + } + }; + function point(λ, φ) { + ranges.push(range = [ λ0 = λ, λ1 = λ ]); + if (φ < φ0) φ0 = φ; + if (φ > φ1) φ1 = φ; + } + function linePoint(λ, φ) { + var p = d3_geo_cartesian([ λ * d3_radians, φ * d3_radians ]); + if (p0) { + var normal = d3_geo_cartesianCross(p0, p), equatorial = [ normal[1], -normal[0], 0 ], inflection = d3_geo_cartesianCross(equatorial, normal); + d3_geo_cartesianNormalize(inflection); + inflection = d3_geo_spherical(inflection); + var dλ = λ - λ_, s = dλ > 0 ? 1 : -1, λi = inflection[0] * d3_degrees * s, antimeridian = abs(dλ) > 180; + if (antimeridian ^ (s * λ_ < λi && λi < s * λ)) { + var φi = inflection[1] * d3_degrees; + if (φi > φ1) φ1 = φi; + } else if (λi = (λi + 360) % 360 - 180, antimeridian ^ (s * λ_ < λi && λi < s * λ)) { + var φi = -inflection[1] * d3_degrees; + if (φi < φ0) φ0 = φi; + } else { + if (φ < φ0) φ0 = φ; + if (φ > φ1) φ1 = φ; + } + if (antimeridian) { + if (λ < λ_) { + if (angle(λ0, λ) > angle(λ0, λ1)) λ1 = λ; + } else { + if (angle(λ, λ1) > angle(λ0, λ1)) λ0 = λ; + } + } else { + if (λ1 >= λ0) { + if (λ < λ0) λ0 = λ; + if (λ > λ1) λ1 = λ; + } else { + if (λ > λ_) { + if (angle(λ0, λ) > angle(λ0, λ1)) λ1 = λ; + } else { + if (angle(λ, λ1) > angle(λ0, λ1)) λ0 = λ; + } + } + } + } else { + point(λ, φ); + } + p0 = p, λ_ = λ; + } + function lineStart() { + bound.point = linePoint; + } + function lineEnd() { + range[0] = λ0, range[1] = λ1; + bound.point = point; + p0 = null; + } + function ringPoint(λ, φ) { + if (p0) { + var dλ = λ - λ_; + dλSum += abs(dλ) > 180 ? dλ + (dλ > 0 ? 360 : -360) : dλ; + } else λ__ = λ, φ__ = φ; + d3_geo_area.point(λ, φ); + linePoint(λ, φ); + } + function ringStart() { + d3_geo_area.lineStart(); + } + function ringEnd() { + ringPoint(λ__, φ__); + d3_geo_area.lineEnd(); + if (abs(dλSum) > ε) λ0 = -(λ1 = 180); + range[0] = λ0, range[1] = λ1; + p0 = null; + } + function angle(λ0, λ1) { + return (λ1 -= λ0) < 0 ? λ1 + 360 : λ1; + } + function compareRanges(a, b) { + return a[0] - b[0]; + } + function withinRange(x, range) { + return range[0] <= range[1] ? range[0] <= x && x <= range[1] : x < range[0] || range[1] < x; + } + return function(feature) { + φ1 = λ1 = -(λ0 = φ0 = Infinity); + ranges = []; + d3.geo.stream(feature, bound); + var n = ranges.length; + if (n) { + ranges.sort(compareRanges); + for (var i = 1, a = ranges[0], b, merged = [ a ]; i < n; ++i) { + b = ranges[i]; + if (withinRange(b[0], a) || withinRange(b[1], a)) { + if (angle(a[0], b[1]) > angle(a[0], a[1])) a[1] = b[1]; + if (angle(b[0], a[1]) > angle(a[0], a[1])) a[0] = b[0]; + } else { + merged.push(a = b); + } + } + var best = -Infinity, dλ; + for (var n = merged.length - 1, i = 0, a = merged[n], b; i <= n; a = b, ++i) { + b = merged[i]; + if ((dλ = angle(a[1], b[0])) > best) best = dλ, λ0 = b[0], λ1 = a[1]; + } + } + ranges = range = null; + return λ0 === Infinity || φ0 === Infinity ? [ [ NaN, NaN ], [ NaN, NaN ] ] : [ [ λ0, φ0 ], [ λ1, φ1 ] ]; + }; + }(); + d3.geo.centroid = function(object) { + d3_geo_centroidW0 = d3_geo_centroidW1 = d3_geo_centroidX0 = d3_geo_centroidY0 = d3_geo_centroidZ0 = d3_geo_centroidX1 = d3_geo_centroidY1 = d3_geo_centroidZ1 = d3_geo_centroidX2 = d3_geo_centroidY2 = d3_geo_centroidZ2 = 0; + d3.geo.stream(object, d3_geo_centroid); + var x = d3_geo_centroidX2, y = d3_geo_centroidY2, z = d3_geo_centroidZ2, m = x * x + y * y + z * z; + if (m < ε2) { + x = d3_geo_centroidX1, y = d3_geo_centroidY1, z = d3_geo_centroidZ1; + if (d3_geo_centroidW1 < ε) x = d3_geo_centroidX0, y = d3_geo_centroidY0, z = d3_geo_centroidZ0; + m = x * x + y * y + z * z; + if (m < ε2) return [ NaN, NaN ]; + } + return [ Math.atan2(y, x) * d3_degrees, d3_asin(z / Math.sqrt(m)) * d3_degrees ]; + }; + var d3_geo_centroidW0, d3_geo_centroidW1, d3_geo_centroidX0, d3_geo_centroidY0, d3_geo_centroidZ0, d3_geo_centroidX1, d3_geo_centroidY1, d3_geo_centroidZ1, d3_geo_centroidX2, d3_geo_centroidY2, d3_geo_centroidZ2; + var d3_geo_centroid = { + sphere: d3_noop, + point: d3_geo_centroidPoint, + lineStart: d3_geo_centroidLineStart, + lineEnd: d3_geo_centroidLineEnd, + polygonStart: function() { + d3_geo_centroid.lineStart = d3_geo_centroidRingStart; + }, + polygonEnd: function() { + d3_geo_centroid.lineStart = d3_geo_centroidLineStart; + } + }; + function d3_geo_centroidPoint(λ, φ) { + λ *= d3_radians; + var cosφ = Math.cos(φ *= d3_radians); + d3_geo_centroidPointXYZ(cosφ * Math.cos(λ), cosφ * Math.sin(λ), Math.sin(φ)); + } + function d3_geo_centroidPointXYZ(x, y, z) { + ++d3_geo_centroidW0; + d3_geo_centroidX0 += (x - d3_geo_centroidX0) / d3_geo_centroidW0; + d3_geo_centroidY0 += (y - d3_geo_centroidY0) / d3_geo_centroidW0; + d3_geo_centroidZ0 += (z - d3_geo_centroidZ0) / d3_geo_centroidW0; + } + function d3_geo_centroidLineStart() { + var x0, y0, z0; + d3_geo_centroid.point = function(λ, φ) { + λ *= d3_radians; + var cosφ = Math.cos(φ *= d3_radians); + x0 = cosφ * Math.cos(λ); + y0 = cosφ * Math.sin(λ); + z0 = Math.sin(φ); + d3_geo_centroid.point = nextPoint; + d3_geo_centroidPointXYZ(x0, y0, z0); + }; + function nextPoint(λ, φ) { + λ *= d3_radians; + var cosφ = Math.cos(φ *= d3_radians), x = cosφ * Math.cos(λ), y = cosφ * Math.sin(λ), z = Math.sin(φ), w = Math.atan2(Math.sqrt((w = y0 * z - z0 * y) * w + (w = z0 * x - x0 * z) * w + (w = x0 * y - y0 * x) * w), x0 * x + y0 * y + z0 * z); + d3_geo_centroidW1 += w; + d3_geo_centroidX1 += w * (x0 + (x0 = x)); + d3_geo_centroidY1 += w * (y0 + (y0 = y)); + d3_geo_centroidZ1 += w * (z0 + (z0 = z)); + d3_geo_centroidPointXYZ(x0, y0, z0); + } + } + function d3_geo_centroidLineEnd() { + d3_geo_centroid.point = d3_geo_centroidPoint; + } + function d3_geo_centroidRingStart() { + var λ00, φ00, x0, y0, z0; + d3_geo_centroid.point = function(λ, φ) { + λ00 = λ, φ00 = φ; + d3_geo_centroid.point = nextPoint; + λ *= d3_radians; + var cosφ = Math.cos(φ *= d3_radians); + x0 = cosφ * Math.cos(λ); + y0 = cosφ * Math.sin(λ); + z0 = Math.sin(φ); + d3_geo_centroidPointXYZ(x0, y0, z0); + }; + d3_geo_centroid.lineEnd = function() { + nextPoint(λ00, φ00); + d3_geo_centroid.lineEnd = d3_geo_centroidLineEnd; + d3_geo_centroid.point = d3_geo_centroidPoint; + }; + function nextPoint(λ, φ) { + λ *= d3_radians; + var cosφ = Math.cos(φ *= d3_radians), x = cosφ * Math.cos(λ), y = cosφ * Math.sin(λ), z = Math.sin(φ), cx = y0 * z - z0 * y, cy = z0 * x - x0 * z, cz = x0 * y - y0 * x, m = Math.sqrt(cx * cx + cy * cy + cz * cz), u = x0 * x + y0 * y + z0 * z, v = m && -d3_acos(u) / m, w = Math.atan2(m, u); + d3_geo_centroidX2 += v * cx; + d3_geo_centroidY2 += v * cy; + d3_geo_centroidZ2 += v * cz; + d3_geo_centroidW1 += w; + d3_geo_centroidX1 += w * (x0 + (x0 = x)); + d3_geo_centroidY1 += w * (y0 + (y0 = y)); + d3_geo_centroidZ1 += w * (z0 + (z0 = z)); + d3_geo_centroidPointXYZ(x0, y0, z0); + } + } + function d3_true() { + return true; + } + function d3_geo_clipPolygon(segments, compare, clipStartInside, interpolate, listener) { + var subject = [], clip = []; + segments.forEach(function(segment) { + if ((n = segment.length - 1) <= 0) return; + var n, p0 = segment[0], p1 = segment[n]; + if (d3_geo_sphericalEqual(p0, p1)) { + listener.lineStart(); + for (var i = 0; i < n; ++i) listener.point((p0 = segment[i])[0], p0[1]); + listener.lineEnd(); + return; + } + var a = new d3_geo_clipPolygonIntersection(p0, segment, null, true), b = new d3_geo_clipPolygonIntersection(p0, null, a, false); + a.o = b; + subject.push(a); + clip.push(b); + a = new d3_geo_clipPolygonIntersection(p1, segment, null, false); + b = new d3_geo_clipPolygonIntersection(p1, null, a, true); + a.o = b; + subject.push(a); + clip.push(b); + }); + clip.sort(compare); + d3_geo_clipPolygonLinkCircular(subject); + d3_geo_clipPolygonLinkCircular(clip); + if (!subject.length) return; + for (var i = 0, entry = clipStartInside, n = clip.length; i < n; ++i) { + clip[i].e = entry = !entry; + } + var start = subject[0], points, point; + while (1) { + var current = start, isSubject = true; + while (current.v) if ((current = current.n) === start) return; + points = current.z; + listener.lineStart(); + do { + current.v = current.o.v = true; + if (current.e) { + if (isSubject) { + for (var i = 0, n = points.length; i < n; ++i) listener.point((point = points[i])[0], point[1]); + } else { + interpolate(current.x, current.n.x, 1, listener); + } + current = current.n; + } else { + if (isSubject) { + points = current.p.z; + for (var i = points.length - 1; i >= 0; --i) listener.point((point = points[i])[0], point[1]); + } else { + interpolate(current.x, current.p.x, -1, listener); + } + current = current.p; + } + current = current.o; + points = current.z; + isSubject = !isSubject; + } while (!current.v); + listener.lineEnd(); + } + } + function d3_geo_clipPolygonLinkCircular(array) { + if (!(n = array.length)) return; + var n, i = 0, a = array[0], b; + while (++i < n) { + a.n = b = array[i]; + b.p = a; + a = b; + } + a.n = b = array[0]; + b.p = a; + } + function d3_geo_clipPolygonIntersection(point, points, other, entry) { + this.x = point; + this.z = points; + this.o = other; + this.e = entry; + this.v = false; + this.n = this.p = null; + } + function d3_geo_clip(pointVisible, clipLine, interpolate, clipStart) { + return function(rotate, listener) { + var line = clipLine(listener), rotatedClipStart = rotate.invert(clipStart[0], clipStart[1]); + var clip = { + point: point, + lineStart: lineStart, + lineEnd: lineEnd, + polygonStart: function() { + clip.point = pointRing; + clip.lineStart = ringStart; + clip.lineEnd = ringEnd; + segments = []; + polygon = []; + }, + polygonEnd: function() { + clip.point = point; + clip.lineStart = lineStart; + clip.lineEnd = lineEnd; + segments = d3.merge(segments); + var clipStartInside = d3_geo_pointInPolygon(rotatedClipStart, polygon); + if (segments.length) { + if (!polygonStarted) listener.polygonStart(), polygonStarted = true; + d3_geo_clipPolygon(segments, d3_geo_clipSort, clipStartInside, interpolate, listener); + } else if (clipStartInside) { + if (!polygonStarted) listener.polygonStart(), polygonStarted = true; + listener.lineStart(); + interpolate(null, null, 1, listener); + listener.lineEnd(); + } + if (polygonStarted) listener.polygonEnd(), polygonStarted = false; + segments = polygon = null; + }, + sphere: function() { + listener.polygonStart(); + listener.lineStart(); + interpolate(null, null, 1, listener); + listener.lineEnd(); + listener.polygonEnd(); + } + }; + function point(λ, φ) { + var point = rotate(λ, φ); + if (pointVisible(λ = point[0], φ = point[1])) listener.point(λ, φ); + } + function pointLine(λ, φ) { + var point = rotate(λ, φ); + line.point(point[0], point[1]); + } + function lineStart() { + clip.point = pointLine; + line.lineStart(); + } + function lineEnd() { + clip.point = point; + line.lineEnd(); + } + var segments; + var buffer = d3_geo_clipBufferListener(), ringListener = clipLine(buffer), polygonStarted = false, polygon, ring; + function pointRing(λ, φ) { + ring.push([ λ, φ ]); + var point = rotate(λ, φ); + ringListener.point(point[0], point[1]); + } + function ringStart() { + ringListener.lineStart(); + ring = []; + } + function ringEnd() { + pointRing(ring[0][0], ring[0][1]); + ringListener.lineEnd(); + var clean = ringListener.clean(), ringSegments = buffer.buffer(), segment, n = ringSegments.length; + ring.pop(); + polygon.push(ring); + ring = null; + if (!n) return; + if (clean & 1) { + segment = ringSegments[0]; + var n = segment.length - 1, i = -1, point; + if (n > 0) { + if (!polygonStarted) listener.polygonStart(), polygonStarted = true; + listener.lineStart(); + while (++i < n) listener.point((point = segment[i])[0], point[1]); + listener.lineEnd(); + } + return; + } + if (n > 1 && clean & 2) ringSegments.push(ringSegments.pop().concat(ringSegments.shift())); + segments.push(ringSegments.filter(d3_geo_clipSegmentLength1)); + } + return clip; + }; + } + function d3_geo_clipSegmentLength1(segment) { + return segment.length > 1; + } + function d3_geo_clipBufferListener() { + var lines = [], line; + return { + lineStart: function() { + lines.push(line = []); + }, + point: function(λ, φ) { + line.push([ λ, φ ]); + }, + lineEnd: d3_noop, + buffer: function() { + var buffer = lines; + lines = []; + line = null; + return buffer; + }, + rejoin: function() { + if (lines.length > 1) lines.push(lines.pop().concat(lines.shift())); + } + }; + } + function d3_geo_clipSort(a, b) { + return ((a = a.x)[0] < 0 ? a[1] - halfπ - ε : halfπ - a[1]) - ((b = b.x)[0] < 0 ? b[1] - halfπ - ε : halfπ - b[1]); + } + function d3_geo_pointInPolygon(point, polygon) { + var meridian = point[0], parallel = point[1], meridianNormal = [ Math.sin(meridian), -Math.cos(meridian), 0 ], polarAngle = 0, winding = 0; + d3_geo_areaRingSum.reset(); + for (var i = 0, n = polygon.length; i < n; ++i) { + var ring = polygon[i], m = ring.length; + if (!m) continue; + var point0 = ring[0], λ0 = point0[0], φ0 = point0[1] / 2 + π / 4, sinφ0 = Math.sin(φ0), cosφ0 = Math.cos(φ0), j = 1; + while (true) { + if (j === m) j = 0; + point = ring[j]; + var λ = point[0], φ = point[1] / 2 + π / 4, sinφ = Math.sin(φ), cosφ = Math.cos(φ), dλ = λ - λ0, sdλ = dλ >= 0 ? 1 : -1, adλ = sdλ * dλ, antimeridian = adλ > π, k = sinφ0 * sinφ; + d3_geo_areaRingSum.add(Math.atan2(k * sdλ * Math.sin(adλ), cosφ0 * cosφ + k * Math.cos(adλ))); + polarAngle += antimeridian ? dλ + sdλ * τ : dλ; + if (antimeridian ^ λ0 >= meridian ^ λ >= meridian) { + var arc = d3_geo_cartesianCross(d3_geo_cartesian(point0), d3_geo_cartesian(point)); + d3_geo_cartesianNormalize(arc); + var intersection = d3_geo_cartesianCross(meridianNormal, arc); + d3_geo_cartesianNormalize(intersection); + var φarc = (antimeridian ^ dλ >= 0 ? -1 : 1) * d3_asin(intersection[2]); + if (parallel > φarc || parallel === φarc && (arc[0] || arc[1])) { + winding += antimeridian ^ dλ >= 0 ? 1 : -1; + } + } + if (!j++) break; + λ0 = λ, sinφ0 = sinφ, cosφ0 = cosφ, point0 = point; + } + } + return (polarAngle < -ε || polarAngle < ε && d3_geo_areaRingSum < 0) ^ winding & 1; + } + var d3_geo_clipAntimeridian = d3_geo_clip(d3_true, d3_geo_clipAntimeridianLine, d3_geo_clipAntimeridianInterpolate, [ -π, -π / 2 ]); + function d3_geo_clipAntimeridianLine(listener) { + var λ0 = NaN, φ0 = NaN, sλ0 = NaN, clean; + return { + lineStart: function() { + listener.lineStart(); + clean = 1; + }, + point: function(λ1, φ1) { + var sλ1 = λ1 > 0 ? π : -π, dλ = abs(λ1 - λ0); + if (abs(dλ - π) < ε) { + listener.point(λ0, φ0 = (φ0 + φ1) / 2 > 0 ? halfπ : -halfπ); + listener.point(sλ0, φ0); + listener.lineEnd(); + listener.lineStart(); + listener.point(sλ1, φ0); + listener.point(λ1, φ0); + clean = 0; + } else if (sλ0 !== sλ1 && dλ >= π) { + if (abs(λ0 - sλ0) < ε) λ0 -= sλ0 * ε; + if (abs(λ1 - sλ1) < ε) λ1 -= sλ1 * ε; + φ0 = d3_geo_clipAntimeridianIntersect(λ0, φ0, λ1, φ1); + listener.point(sλ0, φ0); + listener.lineEnd(); + listener.lineStart(); + listener.point(sλ1, φ0); + clean = 0; + } + listener.point(λ0 = λ1, φ0 = φ1); + sλ0 = sλ1; + }, + lineEnd: function() { + listener.lineEnd(); + λ0 = φ0 = NaN; + }, + clean: function() { + return 2 - clean; + } + }; + } + function d3_geo_clipAntimeridianIntersect(λ0, φ0, λ1, φ1) { + var cosφ0, cosφ1, sinλ0_λ1 = Math.sin(λ0 - λ1); + return abs(sinλ0_λ1) > ε ? Math.atan((Math.sin(φ0) * (cosφ1 = Math.cos(φ1)) * Math.sin(λ1) - Math.sin(φ1) * (cosφ0 = Math.cos(φ0)) * Math.sin(λ0)) / (cosφ0 * cosφ1 * sinλ0_λ1)) : (φ0 + φ1) / 2; + } + function d3_geo_clipAntimeridianInterpolate(from, to, direction, listener) { + var φ; + if (from == null) { + φ = direction * halfπ; + listener.point(-π, φ); + listener.point(0, φ); + listener.point(π, φ); + listener.point(π, 0); + listener.point(π, -φ); + listener.point(0, -φ); + listener.point(-π, -φ); + listener.point(-π, 0); + listener.point(-π, φ); + } else if (abs(from[0] - to[0]) > ε) { + var s = from[0] < to[0] ? π : -π; + φ = direction * s / 2; + listener.point(-s, φ); + listener.point(0, φ); + listener.point(s, φ); + } else { + listener.point(to[0], to[1]); + } + } + function d3_geo_clipCircle(radius) { + var cr = Math.cos(radius), smallRadius = cr > 0, notHemisphere = abs(cr) > ε, interpolate = d3_geo_circleInterpolate(radius, 6 * d3_radians); + return d3_geo_clip(visible, clipLine, interpolate, smallRadius ? [ 0, -radius ] : [ -π, radius - π ]); + function visible(λ, φ) { + return Math.cos(λ) * Math.cos(φ) > cr; + } + function clipLine(listener) { + var point0, c0, v0, v00, clean; + return { + lineStart: function() { + v00 = v0 = false; + clean = 1; + }, + point: function(λ, φ) { + var point1 = [ λ, φ ], point2, v = visible(λ, φ), c = smallRadius ? v ? 0 : code(λ, φ) : v ? code(λ + (λ < 0 ? π : -π), φ) : 0; + if (!point0 && (v00 = v0 = v)) listener.lineStart(); + if (v !== v0) { + point2 = intersect(point0, point1); + if (d3_geo_sphericalEqual(point0, point2) || d3_geo_sphericalEqual(point1, point2)) { + point1[0] += ε; + point1[1] += ε; + v = visible(point1[0], point1[1]); + } + } + if (v !== v0) { + clean = 0; + if (v) { + listener.lineStart(); + point2 = intersect(point1, point0); + listener.point(point2[0], point2[1]); + } else { + point2 = intersect(point0, point1); + listener.point(point2[0], point2[1]); + listener.lineEnd(); + } + point0 = point2; + } else if (notHemisphere && point0 && smallRadius ^ v) { + var t; + if (!(c & c0) && (t = intersect(point1, point0, true))) { + clean = 0; + if (smallRadius) { + listener.lineStart(); + listener.point(t[0][0], t[0][1]); + listener.point(t[1][0], t[1][1]); + listener.lineEnd(); + } else { + listener.point(t[1][0], t[1][1]); + listener.lineEnd(); + listener.lineStart(); + listener.point(t[0][0], t[0][1]); + } + } + } + if (v && (!point0 || !d3_geo_sphericalEqual(point0, point1))) { + listener.point(point1[0], point1[1]); + } + point0 = point1, v0 = v, c0 = c; + }, + lineEnd: function() { + if (v0) listener.lineEnd(); + point0 = null; + }, + clean: function() { + return clean | (v00 && v0) << 1; + } + }; + } + function intersect(a, b, two) { + var pa = d3_geo_cartesian(a), pb = d3_geo_cartesian(b); + var n1 = [ 1, 0, 0 ], n2 = d3_geo_cartesianCross(pa, pb), n2n2 = d3_geo_cartesianDot(n2, n2), n1n2 = n2[0], determinant = n2n2 - n1n2 * n1n2; + if (!determinant) return !two && a; + var c1 = cr * n2n2 / determinant, c2 = -cr * n1n2 / determinant, n1xn2 = d3_geo_cartesianCross(n1, n2), A = d3_geo_cartesianScale(n1, c1), B = d3_geo_cartesianScale(n2, c2); + d3_geo_cartesianAdd(A, B); + var u = n1xn2, w = d3_geo_cartesianDot(A, u), uu = d3_geo_cartesianDot(u, u), t2 = w * w - uu * (d3_geo_cartesianDot(A, A) - 1); + if (t2 < 0) return; + var t = Math.sqrt(t2), q = d3_geo_cartesianScale(u, (-w - t) / uu); + d3_geo_cartesianAdd(q, A); + q = d3_geo_spherical(q); + if (!two) return q; + var λ0 = a[0], λ1 = b[0], φ0 = a[1], φ1 = b[1], z; + if (λ1 < λ0) z = λ0, λ0 = λ1, λ1 = z; + var δλ = λ1 - λ0, polar = abs(δλ - π) < ε, meridian = polar || δλ < ε; + if (!polar && φ1 < φ0) z = φ0, φ0 = φ1, φ1 = z; + if (meridian ? polar ? φ0 + φ1 > 0 ^ q[1] < (abs(q[0] - λ0) < ε ? φ0 : φ1) : φ0 <= q[1] && q[1] <= φ1 : δλ > π ^ (λ0 <= q[0] && q[0] <= λ1)) { + var q1 = d3_geo_cartesianScale(u, (-w + t) / uu); + d3_geo_cartesianAdd(q1, A); + return [ q, d3_geo_spherical(q1) ]; + } + } + function code(λ, φ) { + var r = smallRadius ? radius : π - radius, code = 0; + if (λ < -r) code |= 1; else if (λ > r) code |= 2; + if (φ < -r) code |= 4; else if (φ > r) code |= 8; + return code; + } + } + function d3_geom_clipLine(x0, y0, x1, y1) { + return function(line) { + var a = line.a, b = line.b, ax = a.x, ay = a.y, bx = b.x, by = b.y, t0 = 0, t1 = 1, dx = bx - ax, dy = by - ay, r; + r = x0 - ax; + if (!dx && r > 0) return; + r /= dx; + if (dx < 0) { + if (r < t0) return; + if (r < t1) t1 = r; + } else if (dx > 0) { + if (r > t1) return; + if (r > t0) t0 = r; + } + r = x1 - ax; + if (!dx && r < 0) return; + r /= dx; + if (dx < 0) { + if (r > t1) return; + if (r > t0) t0 = r; + } else if (dx > 0) { + if (r < t0) return; + if (r < t1) t1 = r; + } + r = y0 - ay; + if (!dy && r > 0) return; + r /= dy; + if (dy < 0) { + if (r < t0) return; + if (r < t1) t1 = r; + } else if (dy > 0) { + if (r > t1) return; + if (r > t0) t0 = r; + } + r = y1 - ay; + if (!dy && r < 0) return; + r /= dy; + if (dy < 0) { + if (r > t1) return; + if (r > t0) t0 = r; + } else if (dy > 0) { + if (r < t0) return; + if (r < t1) t1 = r; + } + if (t0 > 0) line.a = { + x: ax + t0 * dx, + y: ay + t0 * dy + }; + if (t1 < 1) line.b = { + x: ax + t1 * dx, + y: ay + t1 * dy + }; + return line; + }; + } + var d3_geo_clipExtentMAX = 1e9; + d3.geo.clipExtent = function() { + var x0, y0, x1, y1, stream, clip, clipExtent = { + stream: function(output) { + if (stream) stream.valid = false; + stream = clip(output); + stream.valid = true; + return stream; + }, + extent: function(_) { + if (!arguments.length) return [ [ x0, y0 ], [ x1, y1 ] ]; + clip = d3_geo_clipExtent(x0 = +_[0][0], y0 = +_[0][1], x1 = +_[1][0], y1 = +_[1][1]); + if (stream) stream.valid = false, stream = null; + return clipExtent; + } + }; + return clipExtent.extent([ [ 0, 0 ], [ 960, 500 ] ]); + }; + function d3_geo_clipExtent(x0, y0, x1, y1) { + return function(listener) { + var listener_ = listener, bufferListener = d3_geo_clipBufferListener(), clipLine = d3_geom_clipLine(x0, y0, x1, y1), segments, polygon, ring; + var clip = { + point: point, + lineStart: lineStart, + lineEnd: lineEnd, + polygonStart: function() { + listener = bufferListener; + segments = []; + polygon = []; + clean = true; + }, + polygonEnd: function() { + listener = listener_; + segments = d3.merge(segments); + var clipStartInside = insidePolygon([ x0, y1 ]), inside = clean && clipStartInside, visible = segments.length; + if (inside || visible) { + listener.polygonStart(); + if (inside) { + listener.lineStart(); + interpolate(null, null, 1, listener); + listener.lineEnd(); + } + if (visible) { + d3_geo_clipPolygon(segments, compare, clipStartInside, interpolate, listener); + } + listener.polygonEnd(); + } + segments = polygon = ring = null; + } + }; + function insidePolygon(p) { + var wn = 0, n = polygon.length, y = p[1]; + for (var i = 0; i < n; ++i) { + for (var j = 1, v = polygon[i], m = v.length, a = v[0], b; j < m; ++j) { + b = v[j]; + if (a[1] <= y) { + if (b[1] > y && d3_cross2d(a, b, p) > 0) ++wn; + } else { + if (b[1] <= y && d3_cross2d(a, b, p) < 0) --wn; + } + a = b; + } + } + return wn !== 0; + } + function interpolate(from, to, direction, listener) { + var a = 0, a1 = 0; + if (from == null || (a = corner(from, direction)) !== (a1 = corner(to, direction)) || comparePoints(from, to) < 0 ^ direction > 0) { + do { + listener.point(a === 0 || a === 3 ? x0 : x1, a > 1 ? y1 : y0); + } while ((a = (a + direction + 4) % 4) !== a1); + } else { + listener.point(to[0], to[1]); + } + } + function pointVisible(x, y) { + return x0 <= x && x <= x1 && y0 <= y && y <= y1; + } + function point(x, y) { + if (pointVisible(x, y)) listener.point(x, y); + } + var x__, y__, v__, x_, y_, v_, first, clean; + function lineStart() { + clip.point = linePoint; + if (polygon) polygon.push(ring = []); + first = true; + v_ = false; + x_ = y_ = NaN; + } + function lineEnd() { + if (segments) { + linePoint(x__, y__); + if (v__ && v_) bufferListener.rejoin(); + segments.push(bufferListener.buffer()); + } + clip.point = point; + if (v_) listener.lineEnd(); + } + function linePoint(x, y) { + x = Math.max(-d3_geo_clipExtentMAX, Math.min(d3_geo_clipExtentMAX, x)); + y = Math.max(-d3_geo_clipExtentMAX, Math.min(d3_geo_clipExtentMAX, y)); + var v = pointVisible(x, y); + if (polygon) ring.push([ x, y ]); + if (first) { + x__ = x, y__ = y, v__ = v; + first = false; + if (v) { + listener.lineStart(); + listener.point(x, y); + } + } else { + if (v && v_) listener.point(x, y); else { + var l = { + a: { + x: x_, + y: y_ + }, + b: { + x: x, + y: y + } + }; + if (clipLine(l)) { + if (!v_) { + listener.lineStart(); + listener.point(l.a.x, l.a.y); + } + listener.point(l.b.x, l.b.y); + if (!v) listener.lineEnd(); + clean = false; + } else if (v) { + listener.lineStart(); + listener.point(x, y); + clean = false; + } + } + } + x_ = x, y_ = y, v_ = v; + } + return clip; + }; + function corner(p, direction) { + return abs(p[0] - x0) < ε ? direction > 0 ? 0 : 3 : abs(p[0] - x1) < ε ? direction > 0 ? 2 : 1 : abs(p[1] - y0) < ε ? direction > 0 ? 1 : 0 : direction > 0 ? 3 : 2; + } + function compare(a, b) { + return comparePoints(a.x, b.x); + } + function comparePoints(a, b) { + var ca = corner(a, 1), cb = corner(b, 1); + return ca !== cb ? ca - cb : ca === 0 ? b[1] - a[1] : ca === 1 ? a[0] - b[0] : ca === 2 ? a[1] - b[1] : b[0] - a[0]; + } + } + function d3_geo_compose(a, b) { + function compose(x, y) { + return x = a(x, y), b(x[0], x[1]); + } + if (a.invert && b.invert) compose.invert = function(x, y) { + return x = b.invert(x, y), x && a.invert(x[0], x[1]); + }; + return compose; + } + function d3_geo_conic(projectAt) { + var φ0 = 0, φ1 = π / 3, m = d3_geo_projectionMutator(projectAt), p = m(φ0, φ1); + p.parallels = function(_) { + if (!arguments.length) return [ φ0 / π * 180, φ1 / π * 180 ]; + return m(φ0 = _[0] * π / 180, φ1 = _[1] * π / 180); + }; + return p; + } + function d3_geo_conicEqualArea(φ0, φ1) { + var sinφ0 = Math.sin(φ0), n = (sinφ0 + Math.sin(φ1)) / 2, C = 1 + sinφ0 * (2 * n - sinφ0), ρ0 = Math.sqrt(C) / n; + function forward(λ, φ) { + var ρ = Math.sqrt(C - 2 * n * Math.sin(φ)) / n; + return [ ρ * Math.sin(λ *= n), ρ0 - ρ * Math.cos(λ) ]; + } + forward.invert = function(x, y) { + var ρ0_y = ρ0 - y; + return [ Math.atan2(x, ρ0_y) / n, d3_asin((C - (x * x + ρ0_y * ρ0_y) * n * n) / (2 * n)) ]; + }; + return forward; + } + (d3.geo.conicEqualArea = function() { + return d3_geo_conic(d3_geo_conicEqualArea); + }).raw = d3_geo_conicEqualArea; + d3.geo.albers = function() { + return d3.geo.conicEqualArea().rotate([ 96, 0 ]).center([ -.6, 38.7 ]).parallels([ 29.5, 45.5 ]).scale(1070); + }; + d3.geo.albersUsa = function() { + var lower48 = d3.geo.albers(); + var alaska = d3.geo.conicEqualArea().rotate([ 154, 0 ]).center([ -2, 58.5 ]).parallels([ 55, 65 ]); + var hawaii = d3.geo.conicEqualArea().rotate([ 157, 0 ]).center([ -3, 19.9 ]).parallels([ 8, 18 ]); + var point, pointStream = { + point: function(x, y) { + point = [ x, y ]; + } + }, lower48Point, alaskaPoint, hawaiiPoint; + function albersUsa(coordinates) { + var x = coordinates[0], y = coordinates[1]; + point = null; + (lower48Point(x, y), point) || (alaskaPoint(x, y), point) || hawaiiPoint(x, y); + return point; + } + albersUsa.invert = function(coordinates) { + var k = lower48.scale(), t = lower48.translate(), x = (coordinates[0] - t[0]) / k, y = (coordinates[1] - t[1]) / k; + return (y >= .12 && y < .234 && x >= -.425 && x < -.214 ? alaska : y >= .166 && y < .234 && x >= -.214 && x < -.115 ? hawaii : lower48).invert(coordinates); + }; + albersUsa.stream = function(stream) { + var lower48Stream = lower48.stream(stream), alaskaStream = alaska.stream(stream), hawaiiStream = hawaii.stream(stream); + return { + point: function(x, y) { + lower48Stream.point(x, y); + alaskaStream.point(x, y); + hawaiiStream.point(x, y); + }, + sphere: function() { + lower48Stream.sphere(); + alaskaStream.sphere(); + hawaiiStream.sphere(); + }, + lineStart: function() { + lower48Stream.lineStart(); + alaskaStream.lineStart(); + hawaiiStream.lineStart(); + }, + lineEnd: function() { + lower48Stream.lineEnd(); + alaskaStream.lineEnd(); + hawaiiStream.lineEnd(); + }, + polygonStart: function() { + lower48Stream.polygonStart(); + alaskaStream.polygonStart(); + hawaiiStream.polygonStart(); + }, + polygonEnd: function() { + lower48Stream.polygonEnd(); + alaskaStream.polygonEnd(); + hawaiiStream.polygonEnd(); + } + }; + }; + albersUsa.precision = function(_) { + if (!arguments.length) return lower48.precision(); + lower48.precision(_); + alaska.precision(_); + hawaii.precision(_); + return albersUsa; + }; + albersUsa.scale = function(_) { + if (!arguments.length) return lower48.scale(); + lower48.scale(_); + alaska.scale(_ * .35); + hawaii.scale(_); + return albersUsa.translate(lower48.translate()); + }; + albersUsa.translate = function(_) { + if (!arguments.length) return lower48.translate(); + var k = lower48.scale(), x = +_[0], y = +_[1]; + lower48Point = lower48.translate(_).clipExtent([ [ x - .455 * k, y - .238 * k ], [ x + .455 * k, y + .238 * k ] ]).stream(pointStream).point; + alaskaPoint = alaska.translate([ x - .307 * k, y + .201 * k ]).clipExtent([ [ x - .425 * k + ε, y + .12 * k + ε ], [ x - .214 * k - ε, y + .234 * k - ε ] ]).stream(pointStream).point; + hawaiiPoint = hawaii.translate([ x - .205 * k, y + .212 * k ]).clipExtent([ [ x - .214 * k + ε, y + .166 * k + ε ], [ x - .115 * k - ε, y + .234 * k - ε ] ]).stream(pointStream).point; + return albersUsa; + }; + return albersUsa.scale(1070); + }; + var d3_geo_pathAreaSum, d3_geo_pathAreaPolygon, d3_geo_pathArea = { + point: d3_noop, + lineStart: d3_noop, + lineEnd: d3_noop, + polygonStart: function() { + d3_geo_pathAreaPolygon = 0; + d3_geo_pathArea.lineStart = d3_geo_pathAreaRingStart; + }, + polygonEnd: function() { + d3_geo_pathArea.lineStart = d3_geo_pathArea.lineEnd = d3_geo_pathArea.point = d3_noop; + d3_geo_pathAreaSum += abs(d3_geo_pathAreaPolygon / 2); + } + }; + function d3_geo_pathAreaRingStart() { + var x00, y00, x0, y0; + d3_geo_pathArea.point = function(x, y) { + d3_geo_pathArea.point = nextPoint; + x00 = x0 = x, y00 = y0 = y; + }; + function nextPoint(x, y) { + d3_geo_pathAreaPolygon += y0 * x - x0 * y; + x0 = x, y0 = y; + } + d3_geo_pathArea.lineEnd = function() { + nextPoint(x00, y00); + }; + } + var d3_geo_pathBoundsX0, d3_geo_pathBoundsY0, d3_geo_pathBoundsX1, d3_geo_pathBoundsY1; + var d3_geo_pathBounds = { + point: d3_geo_pathBoundsPoint, + lineStart: d3_noop, + lineEnd: d3_noop, + polygonStart: d3_noop, + polygonEnd: d3_noop + }; + function d3_geo_pathBoundsPoint(x, y) { + if (x < d3_geo_pathBoundsX0) d3_geo_pathBoundsX0 = x; + if (x > d3_geo_pathBoundsX1) d3_geo_pathBoundsX1 = x; + if (y < d3_geo_pathBoundsY0) d3_geo_pathBoundsY0 = y; + if (y > d3_geo_pathBoundsY1) d3_geo_pathBoundsY1 = y; + } + function d3_geo_pathBuffer() { + var pointCircle = d3_geo_pathBufferCircle(4.5), buffer = []; + var stream = { + point: point, + lineStart: function() { + stream.point = pointLineStart; + }, + lineEnd: lineEnd, + polygonStart: function() { + stream.lineEnd = lineEndPolygon; + }, + polygonEnd: function() { + stream.lineEnd = lineEnd; + stream.point = point; + }, + pointRadius: function(_) { + pointCircle = d3_geo_pathBufferCircle(_); + return stream; + }, + result: function() { + if (buffer.length) { + var result = buffer.join(""); + buffer = []; + return result; + } + } + }; + function point(x, y) { + buffer.push("M", x, ",", y, pointCircle); + } + function pointLineStart(x, y) { + buffer.push("M", x, ",", y); + stream.point = pointLine; + } + function pointLine(x, y) { + buffer.push("L", x, ",", y); + } + function lineEnd() { + stream.point = point; + } + function lineEndPolygon() { + buffer.push("Z"); + } + return stream; + } + function d3_geo_pathBufferCircle(radius) { + return "m0," + radius + "a" + radius + "," + radius + " 0 1,1 0," + -2 * radius + "a" + radius + "," + radius + " 0 1,1 0," + 2 * radius + "z"; + } + var d3_geo_pathCentroid = { + point: d3_geo_pathCentroidPoint, + lineStart: d3_geo_pathCentroidLineStart, + lineEnd: d3_geo_pathCentroidLineEnd, + polygonStart: function() { + d3_geo_pathCentroid.lineStart = d3_geo_pathCentroidRingStart; + }, + polygonEnd: function() { + d3_geo_pathCentroid.point = d3_geo_pathCentroidPoint; + d3_geo_pathCentroid.lineStart = d3_geo_pathCentroidLineStart; + d3_geo_pathCentroid.lineEnd = d3_geo_pathCentroidLineEnd; + } + }; + function d3_geo_pathCentroidPoint(x, y) { + d3_geo_centroidX0 += x; + d3_geo_centroidY0 += y; + ++d3_geo_centroidZ0; + } + function d3_geo_pathCentroidLineStart() { + var x0, y0; + d3_geo_pathCentroid.point = function(x, y) { + d3_geo_pathCentroid.point = nextPoint; + d3_geo_pathCentroidPoint(x0 = x, y0 = y); + }; + function nextPoint(x, y) { + var dx = x - x0, dy = y - y0, z = Math.sqrt(dx * dx + dy * dy); + d3_geo_centroidX1 += z * (x0 + x) / 2; + d3_geo_centroidY1 += z * (y0 + y) / 2; + d3_geo_centroidZ1 += z; + d3_geo_pathCentroidPoint(x0 = x, y0 = y); + } + } + function d3_geo_pathCentroidLineEnd() { + d3_geo_pathCentroid.point = d3_geo_pathCentroidPoint; + } + function d3_geo_pathCentroidRingStart() { + var x00, y00, x0, y0; + d3_geo_pathCentroid.point = function(x, y) { + d3_geo_pathCentroid.point = nextPoint; + d3_geo_pathCentroidPoint(x00 = x0 = x, y00 = y0 = y); + }; + function nextPoint(x, y) { + var dx = x - x0, dy = y - y0, z = Math.sqrt(dx * dx + dy * dy); + d3_geo_centroidX1 += z * (x0 + x) / 2; + d3_geo_centroidY1 += z * (y0 + y) / 2; + d3_geo_centroidZ1 += z; + z = y0 * x - x0 * y; + d3_geo_centroidX2 += z * (x0 + x); + d3_geo_centroidY2 += z * (y0 + y); + d3_geo_centroidZ2 += z * 3; + d3_geo_pathCentroidPoint(x0 = x, y0 = y); + } + d3_geo_pathCentroid.lineEnd = function() { + nextPoint(x00, y00); + }; + } + function d3_geo_pathContext(context) { + var pointRadius = 4.5; + var stream = { + point: point, + lineStart: function() { + stream.point = pointLineStart; + }, + lineEnd: lineEnd, + polygonStart: function() { + stream.lineEnd = lineEndPolygon; + }, + polygonEnd: function() { + stream.lineEnd = lineEnd; + stream.point = point; + }, + pointRadius: function(_) { + pointRadius = _; + return stream; + }, + result: d3_noop + }; + function point(x, y) { + context.moveTo(x, y); + context.arc(x, y, pointRadius, 0, τ); + } + function pointLineStart(x, y) { + context.moveTo(x, y); + stream.point = pointLine; + } + function pointLine(x, y) { + context.lineTo(x, y); + } + function lineEnd() { + stream.point = point; + } + function lineEndPolygon() { + context.closePath(); + } + return stream; + } + function d3_geo_resample(project) { + var δ2 = .5, cosMinDistance = Math.cos(30 * d3_radians), maxDepth = 16; + function resample(stream) { + return (maxDepth ? resampleRecursive : resampleNone)(stream); + } + function resampleNone(stream) { + return d3_geo_transformPoint(stream, function(x, y) { + x = project(x, y); + stream.point(x[0], x[1]); + }); + } + function resampleRecursive(stream) { + var λ00, φ00, x00, y00, a00, b00, c00, λ0, x0, y0, a0, b0, c0; + var resample = { + point: point, + lineStart: lineStart, + lineEnd: lineEnd, + polygonStart: function() { + stream.polygonStart(); + resample.lineStart = ringStart; + }, + polygonEnd: function() { + stream.polygonEnd(); + resample.lineStart = lineStart; + } + }; + function point(x, y) { + x = project(x, y); + stream.point(x[0], x[1]); + } + function lineStart() { + x0 = NaN; + resample.point = linePoint; + stream.lineStart(); + } + function linePoint(λ, φ) { + var c = d3_geo_cartesian([ λ, φ ]), p = project(λ, φ); + resampleLineTo(x0, y0, λ0, a0, b0, c0, x0 = p[0], y0 = p[1], λ0 = λ, a0 = c[0], b0 = c[1], c0 = c[2], maxDepth, stream); + stream.point(x0, y0); + } + function lineEnd() { + resample.point = point; + stream.lineEnd(); + } + function ringStart() { + lineStart(); + resample.point = ringPoint; + resample.lineEnd = ringEnd; + } + function ringPoint(λ, φ) { + linePoint(λ00 = λ, φ00 = φ), x00 = x0, y00 = y0, a00 = a0, b00 = b0, c00 = c0; + resample.point = linePoint; + } + function ringEnd() { + resampleLineTo(x0, y0, λ0, a0, b0, c0, x00, y00, λ00, a00, b00, c00, maxDepth, stream); + resample.lineEnd = lineEnd; + lineEnd(); + } + return resample; + } + function resampleLineTo(x0, y0, λ0, a0, b0, c0, x1, y1, λ1, a1, b1, c1, depth, stream) { + var dx = x1 - x0, dy = y1 - y0, d2 = dx * dx + dy * dy; + if (d2 > 4 * δ2 && depth--) { + var a = a0 + a1, b = b0 + b1, c = c0 + c1, m = Math.sqrt(a * a + b * b + c * c), φ2 = Math.asin(c /= m), λ2 = abs(abs(c) - 1) < ε || abs(λ0 - λ1) < ε ? (λ0 + λ1) / 2 : Math.atan2(b, a), p = project(λ2, φ2), x2 = p[0], y2 = p[1], dx2 = x2 - x0, dy2 = y2 - y0, dz = dy * dx2 - dx * dy2; + if (dz * dz / d2 > δ2 || abs((dx * dx2 + dy * dy2) / d2 - .5) > .3 || a0 * a1 + b0 * b1 + c0 * c1 < cosMinDistance) { + resampleLineTo(x0, y0, λ0, a0, b0, c0, x2, y2, λ2, a /= m, b /= m, c, depth, stream); + stream.point(x2, y2); + resampleLineTo(x2, y2, λ2, a, b, c, x1, y1, λ1, a1, b1, c1, depth, stream); + } + } + } + resample.precision = function(_) { + if (!arguments.length) return Math.sqrt(δ2); + maxDepth = (δ2 = _ * _) > 0 && 16; + return resample; + }; + return resample; + } + d3.geo.path = function() { + var pointRadius = 4.5, projection, context, projectStream, contextStream, cacheStream; + function path(object) { + if (object) { + if (typeof pointRadius === "function") contextStream.pointRadius(+pointRadius.apply(this, arguments)); + if (!cacheStream || !cacheStream.valid) cacheStream = projectStream(contextStream); + d3.geo.stream(object, cacheStream); + } + return contextStream.result(); + } + path.area = function(object) { + d3_geo_pathAreaSum = 0; + d3.geo.stream(object, projectStream(d3_geo_pathArea)); + return d3_geo_pathAreaSum; + }; + path.centroid = function(object) { + d3_geo_centroidX0 = d3_geo_centroidY0 = d3_geo_centroidZ0 = d3_geo_centroidX1 = d3_geo_centroidY1 = d3_geo_centroidZ1 = d3_geo_centroidX2 = d3_geo_centroidY2 = d3_geo_centroidZ2 = 0; + d3.geo.stream(object, projectStream(d3_geo_pathCentroid)); + return d3_geo_centroidZ2 ? [ d3_geo_centroidX2 / d3_geo_centroidZ2, d3_geo_centroidY2 / d3_geo_centroidZ2 ] : d3_geo_centroidZ1 ? [ d3_geo_centroidX1 / d3_geo_centroidZ1, d3_geo_centroidY1 / d3_geo_centroidZ1 ] : d3_geo_centroidZ0 ? [ d3_geo_centroidX0 / d3_geo_centroidZ0, d3_geo_centroidY0 / d3_geo_centroidZ0 ] : [ NaN, NaN ]; + }; + path.bounds = function(object) { + d3_geo_pathBoundsX1 = d3_geo_pathBoundsY1 = -(d3_geo_pathBoundsX0 = d3_geo_pathBoundsY0 = Infinity); + d3.geo.stream(object, projectStream(d3_geo_pathBounds)); + return [ [ d3_geo_pathBoundsX0, d3_geo_pathBoundsY0 ], [ d3_geo_pathBoundsX1, d3_geo_pathBoundsY1 ] ]; + }; + path.projection = function(_) { + if (!arguments.length) return projection; + projectStream = (projection = _) ? _.stream || d3_geo_pathProjectStream(_) : d3_identity; + return reset(); + }; + path.context = function(_) { + if (!arguments.length) return context; + contextStream = (context = _) == null ? new d3_geo_pathBuffer() : new d3_geo_pathContext(_); + if (typeof pointRadius !== "function") contextStream.pointRadius(pointRadius); + return reset(); + }; + path.pointRadius = function(_) { + if (!arguments.length) return pointRadius; + pointRadius = typeof _ === "function" ? _ : (contextStream.pointRadius(+_), +_); + return path; + }; + function reset() { + cacheStream = null; + return path; + } + return path.projection(d3.geo.albersUsa()).context(null); + }; + function d3_geo_pathProjectStream(project) { + var resample = d3_geo_resample(function(x, y) { + return project([ x * d3_degrees, y * d3_degrees ]); + }); + return function(stream) { + return d3_geo_projectionRadians(resample(stream)); + }; + } + d3.geo.transform = function(methods) { + return { + stream: function(stream) { + var transform = new d3_geo_transform(stream); + for (var k in methods) transform[k] = methods[k]; + return transform; + } + }; + }; + function d3_geo_transform(stream) { + this.stream = stream; + } + d3_geo_transform.prototype = { + point: function(x, y) { + this.stream.point(x, y); + }, + sphere: function() { + this.stream.sphere(); + }, + lineStart: function() { + this.stream.lineStart(); + }, + lineEnd: function() { + this.stream.lineEnd(); + }, + polygonStart: function() { + this.stream.polygonStart(); + }, + polygonEnd: function() { + this.stream.polygonEnd(); + } + }; + function d3_geo_transformPoint(stream, point) { + return { + point: point, + sphere: function() { + stream.sphere(); + }, + lineStart: function() { + stream.lineStart(); + }, + lineEnd: function() { + stream.lineEnd(); + }, + polygonStart: function() { + stream.polygonStart(); + }, + polygonEnd: function() { + stream.polygonEnd(); + } + }; + } + d3.geo.projection = d3_geo_projection; + d3.geo.projectionMutator = d3_geo_projectionMutator; + function d3_geo_projection(project) { + return d3_geo_projectionMutator(function() { + return project; + })(); + } + function d3_geo_projectionMutator(projectAt) { + var project, rotate, projectRotate, projectResample = d3_geo_resample(function(x, y) { + x = project(x, y); + return [ x[0] * k + δx, δy - x[1] * k ]; + }), k = 150, x = 480, y = 250, λ = 0, φ = 0, δλ = 0, δφ = 0, δγ = 0, δx, δy, preclip = d3_geo_clipAntimeridian, postclip = d3_identity, clipAngle = null, clipExtent = null, stream; + function projection(point) { + point = projectRotate(point[0] * d3_radians, point[1] * d3_radians); + return [ point[0] * k + δx, δy - point[1] * k ]; + } + function invert(point) { + point = projectRotate.invert((point[0] - δx) / k, (δy - point[1]) / k); + return point && [ point[0] * d3_degrees, point[1] * d3_degrees ]; + } + projection.stream = function(output) { + if (stream) stream.valid = false; + stream = d3_geo_projectionRadians(preclip(rotate, projectResample(postclip(output)))); + stream.valid = true; + return stream; + }; + projection.clipAngle = function(_) { + if (!arguments.length) return clipAngle; + preclip = _ == null ? (clipAngle = _, d3_geo_clipAntimeridian) : d3_geo_clipCircle((clipAngle = +_) * d3_radians); + return invalidate(); + }; + projection.clipExtent = function(_) { + if (!arguments.length) return clipExtent; + clipExtent = _; + postclip = _ ? d3_geo_clipExtent(_[0][0], _[0][1], _[1][0], _[1][1]) : d3_identity; + return invalidate(); + }; + projection.scale = function(_) { + if (!arguments.length) return k; + k = +_; + return reset(); + }; + projection.translate = function(_) { + if (!arguments.length) return [ x, y ]; + x = +_[0]; + y = +_[1]; + return reset(); + }; + projection.center = function(_) { + if (!arguments.length) return [ λ * d3_degrees, φ * d3_degrees ]; + λ = _[0] % 360 * d3_radians; + φ = _[1] % 360 * d3_radians; + return reset(); + }; + projection.rotate = function(_) { + if (!arguments.length) return [ δλ * d3_degrees, δφ * d3_degrees, δγ * d3_degrees ]; + δλ = _[0] % 360 * d3_radians; + δφ = _[1] % 360 * d3_radians; + δγ = _.length > 2 ? _[2] % 360 * d3_radians : 0; + return reset(); + }; + d3.rebind(projection, projectResample, "precision"); + function reset() { + projectRotate = d3_geo_compose(rotate = d3_geo_rotation(δλ, δφ, δγ), project); + var center = project(λ, φ); + δx = x - center[0] * k; + δy = y + center[1] * k; + return invalidate(); + } + function invalidate() { + if (stream) stream.valid = false, stream = null; + return projection; + } + return function() { + project = projectAt.apply(this, arguments); + projection.invert = project.invert && invert; + return reset(); + }; + } + function d3_geo_projectionRadians(stream) { + return d3_geo_transformPoint(stream, function(x, y) { + stream.point(x * d3_radians, y * d3_radians); + }); + } + function d3_geo_equirectangular(λ, φ) { + return [ λ, φ ]; + } + (d3.geo.equirectangular = function() { + return d3_geo_projection(d3_geo_equirectangular); + }).raw = d3_geo_equirectangular.invert = d3_geo_equirectangular; + d3.geo.rotation = function(rotate) { + rotate = d3_geo_rotation(rotate[0] % 360 * d3_radians, rotate[1] * d3_radians, rotate.length > 2 ? rotate[2] * d3_radians : 0); + function forward(coordinates) { + coordinates = rotate(coordinates[0] * d3_radians, coordinates[1] * d3_radians); + return coordinates[0] *= d3_degrees, coordinates[1] *= d3_degrees, coordinates; + } + forward.invert = function(coordinates) { + coordinates = rotate.invert(coordinates[0] * d3_radians, coordinates[1] * d3_radians); + return coordinates[0] *= d3_degrees, coordinates[1] *= d3_degrees, coordinates; + }; + return forward; + }; + function d3_geo_identityRotation(λ, φ) { + return [ λ > π ? λ - τ : λ < -π ? λ + τ : λ, φ ]; + } + d3_geo_identityRotation.invert = d3_geo_equirectangular; + function d3_geo_rotation(δλ, δφ, δγ) { + return δλ ? δφ || δγ ? d3_geo_compose(d3_geo_rotationλ(δλ), d3_geo_rotationφγ(δφ, δγ)) : d3_geo_rotationλ(δλ) : δφ || δγ ? d3_geo_rotationφγ(δφ, δγ) : d3_geo_identityRotation; + } + function d3_geo_forwardRotationλ(δλ) { + return function(λ, φ) { + return λ += δλ, [ λ > π ? λ - τ : λ < -π ? λ + τ : λ, φ ]; + }; + } + function d3_geo_rotationλ(δλ) { + var rotation = d3_geo_forwardRotationλ(δλ); + rotation.invert = d3_geo_forwardRotationλ(-δλ); + return rotation; + } + function d3_geo_rotationφγ(δφ, δγ) { + var cosδφ = Math.cos(δφ), sinδφ = Math.sin(δφ), cosδγ = Math.cos(δγ), sinδγ = Math.sin(δγ); + function rotation(λ, φ) { + var cosφ = Math.cos(φ), x = Math.cos(λ) * cosφ, y = Math.sin(λ) * cosφ, z = Math.sin(φ), k = z * cosδφ + x * sinδφ; + return [ Math.atan2(y * cosδγ - k * sinδγ, x * cosδφ - z * sinδφ), d3_asin(k * cosδγ + y * sinδγ) ]; + } + rotation.invert = function(λ, φ) { + var cosφ = Math.cos(φ), x = Math.cos(λ) * cosφ, y = Math.sin(λ) * cosφ, z = Math.sin(φ), k = z * cosδγ - y * sinδγ; + return [ Math.atan2(y * cosδγ + z * sinδγ, x * cosδφ + k * sinδφ), d3_asin(k * cosδφ - x * sinδφ) ]; + }; + return rotation; + } + d3.geo.circle = function() { + var origin = [ 0, 0 ], angle, precision = 6, interpolate; + function circle() { + var center = typeof origin === "function" ? origin.apply(this, arguments) : origin, rotate = d3_geo_rotation(-center[0] * d3_radians, -center[1] * d3_radians, 0).invert, ring = []; + interpolate(null, null, 1, { + point: function(x, y) { + ring.push(x = rotate(x, y)); + x[0] *= d3_degrees, x[1] *= d3_degrees; + } + }); + return { + type: "Polygon", + coordinates: [ ring ] + }; + } + circle.origin = function(x) { + if (!arguments.length) return origin; + origin = x; + return circle; + }; + circle.angle = function(x) { + if (!arguments.length) return angle; + interpolate = d3_geo_circleInterpolate((angle = +x) * d3_radians, precision * d3_radians); + return circle; + }; + circle.precision = function(_) { + if (!arguments.length) return precision; + interpolate = d3_geo_circleInterpolate(angle * d3_radians, (precision = +_) * d3_radians); + return circle; + }; + return circle.angle(90); + }; + function d3_geo_circleInterpolate(radius, precision) { + var cr = Math.cos(radius), sr = Math.sin(radius); + return function(from, to, direction, listener) { + var step = direction * precision; + if (from != null) { + from = d3_geo_circleAngle(cr, from); + to = d3_geo_circleAngle(cr, to); + if (direction > 0 ? from < to : from > to) from += direction * τ; + } else { + from = radius + direction * τ; + to = radius - .5 * step; + } + for (var point, t = from; direction > 0 ? t > to : t < to; t -= step) { + listener.point((point = d3_geo_spherical([ cr, -sr * Math.cos(t), -sr * Math.sin(t) ]))[0], point[1]); + } + }; + } + function d3_geo_circleAngle(cr, point) { + var a = d3_geo_cartesian(point); + a[0] -= cr; + d3_geo_cartesianNormalize(a); + var angle = d3_acos(-a[1]); + return ((-a[2] < 0 ? -angle : angle) + 2 * Math.PI - ε) % (2 * Math.PI); + } + d3.geo.distance = function(a, b) { + var Δλ = (b[0] - a[0]) * d3_radians, φ0 = a[1] * d3_radians, φ1 = b[1] * d3_radians, sinΔλ = Math.sin(Δλ), cosΔλ = Math.cos(Δλ), sinφ0 = Math.sin(φ0), cosφ0 = Math.cos(φ0), sinφ1 = Math.sin(φ1), cosφ1 = Math.cos(φ1), t; + return Math.atan2(Math.sqrt((t = cosφ1 * sinΔλ) * t + (t = cosφ0 * sinφ1 - sinφ0 * cosφ1 * cosΔλ) * t), sinφ0 * sinφ1 + cosφ0 * cosφ1 * cosΔλ); + }; + d3.geo.graticule = function() { + var x1, x0, X1, X0, y1, y0, Y1, Y0, dx = 10, dy = dx, DX = 90, DY = 360, x, y, X, Y, precision = 2.5; + function graticule() { + return { + type: "MultiLineString", + coordinates: lines() + }; + } + function lines() { + return d3.range(Math.ceil(X0 / DX) * DX, X1, DX).map(X).concat(d3.range(Math.ceil(Y0 / DY) * DY, Y1, DY).map(Y)).concat(d3.range(Math.ceil(x0 / dx) * dx, x1, dx).filter(function(x) { + return abs(x % DX) > ε; + }).map(x)).concat(d3.range(Math.ceil(y0 / dy) * dy, y1, dy).filter(function(y) { + return abs(y % DY) > ε; + }).map(y)); + } + graticule.lines = function() { + return lines().map(function(coordinates) { + return { + type: "LineString", + coordinates: coordinates + }; + }); + }; + graticule.outline = function() { + return { + type: "Polygon", + coordinates: [ X(X0).concat(Y(Y1).slice(1), X(X1).reverse().slice(1), Y(Y0).reverse().slice(1)) ] + }; + }; + graticule.extent = function(_) { + if (!arguments.length) return graticule.minorExtent(); + return graticule.majorExtent(_).minorExtent(_); + }; + graticule.majorExtent = function(_) { + if (!arguments.length) return [ [ X0, Y0 ], [ X1, Y1 ] ]; + X0 = +_[0][0], X1 = +_[1][0]; + Y0 = +_[0][1], Y1 = +_[1][1]; + if (X0 > X1) _ = X0, X0 = X1, X1 = _; + if (Y0 > Y1) _ = Y0, Y0 = Y1, Y1 = _; + return graticule.precision(precision); + }; + graticule.minorExtent = function(_) { + if (!arguments.length) return [ [ x0, y0 ], [ x1, y1 ] ]; + x0 = +_[0][0], x1 = +_[1][0]; + y0 = +_[0][1], y1 = +_[1][1]; + if (x0 > x1) _ = x0, x0 = x1, x1 = _; + if (y0 > y1) _ = y0, y0 = y1, y1 = _; + return graticule.precision(precision); + }; + graticule.step = function(_) { + if (!arguments.length) return graticule.minorStep(); + return graticule.majorStep(_).minorStep(_); + }; + graticule.majorStep = function(_) { + if (!arguments.length) return [ DX, DY ]; + DX = +_[0], DY = +_[1]; + return graticule; + }; + graticule.minorStep = function(_) { + if (!arguments.length) return [ dx, dy ]; + dx = +_[0], dy = +_[1]; + return graticule; + }; + graticule.precision = function(_) { + if (!arguments.length) return precision; + precision = +_; + x = d3_geo_graticuleX(y0, y1, 90); + y = d3_geo_graticuleY(x0, x1, precision); + X = d3_geo_graticuleX(Y0, Y1, 90); + Y = d3_geo_graticuleY(X0, X1, precision); + return graticule; + }; + return graticule.majorExtent([ [ -180, -90 + ε ], [ 180, 90 - ε ] ]).minorExtent([ [ -180, -80 - ε ], [ 180, 80 + ε ] ]); + }; + function d3_geo_graticuleX(y0, y1, dy) { + var y = d3.range(y0, y1 - ε, dy).concat(y1); + return function(x) { + return y.map(function(y) { + return [ x, y ]; + }); + }; + } + function d3_geo_graticuleY(x0, x1, dx) { + var x = d3.range(x0, x1 - ε, dx).concat(x1); + return function(y) { + return x.map(function(x) { + return [ x, y ]; + }); + }; + } + function d3_source(d) { + return d.source; + } + function d3_target(d) { + return d.target; + } + d3.geo.greatArc = function() { + var source = d3_source, source_, target = d3_target, target_; + function greatArc() { + return { + type: "LineString", + coordinates: [ source_ || source.apply(this, arguments), target_ || target.apply(this, arguments) ] + }; + } + greatArc.distance = function() { + return d3.geo.distance(source_ || source.apply(this, arguments), target_ || target.apply(this, arguments)); + }; + greatArc.source = function(_) { + if (!arguments.length) return source; + source = _, source_ = typeof _ === "function" ? null : _; + return greatArc; + }; + greatArc.target = function(_) { + if (!arguments.length) return target; + target = _, target_ = typeof _ === "function" ? null : _; + return greatArc; + }; + greatArc.precision = function() { + return arguments.length ? greatArc : 0; + }; + return greatArc; + }; + d3.geo.interpolate = function(source, target) { + return d3_geo_interpolate(source[0] * d3_radians, source[1] * d3_radians, target[0] * d3_radians, target[1] * d3_radians); + }; + function d3_geo_interpolate(x0, y0, x1, y1) { + var cy0 = Math.cos(y0), sy0 = Math.sin(y0), cy1 = Math.cos(y1), sy1 = Math.sin(y1), kx0 = cy0 * Math.cos(x0), ky0 = cy0 * Math.sin(x0), kx1 = cy1 * Math.cos(x1), ky1 = cy1 * Math.sin(x1), d = 2 * Math.asin(Math.sqrt(d3_haversin(y1 - y0) + cy0 * cy1 * d3_haversin(x1 - x0))), k = 1 / Math.sin(d); + var interpolate = d ? function(t) { + var B = Math.sin(t *= d) * k, A = Math.sin(d - t) * k, x = A * kx0 + B * kx1, y = A * ky0 + B * ky1, z = A * sy0 + B * sy1; + return [ Math.atan2(y, x) * d3_degrees, Math.atan2(z, Math.sqrt(x * x + y * y)) * d3_degrees ]; + } : function() { + return [ x0 * d3_degrees, y0 * d3_degrees ]; + }; + interpolate.distance = d; + return interpolate; + } + d3.geo.length = function(object) { + d3_geo_lengthSum = 0; + d3.geo.stream(object, d3_geo_length); + return d3_geo_lengthSum; + }; + var d3_geo_lengthSum; + var d3_geo_length = { + sphere: d3_noop, + point: d3_noop, + lineStart: d3_geo_lengthLineStart, + lineEnd: d3_noop, + polygonStart: d3_noop, + polygonEnd: d3_noop + }; + function d3_geo_lengthLineStart() { + var λ0, sinφ0, cosφ0; + d3_geo_length.point = function(λ, φ) { + λ0 = λ * d3_radians, sinφ0 = Math.sin(φ *= d3_radians), cosφ0 = Math.cos(φ); + d3_geo_length.point = nextPoint; + }; + d3_geo_length.lineEnd = function() { + d3_geo_length.point = d3_geo_length.lineEnd = d3_noop; + }; + function nextPoint(λ, φ) { + var sinφ = Math.sin(φ *= d3_radians), cosφ = Math.cos(φ), t = abs((λ *= d3_radians) - λ0), cosΔλ = Math.cos(t); + d3_geo_lengthSum += Math.atan2(Math.sqrt((t = cosφ * Math.sin(t)) * t + (t = cosφ0 * sinφ - sinφ0 * cosφ * cosΔλ) * t), sinφ0 * sinφ + cosφ0 * cosφ * cosΔλ); + λ0 = λ, sinφ0 = sinφ, cosφ0 = cosφ; + } + } + function d3_geo_azimuthal(scale, angle) { + function azimuthal(λ, φ) { + var cosλ = Math.cos(λ), cosφ = Math.cos(φ), k = scale(cosλ * cosφ); + return [ k * cosφ * Math.sin(λ), k * Math.sin(φ) ]; + } + azimuthal.invert = function(x, y) { + var ρ = Math.sqrt(x * x + y * y), c = angle(ρ), sinc = Math.sin(c), cosc = Math.cos(c); + return [ Math.atan2(x * sinc, ρ * cosc), Math.asin(ρ && y * sinc / ρ) ]; + }; + return azimuthal; + } + var d3_geo_azimuthalEqualArea = d3_geo_azimuthal(function(cosλcosφ) { + return Math.sqrt(2 / (1 + cosλcosφ)); + }, function(ρ) { + return 2 * Math.asin(ρ / 2); + }); + (d3.geo.azimuthalEqualArea = function() { + return d3_geo_projection(d3_geo_azimuthalEqualArea); + }).raw = d3_geo_azimuthalEqualArea; + var d3_geo_azimuthalEquidistant = d3_geo_azimuthal(function(cosλcosφ) { + var c = Math.acos(cosλcosφ); + return c && c / Math.sin(c); + }, d3_identity); + (d3.geo.azimuthalEquidistant = function() { + return d3_geo_projection(d3_geo_azimuthalEquidistant); + }).raw = d3_geo_azimuthalEquidistant; + function d3_geo_conicConformal(φ0, φ1) { + var cosφ0 = Math.cos(φ0), t = function(φ) { + return Math.tan(π / 4 + φ / 2); + }, n = φ0 === φ1 ? Math.sin(φ0) : Math.log(cosφ0 / Math.cos(φ1)) / Math.log(t(φ1) / t(φ0)), F = cosφ0 * Math.pow(t(φ0), n) / n; + if (!n) return d3_geo_mercator; + function forward(λ, φ) { + if (F > 0) { + if (φ < -halfπ + ε) φ = -halfπ + ε; + } else { + if (φ > halfπ - ε) φ = halfπ - ε; + } + var ρ = F / Math.pow(t(φ), n); + return [ ρ * Math.sin(n * λ), F - ρ * Math.cos(n * λ) ]; + } + forward.invert = function(x, y) { + var ρ0_y = F - y, ρ = d3_sgn(n) * Math.sqrt(x * x + ρ0_y * ρ0_y); + return [ Math.atan2(x, ρ0_y) / n, 2 * Math.atan(Math.pow(F / ρ, 1 / n)) - halfπ ]; + }; + return forward; + } + (d3.geo.conicConformal = function() { + return d3_geo_conic(d3_geo_conicConformal); + }).raw = d3_geo_conicConformal; + function d3_geo_conicEquidistant(φ0, φ1) { + var cosφ0 = Math.cos(φ0), n = φ0 === φ1 ? Math.sin(φ0) : (cosφ0 - Math.cos(φ1)) / (φ1 - φ0), G = cosφ0 / n + φ0; + if (abs(n) < ε) return d3_geo_equirectangular; + function forward(λ, φ) { + var ρ = G - φ; + return [ ρ * Math.sin(n * λ), G - ρ * Math.cos(n * λ) ]; + } + forward.invert = function(x, y) { + var ρ0_y = G - y; + return [ Math.atan2(x, ρ0_y) / n, G - d3_sgn(n) * Math.sqrt(x * x + ρ0_y * ρ0_y) ]; + }; + return forward; + } + (d3.geo.conicEquidistant = function() { + return d3_geo_conic(d3_geo_conicEquidistant); + }).raw = d3_geo_conicEquidistant; + var d3_geo_gnomonic = d3_geo_azimuthal(function(cosλcosφ) { + return 1 / cosλcosφ; + }, Math.atan); + (d3.geo.gnomonic = function() { + return d3_geo_projection(d3_geo_gnomonic); + }).raw = d3_geo_gnomonic; + function d3_geo_mercator(λ, φ) { + return [ λ, Math.log(Math.tan(π / 4 + φ / 2)) ]; + } + d3_geo_mercator.invert = function(x, y) { + return [ x, 2 * Math.atan(Math.exp(y)) - halfπ ]; + }; + function d3_geo_mercatorProjection(project) { + var m = d3_geo_projection(project), scale = m.scale, translate = m.translate, clipExtent = m.clipExtent, clipAuto; + m.scale = function() { + var v = scale.apply(m, arguments); + return v === m ? clipAuto ? m.clipExtent(null) : m : v; + }; + m.translate = function() { + var v = translate.apply(m, arguments); + return v === m ? clipAuto ? m.clipExtent(null) : m : v; + }; + m.clipExtent = function(_) { + var v = clipExtent.apply(m, arguments); + if (v === m) { + if (clipAuto = _ == null) { + var k = π * scale(), t = translate(); + clipExtent([ [ t[0] - k, t[1] - k ], [ t[0] + k, t[1] + k ] ]); + } + } else if (clipAuto) { + v = null; + } + return v; + }; + return m.clipExtent(null); + } + (d3.geo.mercator = function() { + return d3_geo_mercatorProjection(d3_geo_mercator); + }).raw = d3_geo_mercator; + var d3_geo_orthographic = d3_geo_azimuthal(function() { + return 1; + }, Math.asin); + (d3.geo.orthographic = function() { + return d3_geo_projection(d3_geo_orthographic); + }).raw = d3_geo_orthographic; + var d3_geo_stereographic = d3_geo_azimuthal(function(cosλcosφ) { + return 1 / (1 + cosλcosφ); + }, function(ρ) { + return 2 * Math.atan(ρ); + }); + (d3.geo.stereographic = function() { + return d3_geo_projection(d3_geo_stereographic); + }).raw = d3_geo_stereographic; + function d3_geo_transverseMercator(λ, φ) { + return [ Math.log(Math.tan(π / 4 + φ / 2)), -λ ]; + } + d3_geo_transverseMercator.invert = function(x, y) { + return [ -y, 2 * Math.atan(Math.exp(x)) - halfπ ]; + }; + (d3.geo.transverseMercator = function() { + var projection = d3_geo_mercatorProjection(d3_geo_transverseMercator), center = projection.center, rotate = projection.rotate; + projection.center = function(_) { + return _ ? center([ -_[1], _[0] ]) : (_ = center(), [ -_[1], _[0] ]); + }; + projection.rotate = function(_) { + return _ ? rotate([ _[0], _[1], _.length > 2 ? _[2] + 90 : 90 ]) : (_ = rotate(), + [ _[0], _[1], _[2] - 90 ]); + }; + return projection.rotate([ 0, 0 ]); + }).raw = d3_geo_transverseMercator; + d3.geom = {}; + function d3_geom_pointX(d) { + return d[0]; + } + function d3_geom_pointY(d) { + return d[1]; + } + d3.geom.hull = function(vertices) { + var x = d3_geom_pointX, y = d3_geom_pointY; + if (arguments.length) return hull(vertices); + function hull(data) { + if (data.length < 3) return []; + var fx = d3_functor(x), fy = d3_functor(y), i, n = data.length, points = [], flippedPoints = []; + for (i = 0; i < n; i++) { + points.push([ +fx.call(this, data[i], i), +fy.call(this, data[i], i), i ]); + } + points.sort(d3_geom_hullOrder); + for (i = 0; i < n; i++) flippedPoints.push([ points[i][0], -points[i][1] ]); + var upper = d3_geom_hullUpper(points), lower = d3_geom_hullUpper(flippedPoints); + var skipLeft = lower[0] === upper[0], skipRight = lower[lower.length - 1] === upper[upper.length - 1], polygon = []; + for (i = upper.length - 1; i >= 0; --i) polygon.push(data[points[upper[i]][2]]); + for (i = +skipLeft; i < lower.length - skipRight; ++i) polygon.push(data[points[lower[i]][2]]); + return polygon; + } + hull.x = function(_) { + return arguments.length ? (x = _, hull) : x; + }; + hull.y = function(_) { + return arguments.length ? (y = _, hull) : y; + }; + return hull; + }; + function d3_geom_hullUpper(points) { + var n = points.length, hull = [ 0, 1 ], hs = 2; + for (var i = 2; i < n; i++) { + while (hs > 1 && d3_cross2d(points[hull[hs - 2]], points[hull[hs - 1]], points[i]) <= 0) --hs; + hull[hs++] = i; + } + return hull.slice(0, hs); + } + function d3_geom_hullOrder(a, b) { + return a[0] - b[0] || a[1] - b[1]; + } + d3.geom.polygon = function(coordinates) { + d3_subclass(coordinates, d3_geom_polygonPrototype); + return coordinates; + }; + var d3_geom_polygonPrototype = d3.geom.polygon.prototype = []; + d3_geom_polygonPrototype.area = function() { + var i = -1, n = this.length, a, b = this[n - 1], area = 0; + while (++i < n) { + a = b; + b = this[i]; + area += a[1] * b[0] - a[0] * b[1]; + } + return area * .5; + }; + d3_geom_polygonPrototype.centroid = function(k) { + var i = -1, n = this.length, x = 0, y = 0, a, b = this[n - 1], c; + if (!arguments.length) k = -1 / (6 * this.area()); + while (++i < n) { + a = b; + b = this[i]; + c = a[0] * b[1] - b[0] * a[1]; + x += (a[0] + b[0]) * c; + y += (a[1] + b[1]) * c; + } + return [ x * k, y * k ]; + }; + d3_geom_polygonPrototype.clip = function(subject) { + var input, closed = d3_geom_polygonClosed(subject), i = -1, n = this.length - d3_geom_polygonClosed(this), j, m, a = this[n - 1], b, c, d; + while (++i < n) { + input = subject.slice(); + subject.length = 0; + b = this[i]; + c = input[(m = input.length - closed) - 1]; + j = -1; + while (++j < m) { + d = input[j]; + if (d3_geom_polygonInside(d, a, b)) { + if (!d3_geom_polygonInside(c, a, b)) { + subject.push(d3_geom_polygonIntersect(c, d, a, b)); + } + subject.push(d); + } else if (d3_geom_polygonInside(c, a, b)) { + subject.push(d3_geom_polygonIntersect(c, d, a, b)); + } + c = d; + } + if (closed) subject.push(subject[0]); + a = b; + } + return subject; + }; + function d3_geom_polygonInside(p, a, b) { + return (b[0] - a[0]) * (p[1] - a[1]) < (b[1] - a[1]) * (p[0] - a[0]); + } + function d3_geom_polygonIntersect(c, d, a, b) { + var x1 = c[0], x3 = a[0], x21 = d[0] - x1, x43 = b[0] - x3, y1 = c[1], y3 = a[1], y21 = d[1] - y1, y43 = b[1] - y3, ua = (x43 * (y1 - y3) - y43 * (x1 - x3)) / (y43 * x21 - x43 * y21); + return [ x1 + ua * x21, y1 + ua * y21 ]; + } + function d3_geom_polygonClosed(coordinates) { + var a = coordinates[0], b = coordinates[coordinates.length - 1]; + return !(a[0] - b[0] || a[1] - b[1]); + } + var d3_geom_voronoiEdges, d3_geom_voronoiCells, d3_geom_voronoiBeaches, d3_geom_voronoiBeachPool = [], d3_geom_voronoiFirstCircle, d3_geom_voronoiCircles, d3_geom_voronoiCirclePool = []; + function d3_geom_voronoiBeach() { + d3_geom_voronoiRedBlackNode(this); + this.edge = this.site = this.circle = null; + } + function d3_geom_voronoiCreateBeach(site) { + var beach = d3_geom_voronoiBeachPool.pop() || new d3_geom_voronoiBeach(); + beach.site = site; + return beach; + } + function d3_geom_voronoiDetachBeach(beach) { + d3_geom_voronoiDetachCircle(beach); + d3_geom_voronoiBeaches.remove(beach); + d3_geom_voronoiBeachPool.push(beach); + d3_geom_voronoiRedBlackNode(beach); + } + function d3_geom_voronoiRemoveBeach(beach) { + var circle = beach.circle, x = circle.x, y = circle.cy, vertex = { + x: x, + y: y + }, previous = beach.P, next = beach.N, disappearing = [ beach ]; + d3_geom_voronoiDetachBeach(beach); + var lArc = previous; + while (lArc.circle && abs(x - lArc.circle.x) < ε && abs(y - lArc.circle.cy) < ε) { + previous = lArc.P; + disappearing.unshift(lArc); + d3_geom_voronoiDetachBeach(lArc); + lArc = previous; + } + disappearing.unshift(lArc); + d3_geom_voronoiDetachCircle(lArc); + var rArc = next; + while (rArc.circle && abs(x - rArc.circle.x) < ε && abs(y - rArc.circle.cy) < ε) { + next = rArc.N; + disappearing.push(rArc); + d3_geom_voronoiDetachBeach(rArc); + rArc = next; + } + disappearing.push(rArc); + d3_geom_voronoiDetachCircle(rArc); + var nArcs = disappearing.length, iArc; + for (iArc = 1; iArc < nArcs; ++iArc) { + rArc = disappearing[iArc]; + lArc = disappearing[iArc - 1]; + d3_geom_voronoiSetEdgeEnd(rArc.edge, lArc.site, rArc.site, vertex); + } + lArc = disappearing[0]; + rArc = disappearing[nArcs - 1]; + rArc.edge = d3_geom_voronoiCreateEdge(lArc.site, rArc.site, null, vertex); + d3_geom_voronoiAttachCircle(lArc); + d3_geom_voronoiAttachCircle(rArc); + } + function d3_geom_voronoiAddBeach(site) { + var x = site.x, directrix = site.y, lArc, rArc, dxl, dxr, node = d3_geom_voronoiBeaches._; + while (node) { + dxl = d3_geom_voronoiLeftBreakPoint(node, directrix) - x; + if (dxl > ε) node = node.L; else { + dxr = x - d3_geom_voronoiRightBreakPoint(node, directrix); + if (dxr > ε) { + if (!node.R) { + lArc = node; + break; + } + node = node.R; + } else { + if (dxl > -ε) { + lArc = node.P; + rArc = node; + } else if (dxr > -ε) { + lArc = node; + rArc = node.N; + } else { + lArc = rArc = node; + } + break; + } + } + } + var newArc = d3_geom_voronoiCreateBeach(site); + d3_geom_voronoiBeaches.insert(lArc, newArc); + if (!lArc && !rArc) return; + if (lArc === rArc) { + d3_geom_voronoiDetachCircle(lArc); + rArc = d3_geom_voronoiCreateBeach(lArc.site); + d3_geom_voronoiBeaches.insert(newArc, rArc); + newArc.edge = rArc.edge = d3_geom_voronoiCreateEdge(lArc.site, newArc.site); + d3_geom_voronoiAttachCircle(lArc); + d3_geom_voronoiAttachCircle(rArc); + return; + } + if (!rArc) { + newArc.edge = d3_geom_voronoiCreateEdge(lArc.site, newArc.site); + return; + } + d3_geom_voronoiDetachCircle(lArc); + d3_geom_voronoiDetachCircle(rArc); + var lSite = lArc.site, ax = lSite.x, ay = lSite.y, bx = site.x - ax, by = site.y - ay, rSite = rArc.site, cx = rSite.x - ax, cy = rSite.y - ay, d = 2 * (bx * cy - by * cx), hb = bx * bx + by * by, hc = cx * cx + cy * cy, vertex = { + x: (cy * hb - by * hc) / d + ax, + y: (bx * hc - cx * hb) / d + ay + }; + d3_geom_voronoiSetEdgeEnd(rArc.edge, lSite, rSite, vertex); + newArc.edge = d3_geom_voronoiCreateEdge(lSite, site, null, vertex); + rArc.edge = d3_geom_voronoiCreateEdge(site, rSite, null, vertex); + d3_geom_voronoiAttachCircle(lArc); + d3_geom_voronoiAttachCircle(rArc); + } + function d3_geom_voronoiLeftBreakPoint(arc, directrix) { + var site = arc.site, rfocx = site.x, rfocy = site.y, pby2 = rfocy - directrix; + if (!pby2) return rfocx; + var lArc = arc.P; + if (!lArc) return -Infinity; + site = lArc.site; + var lfocx = site.x, lfocy = site.y, plby2 = lfocy - directrix; + if (!plby2) return lfocx; + var hl = lfocx - rfocx, aby2 = 1 / pby2 - 1 / plby2, b = hl / plby2; + if (aby2) return (-b + Math.sqrt(b * b - 2 * aby2 * (hl * hl / (-2 * plby2) - lfocy + plby2 / 2 + rfocy - pby2 / 2))) / aby2 + rfocx; + return (rfocx + lfocx) / 2; + } + function d3_geom_voronoiRightBreakPoint(arc, directrix) { + var rArc = arc.N; + if (rArc) return d3_geom_voronoiLeftBreakPoint(rArc, directrix); + var site = arc.site; + return site.y === directrix ? site.x : Infinity; + } + function d3_geom_voronoiCell(site) { + this.site = site; + this.edges = []; + } + d3_geom_voronoiCell.prototype.prepare = function() { + var halfEdges = this.edges, iHalfEdge = halfEdges.length, edge; + while (iHalfEdge--) { + edge = halfEdges[iHalfEdge].edge; + if (!edge.b || !edge.a) halfEdges.splice(iHalfEdge, 1); + } + halfEdges.sort(d3_geom_voronoiHalfEdgeOrder); + return halfEdges.length; + }; + function d3_geom_voronoiCloseCells(extent) { + var x0 = extent[0][0], x1 = extent[1][0], y0 = extent[0][1], y1 = extent[1][1], x2, y2, x3, y3, cells = d3_geom_voronoiCells, iCell = cells.length, cell, iHalfEdge, halfEdges, nHalfEdges, start, end; + while (iCell--) { + cell = cells[iCell]; + if (!cell || !cell.prepare()) continue; + halfEdges = cell.edges; + nHalfEdges = halfEdges.length; + iHalfEdge = 0; + while (iHalfEdge < nHalfEdges) { + end = halfEdges[iHalfEdge].end(), x3 = end.x, y3 = end.y; + start = halfEdges[++iHalfEdge % nHalfEdges].start(), x2 = start.x, y2 = start.y; + if (abs(x3 - x2) > ε || abs(y3 - y2) > ε) { + halfEdges.splice(iHalfEdge, 0, new d3_geom_voronoiHalfEdge(d3_geom_voronoiCreateBorderEdge(cell.site, end, abs(x3 - x0) < ε && y1 - y3 > ε ? { + x: x0, + y: abs(x2 - x0) < ε ? y2 : y1 + } : abs(y3 - y1) < ε && x1 - x3 > ε ? { + x: abs(y2 - y1) < ε ? x2 : x1, + y: y1 + } : abs(x3 - x1) < ε && y3 - y0 > ε ? { + x: x1, + y: abs(x2 - x1) < ε ? y2 : y0 + } : abs(y3 - y0) < ε && x3 - x0 > ε ? { + x: abs(y2 - y0) < ε ? x2 : x0, + y: y0 + } : null), cell.site, null)); + ++nHalfEdges; + } + } + } + } + function d3_geom_voronoiHalfEdgeOrder(a, b) { + return b.angle - a.angle; + } + function d3_geom_voronoiCircle() { + d3_geom_voronoiRedBlackNode(this); + this.x = this.y = this.arc = this.site = this.cy = null; + } + function d3_geom_voronoiAttachCircle(arc) { + var lArc = arc.P, rArc = arc.N; + if (!lArc || !rArc) return; + var lSite = lArc.site, cSite = arc.site, rSite = rArc.site; + if (lSite === rSite) return; + var bx = cSite.x, by = cSite.y, ax = lSite.x - bx, ay = lSite.y - by, cx = rSite.x - bx, cy = rSite.y - by; + var d = 2 * (ax * cy - ay * cx); + if (d >= -ε2) return; + var ha = ax * ax + ay * ay, hc = cx * cx + cy * cy, x = (cy * ha - ay * hc) / d, y = (ax * hc - cx * ha) / d, cy = y + by; + var circle = d3_geom_voronoiCirclePool.pop() || new d3_geom_voronoiCircle(); + circle.arc = arc; + circle.site = cSite; + circle.x = x + bx; + circle.y = cy + Math.sqrt(x * x + y * y); + circle.cy = cy; + arc.circle = circle; + var before = null, node = d3_geom_voronoiCircles._; + while (node) { + if (circle.y < node.y || circle.y === node.y && circle.x <= node.x) { + if (node.L) node = node.L; else { + before = node.P; + break; + } + } else { + if (node.R) node = node.R; else { + before = node; + break; + } + } + } + d3_geom_voronoiCircles.insert(before, circle); + if (!before) d3_geom_voronoiFirstCircle = circle; + } + function d3_geom_voronoiDetachCircle(arc) { + var circle = arc.circle; + if (circle) { + if (!circle.P) d3_geom_voronoiFirstCircle = circle.N; + d3_geom_voronoiCircles.remove(circle); + d3_geom_voronoiCirclePool.push(circle); + d3_geom_voronoiRedBlackNode(circle); + arc.circle = null; + } + } + function d3_geom_voronoiClipEdges(extent) { + var edges = d3_geom_voronoiEdges, clip = d3_geom_clipLine(extent[0][0], extent[0][1], extent[1][0], extent[1][1]), i = edges.length, e; + while (i--) { + e = edges[i]; + if (!d3_geom_voronoiConnectEdge(e, extent) || !clip(e) || abs(e.a.x - e.b.x) < ε && abs(e.a.y - e.b.y) < ε) { + e.a = e.b = null; + edges.splice(i, 1); + } + } + } + function d3_geom_voronoiConnectEdge(edge, extent) { + var vb = edge.b; + if (vb) return true; + var va = edge.a, x0 = extent[0][0], x1 = extent[1][0], y0 = extent[0][1], y1 = extent[1][1], lSite = edge.l, rSite = edge.r, lx = lSite.x, ly = lSite.y, rx = rSite.x, ry = rSite.y, fx = (lx + rx) / 2, fy = (ly + ry) / 2, fm, fb; + if (ry === ly) { + if (fx < x0 || fx >= x1) return; + if (lx > rx) { + if (!va) va = { + x: fx, + y: y0 + }; else if (va.y >= y1) return; + vb = { + x: fx, + y: y1 + }; + } else { + if (!va) va = { + x: fx, + y: y1 + }; else if (va.y < y0) return; + vb = { + x: fx, + y: y0 + }; + } + } else { + fm = (lx - rx) / (ry - ly); + fb = fy - fm * fx; + if (fm < -1 || fm > 1) { + if (lx > rx) { + if (!va) va = { + x: (y0 - fb) / fm, + y: y0 + }; else if (va.y >= y1) return; + vb = { + x: (y1 - fb) / fm, + y: y1 + }; + } else { + if (!va) va = { + x: (y1 - fb) / fm, + y: y1 + }; else if (va.y < y0) return; + vb = { + x: (y0 - fb) / fm, + y: y0 + }; + } + } else { + if (ly < ry) { + if (!va) va = { + x: x0, + y: fm * x0 + fb + }; else if (va.x >= x1) return; + vb = { + x: x1, + y: fm * x1 + fb + }; + } else { + if (!va) va = { + x: x1, + y: fm * x1 + fb + }; else if (va.x < x0) return; + vb = { + x: x0, + y: fm * x0 + fb + }; + } + } + } + edge.a = va; + edge.b = vb; + return true; + } + function d3_geom_voronoiEdge(lSite, rSite) { + this.l = lSite; + this.r = rSite; + this.a = this.b = null; + } + function d3_geom_voronoiCreateEdge(lSite, rSite, va, vb) { + var edge = new d3_geom_voronoiEdge(lSite, rSite); + d3_geom_voronoiEdges.push(edge); + if (va) d3_geom_voronoiSetEdgeEnd(edge, lSite, rSite, va); + if (vb) d3_geom_voronoiSetEdgeEnd(edge, rSite, lSite, vb); + d3_geom_voronoiCells[lSite.i].edges.push(new d3_geom_voronoiHalfEdge(edge, lSite, rSite)); + d3_geom_voronoiCells[rSite.i].edges.push(new d3_geom_voronoiHalfEdge(edge, rSite, lSite)); + return edge; + } + function d3_geom_voronoiCreateBorderEdge(lSite, va, vb) { + var edge = new d3_geom_voronoiEdge(lSite, null); + edge.a = va; + edge.b = vb; + d3_geom_voronoiEdges.push(edge); + return edge; + } + function d3_geom_voronoiSetEdgeEnd(edge, lSite, rSite, vertex) { + if (!edge.a && !edge.b) { + edge.a = vertex; + edge.l = lSite; + edge.r = rSite; + } else if (edge.l === rSite) { + edge.b = vertex; + } else { + edge.a = vertex; + } + } + function d3_geom_voronoiHalfEdge(edge, lSite, rSite) { + var va = edge.a, vb = edge.b; + this.edge = edge; + this.site = lSite; + this.angle = rSite ? Math.atan2(rSite.y - lSite.y, rSite.x - lSite.x) : edge.l === lSite ? Math.atan2(vb.x - va.x, va.y - vb.y) : Math.atan2(va.x - vb.x, vb.y - va.y); + } + d3_geom_voronoiHalfEdge.prototype = { + start: function() { + return this.edge.l === this.site ? this.edge.a : this.edge.b; + }, + end: function() { + return this.edge.l === this.site ? this.edge.b : this.edge.a; + } + }; + function d3_geom_voronoiRedBlackTree() { + this._ = null; + } + function d3_geom_voronoiRedBlackNode(node) { + node.U = node.C = node.L = node.R = node.P = node.N = null; + } + d3_geom_voronoiRedBlackTree.prototype = { + insert: function(after, node) { + var parent, grandpa, uncle; + if (after) { + node.P = after; + node.N = after.N; + if (after.N) after.N.P = node; + after.N = node; + if (after.R) { + after = after.R; + while (after.L) after = after.L; + after.L = node; + } else { + after.R = node; + } + parent = after; + } else if (this._) { + after = d3_geom_voronoiRedBlackFirst(this._); + node.P = null; + node.N = after; + after.P = after.L = node; + parent = after; + } else { + node.P = node.N = null; + this._ = node; + parent = null; + } + node.L = node.R = null; + node.U = parent; + node.C = true; + after = node; + while (parent && parent.C) { + grandpa = parent.U; + if (parent === grandpa.L) { + uncle = grandpa.R; + if (uncle && uncle.C) { + parent.C = uncle.C = false; + grandpa.C = true; + after = grandpa; + } else { + if (after === parent.R) { + d3_geom_voronoiRedBlackRotateLeft(this, parent); + after = parent; + parent = after.U; + } + parent.C = false; + grandpa.C = true; + d3_geom_voronoiRedBlackRotateRight(this, grandpa); + } + } else { + uncle = grandpa.L; + if (uncle && uncle.C) { + parent.C = uncle.C = false; + grandpa.C = true; + after = grandpa; + } else { + if (after === parent.L) { + d3_geom_voronoiRedBlackRotateRight(this, parent); + after = parent; + parent = after.U; + } + parent.C = false; + grandpa.C = true; + d3_geom_voronoiRedBlackRotateLeft(this, grandpa); + } + } + parent = after.U; + } + this._.C = false; + }, + remove: function(node) { + if (node.N) node.N.P = node.P; + if (node.P) node.P.N = node.N; + node.N = node.P = null; + var parent = node.U, sibling, left = node.L, right = node.R, next, red; + if (!left) next = right; else if (!right) next = left; else next = d3_geom_voronoiRedBlackFirst(right); + if (parent) { + if (parent.L === node) parent.L = next; else parent.R = next; + } else { + this._ = next; + } + if (left && right) { + red = next.C; + next.C = node.C; + next.L = left; + left.U = next; + if (next !== right) { + parent = next.U; + next.U = node.U; + node = next.R; + parent.L = node; + next.R = right; + right.U = next; + } else { + next.U = parent; + parent = next; + node = next.R; + } + } else { + red = node.C; + node = next; + } + if (node) node.U = parent; + if (red) return; + if (node && node.C) { + node.C = false; + return; + } + do { + if (node === this._) break; + if (node === parent.L) { + sibling = parent.R; + if (sibling.C) { + sibling.C = false; + parent.C = true; + d3_geom_voronoiRedBlackRotateLeft(this, parent); + sibling = parent.R; + } + if (sibling.L && sibling.L.C || sibling.R && sibling.R.C) { + if (!sibling.R || !sibling.R.C) { + sibling.L.C = false; + sibling.C = true; + d3_geom_voronoiRedBlackRotateRight(this, sibling); + sibling = parent.R; + } + sibling.C = parent.C; + parent.C = sibling.R.C = false; + d3_geom_voronoiRedBlackRotateLeft(this, parent); + node = this._; + break; + } + } else { + sibling = parent.L; + if (sibling.C) { + sibling.C = false; + parent.C = true; + d3_geom_voronoiRedBlackRotateRight(this, parent); + sibling = parent.L; + } + if (sibling.L && sibling.L.C || sibling.R && sibling.R.C) { + if (!sibling.L || !sibling.L.C) { + sibling.R.C = false; + sibling.C = true; + d3_geom_voronoiRedBlackRotateLeft(this, sibling); + sibling = parent.L; + } + sibling.C = parent.C; + parent.C = sibling.L.C = false; + d3_geom_voronoiRedBlackRotateRight(this, parent); + node = this._; + break; + } + } + sibling.C = true; + node = parent; + parent = parent.U; + } while (!node.C); + if (node) node.C = false; + } + }; + function d3_geom_voronoiRedBlackRotateLeft(tree, node) { + var p = node, q = node.R, parent = p.U; + if (parent) { + if (parent.L === p) parent.L = q; else parent.R = q; + } else { + tree._ = q; + } + q.U = parent; + p.U = q; + p.R = q.L; + if (p.R) p.R.U = p; + q.L = p; + } + function d3_geom_voronoiRedBlackRotateRight(tree, node) { + var p = node, q = node.L, parent = p.U; + if (parent) { + if (parent.L === p) parent.L = q; else parent.R = q; + } else { + tree._ = q; + } + q.U = parent; + p.U = q; + p.L = q.R; + if (p.L) p.L.U = p; + q.R = p; + } + function d3_geom_voronoiRedBlackFirst(node) { + while (node.L) node = node.L; + return node; + } + function d3_geom_voronoi(sites, bbox) { + var site = sites.sort(d3_geom_voronoiVertexOrder).pop(), x0, y0, circle; + d3_geom_voronoiEdges = []; + d3_geom_voronoiCells = new Array(sites.length); + d3_geom_voronoiBeaches = new d3_geom_voronoiRedBlackTree(); + d3_geom_voronoiCircles = new d3_geom_voronoiRedBlackTree(); + while (true) { + circle = d3_geom_voronoiFirstCircle; + if (site && (!circle || site.y < circle.y || site.y === circle.y && site.x < circle.x)) { + if (site.x !== x0 || site.y !== y0) { + d3_geom_voronoiCells[site.i] = new d3_geom_voronoiCell(site); + d3_geom_voronoiAddBeach(site); + x0 = site.x, y0 = site.y; + } + site = sites.pop(); + } else if (circle) { + d3_geom_voronoiRemoveBeach(circle.arc); + } else { + break; + } + } + if (bbox) d3_geom_voronoiClipEdges(bbox), d3_geom_voronoiCloseCells(bbox); + var diagram = { + cells: d3_geom_voronoiCells, + edges: d3_geom_voronoiEdges + }; + d3_geom_voronoiBeaches = d3_geom_voronoiCircles = d3_geom_voronoiEdges = d3_geom_voronoiCells = null; + return diagram; + } + function d3_geom_voronoiVertexOrder(a, b) { + return b.y - a.y || b.x - a.x; + } + d3.geom.voronoi = function(points) { + var x = d3_geom_pointX, y = d3_geom_pointY, fx = x, fy = y, clipExtent = d3_geom_voronoiClipExtent; + if (points) return voronoi(points); + function voronoi(data) { + var polygons = new Array(data.length), x0 = clipExtent[0][0], y0 = clipExtent[0][1], x1 = clipExtent[1][0], y1 = clipExtent[1][1]; + d3_geom_voronoi(sites(data), clipExtent).cells.forEach(function(cell, i) { + var edges = cell.edges, site = cell.site, polygon = polygons[i] = edges.length ? edges.map(function(e) { + var s = e.start(); + return [ s.x, s.y ]; + }) : site.x >= x0 && site.x <= x1 && site.y >= y0 && site.y <= y1 ? [ [ x0, y1 ], [ x1, y1 ], [ x1, y0 ], [ x0, y0 ] ] : []; + polygon.point = data[i]; + }); + return polygons; + } + function sites(data) { + return data.map(function(d, i) { + return { + x: Math.round(fx(d, i) / ε) * ε, + y: Math.round(fy(d, i) / ε) * ε, + i: i + }; + }); + } + voronoi.links = function(data) { + return d3_geom_voronoi(sites(data)).edges.filter(function(edge) { + return edge.l && edge.r; + }).map(function(edge) { + return { + source: data[edge.l.i], + target: data[edge.r.i] + }; + }); + }; + voronoi.triangles = function(data) { + var triangles = []; + d3_geom_voronoi(sites(data)).cells.forEach(function(cell, i) { + var site = cell.site, edges = cell.edges.sort(d3_geom_voronoiHalfEdgeOrder), j = -1, m = edges.length, e0, s0, e1 = edges[m - 1].edge, s1 = e1.l === site ? e1.r : e1.l; + while (++j < m) { + e0 = e1; + s0 = s1; + e1 = edges[j].edge; + s1 = e1.l === site ? e1.r : e1.l; + if (i < s0.i && i < s1.i && d3_geom_voronoiTriangleArea(site, s0, s1) < 0) { + triangles.push([ data[i], data[s0.i], data[s1.i] ]); + } + } + }); + return triangles; + }; + voronoi.x = function(_) { + return arguments.length ? (fx = d3_functor(x = _), voronoi) : x; + }; + voronoi.y = function(_) { + return arguments.length ? (fy = d3_functor(y = _), voronoi) : y; + }; + voronoi.clipExtent = function(_) { + if (!arguments.length) return clipExtent === d3_geom_voronoiClipExtent ? null : clipExtent; + clipExtent = _ == null ? d3_geom_voronoiClipExtent : _; + return voronoi; + }; + voronoi.size = function(_) { + if (!arguments.length) return clipExtent === d3_geom_voronoiClipExtent ? null : clipExtent && clipExtent[1]; + return voronoi.clipExtent(_ && [ [ 0, 0 ], _ ]); + }; + return voronoi; + }; + var d3_geom_voronoiClipExtent = [ [ -1e6, -1e6 ], [ 1e6, 1e6 ] ]; + function d3_geom_voronoiTriangleArea(a, b, c) { + return (a.x - c.x) * (b.y - a.y) - (a.x - b.x) * (c.y - a.y); + } + d3.geom.delaunay = function(vertices) { + return d3.geom.voronoi().triangles(vertices); + }; + d3.geom.quadtree = function(points, x1, y1, x2, y2) { + var x = d3_geom_pointX, y = d3_geom_pointY, compat; + if (compat = arguments.length) { + x = d3_geom_quadtreeCompatX; + y = d3_geom_quadtreeCompatY; + if (compat === 3) { + y2 = y1; + x2 = x1; + y1 = x1 = 0; + } + return quadtree(points); + } + function quadtree(data) { + var d, fx = d3_functor(x), fy = d3_functor(y), xs, ys, i, n, x1_, y1_, x2_, y2_; + if (x1 != null) { + x1_ = x1, y1_ = y1, x2_ = x2, y2_ = y2; + } else { + x2_ = y2_ = -(x1_ = y1_ = Infinity); + xs = [], ys = []; + n = data.length; + if (compat) for (i = 0; i < n; ++i) { + d = data[i]; + if (d.x < x1_) x1_ = d.x; + if (d.y < y1_) y1_ = d.y; + if (d.x > x2_) x2_ = d.x; + if (d.y > y2_) y2_ = d.y; + xs.push(d.x); + ys.push(d.y); + } else for (i = 0; i < n; ++i) { + var x_ = +fx(d = data[i], i), y_ = +fy(d, i); + if (x_ < x1_) x1_ = x_; + if (y_ < y1_) y1_ = y_; + if (x_ > x2_) x2_ = x_; + if (y_ > y2_) y2_ = y_; + xs.push(x_); + ys.push(y_); + } + } + var dx = x2_ - x1_, dy = y2_ - y1_; + if (dx > dy) y2_ = y1_ + dx; else x2_ = x1_ + dy; + function insert(n, d, x, y, x1, y1, x2, y2) { + if (isNaN(x) || isNaN(y)) return; + if (n.leaf) { + var nx = n.x, ny = n.y; + if (nx != null) { + if (abs(nx - x) + abs(ny - y) < .01) { + insertChild(n, d, x, y, x1, y1, x2, y2); + } else { + var nPoint = n.point; + n.x = n.y = n.point = null; + insertChild(n, nPoint, nx, ny, x1, y1, x2, y2); + insertChild(n, d, x, y, x1, y1, x2, y2); + } + } else { + n.x = x, n.y = y, n.point = d; + } + } else { + insertChild(n, d, x, y, x1, y1, x2, y2); + } + } + function insertChild(n, d, x, y, x1, y1, x2, y2) { + var sx = (x1 + x2) * .5, sy = (y1 + y2) * .5, right = x >= sx, bottom = y >= sy, i = (bottom << 1) + right; + n.leaf = false; + n = n.nodes[i] || (n.nodes[i] = d3_geom_quadtreeNode()); + if (right) x1 = sx; else x2 = sx; + if (bottom) y1 = sy; else y2 = sy; + insert(n, d, x, y, x1, y1, x2, y2); + } + var root = d3_geom_quadtreeNode(); + root.add = function(d) { + insert(root, d, +fx(d, ++i), +fy(d, i), x1_, y1_, x2_, y2_); + }; + root.visit = function(f) { + d3_geom_quadtreeVisit(f, root, x1_, y1_, x2_, y2_); + }; + i = -1; + if (x1 == null) { + while (++i < n) { + insert(root, data[i], xs[i], ys[i], x1_, y1_, x2_, y2_); + } + --i; + } else data.forEach(root.add); + xs = ys = data = d = null; + return root; + } + quadtree.x = function(_) { + return arguments.length ? (x = _, quadtree) : x; + }; + quadtree.y = function(_) { + return arguments.length ? (y = _, quadtree) : y; + }; + quadtree.extent = function(_) { + if (!arguments.length) return x1 == null ? null : [ [ x1, y1 ], [ x2, y2 ] ]; + if (_ == null) x1 = y1 = x2 = y2 = null; else x1 = +_[0][0], y1 = +_[0][1], x2 = +_[1][0], + y2 = +_[1][1]; + return quadtree; + }; + quadtree.size = function(_) { + if (!arguments.length) return x1 == null ? null : [ x2 - x1, y2 - y1 ]; + if (_ == null) x1 = y1 = x2 = y2 = null; else x1 = y1 = 0, x2 = +_[0], y2 = +_[1]; + return quadtree; + }; + return quadtree; + }; + function d3_geom_quadtreeCompatX(d) { + return d.x; + } + function d3_geom_quadtreeCompatY(d) { + return d.y; + } + function d3_geom_quadtreeNode() { + return { + leaf: true, + nodes: [], + point: null, + x: null, + y: null + }; + } + function d3_geom_quadtreeVisit(f, node, x1, y1, x2, y2) { + if (!f(node, x1, y1, x2, y2)) { + var sx = (x1 + x2) * .5, sy = (y1 + y2) * .5, children = node.nodes; + if (children[0]) d3_geom_quadtreeVisit(f, children[0], x1, y1, sx, sy); + if (children[1]) d3_geom_quadtreeVisit(f, children[1], sx, y1, x2, sy); + if (children[2]) d3_geom_quadtreeVisit(f, children[2], x1, sy, sx, y2); + if (children[3]) d3_geom_quadtreeVisit(f, children[3], sx, sy, x2, y2); + } + } + d3.interpolateRgb = d3_interpolateRgb; + function d3_interpolateRgb(a, b) { + a = d3.rgb(a); + b = d3.rgb(b); + var ar = a.r, ag = a.g, ab = a.b, br = b.r - ar, bg = b.g - ag, bb = b.b - ab; + return function(t) { + return "#" + d3_rgb_hex(Math.round(ar + br * t)) + d3_rgb_hex(Math.round(ag + bg * t)) + d3_rgb_hex(Math.round(ab + bb * t)); + }; + } + d3.interpolateObject = d3_interpolateObject; + function d3_interpolateObject(a, b) { + var i = {}, c = {}, k; + for (k in a) { + if (k in b) { + i[k] = d3_interpolate(a[k], b[k]); + } else { + c[k] = a[k]; + } + } + for (k in b) { + if (!(k in a)) { + c[k] = b[k]; + } + } + return function(t) { + for (k in i) c[k] = i[k](t); + return c; + }; + } + d3.interpolateNumber = d3_interpolateNumber; + function d3_interpolateNumber(a, b) { + b -= a = +a; + return function(t) { + return a + b * t; + }; + } + d3.interpolateString = d3_interpolateString; + function d3_interpolateString(a, b) { + var bi = d3_interpolate_numberA.lastIndex = d3_interpolate_numberB.lastIndex = 0, am, bm, bs, i = -1, s = [], q = []; + a = a + "", b = b + ""; + while ((am = d3_interpolate_numberA.exec(a)) && (bm = d3_interpolate_numberB.exec(b))) { + if ((bs = bm.index) > bi) { + bs = b.substring(bi, bs); + if (s[i]) s[i] += bs; else s[++i] = bs; + } + if ((am = am[0]) === (bm = bm[0])) { + if (s[i]) s[i] += bm; else s[++i] = bm; + } else { + s[++i] = null; + q.push({ + i: i, + x: d3_interpolateNumber(am, bm) + }); + } + bi = d3_interpolate_numberB.lastIndex; + } + if (bi < b.length) { + bs = b.substring(bi); + if (s[i]) s[i] += bs; else s[++i] = bs; + } + return s.length < 2 ? q[0] ? (b = q[0].x, function(t) { + return b(t) + ""; + }) : function() { + return b; + } : (b = q.length, function(t) { + for (var i = 0, o; i < b; ++i) s[(o = q[i]).i] = o.x(t); + return s.join(""); + }); + } + var d3_interpolate_numberA = /[-+]?(?:\d+\.?\d*|\.?\d+)(?:[eE][-+]?\d+)?/g, d3_interpolate_numberB = new RegExp(d3_interpolate_numberA.source, "g"); + d3.interpolate = d3_interpolate; + function d3_interpolate(a, b) { + var i = d3.interpolators.length, f; + while (--i >= 0 && !(f = d3.interpolators[i](a, b))) ; + return f; + } + d3.interpolators = [ function(a, b) { + var t = typeof b; + return (t === "string" ? d3_rgb_names.has(b) || /^(#|rgb\(|hsl\()/.test(b) ? d3_interpolateRgb : d3_interpolateString : b instanceof d3_Color ? d3_interpolateRgb : Array.isArray(b) ? d3_interpolateArray : t === "object" && isNaN(b) ? d3_interpolateObject : d3_interpolateNumber)(a, b); + } ]; + d3.interpolateArray = d3_interpolateArray; + function d3_interpolateArray(a, b) { + var x = [], c = [], na = a.length, nb = b.length, n0 = Math.min(a.length, b.length), i; + for (i = 0; i < n0; ++i) x.push(d3_interpolate(a[i], b[i])); + for (;i < na; ++i) c[i] = a[i]; + for (;i < nb; ++i) c[i] = b[i]; + return function(t) { + for (i = 0; i < n0; ++i) c[i] = x[i](t); + return c; + }; + } + var d3_ease_default = function() { + return d3_identity; + }; + var d3_ease = d3.map({ + linear: d3_ease_default, + poly: d3_ease_poly, + quad: function() { + return d3_ease_quad; + }, + cubic: function() { + return d3_ease_cubic; + }, + sin: function() { + return d3_ease_sin; + }, + exp: function() { + return d3_ease_exp; + }, + circle: function() { + return d3_ease_circle; + }, + elastic: d3_ease_elastic, + back: d3_ease_back, + bounce: function() { + return d3_ease_bounce; + } + }); + var d3_ease_mode = d3.map({ + "in": d3_identity, + out: d3_ease_reverse, + "in-out": d3_ease_reflect, + "out-in": function(f) { + return d3_ease_reflect(d3_ease_reverse(f)); + } + }); + d3.ease = function(name) { + var i = name.indexOf("-"), t = i >= 0 ? name.substring(0, i) : name, m = i >= 0 ? name.substring(i + 1) : "in"; + t = d3_ease.get(t) || d3_ease_default; + m = d3_ease_mode.get(m) || d3_identity; + return d3_ease_clamp(m(t.apply(null, d3_arraySlice.call(arguments, 1)))); + }; + function d3_ease_clamp(f) { + return function(t) { + return t <= 0 ? 0 : t >= 1 ? 1 : f(t); + }; + } + function d3_ease_reverse(f) { + return function(t) { + return 1 - f(1 - t); + }; + } + function d3_ease_reflect(f) { + return function(t) { + return .5 * (t < .5 ? f(2 * t) : 2 - f(2 - 2 * t)); + }; + } + function d3_ease_quad(t) { + return t * t; + } + function d3_ease_cubic(t) { + return t * t * t; + } + function d3_ease_cubicInOut(t) { + if (t <= 0) return 0; + if (t >= 1) return 1; + var t2 = t * t, t3 = t2 * t; + return 4 * (t < .5 ? t3 : 3 * (t - t2) + t3 - .75); + } + function d3_ease_poly(e) { + return function(t) { + return Math.pow(t, e); + }; + } + function d3_ease_sin(t) { + return 1 - Math.cos(t * halfπ); + } + function d3_ease_exp(t) { + return Math.pow(2, 10 * (t - 1)); + } + function d3_ease_circle(t) { + return 1 - Math.sqrt(1 - t * t); + } + function d3_ease_elastic(a, p) { + var s; + if (arguments.length < 2) p = .45; + if (arguments.length) s = p / τ * Math.asin(1 / a); else a = 1, s = p / 4; + return function(t) { + return 1 + a * Math.pow(2, -10 * t) * Math.sin((t - s) * τ / p); + }; + } + function d3_ease_back(s) { + if (!s) s = 1.70158; + return function(t) { + return t * t * ((s + 1) * t - s); + }; + } + function d3_ease_bounce(t) { + return t < 1 / 2.75 ? 7.5625 * t * t : t < 2 / 2.75 ? 7.5625 * (t -= 1.5 / 2.75) * t + .75 : t < 2.5 / 2.75 ? 7.5625 * (t -= 2.25 / 2.75) * t + .9375 : 7.5625 * (t -= 2.625 / 2.75) * t + .984375; + } + d3.interpolateHcl = d3_interpolateHcl; + function d3_interpolateHcl(a, b) { + a = d3.hcl(a); + b = d3.hcl(b); + var ah = a.h, ac = a.c, al = a.l, bh = b.h - ah, bc = b.c - ac, bl = b.l - al; + if (isNaN(bc)) bc = 0, ac = isNaN(ac) ? b.c : ac; + if (isNaN(bh)) bh = 0, ah = isNaN(ah) ? b.h : ah; else if (bh > 180) bh -= 360; else if (bh < -180) bh += 360; + return function(t) { + return d3_hcl_lab(ah + bh * t, ac + bc * t, al + bl * t) + ""; + }; + } + d3.interpolateHsl = d3_interpolateHsl; + function d3_interpolateHsl(a, b) { + a = d3.hsl(a); + b = d3.hsl(b); + var ah = a.h, as = a.s, al = a.l, bh = b.h - ah, bs = b.s - as, bl = b.l - al; + if (isNaN(bs)) bs = 0, as = isNaN(as) ? b.s : as; + if (isNaN(bh)) bh = 0, ah = isNaN(ah) ? b.h : ah; else if (bh > 180) bh -= 360; else if (bh < -180) bh += 360; + return function(t) { + return d3_hsl_rgb(ah + bh * t, as + bs * t, al + bl * t) + ""; + }; + } + d3.interpolateLab = d3_interpolateLab; + function d3_interpolateLab(a, b) { + a = d3.lab(a); + b = d3.lab(b); + var al = a.l, aa = a.a, ab = a.b, bl = b.l - al, ba = b.a - aa, bb = b.b - ab; + return function(t) { + return d3_lab_rgb(al + bl * t, aa + ba * t, ab + bb * t) + ""; + }; + } + d3.interpolateRound = d3_interpolateRound; + function d3_interpolateRound(a, b) { + b -= a; + return function(t) { + return Math.round(a + b * t); + }; + } + d3.transform = function(string) { + var g = d3_document.createElementNS(d3.ns.prefix.svg, "g"); + return (d3.transform = function(string) { + if (string != null) { + g.setAttribute("transform", string); + var t = g.transform.baseVal.consolidate(); + } + return new d3_transform(t ? t.matrix : d3_transformIdentity); + })(string); + }; + function d3_transform(m) { + var r0 = [ m.a, m.b ], r1 = [ m.c, m.d ], kx = d3_transformNormalize(r0), kz = d3_transformDot(r0, r1), ky = d3_transformNormalize(d3_transformCombine(r1, r0, -kz)) || 0; + if (r0[0] * r1[1] < r1[0] * r0[1]) { + r0[0] *= -1; + r0[1] *= -1; + kx *= -1; + kz *= -1; + } + this.rotate = (kx ? Math.atan2(r0[1], r0[0]) : Math.atan2(-r1[0], r1[1])) * d3_degrees; + this.translate = [ m.e, m.f ]; + this.scale = [ kx, ky ]; + this.skew = ky ? Math.atan2(kz, ky) * d3_degrees : 0; + } + d3_transform.prototype.toString = function() { + return "translate(" + this.translate + ")rotate(" + this.rotate + ")skewX(" + this.skew + ")scale(" + this.scale + ")"; + }; + function d3_transformDot(a, b) { + return a[0] * b[0] + a[1] * b[1]; + } + function d3_transformNormalize(a) { + var k = Math.sqrt(d3_transformDot(a, a)); + if (k) { + a[0] /= k; + a[1] /= k; + } + return k; + } + function d3_transformCombine(a, b, k) { + a[0] += k * b[0]; + a[1] += k * b[1]; + return a; + } + var d3_transformIdentity = { + a: 1, + b: 0, + c: 0, + d: 1, + e: 0, + f: 0 + }; + d3.interpolateTransform = d3_interpolateTransform; + function d3_interpolateTransform(a, b) { + var s = [], q = [], n, A = d3.transform(a), B = d3.transform(b), ta = A.translate, tb = B.translate, ra = A.rotate, rb = B.rotate, wa = A.skew, wb = B.skew, ka = A.scale, kb = B.scale; + if (ta[0] != tb[0] || ta[1] != tb[1]) { + s.push("translate(", null, ",", null, ")"); + q.push({ + i: 1, + x: d3_interpolateNumber(ta[0], tb[0]) + }, { + i: 3, + x: d3_interpolateNumber(ta[1], tb[1]) + }); + } else if (tb[0] || tb[1]) { + s.push("translate(" + tb + ")"); + } else { + s.push(""); + } + if (ra != rb) { + if (ra - rb > 180) rb += 360; else if (rb - ra > 180) ra += 360; + q.push({ + i: s.push(s.pop() + "rotate(", null, ")") - 2, + x: d3_interpolateNumber(ra, rb) + }); + } else if (rb) { + s.push(s.pop() + "rotate(" + rb + ")"); + } + if (wa != wb) { + q.push({ + i: s.push(s.pop() + "skewX(", null, ")") - 2, + x: d3_interpolateNumber(wa, wb) + }); + } else if (wb) { + s.push(s.pop() + "skewX(" + wb + ")"); + } + if (ka[0] != kb[0] || ka[1] != kb[1]) { + n = s.push(s.pop() + "scale(", null, ",", null, ")"); + q.push({ + i: n - 4, + x: d3_interpolateNumber(ka[0], kb[0]) + }, { + i: n - 2, + x: d3_interpolateNumber(ka[1], kb[1]) + }); + } else if (kb[0] != 1 || kb[1] != 1) { + s.push(s.pop() + "scale(" + kb + ")"); + } + n = q.length; + return function(t) { + var i = -1, o; + while (++i < n) s[(o = q[i]).i] = o.x(t); + return s.join(""); + }; + } + function d3_uninterpolateNumber(a, b) { + b = b - (a = +a) ? 1 / (b - a) : 0; + return function(x) { + return (x - a) * b; + }; + } + function d3_uninterpolateClamp(a, b) { + b = b - (a = +a) ? 1 / (b - a) : 0; + return function(x) { + return Math.max(0, Math.min(1, (x - a) * b)); + }; + } + d3.layout = {}; + d3.layout.bundle = function() { + return function(links) { + var paths = [], i = -1, n = links.length; + while (++i < n) paths.push(d3_layout_bundlePath(links[i])); + return paths; + }; + }; + function d3_layout_bundlePath(link) { + var start = link.source, end = link.target, lca = d3_layout_bundleLeastCommonAncestor(start, end), points = [ start ]; + while (start !== lca) { + start = start.parent; + points.push(start); + } + var k = points.length; + while (end !== lca) { + points.splice(k, 0, end); + end = end.parent; + } + return points; + } + function d3_layout_bundleAncestors(node) { + var ancestors = [], parent = node.parent; + while (parent != null) { + ancestors.push(node); + node = parent; + parent = parent.parent; + } + ancestors.push(node); + return ancestors; + } + function d3_layout_bundleLeastCommonAncestor(a, b) { + if (a === b) return a; + var aNodes = d3_layout_bundleAncestors(a), bNodes = d3_layout_bundleAncestors(b), aNode = aNodes.pop(), bNode = bNodes.pop(), sharedNode = null; + while (aNode === bNode) { + sharedNode = aNode; + aNode = aNodes.pop(); + bNode = bNodes.pop(); + } + return sharedNode; + } + d3.layout.chord = function() { + var chord = {}, chords, groups, matrix, n, padding = 0, sortGroups, sortSubgroups, sortChords; + function relayout() { + var subgroups = {}, groupSums = [], groupIndex = d3.range(n), subgroupIndex = [], k, x, x0, i, j; + chords = []; + groups = []; + k = 0, i = -1; + while (++i < n) { + x = 0, j = -1; + while (++j < n) { + x += matrix[i][j]; + } + groupSums.push(x); + subgroupIndex.push(d3.range(n)); + k += x; + } + if (sortGroups) { + groupIndex.sort(function(a, b) { + return sortGroups(groupSums[a], groupSums[b]); + }); + } + if (sortSubgroups) { + subgroupIndex.forEach(function(d, i) { + d.sort(function(a, b) { + return sortSubgroups(matrix[i][a], matrix[i][b]); + }); + }); + } + k = (τ - padding * n) / k; + x = 0, i = -1; + while (++i < n) { + x0 = x, j = -1; + while (++j < n) { + var di = groupIndex[i], dj = subgroupIndex[di][j], v = matrix[di][dj], a0 = x, a1 = x += v * k; + subgroups[di + "-" + dj] = { + index: di, + subindex: dj, + startAngle: a0, + endAngle: a1, + value: v + }; + } + groups[di] = { + index: di, + startAngle: x0, + endAngle: x, + value: (x - x0) / k + }; + x += padding; + } + i = -1; + while (++i < n) { + j = i - 1; + while (++j < n) { + var source = subgroups[i + "-" + j], target = subgroups[j + "-" + i]; + if (source.value || target.value) { + chords.push(source.value < target.value ? { + source: target, + target: source + } : { + source: source, + target: target + }); + } + } + } + if (sortChords) resort(); + } + function resort() { + chords.sort(function(a, b) { + return sortChords((a.source.value + a.target.value) / 2, (b.source.value + b.target.value) / 2); + }); + } + chord.matrix = function(x) { + if (!arguments.length) return matrix; + n = (matrix = x) && matrix.length; + chords = groups = null; + return chord; + }; + chord.padding = function(x) { + if (!arguments.length) return padding; + padding = x; + chords = groups = null; + return chord; + }; + chord.sortGroups = function(x) { + if (!arguments.length) return sortGroups; + sortGroups = x; + chords = groups = null; + return chord; + }; + chord.sortSubgroups = function(x) { + if (!arguments.length) return sortSubgroups; + sortSubgroups = x; + chords = null; + return chord; + }; + chord.sortChords = function(x) { + if (!arguments.length) return sortChords; + sortChords = x; + if (chords) resort(); + return chord; + }; + chord.chords = function() { + if (!chords) relayout(); + return chords; + }; + chord.groups = function() { + if (!groups) relayout(); + return groups; + }; + return chord; + }; + d3.layout.force = function() { + var force = {}, event = d3.dispatch("start", "tick", "end"), size = [ 1, 1 ], drag, alpha, friction = .9, linkDistance = d3_layout_forceLinkDistance, linkStrength = d3_layout_forceLinkStrength, charge = -30, chargeDistance2 = d3_layout_forceChargeDistance2, gravity = .1, theta2 = .64, nodes = [], links = [], distances, strengths, charges; + function repulse(node) { + return function(quad, x1, _, x2) { + if (quad.point !== node) { + var dx = quad.cx - node.x, dy = quad.cy - node.y, dw = x2 - x1, dn = dx * dx + dy * dy; + if (dw * dw / theta2 < dn) { + if (dn < chargeDistance2) { + var k = quad.charge / dn; + node.px -= dx * k; + node.py -= dy * k; + } + return true; + } + if (quad.point && dn && dn < chargeDistance2) { + var k = quad.pointCharge / dn; + node.px -= dx * k; + node.py -= dy * k; + } + } + return !quad.charge; + }; + } + force.tick = function() { + if ((alpha *= .99) < .005) { + event.end({ + type: "end", + alpha: alpha = 0 + }); + return true; + } + var n = nodes.length, m = links.length, q, i, o, s, t, l, k, x, y; + for (i = 0; i < m; ++i) { + o = links[i]; + s = o.source; + t = o.target; + x = t.x - s.x; + y = t.y - s.y; + if (l = x * x + y * y) { + l = alpha * strengths[i] * ((l = Math.sqrt(l)) - distances[i]) / l; + x *= l; + y *= l; + t.x -= x * (k = s.weight / (t.weight + s.weight)); + t.y -= y * k; + s.x += x * (k = 1 - k); + s.y += y * k; + } + } + if (k = alpha * gravity) { + x = size[0] / 2; + y = size[1] / 2; + i = -1; + if (k) while (++i < n) { + o = nodes[i]; + o.x += (x - o.x) * k; + o.y += (y - o.y) * k; + } + } + if (charge) { + d3_layout_forceAccumulate(q = d3.geom.quadtree(nodes), alpha, charges); + i = -1; + while (++i < n) { + if (!(o = nodes[i]).fixed) { + q.visit(repulse(o)); + } + } + } + i = -1; + while (++i < n) { + o = nodes[i]; + if (o.fixed) { + o.x = o.px; + o.y = o.py; + } else { + o.x -= (o.px - (o.px = o.x)) * friction; + o.y -= (o.py - (o.py = o.y)) * friction; + } + } + event.tick({ + type: "tick", + alpha: alpha + }); + }; + force.nodes = function(x) { + if (!arguments.length) return nodes; + nodes = x; + return force; + }; + force.links = function(x) { + if (!arguments.length) return links; + links = x; + return force; + }; + force.size = function(x) { + if (!arguments.length) return size; + size = x; + return force; + }; + force.linkDistance = function(x) { + if (!arguments.length) return linkDistance; + linkDistance = typeof x === "function" ? x : +x; + return force; + }; + force.distance = force.linkDistance; + force.linkStrength = function(x) { + if (!arguments.length) return linkStrength; + linkStrength = typeof x === "function" ? x : +x; + return force; + }; + force.friction = function(x) { + if (!arguments.length) return friction; + friction = +x; + return force; + }; + force.charge = function(x) { + if (!arguments.length) return charge; + charge = typeof x === "function" ? x : +x; + return force; + }; + force.chargeDistance = function(x) { + if (!arguments.length) return Math.sqrt(chargeDistance2); + chargeDistance2 = x * x; + return force; + }; + force.gravity = function(x) { + if (!arguments.length) return gravity; + gravity = +x; + return force; + }; + force.theta = function(x) { + if (!arguments.length) return Math.sqrt(theta2); + theta2 = x * x; + return force; + }; + force.alpha = function(x) { + if (!arguments.length) return alpha; + x = +x; + if (alpha) { + if (x > 0) alpha = x; else alpha = 0; + } else if (x > 0) { + event.start({ + type: "start", + alpha: alpha = x + }); + d3.timer(force.tick); + } + return force; + }; + force.start = function() { + var i, n = nodes.length, m = links.length, w = size[0], h = size[1], neighbors, o; + for (i = 0; i < n; ++i) { + (o = nodes[i]).index = i; + o.weight = 0; + } + for (i = 0; i < m; ++i) { + o = links[i]; + if (typeof o.source == "number") o.source = nodes[o.source]; + if (typeof o.target == "number") o.target = nodes[o.target]; + ++o.source.weight; + ++o.target.weight; + } + for (i = 0; i < n; ++i) { + o = nodes[i]; + if (isNaN(o.x)) o.x = position("x", w); + if (isNaN(o.y)) o.y = position("y", h); + if (isNaN(o.px)) o.px = o.x; + if (isNaN(o.py)) o.py = o.y; + } + distances = []; + if (typeof linkDistance === "function") for (i = 0; i < m; ++i) distances[i] = +linkDistance.call(this, links[i], i); else for (i = 0; i < m; ++i) distances[i] = linkDistance; + strengths = []; + if (typeof linkStrength === "function") for (i = 0; i < m; ++i) strengths[i] = +linkStrength.call(this, links[i], i); else for (i = 0; i < m; ++i) strengths[i] = linkStrength; + charges = []; + if (typeof charge === "function") for (i = 0; i < n; ++i) charges[i] = +charge.call(this, nodes[i], i); else for (i = 0; i < n; ++i) charges[i] = charge; + function position(dimension, size) { + if (!neighbors) { + neighbors = new Array(n); + for (j = 0; j < n; ++j) { + neighbors[j] = []; + } + for (j = 0; j < m; ++j) { + var o = links[j]; + neighbors[o.source.index].push(o.target); + neighbors[o.target.index].push(o.source); + } + } + var candidates = neighbors[i], j = -1, m = candidates.length, x; + while (++j < m) if (!isNaN(x = candidates[j][dimension])) return x; + return Math.random() * size; + } + return force.resume(); + }; + force.resume = function() { + return force.alpha(.1); + }; + force.stop = function() { + return force.alpha(0); + }; + force.drag = function() { + if (!drag) drag = d3.behavior.drag().origin(d3_identity).on("dragstart.force", d3_layout_forceDragstart).on("drag.force", dragmove).on("dragend.force", d3_layout_forceDragend); + if (!arguments.length) return drag; + this.on("mouseover.force", d3_layout_forceMouseover).on("mouseout.force", d3_layout_forceMouseout).call(drag); + }; + function dragmove(d) { + d.px = d3.event.x, d.py = d3.event.y; + force.resume(); + } + return d3.rebind(force, event, "on"); + }; + function d3_layout_forceDragstart(d) { + d.fixed |= 2; + } + function d3_layout_forceDragend(d) { + d.fixed &= ~6; + } + function d3_layout_forceMouseover(d) { + d.fixed |= 4; + d.px = d.x, d.py = d.y; + } + function d3_layout_forceMouseout(d) { + d.fixed &= ~4; + } + function d3_layout_forceAccumulate(quad, alpha, charges) { + var cx = 0, cy = 0; + quad.charge = 0; + if (!quad.leaf) { + var nodes = quad.nodes, n = nodes.length, i = -1, c; + while (++i < n) { + c = nodes[i]; + if (c == null) continue; + d3_layout_forceAccumulate(c, alpha, charges); + quad.charge += c.charge; + cx += c.charge * c.cx; + cy += c.charge * c.cy; + } + } + if (quad.point) { + if (!quad.leaf) { + quad.point.x += Math.random() - .5; + quad.point.y += Math.random() - .5; + } + var k = alpha * charges[quad.point.index]; + quad.charge += quad.pointCharge = k; + cx += k * quad.point.x; + cy += k * quad.point.y; + } + quad.cx = cx / quad.charge; + quad.cy = cy / quad.charge; + } + var d3_layout_forceLinkDistance = 20, d3_layout_forceLinkStrength = 1, d3_layout_forceChargeDistance2 = Infinity; + d3.layout.hierarchy = function() { + var sort = d3_layout_hierarchySort, children = d3_layout_hierarchyChildren, value = d3_layout_hierarchyValue; + function hierarchy(root) { + var stack = [ root ], nodes = [], node; + root.depth = 0; + while ((node = stack.pop()) != null) { + nodes.push(node); + if ((childs = children.call(hierarchy, node, node.depth)) && (n = childs.length)) { + var n, childs, child; + while (--n >= 0) { + stack.push(child = childs[n]); + child.parent = node; + child.depth = node.depth + 1; + } + if (value) node.value = 0; + node.children = childs; + } else { + if (value) node.value = +value.call(hierarchy, node, node.depth) || 0; + delete node.children; + } + } + d3_layout_hierarchyVisitAfter(root, function(node) { + var childs, parent; + if (sort && (childs = node.children)) childs.sort(sort); + if (value && (parent = node.parent)) parent.value += node.value; + }); + return nodes; + } + hierarchy.sort = function(x) { + if (!arguments.length) return sort; + sort = x; + return hierarchy; + }; + hierarchy.children = function(x) { + if (!arguments.length) return children; + children = x; + return hierarchy; + }; + hierarchy.value = function(x) { + if (!arguments.length) return value; + value = x; + return hierarchy; + }; + hierarchy.revalue = function(root) { + if (value) { + d3_layout_hierarchyVisitBefore(root, function(node) { + if (node.children) node.value = 0; + }); + d3_layout_hierarchyVisitAfter(root, function(node) { + var parent; + if (!node.children) node.value = +value.call(hierarchy, node, node.depth) || 0; + if (parent = node.parent) parent.value += node.value; + }); + } + return root; + }; + return hierarchy; + }; + function d3_layout_hierarchyRebind(object, hierarchy) { + d3.rebind(object, hierarchy, "sort", "children", "value"); + object.nodes = object; + object.links = d3_layout_hierarchyLinks; + return object; + } + function d3_layout_hierarchyVisitBefore(node, callback) { + var nodes = [ node ]; + while ((node = nodes.pop()) != null) { + callback(node); + if ((children = node.children) && (n = children.length)) { + var n, children; + while (--n >= 0) nodes.push(children[n]); + } + } + } + function d3_layout_hierarchyVisitAfter(node, callback) { + var nodes = [ node ], nodes2 = []; + while ((node = nodes.pop()) != null) { + nodes2.push(node); + if ((children = node.children) && (n = children.length)) { + var i = -1, n, children; + while (++i < n) nodes.push(children[i]); + } + } + while ((node = nodes2.pop()) != null) { + callback(node); + } + } + function d3_layout_hierarchyChildren(d) { + return d.children; + } + function d3_layout_hierarchyValue(d) { + return d.value; + } + function d3_layout_hierarchySort(a, b) { + return b.value - a.value; + } + function d3_layout_hierarchyLinks(nodes) { + return d3.merge(nodes.map(function(parent) { + return (parent.children || []).map(function(child) { + return { + source: parent, + target: child + }; + }); + })); + } + d3.layout.partition = function() { + var hierarchy = d3.layout.hierarchy(), size = [ 1, 1 ]; + function position(node, x, dx, dy) { + var children = node.children; + node.x = x; + node.y = node.depth * dy; + node.dx = dx; + node.dy = dy; + if (children && (n = children.length)) { + var i = -1, n, c, d; + dx = node.value ? dx / node.value : 0; + while (++i < n) { + position(c = children[i], x, d = c.value * dx, dy); + x += d; + } + } + } + function depth(node) { + var children = node.children, d = 0; + if (children && (n = children.length)) { + var i = -1, n; + while (++i < n) d = Math.max(d, depth(children[i])); + } + return 1 + d; + } + function partition(d, i) { + var nodes = hierarchy.call(this, d, i); + position(nodes[0], 0, size[0], size[1] / depth(nodes[0])); + return nodes; + } + partition.size = function(x) { + if (!arguments.length) return size; + size = x; + return partition; + }; + return d3_layout_hierarchyRebind(partition, hierarchy); + }; + d3.layout.pie = function() { + var value = Number, sort = d3_layout_pieSortByValue, startAngle = 0, endAngle = τ; + function pie(data) { + var values = data.map(function(d, i) { + return +value.call(pie, d, i); + }); + var a = +(typeof startAngle === "function" ? startAngle.apply(this, arguments) : startAngle); + var k = ((typeof endAngle === "function" ? endAngle.apply(this, arguments) : endAngle) - a) / d3.sum(values); + var index = d3.range(data.length); + if (sort != null) index.sort(sort === d3_layout_pieSortByValue ? function(i, j) { + return values[j] - values[i]; + } : function(i, j) { + return sort(data[i], data[j]); + }); + var arcs = []; + index.forEach(function(i) { + var d; + arcs[i] = { + data: data[i], + value: d = values[i], + startAngle: a, + endAngle: a += d * k + }; + }); + return arcs; + } + pie.value = function(x) { + if (!arguments.length) return value; + value = x; + return pie; + }; + pie.sort = function(x) { + if (!arguments.length) return sort; + sort = x; + return pie; + }; + pie.startAngle = function(x) { + if (!arguments.length) return startAngle; + startAngle = x; + return pie; + }; + pie.endAngle = function(x) { + if (!arguments.length) return endAngle; + endAngle = x; + return pie; + }; + return pie; + }; + var d3_layout_pieSortByValue = {}; + d3.layout.stack = function() { + var values = d3_identity, order = d3_layout_stackOrderDefault, offset = d3_layout_stackOffsetZero, out = d3_layout_stackOut, x = d3_layout_stackX, y = d3_layout_stackY; + function stack(data, index) { + var series = data.map(function(d, i) { + return values.call(stack, d, i); + }); + var points = series.map(function(d) { + return d.map(function(v, i) { + return [ x.call(stack, v, i), y.call(stack, v, i) ]; + }); + }); + var orders = order.call(stack, points, index); + series = d3.permute(series, orders); + points = d3.permute(points, orders); + var offsets = offset.call(stack, points, index); + var n = series.length, m = series[0].length, i, j, o; + for (j = 0; j < m; ++j) { + out.call(stack, series[0][j], o = offsets[j], points[0][j][1]); + for (i = 1; i < n; ++i) { + out.call(stack, series[i][j], o += points[i - 1][j][1], points[i][j][1]); + } + } + return data; + } + stack.values = function(x) { + if (!arguments.length) return values; + values = x; + return stack; + }; + stack.order = function(x) { + if (!arguments.length) return order; + order = typeof x === "function" ? x : d3_layout_stackOrders.get(x) || d3_layout_stackOrderDefault; + return stack; + }; + stack.offset = function(x) { + if (!arguments.length) return offset; + offset = typeof x === "function" ? x : d3_layout_stackOffsets.get(x) || d3_layout_stackOffsetZero; + return stack; + }; + stack.x = function(z) { + if (!arguments.length) return x; + x = z; + return stack; + }; + stack.y = function(z) { + if (!arguments.length) return y; + y = z; + return stack; + }; + stack.out = function(z) { + if (!arguments.length) return out; + out = z; + return stack; + }; + return stack; + }; + function d3_layout_stackX(d) { + return d.x; + } + function d3_layout_stackY(d) { + return d.y; + } + function d3_layout_stackOut(d, y0, y) { + d.y0 = y0; + d.y = y; + } + var d3_layout_stackOrders = d3.map({ + "inside-out": function(data) { + var n = data.length, i, j, max = data.map(d3_layout_stackMaxIndex), sums = data.map(d3_layout_stackReduceSum), index = d3.range(n).sort(function(a, b) { + return max[a] - max[b]; + }), top = 0, bottom = 0, tops = [], bottoms = []; + for (i = 0; i < n; ++i) { + j = index[i]; + if (top < bottom) { + top += sums[j]; + tops.push(j); + } else { + bottom += sums[j]; + bottoms.push(j); + } + } + return bottoms.reverse().concat(tops); + }, + reverse: function(data) { + return d3.range(data.length).reverse(); + }, + "default": d3_layout_stackOrderDefault + }); + var d3_layout_stackOffsets = d3.map({ + silhouette: function(data) { + var n = data.length, m = data[0].length, sums = [], max = 0, i, j, o, y0 = []; + for (j = 0; j < m; ++j) { + for (i = 0, o = 0; i < n; i++) o += data[i][j][1]; + if (o > max) max = o; + sums.push(o); + } + for (j = 0; j < m; ++j) { + y0[j] = (max - sums[j]) / 2; + } + return y0; + }, + wiggle: function(data) { + var n = data.length, x = data[0], m = x.length, i, j, k, s1, s2, s3, dx, o, o0, y0 = []; + y0[0] = o = o0 = 0; + for (j = 1; j < m; ++j) { + for (i = 0, s1 = 0; i < n; ++i) s1 += data[i][j][1]; + for (i = 0, s2 = 0, dx = x[j][0] - x[j - 1][0]; i < n; ++i) { + for (k = 0, s3 = (data[i][j][1] - data[i][j - 1][1]) / (2 * dx); k < i; ++k) { + s3 += (data[k][j][1] - data[k][j - 1][1]) / dx; + } + s2 += s3 * data[i][j][1]; + } + y0[j] = o -= s1 ? s2 / s1 * dx : 0; + if (o < o0) o0 = o; + } + for (j = 0; j < m; ++j) y0[j] -= o0; + return y0; + }, + expand: function(data) { + var n = data.length, m = data[0].length, k = 1 / n, i, j, o, y0 = []; + for (j = 0; j < m; ++j) { + for (i = 0, o = 0; i < n; i++) o += data[i][j][1]; + if (o) for (i = 0; i < n; i++) data[i][j][1] /= o; else for (i = 0; i < n; i++) data[i][j][1] = k; + } + for (j = 0; j < m; ++j) y0[j] = 0; + return y0; + }, + zero: d3_layout_stackOffsetZero + }); + function d3_layout_stackOrderDefault(data) { + return d3.range(data.length); + } + function d3_layout_stackOffsetZero(data) { + var j = -1, m = data[0].length, y0 = []; + while (++j < m) y0[j] = 0; + return y0; + } + function d3_layout_stackMaxIndex(array) { + var i = 1, j = 0, v = array[0][1], k, n = array.length; + for (;i < n; ++i) { + if ((k = array[i][1]) > v) { + j = i; + v = k; + } + } + return j; + } + function d3_layout_stackReduceSum(d) { + return d.reduce(d3_layout_stackSum, 0); + } + function d3_layout_stackSum(p, d) { + return p + d[1]; + } + d3.layout.histogram = function() { + var frequency = true, valuer = Number, ranger = d3_layout_histogramRange, binner = d3_layout_histogramBinSturges; + function histogram(data, i) { + var bins = [], values = data.map(valuer, this), range = ranger.call(this, values, i), thresholds = binner.call(this, range, values, i), bin, i = -1, n = values.length, m = thresholds.length - 1, k = frequency ? 1 : 1 / n, x; + while (++i < m) { + bin = bins[i] = []; + bin.dx = thresholds[i + 1] - (bin.x = thresholds[i]); + bin.y = 0; + } + if (m > 0) { + i = -1; + while (++i < n) { + x = values[i]; + if (x >= range[0] && x <= range[1]) { + bin = bins[d3.bisect(thresholds, x, 1, m) - 1]; + bin.y += k; + bin.push(data[i]); + } + } + } + return bins; + } + histogram.value = function(x) { + if (!arguments.length) return valuer; + valuer = x; + return histogram; + }; + histogram.range = function(x) { + if (!arguments.length) return ranger; + ranger = d3_functor(x); + return histogram; + }; + histogram.bins = function(x) { + if (!arguments.length) return binner; + binner = typeof x === "number" ? function(range) { + return d3_layout_histogramBinFixed(range, x); + } : d3_functor(x); + return histogram; + }; + histogram.frequency = function(x) { + if (!arguments.length) return frequency; + frequency = !!x; + return histogram; + }; + return histogram; + }; + function d3_layout_histogramBinSturges(range, values) { + return d3_layout_histogramBinFixed(range, Math.ceil(Math.log(values.length) / Math.LN2 + 1)); + } + function d3_layout_histogramBinFixed(range, n) { + var x = -1, b = +range[0], m = (range[1] - b) / n, f = []; + while (++x <= n) f[x] = m * x + b; + return f; + } + function d3_layout_histogramRange(values) { + return [ d3.min(values), d3.max(values) ]; + } + d3.layout.pack = function() { + var hierarchy = d3.layout.hierarchy().sort(d3_layout_packSort), padding = 0, size = [ 1, 1 ], radius; + function pack(d, i) { + var nodes = hierarchy.call(this, d, i), root = nodes[0], w = size[0], h = size[1], r = radius == null ? Math.sqrt : typeof radius === "function" ? radius : function() { + return radius; + }; + root.x = root.y = 0; + d3_layout_hierarchyVisitAfter(root, function(d) { + d.r = +r(d.value); + }); + d3_layout_hierarchyVisitAfter(root, d3_layout_packSiblings); + if (padding) { + var dr = padding * (radius ? 1 : Math.max(2 * root.r / w, 2 * root.r / h)) / 2; + d3_layout_hierarchyVisitAfter(root, function(d) { + d.r += dr; + }); + d3_layout_hierarchyVisitAfter(root, d3_layout_packSiblings); + d3_layout_hierarchyVisitAfter(root, function(d) { + d.r -= dr; + }); + } + d3_layout_packTransform(root, w / 2, h / 2, radius ? 1 : 1 / Math.max(2 * root.r / w, 2 * root.r / h)); + return nodes; + } + pack.size = function(_) { + if (!arguments.length) return size; + size = _; + return pack; + }; + pack.radius = function(_) { + if (!arguments.length) return radius; + radius = _ == null || typeof _ === "function" ? _ : +_; + return pack; + }; + pack.padding = function(_) { + if (!arguments.length) return padding; + padding = +_; + return pack; + }; + return d3_layout_hierarchyRebind(pack, hierarchy); + }; + function d3_layout_packSort(a, b) { + return a.value - b.value; + } + function d3_layout_packInsert(a, b) { + var c = a._pack_next; + a._pack_next = b; + b._pack_prev = a; + b._pack_next = c; + c._pack_prev = b; + } + function d3_layout_packSplice(a, b) { + a._pack_next = b; + b._pack_prev = a; + } + function d3_layout_packIntersects(a, b) { + var dx = b.x - a.x, dy = b.y - a.y, dr = a.r + b.r; + return .999 * dr * dr > dx * dx + dy * dy; + } + function d3_layout_packSiblings(node) { + if (!(nodes = node.children) || !(n = nodes.length)) return; + var nodes, xMin = Infinity, xMax = -Infinity, yMin = Infinity, yMax = -Infinity, a, b, c, i, j, k, n; + function bound(node) { + xMin = Math.min(node.x - node.r, xMin); + xMax = Math.max(node.x + node.r, xMax); + yMin = Math.min(node.y - node.r, yMin); + yMax = Math.max(node.y + node.r, yMax); + } + nodes.forEach(d3_layout_packLink); + a = nodes[0]; + a.x = -a.r; + a.y = 0; + bound(a); + if (n > 1) { + b = nodes[1]; + b.x = b.r; + b.y = 0; + bound(b); + if (n > 2) { + c = nodes[2]; + d3_layout_packPlace(a, b, c); + bound(c); + d3_layout_packInsert(a, c); + a._pack_prev = c; + d3_layout_packInsert(c, b); + b = a._pack_next; + for (i = 3; i < n; i++) { + d3_layout_packPlace(a, b, c = nodes[i]); + var isect = 0, s1 = 1, s2 = 1; + for (j = b._pack_next; j !== b; j = j._pack_next, s1++) { + if (d3_layout_packIntersects(j, c)) { + isect = 1; + break; + } + } + if (isect == 1) { + for (k = a._pack_prev; k !== j._pack_prev; k = k._pack_prev, s2++) { + if (d3_layout_packIntersects(k, c)) { + break; + } + } + } + if (isect) { + if (s1 < s2 || s1 == s2 && b.r < a.r) d3_layout_packSplice(a, b = j); else d3_layout_packSplice(a = k, b); + i--; + } else { + d3_layout_packInsert(a, c); + b = c; + bound(c); + } + } + } + } + var cx = (xMin + xMax) / 2, cy = (yMin + yMax) / 2, cr = 0; + for (i = 0; i < n; i++) { + c = nodes[i]; + c.x -= cx; + c.y -= cy; + cr = Math.max(cr, c.r + Math.sqrt(c.x * c.x + c.y * c.y)); + } + node.r = cr; + nodes.forEach(d3_layout_packUnlink); + } + function d3_layout_packLink(node) { + node._pack_next = node._pack_prev = node; + } + function d3_layout_packUnlink(node) { + delete node._pack_next; + delete node._pack_prev; + } + function d3_layout_packTransform(node, x, y, k) { + var children = node.children; + node.x = x += k * node.x; + node.y = y += k * node.y; + node.r *= k; + if (children) { + var i = -1, n = children.length; + while (++i < n) d3_layout_packTransform(children[i], x, y, k); + } + } + function d3_layout_packPlace(a, b, c) { + var db = a.r + c.r, dx = b.x - a.x, dy = b.y - a.y; + if (db && (dx || dy)) { + var da = b.r + c.r, dc = dx * dx + dy * dy; + da *= da; + db *= db; + var x = .5 + (db - da) / (2 * dc), y = Math.sqrt(Math.max(0, 2 * da * (db + dc) - (db -= dc) * db - da * da)) / (2 * dc); + c.x = a.x + x * dx + y * dy; + c.y = a.y + x * dy - y * dx; + } else { + c.x = a.x + db; + c.y = a.y; + } + } + d3.layout.tree = function() { + var hierarchy = d3.layout.hierarchy().sort(null).value(null), separation = d3_layout_treeSeparation, size = [ 1, 1 ], nodeSize = null; + function tree(d, i) { + var nodes = hierarchy.call(this, d, i), root0 = nodes[0], root1 = wrapTree(root0); + d3_layout_hierarchyVisitAfter(root1, firstWalk), root1.parent.m = -root1.z; + d3_layout_hierarchyVisitBefore(root1, secondWalk); + if (nodeSize) d3_layout_hierarchyVisitBefore(root0, sizeNode); else { + var left = root0, right = root0, bottom = root0; + d3_layout_hierarchyVisitBefore(root0, function(node) { + if (node.x < left.x) left = node; + if (node.x > right.x) right = node; + if (node.depth > bottom.depth) bottom = node; + }); + var tx = separation(left, right) / 2 - left.x, kx = size[0] / (right.x + separation(right, left) / 2 + tx), ky = size[1] / (bottom.depth || 1); + d3_layout_hierarchyVisitBefore(root0, function(node) { + node.x = (node.x + tx) * kx; + node.y = node.depth * ky; + }); + } + return nodes; + } + function wrapTree(root0) { + var root1 = { + A: null, + children: [ root0 ] + }, queue = [ root1 ], node1; + while ((node1 = queue.pop()) != null) { + for (var children = node1.children, child, i = 0, n = children.length; i < n; ++i) { + queue.push((children[i] = child = { + _: children[i], + parent: node1, + children: (child = children[i].children) && child.slice() || [], + A: null, + a: null, + z: 0, + m: 0, + c: 0, + s: 0, + t: null, + i: i + }).a = child); + } + } + return root1.children[0]; + } + function firstWalk(v) { + var children = v.children, siblings = v.parent.children, w = v.i ? siblings[v.i - 1] : null; + if (children.length) { + d3_layout_treeShift(v); + var midpoint = (children[0].z + children[children.length - 1].z) / 2; + if (w) { + v.z = w.z + separation(v._, w._); + v.m = v.z - midpoint; + } else { + v.z = midpoint; + } + } else if (w) { + v.z = w.z + separation(v._, w._); + } + v.parent.A = apportion(v, w, v.parent.A || siblings[0]); + } + function secondWalk(v) { + v._.x = v.z + v.parent.m; + v.m += v.parent.m; + } + function apportion(v, w, ancestor) { + if (w) { + var vip = v, vop = v, vim = w, vom = vip.parent.children[0], sip = vip.m, sop = vop.m, sim = vim.m, som = vom.m, shift; + while (vim = d3_layout_treeRight(vim), vip = d3_layout_treeLeft(vip), vim && vip) { + vom = d3_layout_treeLeft(vom); + vop = d3_layout_treeRight(vop); + vop.a = v; + shift = vim.z + sim - vip.z - sip + separation(vim._, vip._); + if (shift > 0) { + d3_layout_treeMove(d3_layout_treeAncestor(vim, v, ancestor), v, shift); + sip += shift; + sop += shift; + } + sim += vim.m; + sip += vip.m; + som += vom.m; + sop += vop.m; + } + if (vim && !d3_layout_treeRight(vop)) { + vop.t = vim; + vop.m += sim - sop; + } + if (vip && !d3_layout_treeLeft(vom)) { + vom.t = vip; + vom.m += sip - som; + ancestor = v; + } + } + return ancestor; + } + function sizeNode(node) { + node.x *= size[0]; + node.y = node.depth * size[1]; + } + tree.separation = function(x) { + if (!arguments.length) return separation; + separation = x; + return tree; + }; + tree.size = function(x) { + if (!arguments.length) return nodeSize ? null : size; + nodeSize = (size = x) == null ? sizeNode : null; + return tree; + }; + tree.nodeSize = function(x) { + if (!arguments.length) return nodeSize ? size : null; + nodeSize = (size = x) == null ? null : sizeNode; + return tree; + }; + return d3_layout_hierarchyRebind(tree, hierarchy); + }; + function d3_layout_treeSeparation(a, b) { + return a.parent == b.parent ? 1 : 2; + } + function d3_layout_treeLeft(v) { + var children = v.children; + return children.length ? children[0] : v.t; + } + function d3_layout_treeRight(v) { + var children = v.children, n; + return (n = children.length) ? children[n - 1] : v.t; + } + function d3_layout_treeMove(wm, wp, shift) { + var change = shift / (wp.i - wm.i); + wp.c -= change; + wp.s += shift; + wm.c += change; + wp.z += shift; + wp.m += shift; + } + function d3_layout_treeShift(v) { + var shift = 0, change = 0, children = v.children, i = children.length, w; + while (--i >= 0) { + w = children[i]; + w.z += shift; + w.m += shift; + shift += w.s + (change += w.c); + } + } + function d3_layout_treeAncestor(vim, v, ancestor) { + return vim.a.parent === v.parent ? vim.a : ancestor; + } + d3.layout.cluster = function() { + var hierarchy = d3.layout.hierarchy().sort(null).value(null), separation = d3_layout_treeSeparation, size = [ 1, 1 ], nodeSize = false; + function cluster(d, i) { + var nodes = hierarchy.call(this, d, i), root = nodes[0], previousNode, x = 0; + d3_layout_hierarchyVisitAfter(root, function(node) { + var children = node.children; + if (children && children.length) { + node.x = d3_layout_clusterX(children); + node.y = d3_layout_clusterY(children); + } else { + node.x = previousNode ? x += separation(node, previousNode) : 0; + node.y = 0; + previousNode = node; + } + }); + var left = d3_layout_clusterLeft(root), right = d3_layout_clusterRight(root), x0 = left.x - separation(left, right) / 2, x1 = right.x + separation(right, left) / 2; + d3_layout_hierarchyVisitAfter(root, nodeSize ? function(node) { + node.x = (node.x - root.x) * size[0]; + node.y = (root.y - node.y) * size[1]; + } : function(node) { + node.x = (node.x - x0) / (x1 - x0) * size[0]; + node.y = (1 - (root.y ? node.y / root.y : 1)) * size[1]; + }); + return nodes; + } + cluster.separation = function(x) { + if (!arguments.length) return separation; + separation = x; + return cluster; + }; + cluster.size = function(x) { + if (!arguments.length) return nodeSize ? null : size; + nodeSize = (size = x) == null; + return cluster; + }; + cluster.nodeSize = function(x) { + if (!arguments.length) return nodeSize ? size : null; + nodeSize = (size = x) != null; + return cluster; + }; + return d3_layout_hierarchyRebind(cluster, hierarchy); + }; + function d3_layout_clusterY(children) { + return 1 + d3.max(children, function(child) { + return child.y; + }); + } + function d3_layout_clusterX(children) { + return children.reduce(function(x, child) { + return x + child.x; + }, 0) / children.length; + } + function d3_layout_clusterLeft(node) { + var children = node.children; + return children && children.length ? d3_layout_clusterLeft(children[0]) : node; + } + function d3_layout_clusterRight(node) { + var children = node.children, n; + return children && (n = children.length) ? d3_layout_clusterRight(children[n - 1]) : node; + } + d3.layout.treemap = function() { + var hierarchy = d3.layout.hierarchy(), round = Math.round, size = [ 1, 1 ], padding = null, pad = d3_layout_treemapPadNull, sticky = false, stickies, mode = "squarify", ratio = .5 * (1 + Math.sqrt(5)); + function scale(children, k) { + var i = -1, n = children.length, child, area; + while (++i < n) { + area = (child = children[i]).value * (k < 0 ? 0 : k); + child.area = isNaN(area) || area <= 0 ? 0 : area; + } + } + function squarify(node) { + var children = node.children; + if (children && children.length) { + var rect = pad(node), row = [], remaining = children.slice(), child, best = Infinity, score, u = mode === "slice" ? rect.dx : mode === "dice" ? rect.dy : mode === "slice-dice" ? node.depth & 1 ? rect.dy : rect.dx : Math.min(rect.dx, rect.dy), n; + scale(remaining, rect.dx * rect.dy / node.value); + row.area = 0; + while ((n = remaining.length) > 0) { + row.push(child = remaining[n - 1]); + row.area += child.area; + if (mode !== "squarify" || (score = worst(row, u)) <= best) { + remaining.pop(); + best = score; + } else { + row.area -= row.pop().area; + position(row, u, rect, false); + u = Math.min(rect.dx, rect.dy); + row.length = row.area = 0; + best = Infinity; + } + } + if (row.length) { + position(row, u, rect, true); + row.length = row.area = 0; + } + children.forEach(squarify); + } + } + function stickify(node) { + var children = node.children; + if (children && children.length) { + var rect = pad(node), remaining = children.slice(), child, row = []; + scale(remaining, rect.dx * rect.dy / node.value); + row.area = 0; + while (child = remaining.pop()) { + row.push(child); + row.area += child.area; + if (child.z != null) { + position(row, child.z ? rect.dx : rect.dy, rect, !remaining.length); + row.length = row.area = 0; + } + } + children.forEach(stickify); + } + } + function worst(row, u) { + var s = row.area, r, rmax = 0, rmin = Infinity, i = -1, n = row.length; + while (++i < n) { + if (!(r = row[i].area)) continue; + if (r < rmin) rmin = r; + if (r > rmax) rmax = r; + } + s *= s; + u *= u; + return s ? Math.max(u * rmax * ratio / s, s / (u * rmin * ratio)) : Infinity; + } + function position(row, u, rect, flush) { + var i = -1, n = row.length, x = rect.x, y = rect.y, v = u ? round(row.area / u) : 0, o; + if (u == rect.dx) { + if (flush || v > rect.dy) v = rect.dy; + while (++i < n) { + o = row[i]; + o.x = x; + o.y = y; + o.dy = v; + x += o.dx = Math.min(rect.x + rect.dx - x, v ? round(o.area / v) : 0); + } + o.z = true; + o.dx += rect.x + rect.dx - x; + rect.y += v; + rect.dy -= v; + } else { + if (flush || v > rect.dx) v = rect.dx; + while (++i < n) { + o = row[i]; + o.x = x; + o.y = y; + o.dx = v; + y += o.dy = Math.min(rect.y + rect.dy - y, v ? round(o.area / v) : 0); + } + o.z = false; + o.dy += rect.y + rect.dy - y; + rect.x += v; + rect.dx -= v; + } + } + function treemap(d) { + var nodes = stickies || hierarchy(d), root = nodes[0]; + root.x = 0; + root.y = 0; + root.dx = size[0]; + root.dy = size[1]; + if (stickies) hierarchy.revalue(root); + scale([ root ], root.dx * root.dy / root.value); + (stickies ? stickify : squarify)(root); + if (sticky) stickies = nodes; + return nodes; + } + treemap.size = function(x) { + if (!arguments.length) return size; + size = x; + return treemap; + }; + treemap.padding = function(x) { + if (!arguments.length) return padding; + function padFunction(node) { + var p = x.call(treemap, node, node.depth); + return p == null ? d3_layout_treemapPadNull(node) : d3_layout_treemapPad(node, typeof p === "number" ? [ p, p, p, p ] : p); + } + function padConstant(node) { + return d3_layout_treemapPad(node, x); + } + var type; + pad = (padding = x) == null ? d3_layout_treemapPadNull : (type = typeof x) === "function" ? padFunction : type === "number" ? (x = [ x, x, x, x ], + padConstant) : padConstant; + return treemap; + }; + treemap.round = function(x) { + if (!arguments.length) return round != Number; + round = x ? Math.round : Number; + return treemap; + }; + treemap.sticky = function(x) { + if (!arguments.length) return sticky; + sticky = x; + stickies = null; + return treemap; + }; + treemap.ratio = function(x) { + if (!arguments.length) return ratio; + ratio = x; + return treemap; + }; + treemap.mode = function(x) { + if (!arguments.length) return mode; + mode = x + ""; + return treemap; + }; + return d3_layout_hierarchyRebind(treemap, hierarchy); + }; + function d3_layout_treemapPadNull(node) { + return { + x: node.x, + y: node.y, + dx: node.dx, + dy: node.dy + }; + } + function d3_layout_treemapPad(node, padding) { + var x = node.x + padding[3], y = node.y + padding[0], dx = node.dx - padding[1] - padding[3], dy = node.dy - padding[0] - padding[2]; + if (dx < 0) { + x += dx / 2; + dx = 0; + } + if (dy < 0) { + y += dy / 2; + dy = 0; + } + return { + x: x, + y: y, + dx: dx, + dy: dy + }; + } + d3.random = { + normal: function(µ, σ) { + var n = arguments.length; + if (n < 2) σ = 1; + if (n < 1) µ = 0; + return function() { + var x, y, r; + do { + x = Math.random() * 2 - 1; + y = Math.random() * 2 - 1; + r = x * x + y * y; + } while (!r || r > 1); + return µ + σ * x * Math.sqrt(-2 * Math.log(r) / r); + }; + }, + logNormal: function() { + var random = d3.random.normal.apply(d3, arguments); + return function() { + return Math.exp(random()); + }; + }, + bates: function(m) { + var random = d3.random.irwinHall(m); + return function() { + return random() / m; + }; + }, + irwinHall: function(m) { + return function() { + for (var s = 0, j = 0; j < m; j++) s += Math.random(); + return s; + }; + } + }; + d3.scale = {}; + function d3_scaleExtent(domain) { + var start = domain[0], stop = domain[domain.length - 1]; + return start < stop ? [ start, stop ] : [ stop, start ]; + } + function d3_scaleRange(scale) { + return scale.rangeExtent ? scale.rangeExtent() : d3_scaleExtent(scale.range()); + } + function d3_scale_bilinear(domain, range, uninterpolate, interpolate) { + var u = uninterpolate(domain[0], domain[1]), i = interpolate(range[0], range[1]); + return function(x) { + return i(u(x)); + }; + } + function d3_scale_nice(domain, nice) { + var i0 = 0, i1 = domain.length - 1, x0 = domain[i0], x1 = domain[i1], dx; + if (x1 < x0) { + dx = i0, i0 = i1, i1 = dx; + dx = x0, x0 = x1, x1 = dx; + } + domain[i0] = nice.floor(x0); + domain[i1] = nice.ceil(x1); + return domain; + } + function d3_scale_niceStep(step) { + return step ? { + floor: function(x) { + return Math.floor(x / step) * step; + }, + ceil: function(x) { + return Math.ceil(x / step) * step; + } + } : d3_scale_niceIdentity; + } + var d3_scale_niceIdentity = { + floor: d3_identity, + ceil: d3_identity + }; + function d3_scale_polylinear(domain, range, uninterpolate, interpolate) { + var u = [], i = [], j = 0, k = Math.min(domain.length, range.length) - 1; + if (domain[k] < domain[0]) { + domain = domain.slice().reverse(); + range = range.slice().reverse(); + } + while (++j <= k) { + u.push(uninterpolate(domain[j - 1], domain[j])); + i.push(interpolate(range[j - 1], range[j])); + } + return function(x) { + var j = d3.bisect(domain, x, 1, k) - 1; + return i[j](u[j](x)); + }; + } + d3.scale.linear = function() { + return d3_scale_linear([ 0, 1 ], [ 0, 1 ], d3_interpolate, false); + }; + function d3_scale_linear(domain, range, interpolate, clamp) { + var output, input; + function rescale() { + var linear = Math.min(domain.length, range.length) > 2 ? d3_scale_polylinear : d3_scale_bilinear, uninterpolate = clamp ? d3_uninterpolateClamp : d3_uninterpolateNumber; + output = linear(domain, range, uninterpolate, interpolate); + input = linear(range, domain, uninterpolate, d3_interpolate); + return scale; + } + function scale(x) { + return output(x); + } + scale.invert = function(y) { + return input(y); + }; + scale.domain = function(x) { + if (!arguments.length) return domain; + domain = x.map(Number); + return rescale(); + }; + scale.range = function(x) { + if (!arguments.length) return range; + range = x; + return rescale(); + }; + scale.rangeRound = function(x) { + return scale.range(x).interpolate(d3_interpolateRound); + }; + scale.clamp = function(x) { + if (!arguments.length) return clamp; + clamp = x; + return rescale(); + }; + scale.interpolate = function(x) { + if (!arguments.length) return interpolate; + interpolate = x; + return rescale(); + }; + scale.ticks = function(m) { + return d3_scale_linearTicks(domain, m); + }; + scale.tickFormat = function(m, format) { + return d3_scale_linearTickFormat(domain, m, format); + }; + scale.nice = function(m) { + d3_scale_linearNice(domain, m); + return rescale(); + }; + scale.copy = function() { + return d3_scale_linear(domain, range, interpolate, clamp); + }; + return rescale(); + } + function d3_scale_linearRebind(scale, linear) { + return d3.rebind(scale, linear, "range", "rangeRound", "interpolate", "clamp"); + } + function d3_scale_linearNice(domain, m) { + return d3_scale_nice(domain, d3_scale_niceStep(d3_scale_linearTickRange(domain, m)[2])); + } + function d3_scale_linearTickRange(domain, m) { + if (m == null) m = 10; + var extent = d3_scaleExtent(domain), span = extent[1] - extent[0], step = Math.pow(10, Math.floor(Math.log(span / m) / Math.LN10)), err = m / span * step; + if (err <= .15) step *= 10; else if (err <= .35) step *= 5; else if (err <= .75) step *= 2; + extent[0] = Math.ceil(extent[0] / step) * step; + extent[1] = Math.floor(extent[1] / step) * step + step * .5; + extent[2] = step; + return extent; + } + function d3_scale_linearTicks(domain, m) { + return d3.range.apply(d3, d3_scale_linearTickRange(domain, m)); + } + function d3_scale_linearTickFormat(domain, m, format) { + var range = d3_scale_linearTickRange(domain, m); + if (format) { + var match = d3_format_re.exec(format); + match.shift(); + if (match[8] === "s") { + var prefix = d3.formatPrefix(Math.max(abs(range[0]), abs(range[1]))); + if (!match[7]) match[7] = "." + d3_scale_linearPrecision(prefix.scale(range[2])); + match[8] = "f"; + format = d3.format(match.join("")); + return function(d) { + return format(prefix.scale(d)) + prefix.symbol; + }; + } + if (!match[7]) match[7] = "." + d3_scale_linearFormatPrecision(match[8], range); + format = match.join(""); + } else { + format = ",." + d3_scale_linearPrecision(range[2]) + "f"; + } + return d3.format(format); + } + var d3_scale_linearFormatSignificant = { + s: 1, + g: 1, + p: 1, + r: 1, + e: 1 + }; + function d3_scale_linearPrecision(value) { + return -Math.floor(Math.log(value) / Math.LN10 + .01); + } + function d3_scale_linearFormatPrecision(type, range) { + var p = d3_scale_linearPrecision(range[2]); + return type in d3_scale_linearFormatSignificant ? Math.abs(p - d3_scale_linearPrecision(Math.max(abs(range[0]), abs(range[1])))) + +(type !== "e") : p - (type === "%") * 2; + } + d3.scale.log = function() { + return d3_scale_log(d3.scale.linear().domain([ 0, 1 ]), 10, true, [ 1, 10 ]); + }; + function d3_scale_log(linear, base, positive, domain) { + function log(x) { + return (positive ? Math.log(x < 0 ? 0 : x) : -Math.log(x > 0 ? 0 : -x)) / Math.log(base); + } + function pow(x) { + return positive ? Math.pow(base, x) : -Math.pow(base, -x); + } + function scale(x) { + return linear(log(x)); + } + scale.invert = function(x) { + return pow(linear.invert(x)); + }; + scale.domain = function(x) { + if (!arguments.length) return domain; + positive = x[0] >= 0; + linear.domain((domain = x.map(Number)).map(log)); + return scale; + }; + scale.base = function(_) { + if (!arguments.length) return base; + base = +_; + linear.domain(domain.map(log)); + return scale; + }; + scale.nice = function() { + var niced = d3_scale_nice(domain.map(log), positive ? Math : d3_scale_logNiceNegative); + linear.domain(niced); + domain = niced.map(pow); + return scale; + }; + scale.ticks = function() { + var extent = d3_scaleExtent(domain), ticks = [], u = extent[0], v = extent[1], i = Math.floor(log(u)), j = Math.ceil(log(v)), n = base % 1 ? 2 : base; + if (isFinite(j - i)) { + if (positive) { + for (;i < j; i++) for (var k = 1; k < n; k++) ticks.push(pow(i) * k); + ticks.push(pow(i)); + } else { + ticks.push(pow(i)); + for (;i++ < j; ) for (var k = n - 1; k > 0; k--) ticks.push(pow(i) * k); + } + for (i = 0; ticks[i] < u; i++) {} + for (j = ticks.length; ticks[j - 1] > v; j--) {} + ticks = ticks.slice(i, j); + } + return ticks; + }; + scale.tickFormat = function(n, format) { + if (!arguments.length) return d3_scale_logFormat; + if (arguments.length < 2) format = d3_scale_logFormat; else if (typeof format !== "function") format = d3.format(format); + var k = Math.max(.1, n / scale.ticks().length), f = positive ? (e = 1e-12, Math.ceil) : (e = -1e-12, + Math.floor), e; + return function(d) { + return d / pow(f(log(d) + e)) <= k ? format(d) : ""; + }; + }; + scale.copy = function() { + return d3_scale_log(linear.copy(), base, positive, domain); + }; + return d3_scale_linearRebind(scale, linear); + } + var d3_scale_logFormat = d3.format(".0e"), d3_scale_logNiceNegative = { + floor: function(x) { + return -Math.ceil(-x); + }, + ceil: function(x) { + return -Math.floor(-x); + } + }; + d3.scale.pow = function() { + return d3_scale_pow(d3.scale.linear(), 1, [ 0, 1 ]); + }; + function d3_scale_pow(linear, exponent, domain) { + var powp = d3_scale_powPow(exponent), powb = d3_scale_powPow(1 / exponent); + function scale(x) { + return linear(powp(x)); + } + scale.invert = function(x) { + return powb(linear.invert(x)); + }; + scale.domain = function(x) { + if (!arguments.length) return domain; + linear.domain((domain = x.map(Number)).map(powp)); + return scale; + }; + scale.ticks = function(m) { + return d3_scale_linearTicks(domain, m); + }; + scale.tickFormat = function(m, format) { + return d3_scale_linearTickFormat(domain, m, format); + }; + scale.nice = function(m) { + return scale.domain(d3_scale_linearNice(domain, m)); + }; + scale.exponent = function(x) { + if (!arguments.length) return exponent; + powp = d3_scale_powPow(exponent = x); + powb = d3_scale_powPow(1 / exponent); + linear.domain(domain.map(powp)); + return scale; + }; + scale.copy = function() { + return d3_scale_pow(linear.copy(), exponent, domain); + }; + return d3_scale_linearRebind(scale, linear); + } + function d3_scale_powPow(e) { + return function(x) { + return x < 0 ? -Math.pow(-x, e) : Math.pow(x, e); + }; + } + d3.scale.sqrt = function() { + return d3.scale.pow().exponent(.5); + }; + d3.scale.ordinal = function() { + return d3_scale_ordinal([], { + t: "range", + a: [ [] ] + }); + }; + function d3_scale_ordinal(domain, ranger) { + var index, range, rangeBand; + function scale(x) { + return range[((index.get(x) || (ranger.t === "range" ? index.set(x, domain.push(x)) : NaN)) - 1) % range.length]; + } + function steps(start, step) { + return d3.range(domain.length).map(function(i) { + return start + step * i; + }); + } + scale.domain = function(x) { + if (!arguments.length) return domain; + domain = []; + index = new d3_Map(); + var i = -1, n = x.length, xi; + while (++i < n) if (!index.has(xi = x[i])) index.set(xi, domain.push(xi)); + return scale[ranger.t].apply(scale, ranger.a); + }; + scale.range = function(x) { + if (!arguments.length) return range; + range = x; + rangeBand = 0; + ranger = { + t: "range", + a: arguments + }; + return scale; + }; + scale.rangePoints = function(x, padding) { + if (arguments.length < 2) padding = 0; + var start = x[0], stop = x[1], step = (stop - start) / (Math.max(1, domain.length - 1) + padding); + range = steps(domain.length < 2 ? (start + stop) / 2 : start + step * padding / 2, step); + rangeBand = 0; + ranger = { + t: "rangePoints", + a: arguments + }; + return scale; + }; + scale.rangeBands = function(x, padding, outerPadding) { + if (arguments.length < 2) padding = 0; + if (arguments.length < 3) outerPadding = padding; + var reverse = x[1] < x[0], start = x[reverse - 0], stop = x[1 - reverse], step = (stop - start) / (domain.length - padding + 2 * outerPadding); + range = steps(start + step * outerPadding, step); + if (reverse) range.reverse(); + rangeBand = step * (1 - padding); + ranger = { + t: "rangeBands", + a: arguments + }; + return scale; + }; + scale.rangeRoundBands = function(x, padding, outerPadding) { + if (arguments.length < 2) padding = 0; + if (arguments.length < 3) outerPadding = padding; + var reverse = x[1] < x[0], start = x[reverse - 0], stop = x[1 - reverse], step = Math.floor((stop - start) / (domain.length - padding + 2 * outerPadding)), error = stop - start - (domain.length - padding) * step; + range = steps(start + Math.round(error / 2), step); + if (reverse) range.reverse(); + rangeBand = Math.round(step * (1 - padding)); + ranger = { + t: "rangeRoundBands", + a: arguments + }; + return scale; + }; + scale.rangeBand = function() { + return rangeBand; + }; + scale.rangeExtent = function() { + return d3_scaleExtent(ranger.a[0]); + }; + scale.copy = function() { + return d3_scale_ordinal(domain, ranger); + }; + return scale.domain(domain); + } + d3.scale.category10 = function() { + return d3.scale.ordinal().range(d3_category10); + }; + d3.scale.category20 = function() { + return d3.scale.ordinal().range(d3_category20); + }; + d3.scale.category20b = function() { + return d3.scale.ordinal().range(d3_category20b); + }; + d3.scale.category20c = function() { + return d3.scale.ordinal().range(d3_category20c); + }; + var d3_category10 = [ 2062260, 16744206, 2924588, 14034728, 9725885, 9197131, 14907330, 8355711, 12369186, 1556175 ].map(d3_rgbString); + var d3_category20 = [ 2062260, 11454440, 16744206, 16759672, 2924588, 10018698, 14034728, 16750742, 9725885, 12955861, 9197131, 12885140, 14907330, 16234194, 8355711, 13092807, 12369186, 14408589, 1556175, 10410725 ].map(d3_rgbString); + var d3_category20b = [ 3750777, 5395619, 7040719, 10264286, 6519097, 9216594, 11915115, 13556636, 9202993, 12426809, 15186514, 15190932, 8666169, 11356490, 14049643, 15177372, 8077683, 10834324, 13528509, 14589654 ].map(d3_rgbString); + var d3_category20c = [ 3244733, 7057110, 10406625, 13032431, 15095053, 16616764, 16625259, 16634018, 3253076, 7652470, 10607003, 13101504, 7695281, 10394312, 12369372, 14342891, 6513507, 9868950, 12434877, 14277081 ].map(d3_rgbString); + d3.scale.quantile = function() { + return d3_scale_quantile([], []); + }; + function d3_scale_quantile(domain, range) { + var thresholds; + function rescale() { + var k = 0, q = range.length; + thresholds = []; + while (++k < q) thresholds[k - 1] = d3.quantile(domain, k / q); + return scale; + } + function scale(x) { + if (!isNaN(x = +x)) return range[d3.bisect(thresholds, x)]; + } + scale.domain = function(x) { + if (!arguments.length) return domain; + domain = x.filter(d3_number).sort(d3_ascending); + return rescale(); + }; + scale.range = function(x) { + if (!arguments.length) return range; + range = x; + return rescale(); + }; + scale.quantiles = function() { + return thresholds; + }; + scale.invertExtent = function(y) { + y = range.indexOf(y); + return y < 0 ? [ NaN, NaN ] : [ y > 0 ? thresholds[y - 1] : domain[0], y < thresholds.length ? thresholds[y] : domain[domain.length - 1] ]; + }; + scale.copy = function() { + return d3_scale_quantile(domain, range); + }; + return rescale(); + } + d3.scale.quantize = function() { + return d3_scale_quantize(0, 1, [ 0, 1 ]); + }; + function d3_scale_quantize(x0, x1, range) { + var kx, i; + function scale(x) { + return range[Math.max(0, Math.min(i, Math.floor(kx * (x - x0))))]; + } + function rescale() { + kx = range.length / (x1 - x0); + i = range.length - 1; + return scale; + } + scale.domain = function(x) { + if (!arguments.length) return [ x0, x1 ]; + x0 = +x[0]; + x1 = +x[x.length - 1]; + return rescale(); + }; + scale.range = function(x) { + if (!arguments.length) return range; + range = x; + return rescale(); + }; + scale.invertExtent = function(y) { + y = range.indexOf(y); + y = y < 0 ? NaN : y / kx + x0; + return [ y, y + 1 / kx ]; + }; + scale.copy = function() { + return d3_scale_quantize(x0, x1, range); + }; + return rescale(); + } + d3.scale.threshold = function() { + return d3_scale_threshold([ .5 ], [ 0, 1 ]); + }; + function d3_scale_threshold(domain, range) { + function scale(x) { + if (x <= x) return range[d3.bisect(domain, x)]; + } + scale.domain = function(_) { + if (!arguments.length) return domain; + domain = _; + return scale; + }; + scale.range = function(_) { + if (!arguments.length) return range; + range = _; + return scale; + }; + scale.invertExtent = function(y) { + y = range.indexOf(y); + return [ domain[y - 1], domain[y] ]; + }; + scale.copy = function() { + return d3_scale_threshold(domain, range); + }; + return scale; + } + d3.scale.identity = function() { + return d3_scale_identity([ 0, 1 ]); + }; + function d3_scale_identity(domain) { + function identity(x) { + return +x; + } + identity.invert = identity; + identity.domain = identity.range = function(x) { + if (!arguments.length) return domain; + domain = x.map(identity); + return identity; + }; + identity.ticks = function(m) { + return d3_scale_linearTicks(domain, m); + }; + identity.tickFormat = function(m, format) { + return d3_scale_linearTickFormat(domain, m, format); + }; + identity.copy = function() { + return d3_scale_identity(domain); + }; + return identity; + } + d3.svg = {}; + d3.svg.arc = function() { + var innerRadius = d3_svg_arcInnerRadius, outerRadius = d3_svg_arcOuterRadius, startAngle = d3_svg_arcStartAngle, endAngle = d3_svg_arcEndAngle; + function arc() { + var r0 = innerRadius.apply(this, arguments), r1 = outerRadius.apply(this, arguments), a0 = startAngle.apply(this, arguments) + d3_svg_arcOffset, a1 = endAngle.apply(this, arguments) + d3_svg_arcOffset, da = (a1 < a0 && (da = a0, + a0 = a1, a1 = da), a1 - a0), df = da < π ? "0" : "1", c0 = Math.cos(a0), s0 = Math.sin(a0), c1 = Math.cos(a1), s1 = Math.sin(a1); + return da >= d3_svg_arcMax ? r0 ? "M0," + r1 + "A" + r1 + "," + r1 + " 0 1,1 0," + -r1 + "A" + r1 + "," + r1 + " 0 1,1 0," + r1 + "M0," + r0 + "A" + r0 + "," + r0 + " 0 1,0 0," + -r0 + "A" + r0 + "," + r0 + " 0 1,0 0," + r0 + "Z" : "M0," + r1 + "A" + r1 + "," + r1 + " 0 1,1 0," + -r1 + "A" + r1 + "," + r1 + " 0 1,1 0," + r1 + "Z" : r0 ? "M" + r1 * c0 + "," + r1 * s0 + "A" + r1 + "," + r1 + " 0 " + df + ",1 " + r1 * c1 + "," + r1 * s1 + "L" + r0 * c1 + "," + r0 * s1 + "A" + r0 + "," + r0 + " 0 " + df + ",0 " + r0 * c0 + "," + r0 * s0 + "Z" : "M" + r1 * c0 + "," + r1 * s0 + "A" + r1 + "," + r1 + " 0 " + df + ",1 " + r1 * c1 + "," + r1 * s1 + "L0,0" + "Z"; + } + arc.innerRadius = function(v) { + if (!arguments.length) return innerRadius; + innerRadius = d3_functor(v); + return arc; + }; + arc.outerRadius = function(v) { + if (!arguments.length) return outerRadius; + outerRadius = d3_functor(v); + return arc; + }; + arc.startAngle = function(v) { + if (!arguments.length) return startAngle; + startAngle = d3_functor(v); + return arc; + }; + arc.endAngle = function(v) { + if (!arguments.length) return endAngle; + endAngle = d3_functor(v); + return arc; + }; + arc.centroid = function() { + var r = (innerRadius.apply(this, arguments) + outerRadius.apply(this, arguments)) / 2, a = (startAngle.apply(this, arguments) + endAngle.apply(this, arguments)) / 2 + d3_svg_arcOffset; + return [ Math.cos(a) * r, Math.sin(a) * r ]; + }; + return arc; + }; + var d3_svg_arcOffset = -halfπ, d3_svg_arcMax = τ - ε; + function d3_svg_arcInnerRadius(d) { + return d.innerRadius; + } + function d3_svg_arcOuterRadius(d) { + return d.outerRadius; + } + function d3_svg_arcStartAngle(d) { + return d.startAngle; + } + function d3_svg_arcEndAngle(d) { + return d.endAngle; + } + function d3_svg_line(projection) { + var x = d3_geom_pointX, y = d3_geom_pointY, defined = d3_true, interpolate = d3_svg_lineLinear, interpolateKey = interpolate.key, tension = .7; + function line(data) { + var segments = [], points = [], i = -1, n = data.length, d, fx = d3_functor(x), fy = d3_functor(y); + function segment() { + segments.push("M", interpolate(projection(points), tension)); + } + while (++i < n) { + if (defined.call(this, d = data[i], i)) { + points.push([ +fx.call(this, d, i), +fy.call(this, d, i) ]); + } else if (points.length) { + segment(); + points = []; + } + } + if (points.length) segment(); + return segments.length ? segments.join("") : null; + } + line.x = function(_) { + if (!arguments.length) return x; + x = _; + return line; + }; + line.y = function(_) { + if (!arguments.length) return y; + y = _; + return line; + }; + line.defined = function(_) { + if (!arguments.length) return defined; + defined = _; + return line; + }; + line.interpolate = function(_) { + if (!arguments.length) return interpolateKey; + if (typeof _ === "function") interpolateKey = interpolate = _; else interpolateKey = (interpolate = d3_svg_lineInterpolators.get(_) || d3_svg_lineLinear).key; + return line; + }; + line.tension = function(_) { + if (!arguments.length) return tension; + tension = _; + return line; + }; + return line; + } + d3.svg.line = function() { + return d3_svg_line(d3_identity); + }; + var d3_svg_lineInterpolators = d3.map({ + linear: d3_svg_lineLinear, + "linear-closed": d3_svg_lineLinearClosed, + step: d3_svg_lineStep, + "step-before": d3_svg_lineStepBefore, + "step-after": d3_svg_lineStepAfter, + basis: d3_svg_lineBasis, + "basis-open": d3_svg_lineBasisOpen, + "basis-closed": d3_svg_lineBasisClosed, + bundle: d3_svg_lineBundle, + cardinal: d3_svg_lineCardinal, + "cardinal-open": d3_svg_lineCardinalOpen, + "cardinal-closed": d3_svg_lineCardinalClosed, + monotone: d3_svg_lineMonotone + }); + d3_svg_lineInterpolators.forEach(function(key, value) { + value.key = key; + value.closed = /-closed$/.test(key); + }); + function d3_svg_lineLinear(points) { + return points.join("L"); + } + function d3_svg_lineLinearClosed(points) { + return d3_svg_lineLinear(points) + "Z"; + } + function d3_svg_lineStep(points) { + var i = 0, n = points.length, p = points[0], path = [ p[0], ",", p[1] ]; + while (++i < n) path.push("H", (p[0] + (p = points[i])[0]) / 2, "V", p[1]); + if (n > 1) path.push("H", p[0]); + return path.join(""); + } + function d3_svg_lineStepBefore(points) { + var i = 0, n = points.length, p = points[0], path = [ p[0], ",", p[1] ]; + while (++i < n) path.push("V", (p = points[i])[1], "H", p[0]); + return path.join(""); + } + function d3_svg_lineStepAfter(points) { + var i = 0, n = points.length, p = points[0], path = [ p[0], ",", p[1] ]; + while (++i < n) path.push("H", (p = points[i])[0], "V", p[1]); + return path.join(""); + } + function d3_svg_lineCardinalOpen(points, tension) { + return points.length < 4 ? d3_svg_lineLinear(points) : points[1] + d3_svg_lineHermite(points.slice(1, points.length - 1), d3_svg_lineCardinalTangents(points, tension)); + } + function d3_svg_lineCardinalClosed(points, tension) { + return points.length < 3 ? d3_svg_lineLinear(points) : points[0] + d3_svg_lineHermite((points.push(points[0]), + points), d3_svg_lineCardinalTangents([ points[points.length - 2] ].concat(points, [ points[1] ]), tension)); + } + function d3_svg_lineCardinal(points, tension) { + return points.length < 3 ? d3_svg_lineLinear(points) : points[0] + d3_svg_lineHermite(points, d3_svg_lineCardinalTangents(points, tension)); + } + function d3_svg_lineHermite(points, tangents) { + if (tangents.length < 1 || points.length != tangents.length && points.length != tangents.length + 2) { + return d3_svg_lineLinear(points); + } + var quad = points.length != tangents.length, path = "", p0 = points[0], p = points[1], t0 = tangents[0], t = t0, pi = 1; + if (quad) { + path += "Q" + (p[0] - t0[0] * 2 / 3) + "," + (p[1] - t0[1] * 2 / 3) + "," + p[0] + "," + p[1]; + p0 = points[1]; + pi = 2; + } + if (tangents.length > 1) { + t = tangents[1]; + p = points[pi]; + pi++; + path += "C" + (p0[0] + t0[0]) + "," + (p0[1] + t0[1]) + "," + (p[0] - t[0]) + "," + (p[1] - t[1]) + "," + p[0] + "," + p[1]; + for (var i = 2; i < tangents.length; i++, pi++) { + p = points[pi]; + t = tangents[i]; + path += "S" + (p[0] - t[0]) + "," + (p[1] - t[1]) + "," + p[0] + "," + p[1]; + } + } + if (quad) { + var lp = points[pi]; + path += "Q" + (p[0] + t[0] * 2 / 3) + "," + (p[1] + t[1] * 2 / 3) + "," + lp[0] + "," + lp[1]; + } + return path; + } + function d3_svg_lineCardinalTangents(points, tension) { + var tangents = [], a = (1 - tension) / 2, p0, p1 = points[0], p2 = points[1], i = 1, n = points.length; + while (++i < n) { + p0 = p1; + p1 = p2; + p2 = points[i]; + tangents.push([ a * (p2[0] - p0[0]), a * (p2[1] - p0[1]) ]); + } + return tangents; + } + function d3_svg_lineBasis(points) { + if (points.length < 3) return d3_svg_lineLinear(points); + var i = 1, n = points.length, pi = points[0], x0 = pi[0], y0 = pi[1], px = [ x0, x0, x0, (pi = points[1])[0] ], py = [ y0, y0, y0, pi[1] ], path = [ x0, ",", y0, "L", d3_svg_lineDot4(d3_svg_lineBasisBezier3, px), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier3, py) ]; + points.push(points[n - 1]); + while (++i <= n) { + pi = points[i]; + px.shift(); + px.push(pi[0]); + py.shift(); + py.push(pi[1]); + d3_svg_lineBasisBezier(path, px, py); + } + points.pop(); + path.push("L", pi); + return path.join(""); + } + function d3_svg_lineBasisOpen(points) { + if (points.length < 4) return d3_svg_lineLinear(points); + var path = [], i = -1, n = points.length, pi, px = [ 0 ], py = [ 0 ]; + while (++i < 3) { + pi = points[i]; + px.push(pi[0]); + py.push(pi[1]); + } + path.push(d3_svg_lineDot4(d3_svg_lineBasisBezier3, px) + "," + d3_svg_lineDot4(d3_svg_lineBasisBezier3, py)); + --i; + while (++i < n) { + pi = points[i]; + px.shift(); + px.push(pi[0]); + py.shift(); + py.push(pi[1]); + d3_svg_lineBasisBezier(path, px, py); + } + return path.join(""); + } + function d3_svg_lineBasisClosed(points) { + var path, i = -1, n = points.length, m = n + 4, pi, px = [], py = []; + while (++i < 4) { + pi = points[i % n]; + px.push(pi[0]); + py.push(pi[1]); + } + path = [ d3_svg_lineDot4(d3_svg_lineBasisBezier3, px), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier3, py) ]; + --i; + while (++i < m) { + pi = points[i % n]; + px.shift(); + px.push(pi[0]); + py.shift(); + py.push(pi[1]); + d3_svg_lineBasisBezier(path, px, py); + } + return path.join(""); + } + function d3_svg_lineBundle(points, tension) { + var n = points.length - 1; + if (n) { + var x0 = points[0][0], y0 = points[0][1], dx = points[n][0] - x0, dy = points[n][1] - y0, i = -1, p, t; + while (++i <= n) { + p = points[i]; + t = i / n; + p[0] = tension * p[0] + (1 - tension) * (x0 + t * dx); + p[1] = tension * p[1] + (1 - tension) * (y0 + t * dy); + } + } + return d3_svg_lineBasis(points); + } + function d3_svg_lineDot4(a, b) { + return a[0] * b[0] + a[1] * b[1] + a[2] * b[2] + a[3] * b[3]; + } + var d3_svg_lineBasisBezier1 = [ 0, 2 / 3, 1 / 3, 0 ], d3_svg_lineBasisBezier2 = [ 0, 1 / 3, 2 / 3, 0 ], d3_svg_lineBasisBezier3 = [ 0, 1 / 6, 2 / 3, 1 / 6 ]; + function d3_svg_lineBasisBezier(path, x, y) { + path.push("C", d3_svg_lineDot4(d3_svg_lineBasisBezier1, x), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier1, y), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier2, x), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier2, y), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier3, x), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier3, y)); + } + function d3_svg_lineSlope(p0, p1) { + return (p1[1] - p0[1]) / (p1[0] - p0[0]); + } + function d3_svg_lineFiniteDifferences(points) { + var i = 0, j = points.length - 1, m = [], p0 = points[0], p1 = points[1], d = m[0] = d3_svg_lineSlope(p0, p1); + while (++i < j) { + m[i] = (d + (d = d3_svg_lineSlope(p0 = p1, p1 = points[i + 1]))) / 2; + } + m[i] = d; + return m; + } + function d3_svg_lineMonotoneTangents(points) { + var tangents = [], d, a, b, s, m = d3_svg_lineFiniteDifferences(points), i = -1, j = points.length - 1; + while (++i < j) { + d = d3_svg_lineSlope(points[i], points[i + 1]); + if (abs(d) < ε) { + m[i] = m[i + 1] = 0; + } else { + a = m[i] / d; + b = m[i + 1] / d; + s = a * a + b * b; + if (s > 9) { + s = d * 3 / Math.sqrt(s); + m[i] = s * a; + m[i + 1] = s * b; + } + } + } + i = -1; + while (++i <= j) { + s = (points[Math.min(j, i + 1)][0] - points[Math.max(0, i - 1)][0]) / (6 * (1 + m[i] * m[i])); + tangents.push([ s || 0, m[i] * s || 0 ]); + } + return tangents; + } + function d3_svg_lineMonotone(points) { + return points.length < 3 ? d3_svg_lineLinear(points) : points[0] + d3_svg_lineHermite(points, d3_svg_lineMonotoneTangents(points)); + } + d3.svg.line.radial = function() { + var line = d3_svg_line(d3_svg_lineRadial); + line.radius = line.x, delete line.x; + line.angle = line.y, delete line.y; + return line; + }; + function d3_svg_lineRadial(points) { + var point, i = -1, n = points.length, r, a; + while (++i < n) { + point = points[i]; + r = point[0]; + a = point[1] + d3_svg_arcOffset; + point[0] = r * Math.cos(a); + point[1] = r * Math.sin(a); + } + return points; + } + function d3_svg_area(projection) { + var x0 = d3_geom_pointX, x1 = d3_geom_pointX, y0 = 0, y1 = d3_geom_pointY, defined = d3_true, interpolate = d3_svg_lineLinear, interpolateKey = interpolate.key, interpolateReverse = interpolate, L = "L", tension = .7; + function area(data) { + var segments = [], points0 = [], points1 = [], i = -1, n = data.length, d, fx0 = d3_functor(x0), fy0 = d3_functor(y0), fx1 = x0 === x1 ? function() { + return x; + } : d3_functor(x1), fy1 = y0 === y1 ? function() { + return y; + } : d3_functor(y1), x, y; + function segment() { + segments.push("M", interpolate(projection(points1), tension), L, interpolateReverse(projection(points0.reverse()), tension), "Z"); + } + while (++i < n) { + if (defined.call(this, d = data[i], i)) { + points0.push([ x = +fx0.call(this, d, i), y = +fy0.call(this, d, i) ]); + points1.push([ +fx1.call(this, d, i), +fy1.call(this, d, i) ]); + } else if (points0.length) { + segment(); + points0 = []; + points1 = []; + } + } + if (points0.length) segment(); + return segments.length ? segments.join("") : null; + } + area.x = function(_) { + if (!arguments.length) return x1; + x0 = x1 = _; + return area; + }; + area.x0 = function(_) { + if (!arguments.length) return x0; + x0 = _; + return area; + }; + area.x1 = function(_) { + if (!arguments.length) return x1; + x1 = _; + return area; + }; + area.y = function(_) { + if (!arguments.length) return y1; + y0 = y1 = _; + return area; + }; + area.y0 = function(_) { + if (!arguments.length) return y0; + y0 = _; + return area; + }; + area.y1 = function(_) { + if (!arguments.length) return y1; + y1 = _; + return area; + }; + area.defined = function(_) { + if (!arguments.length) return defined; + defined = _; + return area; + }; + area.interpolate = function(_) { + if (!arguments.length) return interpolateKey; + if (typeof _ === "function") interpolateKey = interpolate = _; else interpolateKey = (interpolate = d3_svg_lineInterpolators.get(_) || d3_svg_lineLinear).key; + interpolateReverse = interpolate.reverse || interpolate; + L = interpolate.closed ? "M" : "L"; + return area; + }; + area.tension = function(_) { + if (!arguments.length) return tension; + tension = _; + return area; + }; + return area; + } + d3_svg_lineStepBefore.reverse = d3_svg_lineStepAfter; + d3_svg_lineStepAfter.reverse = d3_svg_lineStepBefore; + d3.svg.area = function() { + return d3_svg_area(d3_identity); + }; + d3.svg.area.radial = function() { + var area = d3_svg_area(d3_svg_lineRadial); + area.radius = area.x, delete area.x; + area.innerRadius = area.x0, delete area.x0; + area.outerRadius = area.x1, delete area.x1; + area.angle = area.y, delete area.y; + area.startAngle = area.y0, delete area.y0; + area.endAngle = area.y1, delete area.y1; + return area; + }; + d3.svg.chord = function() { + var source = d3_source, target = d3_target, radius = d3_svg_chordRadius, startAngle = d3_svg_arcStartAngle, endAngle = d3_svg_arcEndAngle; + function chord(d, i) { + var s = subgroup(this, source, d, i), t = subgroup(this, target, d, i); + return "M" + s.p0 + arc(s.r, s.p1, s.a1 - s.a0) + (equals(s, t) ? curve(s.r, s.p1, s.r, s.p0) : curve(s.r, s.p1, t.r, t.p0) + arc(t.r, t.p1, t.a1 - t.a0) + curve(t.r, t.p1, s.r, s.p0)) + "Z"; + } + function subgroup(self, f, d, i) { + var subgroup = f.call(self, d, i), r = radius.call(self, subgroup, i), a0 = startAngle.call(self, subgroup, i) + d3_svg_arcOffset, a1 = endAngle.call(self, subgroup, i) + d3_svg_arcOffset; + return { + r: r, + a0: a0, + a1: a1, + p0: [ r * Math.cos(a0), r * Math.sin(a0) ], + p1: [ r * Math.cos(a1), r * Math.sin(a1) ] + }; + } + function equals(a, b) { + return a.a0 == b.a0 && a.a1 == b.a1; + } + function arc(r, p, a) { + return "A" + r + "," + r + " 0 " + +(a > π) + ",1 " + p; + } + function curve(r0, p0, r1, p1) { + return "Q 0,0 " + p1; + } + chord.radius = function(v) { + if (!arguments.length) return radius; + radius = d3_functor(v); + return chord; + }; + chord.source = function(v) { + if (!arguments.length) return source; + source = d3_functor(v); + return chord; + }; + chord.target = function(v) { + if (!arguments.length) return target; + target = d3_functor(v); + return chord; + }; + chord.startAngle = function(v) { + if (!arguments.length) return startAngle; + startAngle = d3_functor(v); + return chord; + }; + chord.endAngle = function(v) { + if (!arguments.length) return endAngle; + endAngle = d3_functor(v); + return chord; + }; + return chord; + }; + function d3_svg_chordRadius(d) { + return d.radius; + } + d3.svg.diagonal = function() { + var source = d3_source, target = d3_target, projection = d3_svg_diagonalProjection; + function diagonal(d, i) { + var p0 = source.call(this, d, i), p3 = target.call(this, d, i), m = (p0.y + p3.y) / 2, p = [ p0, { + x: p0.x, + y: m + }, { + x: p3.x, + y: m + }, p3 ]; + p = p.map(projection); + return "M" + p[0] + "C" + p[1] + " " + p[2] + " " + p[3]; + } + diagonal.source = function(x) { + if (!arguments.length) return source; + source = d3_functor(x); + return diagonal; + }; + diagonal.target = function(x) { + if (!arguments.length) return target; + target = d3_functor(x); + return diagonal; + }; + diagonal.projection = function(x) { + if (!arguments.length) return projection; + projection = x; + return diagonal; + }; + return diagonal; + }; + function d3_svg_diagonalProjection(d) { + return [ d.x, d.y ]; + } + d3.svg.diagonal.radial = function() { + var diagonal = d3.svg.diagonal(), projection = d3_svg_diagonalProjection, projection_ = diagonal.projection; + diagonal.projection = function(x) { + return arguments.length ? projection_(d3_svg_diagonalRadialProjection(projection = x)) : projection; + }; + return diagonal; + }; + function d3_svg_diagonalRadialProjection(projection) { + return function() { + var d = projection.apply(this, arguments), r = d[0], a = d[1] + d3_svg_arcOffset; + return [ r * Math.cos(a), r * Math.sin(a) ]; + }; + } + d3.svg.symbol = function() { + var type = d3_svg_symbolType, size = d3_svg_symbolSize; + function symbol(d, i) { + return (d3_svg_symbols.get(type.call(this, d, i)) || d3_svg_symbolCircle)(size.call(this, d, i)); + } + symbol.type = function(x) { + if (!arguments.length) return type; + type = d3_functor(x); + return symbol; + }; + symbol.size = function(x) { + if (!arguments.length) return size; + size = d3_functor(x); + return symbol; + }; + return symbol; + }; + function d3_svg_symbolSize() { + return 64; + } + function d3_svg_symbolType() { + return "circle"; + } + function d3_svg_symbolCircle(size) { + var r = Math.sqrt(size / π); + return "M0," + r + "A" + r + "," + r + " 0 1,1 0," + -r + "A" + r + "," + r + " 0 1,1 0," + r + "Z"; + } + var d3_svg_symbols = d3.map({ + circle: d3_svg_symbolCircle, + cross: function(size) { + var r = Math.sqrt(size / 5) / 2; + return "M" + -3 * r + "," + -r + "H" + -r + "V" + -3 * r + "H" + r + "V" + -r + "H" + 3 * r + "V" + r + "H" + r + "V" + 3 * r + "H" + -r + "V" + r + "H" + -3 * r + "Z"; + }, + diamond: function(size) { + var ry = Math.sqrt(size / (2 * d3_svg_symbolTan30)), rx = ry * d3_svg_symbolTan30; + return "M0," + -ry + "L" + rx + ",0" + " 0," + ry + " " + -rx + ",0" + "Z"; + }, + square: function(size) { + var r = Math.sqrt(size) / 2; + return "M" + -r + "," + -r + "L" + r + "," + -r + " " + r + "," + r + " " + -r + "," + r + "Z"; + }, + "triangle-down": function(size) { + var rx = Math.sqrt(size / d3_svg_symbolSqrt3), ry = rx * d3_svg_symbolSqrt3 / 2; + return "M0," + ry + "L" + rx + "," + -ry + " " + -rx + "," + -ry + "Z"; + }, + "triangle-up": function(size) { + var rx = Math.sqrt(size / d3_svg_symbolSqrt3), ry = rx * d3_svg_symbolSqrt3 / 2; + return "M0," + -ry + "L" + rx + "," + ry + " " + -rx + "," + ry + "Z"; + } + }); + d3.svg.symbolTypes = d3_svg_symbols.keys(); + var d3_svg_symbolSqrt3 = Math.sqrt(3), d3_svg_symbolTan30 = Math.tan(30 * d3_radians); + function d3_transition(groups, id) { + d3_subclass(groups, d3_transitionPrototype); + groups.id = id; + return groups; + } + var d3_transitionPrototype = [], d3_transitionId = 0, d3_transitionInheritId, d3_transitionInherit; + d3_transitionPrototype.call = d3_selectionPrototype.call; + d3_transitionPrototype.empty = d3_selectionPrototype.empty; + d3_transitionPrototype.node = d3_selectionPrototype.node; + d3_transitionPrototype.size = d3_selectionPrototype.size; + d3.transition = function(selection) { + return arguments.length ? d3_transitionInheritId ? selection.transition() : selection : d3_selectionRoot.transition(); + }; + d3.transition.prototype = d3_transitionPrototype; + d3_transitionPrototype.select = function(selector) { + var id = this.id, subgroups = [], subgroup, subnode, node; + selector = d3_selection_selector(selector); + for (var j = -1, m = this.length; ++j < m; ) { + subgroups.push(subgroup = []); + for (var group = this[j], i = -1, n = group.length; ++i < n; ) { + if ((node = group[i]) && (subnode = selector.call(node, node.__data__, i, j))) { + if ("__data__" in node) subnode.__data__ = node.__data__; + d3_transitionNode(subnode, i, id, node.__transition__[id]); + subgroup.push(subnode); + } else { + subgroup.push(null); + } + } + } + return d3_transition(subgroups, id); + }; + d3_transitionPrototype.selectAll = function(selector) { + var id = this.id, subgroups = [], subgroup, subnodes, node, subnode, transition; + selector = d3_selection_selectorAll(selector); + for (var j = -1, m = this.length; ++j < m; ) { + for (var group = this[j], i = -1, n = group.length; ++i < n; ) { + if (node = group[i]) { + transition = node.__transition__[id]; + subnodes = selector.call(node, node.__data__, i, j); + subgroups.push(subgroup = []); + for (var k = -1, o = subnodes.length; ++k < o; ) { + if (subnode = subnodes[k]) d3_transitionNode(subnode, k, id, transition); + subgroup.push(subnode); + } + } + } + } + return d3_transition(subgroups, id); + }; + d3_transitionPrototype.filter = function(filter) { + var subgroups = [], subgroup, group, node; + if (typeof filter !== "function") filter = d3_selection_filter(filter); + for (var j = 0, m = this.length; j < m; j++) { + subgroups.push(subgroup = []); + for (var group = this[j], i = 0, n = group.length; i < n; i++) { + if ((node = group[i]) && filter.call(node, node.__data__, i, j)) { + subgroup.push(node); + } + } + } + return d3_transition(subgroups, this.id); + }; + d3_transitionPrototype.tween = function(name, tween) { + var id = this.id; + if (arguments.length < 2) return this.node().__transition__[id].tween.get(name); + return d3_selection_each(this, tween == null ? function(node) { + node.__transition__[id].tween.remove(name); + } : function(node) { + node.__transition__[id].tween.set(name, tween); + }); + }; + function d3_transition_tween(groups, name, value, tween) { + var id = groups.id; + return d3_selection_each(groups, typeof value === "function" ? function(node, i, j) { + node.__transition__[id].tween.set(name, tween(value.call(node, node.__data__, i, j))); + } : (value = tween(value), function(node) { + node.__transition__[id].tween.set(name, value); + })); + } + d3_transitionPrototype.attr = function(nameNS, value) { + if (arguments.length < 2) { + for (value in nameNS) this.attr(value, nameNS[value]); + return this; + } + var interpolate = nameNS == "transform" ? d3_interpolateTransform : d3_interpolate, name = d3.ns.qualify(nameNS); + function attrNull() { + this.removeAttribute(name); + } + function attrNullNS() { + this.removeAttributeNS(name.space, name.local); + } + function attrTween(b) { + return b == null ? attrNull : (b += "", function() { + var a = this.getAttribute(name), i; + return a !== b && (i = interpolate(a, b), function(t) { + this.setAttribute(name, i(t)); + }); + }); + } + function attrTweenNS(b) { + return b == null ? attrNullNS : (b += "", function() { + var a = this.getAttributeNS(name.space, name.local), i; + return a !== b && (i = interpolate(a, b), function(t) { + this.setAttributeNS(name.space, name.local, i(t)); + }); + }); + } + return d3_transition_tween(this, "attr." + nameNS, value, name.local ? attrTweenNS : attrTween); + }; + d3_transitionPrototype.attrTween = function(nameNS, tween) { + var name = d3.ns.qualify(nameNS); + function attrTween(d, i) { + var f = tween.call(this, d, i, this.getAttribute(name)); + return f && function(t) { + this.setAttribute(name, f(t)); + }; + } + function attrTweenNS(d, i) { + var f = tween.call(this, d, i, this.getAttributeNS(name.space, name.local)); + return f && function(t) { + this.setAttributeNS(name.space, name.local, f(t)); + }; + } + return this.tween("attr." + nameNS, name.local ? attrTweenNS : attrTween); + }; + d3_transitionPrototype.style = function(name, value, priority) { + var n = arguments.length; + if (n < 3) { + if (typeof name !== "string") { + if (n < 2) value = ""; + for (priority in name) this.style(priority, name[priority], value); + return this; + } + priority = ""; + } + function styleNull() { + this.style.removeProperty(name); + } + function styleString(b) { + return b == null ? styleNull : (b += "", function() { + var a = d3_window.getComputedStyle(this, null).getPropertyValue(name), i; + return a !== b && (i = d3_interpolate(a, b), function(t) { + this.style.setProperty(name, i(t), priority); + }); + }); + } + return d3_transition_tween(this, "style." + name, value, styleString); + }; + d3_transitionPrototype.styleTween = function(name, tween, priority) { + if (arguments.length < 3) priority = ""; + function styleTween(d, i) { + var f = tween.call(this, d, i, d3_window.getComputedStyle(this, null).getPropertyValue(name)); + return f && function(t) { + this.style.setProperty(name, f(t), priority); + }; + } + return this.tween("style." + name, styleTween); + }; + d3_transitionPrototype.text = function(value) { + return d3_transition_tween(this, "text", value, d3_transition_text); + }; + function d3_transition_text(b) { + if (b == null) b = ""; + return function() { + this.textContent = b; + }; + } + d3_transitionPrototype.remove = function() { + return this.each("end.transition", function() { + var p; + if (this.__transition__.count < 2 && (p = this.parentNode)) p.removeChild(this); + }); + }; + d3_transitionPrototype.ease = function(value) { + var id = this.id; + if (arguments.length < 1) return this.node().__transition__[id].ease; + if (typeof value !== "function") value = d3.ease.apply(d3, arguments); + return d3_selection_each(this, function(node) { + node.__transition__[id].ease = value; + }); + }; + d3_transitionPrototype.delay = function(value) { + var id = this.id; + if (arguments.length < 1) return this.node().__transition__[id].delay; + return d3_selection_each(this, typeof value === "function" ? function(node, i, j) { + node.__transition__[id].delay = +value.call(node, node.__data__, i, j); + } : (value = +value, function(node) { + node.__transition__[id].delay = value; + })); + }; + d3_transitionPrototype.duration = function(value) { + var id = this.id; + if (arguments.length < 1) return this.node().__transition__[id].duration; + return d3_selection_each(this, typeof value === "function" ? function(node, i, j) { + node.__transition__[id].duration = Math.max(1, value.call(node, node.__data__, i, j)); + } : (value = Math.max(1, value), function(node) { + node.__transition__[id].duration = value; + })); + }; + d3_transitionPrototype.each = function(type, listener) { + var id = this.id; + if (arguments.length < 2) { + var inherit = d3_transitionInherit, inheritId = d3_transitionInheritId; + d3_transitionInheritId = id; + d3_selection_each(this, function(node, i, j) { + d3_transitionInherit = node.__transition__[id]; + type.call(node, node.__data__, i, j); + }); + d3_transitionInherit = inherit; + d3_transitionInheritId = inheritId; + } else { + d3_selection_each(this, function(node) { + var transition = node.__transition__[id]; + (transition.event || (transition.event = d3.dispatch("start", "end"))).on(type, listener); + }); + } + return this; + }; + d3_transitionPrototype.transition = function() { + var id0 = this.id, id1 = ++d3_transitionId, subgroups = [], subgroup, group, node, transition; + for (var j = 0, m = this.length; j < m; j++) { + subgroups.push(subgroup = []); + for (var group = this[j], i = 0, n = group.length; i < n; i++) { + if (node = group[i]) { + transition = Object.create(node.__transition__[id0]); + transition.delay += transition.duration; + d3_transitionNode(node, i, id1, transition); + } + subgroup.push(node); + } + } + return d3_transition(subgroups, id1); + }; + function d3_transitionNode(node, i, id, inherit) { + var lock = node.__transition__ || (node.__transition__ = { + active: 0, + count: 0 + }), transition = lock[id]; + if (!transition) { + var time = inherit.time; + transition = lock[id] = { + tween: new d3_Map(), + time: time, + ease: inherit.ease, + delay: inherit.delay, + duration: inherit.duration + }; + ++lock.count; + d3.timer(function(elapsed) { + var d = node.__data__, ease = transition.ease, delay = transition.delay, duration = transition.duration, timer = d3_timer_active, tweened = []; + timer.t = delay + time; + if (delay <= elapsed) return start(elapsed - delay); + timer.c = start; + function start(elapsed) { + if (lock.active > id) return stop(); + lock.active = id; + transition.event && transition.event.start.call(node, d, i); + transition.tween.forEach(function(key, value) { + if (value = value.call(node, d, i)) { + tweened.push(value); + } + }); + d3.timer(function() { + timer.c = tick(elapsed || 1) ? d3_true : tick; + return 1; + }, 0, time); + } + function tick(elapsed) { + if (lock.active !== id) return stop(); + var t = elapsed / duration, e = ease(t), n = tweened.length; + while (n > 0) { + tweened[--n].call(node, e); + } + if (t >= 1) { + transition.event && transition.event.end.call(node, d, i); + return stop(); + } + } + function stop() { + if (--lock.count) delete lock[id]; else delete node.__transition__; + return 1; + } + }, 0, time); + } + } + d3.svg.axis = function() { + var scale = d3.scale.linear(), orient = d3_svg_axisDefaultOrient, innerTickSize = 6, outerTickSize = 6, tickPadding = 3, tickArguments_ = [ 10 ], tickValues = null, tickFormat_; + function axis(g) { + g.each(function() { + var g = d3.select(this); + var scale0 = this.__chart__ || scale, scale1 = this.__chart__ = scale.copy(); + var ticks = tickValues == null ? scale1.ticks ? scale1.ticks.apply(scale1, tickArguments_) : scale1.domain() : tickValues, tickFormat = tickFormat_ == null ? scale1.tickFormat ? scale1.tickFormat.apply(scale1, tickArguments_) : d3_identity : tickFormat_, tick = g.selectAll(".tick").data(ticks, scale1), tickEnter = tick.enter().insert("g", ".domain").attr("class", "tick").style("opacity", ε), tickExit = d3.transition(tick.exit()).style("opacity", ε).remove(), tickUpdate = d3.transition(tick.order()).style("opacity", 1), tickTransform; + var range = d3_scaleRange(scale1), path = g.selectAll(".domain").data([ 0 ]), pathUpdate = (path.enter().append("path").attr("class", "domain"), + d3.transition(path)); + tickEnter.append("line"); + tickEnter.append("text"); + var lineEnter = tickEnter.select("line"), lineUpdate = tickUpdate.select("line"), text = tick.select("text").text(tickFormat), textEnter = tickEnter.select("text"), textUpdate = tickUpdate.select("text"); + switch (orient) { + case "bottom": + { + tickTransform = d3_svg_axisX; + lineEnter.attr("y2", innerTickSize); + textEnter.attr("y", Math.max(innerTickSize, 0) + tickPadding); + lineUpdate.attr("x2", 0).attr("y2", innerTickSize); + textUpdate.attr("x", 0).attr("y", Math.max(innerTickSize, 0) + tickPadding); + text.attr("dy", ".71em").style("text-anchor", "middle"); + pathUpdate.attr("d", "M" + range[0] + "," + outerTickSize + "V0H" + range[1] + "V" + outerTickSize); + break; + } + + case "top": + { + tickTransform = d3_svg_axisX; + lineEnter.attr("y2", -innerTickSize); + textEnter.attr("y", -(Math.max(innerTickSize, 0) + tickPadding)); + lineUpdate.attr("x2", 0).attr("y2", -innerTickSize); + textUpdate.attr("x", 0).attr("y", -(Math.max(innerTickSize, 0) + tickPadding)); + text.attr("dy", "0em").style("text-anchor", "middle"); + pathUpdate.attr("d", "M" + range[0] + "," + -outerTickSize + "V0H" + range[1] + "V" + -outerTickSize); + break; + } + + case "left": + { + tickTransform = d3_svg_axisY; + lineEnter.attr("x2", -innerTickSize); + textEnter.attr("x", -(Math.max(innerTickSize, 0) + tickPadding)); + lineUpdate.attr("x2", -innerTickSize).attr("y2", 0); + textUpdate.attr("x", -(Math.max(innerTickSize, 0) + tickPadding)).attr("y", 0); + text.attr("dy", ".32em").style("text-anchor", "end"); + pathUpdate.attr("d", "M" + -outerTickSize + "," + range[0] + "H0V" + range[1] + "H" + -outerTickSize); + break; + } + + case "right": + { + tickTransform = d3_svg_axisY; + lineEnter.attr("x2", innerTickSize); + textEnter.attr("x", Math.max(innerTickSize, 0) + tickPadding); + lineUpdate.attr("x2", innerTickSize).attr("y2", 0); + textUpdate.attr("x", Math.max(innerTickSize, 0) + tickPadding).attr("y", 0); + text.attr("dy", ".32em").style("text-anchor", "start"); + pathUpdate.attr("d", "M" + outerTickSize + "," + range[0] + "H0V" + range[1] + "H" + outerTickSize); + break; + } + } + if (scale1.rangeBand) { + var x = scale1, dx = x.rangeBand() / 2; + scale0 = scale1 = function(d) { + return x(d) + dx; + }; + } else if (scale0.rangeBand) { + scale0 = scale1; + } else { + tickExit.call(tickTransform, scale1); + } + tickEnter.call(tickTransform, scale0); + tickUpdate.call(tickTransform, scale1); + }); + } + axis.scale = function(x) { + if (!arguments.length) return scale; + scale = x; + return axis; + }; + axis.orient = function(x) { + if (!arguments.length) return orient; + orient = x in d3_svg_axisOrients ? x + "" : d3_svg_axisDefaultOrient; + return axis; + }; + axis.ticks = function() { + if (!arguments.length) return tickArguments_; + tickArguments_ = arguments; + return axis; + }; + axis.tickValues = function(x) { + if (!arguments.length) return tickValues; + tickValues = x; + return axis; + }; + axis.tickFormat = function(x) { + if (!arguments.length) return tickFormat_; + tickFormat_ = x; + return axis; + }; + axis.tickSize = function(x) { + var n = arguments.length; + if (!n) return innerTickSize; + innerTickSize = +x; + outerTickSize = +arguments[n - 1]; + return axis; + }; + axis.innerTickSize = function(x) { + if (!arguments.length) return innerTickSize; + innerTickSize = +x; + return axis; + }; + axis.outerTickSize = function(x) { + if (!arguments.length) return outerTickSize; + outerTickSize = +x; + return axis; + }; + axis.tickPadding = function(x) { + if (!arguments.length) return tickPadding; + tickPadding = +x; + return axis; + }; + axis.tickSubdivide = function() { + return arguments.length && axis; + }; + return axis; + }; + var d3_svg_axisDefaultOrient = "bottom", d3_svg_axisOrients = { + top: 1, + right: 1, + bottom: 1, + left: 1 + }; + function d3_svg_axisX(selection, x) { + selection.attr("transform", function(d) { + return "translate(" + x(d) + ",0)"; + }); + } + function d3_svg_axisY(selection, y) { + selection.attr("transform", function(d) { + return "translate(0," + y(d) + ")"; + }); + } + d3.svg.brush = function() { + var event = d3_eventDispatch(brush, "brushstart", "brush", "brushend"), x = null, y = null, xExtent = [ 0, 0 ], yExtent = [ 0, 0 ], xExtentDomain, yExtentDomain, xClamp = true, yClamp = true, resizes = d3_svg_brushResizes[0]; + function brush(g) { + g.each(function() { + var g = d3.select(this).style("pointer-events", "all").style("-webkit-tap-highlight-color", "rgba(0,0,0,0)").on("mousedown.brush", brushstart).on("touchstart.brush", brushstart); + var background = g.selectAll(".background").data([ 0 ]); + background.enter().append("rect").attr("class", "background").style("visibility", "hidden").style("cursor", "crosshair"); + g.selectAll(".extent").data([ 0 ]).enter().append("rect").attr("class", "extent").style("cursor", "move"); + var resize = g.selectAll(".resize").data(resizes, d3_identity); + resize.exit().remove(); + resize.enter().append("g").attr("class", function(d) { + return "resize " + d; + }).style("cursor", function(d) { + return d3_svg_brushCursor[d]; + }).append("rect").attr("x", function(d) { + return /[ew]$/.test(d) ? -3 : null; + }).attr("y", function(d) { + return /^[ns]/.test(d) ? -3 : null; + }).attr("width", 6).attr("height", 6).style("visibility", "hidden"); + resize.style("display", brush.empty() ? "none" : null); + var gUpdate = d3.transition(g), backgroundUpdate = d3.transition(background), range; + if (x) { + range = d3_scaleRange(x); + backgroundUpdate.attr("x", range[0]).attr("width", range[1] - range[0]); + redrawX(gUpdate); + } + if (y) { + range = d3_scaleRange(y); + backgroundUpdate.attr("y", range[0]).attr("height", range[1] - range[0]); + redrawY(gUpdate); + } + redraw(gUpdate); + }); + } + brush.event = function(g) { + g.each(function() { + var event_ = event.of(this, arguments), extent1 = { + x: xExtent, + y: yExtent, + i: xExtentDomain, + j: yExtentDomain + }, extent0 = this.__chart__ || extent1; + this.__chart__ = extent1; + if (d3_transitionInheritId) { + d3.select(this).transition().each("start.brush", function() { + xExtentDomain = extent0.i; + yExtentDomain = extent0.j; + xExtent = extent0.x; + yExtent = extent0.y; + event_({ + type: "brushstart" + }); + }).tween("brush:brush", function() { + var xi = d3_interpolateArray(xExtent, extent1.x), yi = d3_interpolateArray(yExtent, extent1.y); + xExtentDomain = yExtentDomain = null; + return function(t) { + xExtent = extent1.x = xi(t); + yExtent = extent1.y = yi(t); + event_({ + type: "brush", + mode: "resize" + }); + }; + }).each("end.brush", function() { + xExtentDomain = extent1.i; + yExtentDomain = extent1.j; + event_({ + type: "brush", + mode: "resize" + }); + event_({ + type: "brushend" + }); + }); + } else { + event_({ + type: "brushstart" + }); + event_({ + type: "brush", + mode: "resize" + }); + event_({ + type: "brushend" + }); + } + }); + }; + function redraw(g) { + g.selectAll(".resize").attr("transform", function(d) { + return "translate(" + xExtent[+/e$/.test(d)] + "," + yExtent[+/^s/.test(d)] + ")"; + }); + } + function redrawX(g) { + g.select(".extent").attr("x", xExtent[0]); + g.selectAll(".extent,.n>rect,.s>rect").attr("width", xExtent[1] - xExtent[0]); + } + function redrawY(g) { + g.select(".extent").attr("y", yExtent[0]); + g.selectAll(".extent,.e>rect,.w>rect").attr("height", yExtent[1] - yExtent[0]); + } + function brushstart() { + var target = this, eventTarget = d3.select(d3.event.target), event_ = event.of(target, arguments), g = d3.select(target), resizing = eventTarget.datum(), resizingX = !/^(n|s)$/.test(resizing) && x, resizingY = !/^(e|w)$/.test(resizing) && y, dragging = eventTarget.classed("extent"), dragRestore = d3_event_dragSuppress(), center, origin = d3.mouse(target), offset; + var w = d3.select(d3_window).on("keydown.brush", keydown).on("keyup.brush", keyup); + if (d3.event.changedTouches) { + w.on("touchmove.brush", brushmove).on("touchend.brush", brushend); + } else { + w.on("mousemove.brush", brushmove).on("mouseup.brush", brushend); + } + g.interrupt().selectAll("*").interrupt(); + if (dragging) { + origin[0] = xExtent[0] - origin[0]; + origin[1] = yExtent[0] - origin[1]; + } else if (resizing) { + var ex = +/w$/.test(resizing), ey = +/^n/.test(resizing); + offset = [ xExtent[1 - ex] - origin[0], yExtent[1 - ey] - origin[1] ]; + origin[0] = xExtent[ex]; + origin[1] = yExtent[ey]; + } else if (d3.event.altKey) center = origin.slice(); + g.style("pointer-events", "none").selectAll(".resize").style("display", null); + d3.select("body").style("cursor", eventTarget.style("cursor")); + event_({ + type: "brushstart" + }); + brushmove(); + function keydown() { + if (d3.event.keyCode == 32) { + if (!dragging) { + center = null; + origin[0] -= xExtent[1]; + origin[1] -= yExtent[1]; + dragging = 2; + } + d3_eventPreventDefault(); + } + } + function keyup() { + if (d3.event.keyCode == 32 && dragging == 2) { + origin[0] += xExtent[1]; + origin[1] += yExtent[1]; + dragging = 0; + d3_eventPreventDefault(); + } + } + function brushmove() { + var point = d3.mouse(target), moved = false; + if (offset) { + point[0] += offset[0]; + point[1] += offset[1]; + } + if (!dragging) { + if (d3.event.altKey) { + if (!center) center = [ (xExtent[0] + xExtent[1]) / 2, (yExtent[0] + yExtent[1]) / 2 ]; + origin[0] = xExtent[+(point[0] < center[0])]; + origin[1] = yExtent[+(point[1] < center[1])]; + } else center = null; + } + if (resizingX && move1(point, x, 0)) { + redrawX(g); + moved = true; + } + if (resizingY && move1(point, y, 1)) { + redrawY(g); + moved = true; + } + if (moved) { + redraw(g); + event_({ + type: "brush", + mode: dragging ? "move" : "resize" + }); + } + } + function move1(point, scale, i) { + var range = d3_scaleRange(scale), r0 = range[0], r1 = range[1], position = origin[i], extent = i ? yExtent : xExtent, size = extent[1] - extent[0], min, max; + if (dragging) { + r0 -= position; + r1 -= size + position; + } + min = (i ? yClamp : xClamp) ? Math.max(r0, Math.min(r1, point[i])) : point[i]; + if (dragging) { + max = (min += position) + size; + } else { + if (center) position = Math.max(r0, Math.min(r1, 2 * center[i] - min)); + if (position < min) { + max = min; + min = position; + } else { + max = position; + } + } + if (extent[0] != min || extent[1] != max) { + if (i) yExtentDomain = null; else xExtentDomain = null; + extent[0] = min; + extent[1] = max; + return true; + } + } + function brushend() { + brushmove(); + g.style("pointer-events", "all").selectAll(".resize").style("display", brush.empty() ? "none" : null); + d3.select("body").style("cursor", null); + w.on("mousemove.brush", null).on("mouseup.brush", null).on("touchmove.brush", null).on("touchend.brush", null).on("keydown.brush", null).on("keyup.brush", null); + dragRestore(); + event_({ + type: "brushend" + }); + } + } + brush.x = function(z) { + if (!arguments.length) return x; + x = z; + resizes = d3_svg_brushResizes[!x << 1 | !y]; + return brush; + }; + brush.y = function(z) { + if (!arguments.length) return y; + y = z; + resizes = d3_svg_brushResizes[!x << 1 | !y]; + return brush; + }; + brush.clamp = function(z) { + if (!arguments.length) return x && y ? [ xClamp, yClamp ] : x ? xClamp : y ? yClamp : null; + if (x && y) xClamp = !!z[0], yClamp = !!z[1]; else if (x) xClamp = !!z; else if (y) yClamp = !!z; + return brush; + }; + brush.extent = function(z) { + var x0, x1, y0, y1, t; + if (!arguments.length) { + if (x) { + if (xExtentDomain) { + x0 = xExtentDomain[0], x1 = xExtentDomain[1]; + } else { + x0 = xExtent[0], x1 = xExtent[1]; + if (x.invert) x0 = x.invert(x0), x1 = x.invert(x1); + if (x1 < x0) t = x0, x0 = x1, x1 = t; + } + } + if (y) { + if (yExtentDomain) { + y0 = yExtentDomain[0], y1 = yExtentDomain[1]; + } else { + y0 = yExtent[0], y1 = yExtent[1]; + if (y.invert) y0 = y.invert(y0), y1 = y.invert(y1); + if (y1 < y0) t = y0, y0 = y1, y1 = t; + } + } + return x && y ? [ [ x0, y0 ], [ x1, y1 ] ] : x ? [ x0, x1 ] : y && [ y0, y1 ]; + } + if (x) { + x0 = z[0], x1 = z[1]; + if (y) x0 = x0[0], x1 = x1[0]; + xExtentDomain = [ x0, x1 ]; + if (x.invert) x0 = x(x0), x1 = x(x1); + if (x1 < x0) t = x0, x0 = x1, x1 = t; + if (x0 != xExtent[0] || x1 != xExtent[1]) xExtent = [ x0, x1 ]; + } + if (y) { + y0 = z[0], y1 = z[1]; + if (x) y0 = y0[1], y1 = y1[1]; + yExtentDomain = [ y0, y1 ]; + if (y.invert) y0 = y(y0), y1 = y(y1); + if (y1 < y0) t = y0, y0 = y1, y1 = t; + if (y0 != yExtent[0] || y1 != yExtent[1]) yExtent = [ y0, y1 ]; + } + return brush; + }; + brush.clear = function() { + if (!brush.empty()) { + xExtent = [ 0, 0 ], yExtent = [ 0, 0 ]; + xExtentDomain = yExtentDomain = null; + } + return brush; + }; + brush.empty = function() { + return !!x && xExtent[0] == xExtent[1] || !!y && yExtent[0] == yExtent[1]; + }; + return d3.rebind(brush, event, "on"); + }; + var d3_svg_brushCursor = { + n: "ns-resize", + e: "ew-resize", + s: "ns-resize", + w: "ew-resize", + nw: "nwse-resize", + ne: "nesw-resize", + se: "nwse-resize", + sw: "nesw-resize" + }; + var d3_svg_brushResizes = [ [ "n", "e", "s", "w", "nw", "ne", "se", "sw" ], [ "e", "w" ], [ "n", "s" ], [] ]; + var d3_time_format = d3_time.format = d3_locale_enUS.timeFormat; + var d3_time_formatUtc = d3_time_format.utc; + var d3_time_formatIso = d3_time_formatUtc("%Y-%m-%dT%H:%M:%S.%LZ"); + d3_time_format.iso = Date.prototype.toISOString && +new Date("2000-01-01T00:00:00.000Z") ? d3_time_formatIsoNative : d3_time_formatIso; + function d3_time_formatIsoNative(date) { + return date.toISOString(); + } + d3_time_formatIsoNative.parse = function(string) { + var date = new Date(string); + return isNaN(date) ? null : date; + }; + d3_time_formatIsoNative.toString = d3_time_formatIso.toString; + d3_time.second = d3_time_interval(function(date) { + return new d3_date(Math.floor(date / 1e3) * 1e3); + }, function(date, offset) { + date.setTime(date.getTime() + Math.floor(offset) * 1e3); + }, function(date) { + return date.getSeconds(); + }); + d3_time.seconds = d3_time.second.range; + d3_time.seconds.utc = d3_time.second.utc.range; + d3_time.minute = d3_time_interval(function(date) { + return new d3_date(Math.floor(date / 6e4) * 6e4); + }, function(date, offset) { + date.setTime(date.getTime() + Math.floor(offset) * 6e4); + }, function(date) { + return date.getMinutes(); + }); + d3_time.minutes = d3_time.minute.range; + d3_time.minutes.utc = d3_time.minute.utc.range; + d3_time.hour = d3_time_interval(function(date) { + var timezone = date.getTimezoneOffset() / 60; + return new d3_date((Math.floor(date / 36e5 - timezone) + timezone) * 36e5); + }, function(date, offset) { + date.setTime(date.getTime() + Math.floor(offset) * 36e5); + }, function(date) { + return date.getHours(); + }); + d3_time.hours = d3_time.hour.range; + d3_time.hours.utc = d3_time.hour.utc.range; + d3_time.month = d3_time_interval(function(date) { + date = d3_time.day(date); + date.setDate(1); + return date; + }, function(date, offset) { + date.setMonth(date.getMonth() + offset); + }, function(date) { + return date.getMonth(); + }); + d3_time.months = d3_time.month.range; + d3_time.months.utc = d3_time.month.utc.range; + function d3_time_scale(linear, methods, format) { + function scale(x) { + return linear(x); + } + scale.invert = function(x) { + return d3_time_scaleDate(linear.invert(x)); + }; + scale.domain = function(x) { + if (!arguments.length) return linear.domain().map(d3_time_scaleDate); + linear.domain(x); + return scale; + }; + function tickMethod(extent, count) { + var span = extent[1] - extent[0], target = span / count, i = d3.bisect(d3_time_scaleSteps, target); + return i == d3_time_scaleSteps.length ? [ methods.year, d3_scale_linearTickRange(extent.map(function(d) { + return d / 31536e6; + }), count)[2] ] : !i ? [ d3_time_scaleMilliseconds, d3_scale_linearTickRange(extent, count)[2] ] : methods[target / d3_time_scaleSteps[i - 1] < d3_time_scaleSteps[i] / target ? i - 1 : i]; + } + scale.nice = function(interval, skip) { + var domain = scale.domain(), extent = d3_scaleExtent(domain), method = interval == null ? tickMethod(extent, 10) : typeof interval === "number" && tickMethod(extent, interval); + if (method) interval = method[0], skip = method[1]; + function skipped(date) { + return !isNaN(date) && !interval.range(date, d3_time_scaleDate(+date + 1), skip).length; + } + return scale.domain(d3_scale_nice(domain, skip > 1 ? { + floor: function(date) { + while (skipped(date = interval.floor(date))) date = d3_time_scaleDate(date - 1); + return date; + }, + ceil: function(date) { + while (skipped(date = interval.ceil(date))) date = d3_time_scaleDate(+date + 1); + return date; + } + } : interval)); + }; + scale.ticks = function(interval, skip) { + var extent = d3_scaleExtent(scale.domain()), method = interval == null ? tickMethod(extent, 10) : typeof interval === "number" ? tickMethod(extent, interval) : !interval.range && [ { + range: interval + }, skip ]; + if (method) interval = method[0], skip = method[1]; + return interval.range(extent[0], d3_time_scaleDate(+extent[1] + 1), skip < 1 ? 1 : skip); + }; + scale.tickFormat = function() { + return format; + }; + scale.copy = function() { + return d3_time_scale(linear.copy(), methods, format); + }; + return d3_scale_linearRebind(scale, linear); + } + function d3_time_scaleDate(t) { + return new Date(t); + } + var d3_time_scaleSteps = [ 1e3, 5e3, 15e3, 3e4, 6e4, 3e5, 9e5, 18e5, 36e5, 108e5, 216e5, 432e5, 864e5, 1728e5, 6048e5, 2592e6, 7776e6, 31536e6 ]; + var d3_time_scaleLocalMethods = [ [ d3_time.second, 1 ], [ d3_time.second, 5 ], [ d3_time.second, 15 ], [ d3_time.second, 30 ], [ d3_time.minute, 1 ], [ d3_time.minute, 5 ], [ d3_time.minute, 15 ], [ d3_time.minute, 30 ], [ d3_time.hour, 1 ], [ d3_time.hour, 3 ], [ d3_time.hour, 6 ], [ d3_time.hour, 12 ], [ d3_time.day, 1 ], [ d3_time.day, 2 ], [ d3_time.week, 1 ], [ d3_time.month, 1 ], [ d3_time.month, 3 ], [ d3_time.year, 1 ] ]; + var d3_time_scaleLocalFormat = d3_time_format.multi([ [ ".%L", function(d) { + return d.getMilliseconds(); + } ], [ ":%S", function(d) { + return d.getSeconds(); + } ], [ "%I:%M", function(d) { + return d.getMinutes(); + } ], [ "%I %p", function(d) { + return d.getHours(); + } ], [ "%a %d", function(d) { + return d.getDay() && d.getDate() != 1; + } ], [ "%b %d", function(d) { + return d.getDate() != 1; + } ], [ "%B", function(d) { + return d.getMonth(); + } ], [ "%Y", d3_true ] ]); + var d3_time_scaleMilliseconds = { + range: function(start, stop, step) { + return d3.range(Math.ceil(start / step) * step, +stop, step).map(d3_time_scaleDate); + }, + floor: d3_identity, + ceil: d3_identity + }; + d3_time_scaleLocalMethods.year = d3_time.year; + d3_time.scale = function() { + return d3_time_scale(d3.scale.linear(), d3_time_scaleLocalMethods, d3_time_scaleLocalFormat); + }; + var d3_time_scaleUtcMethods = d3_time_scaleLocalMethods.map(function(m) { + return [ m[0].utc, m[1] ]; + }); + var d3_time_scaleUtcFormat = d3_time_formatUtc.multi([ [ ".%L", function(d) { + return d.getUTCMilliseconds(); + } ], [ ":%S", function(d) { + return d.getUTCSeconds(); + } ], [ "%I:%M", function(d) { + return d.getUTCMinutes(); + } ], [ "%I %p", function(d) { + return d.getUTCHours(); + } ], [ "%a %d", function(d) { + return d.getUTCDay() && d.getUTCDate() != 1; + } ], [ "%b %d", function(d) { + return d.getUTCDate() != 1; + } ], [ "%B", function(d) { + return d.getUTCMonth(); + } ], [ "%Y", d3_true ] ]); + d3_time_scaleUtcMethods.year = d3_time.year.utc; + d3_time.scale.utc = function() { + return d3_time_scale(d3.scale.linear(), d3_time_scaleUtcMethods, d3_time_scaleUtcFormat); + }; + d3.text = d3_xhrType(function(request) { + return request.responseText; + }); + d3.json = function(url, callback) { + return d3_xhr(url, "application/json", d3_json, callback); + }; + function d3_json(request) { + return JSON.parse(request.responseText); + } + d3.html = function(url, callback) { + return d3_xhr(url, "text/html", d3_html, callback); + }; + function d3_html(request) { + var range = d3_document.createRange(); + range.selectNode(d3_document.body); + return range.createContextualFragment(request.responseText); + } + d3.xml = d3_xhrType(function(request) { + return request.responseXML; + }); + if (typeof define === "function" && define.amd) { + define(d3); + } else if (typeof module === "object" && module.exports) { + module.exports = d3; + } else { + this.d3 = d3; + } +}(); diff --git a/Afni_proc_through_nipype/files/_0x2a29d196401e292490f5a331c7b8bf30.json b/Afni_proc_through_nipype/files/_0x2a29d196401e292490f5a331c7b8bf30.json new file mode 100644 index 00000000..8e2b9c7c --- /dev/null +++ b/Afni_proc_through_nipype/files/_0x2a29d196401e292490f5a331c7b8bf30.json @@ -0,0 +1,24 @@ +[ + [ + "base_directory", + "." + ], + [ + "force_lists", + false + ], + [ + "raise_on_empty", + true + ], + [ + "sort_filelist", + true + ], + [ + "needed_outputs", + [ + "command" + ] + ] +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/files/_inputs.pklz b/Afni_proc_through_nipype/files/_inputs.pklz new file mode 100644 index 00000000..9f9f79e4 Binary files /dev/null and b/Afni_proc_through_nipype/files/_inputs.pklz differ diff --git a/Afni_proc_through_nipype/files/_node.pklz b/Afni_proc_through_nipype/files/_node.pklz new file mode 100644 index 00000000..4570e86a Binary files /dev/null and b/Afni_proc_through_nipype/files/_node.pklz differ diff --git a/Afni_proc_through_nipype/files/_report/report.rst b/Afni_proc_through_nipype/files/_report/report.rst new file mode 100644 index 00000000..3f6332be --- /dev/null +++ b/Afni_proc_through_nipype/files/_report/report.rst @@ -0,0 +1,114 @@ +Node: files (io) +================ + + + Hierarchy : Afni_proc_through_nipype.files + Exec ID : files + + +Original Inputs +--------------- + + +* base_directory : . +* force_lists : False +* raise_on_empty : True +* sort_filelist : True + + +Execution Inputs +---------------- + + +* base_directory : . +* force_lists : False +* raise_on_empty : True +* sort_filelist : True + + +Execution Outputs +----------------- + + +* command : /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel + + +Runtime info +------------ + + +* duration : 0.000182 +* hostname : ptb-03230001.irisa.fr +* prev_wd : /home/jlefortb/narps_open_pipelines +* working_dir : /home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/files + + +Environment +~~~~~~~~~~~ + + +* COLORTERM : truecolor +* DBUS_SESSION_BUS_ADDRESS : unix:path=/run/user/670967/bus +* DEBUGINFOD_URLS : https://debuginfod.fedoraproject.org/ +* DESKTOP_SESSION : gnome +* DISPLAY : :0 +* EDITOR : /usr/bin/nano +* FSLDIR : /usr/local/fsl +* FSLGECUDAQ : cuda.q +* FSLMULTIFILEQUIT : TRUE +* FSLOUTPUTTYPE : NIFTI_GZ +* FSLTCLSH : /usr/local/fsl/bin/fsltclsh +* FSLWISH : /usr/local/fsl/bin/fslwish +* FSL_LOAD_NIFTI_EXTENSIONS : 0 +* FSL_SKIP_GLOBAL : 0 +* GDMSESSION : gnome +* GDM_LANG : en_US.UTF-8 +* GNOME_SETUP_DISPLAY : :1 +* GNOME_TERMINAL_SCREEN : /org/gnome/Terminal/screen/3627c221_9f8a_4ca7_a192_68617ea35d25 +* GNOME_TERMINAL_SERVICE : :1.180 +* GUESTFISH_INIT : \e[1;34m +* GUESTFISH_OUTPUT : \e[0m +* GUESTFISH_PS1 : \[\e[1;32m\]>\[\e[0;31m\] +* GUESTFISH_RESTORE : \e[0m +* HISTCONTROL : ignoredups +* HISTSIZE : 1000 +* HOME : /home/jlefortb +* HOSTNAME : ptb-03230001.irisa.fr +* KDEDIRS : /usr +* LANG : en_US.UTF-8 +* LESSOPEN : ||/usr/bin/lesspipe.sh %s +* LOGNAME : jlefortb +* LS_COLORS : rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=01;37;41:su=37;41:sg=30;43:ca=00:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.zst=01;31:*.tzst=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.wim=01;31:*.swm=01;31:*.dwm=01;31:*.esd=01;31:*.avif=01;35:*.jpg=01;35:*.jpeg=01;35:*.mjpg=01;35:*.mjpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.webp=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=01;36:*.au=01;36:*.flac=01;36:*.m4a=01;36:*.mid=01;36:*.midi=01;36:*.mka=01;36:*.mp3=01;36:*.mpc=01;36:*.ogg=01;36:*.ra=01;36:*.wav=01;36:*.oga=01;36:*.opus=01;36:*.spx=01;36:*.xspf=01;36:*~=00;90:*#=00;90:*.bak=00;90:*.old=00;90:*.orig=00;90:*.part=00;90:*.rej=00;90:*.swp=00;90:*.tmp=00;90:*.dpkg-dist=00;90:*.dpkg-old=00;90:*.ucf-dist=00;90:*.ucf-new=00;90:*.ucf-old=00;90:*.rpmnew=00;90:*.rpmorig=00;90:*.rpmsave=00;90: +* MAIL : /var/spool/mail/jlefortb +* MOZ_GMP_PATH : /usr/lib64/mozilla/plugins/gmp-gmpopenh264/system-installed +* PATH : /home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/reproduction/bin:/usr/local/fsl/share/fsl/bin:/usr/local/fsl/share/fsl/bin:/home/jlefortb/.local/bin:/home/jlefortb/bin:/usr/lib64/qt-3.3/bin:/usr/lib64/ccache:/usr/local/bin:/usr/local/sbin:/usr/bin:/usr/sbin:/home/jlefortb/abin:/home/jlefortb/abin +* PS1 : (reproduction) [\u@\h (Fedora 37) \W]$ +* PWD : /home/jlefortb +* QTDIR : /usr/lib64/qt-3.3 +* QTINC : /usr/lib64/qt-3.3/include +* QTLIB : /usr/lib64/qt-3.3/lib +* QT_IM_MODULE : ibus +* R_LIBS : /home/jlefortb/R +* SESSION_MANAGER : local/unix:@/tmp/.ICE-unix/12471,unix/unix:/tmp/.ICE-unix/12471 +* SHELL : /bin/bash +* SHLVL : 1 +* SSH_AUTH_SOCK : /run/user/670967/keyring/ssh +* SYSTEMD_EXEC_PID : 12526 +* TERM : xterm-256color +* USER : jlefortb +* USERNAME : jlefortb +* VIRTUAL_ENV : /home/jlefortb/reproduction +* VIRTUAL_ENV_PROMPT : (reproduction) +* VTE_VERSION : 7006 +* WAYLAND_DISPLAY : wayland-0 +* XAUTHORITY : /run/user/670967/.mutter-Xwaylandauth.LIAOF2 +* XDG_CURRENT_DESKTOP : GNOME +* XDG_DATA_DIRS : /home/jlefortb/.local/share/flatpak/exports/share:/var/lib/flatpak/exports/share:/usr/local/share/:/usr/share/ +* XDG_MENU_PREFIX : gnome- +* XDG_RUNTIME_DIR : /run/user/670967 +* XDG_SESSION_CLASS : user +* XDG_SESSION_DESKTOP : gnome +* XDG_SESSION_TYPE : wayland +* XMODIFIERS : @im=ibus +* _ : /home/jlefortb/reproduction/bin/ipython + diff --git a/Afni_proc_through_nipype/files/result_files.pklz b/Afni_proc_through_nipype/files/result_files.pklz new file mode 100644 index 00000000..dd4dbcf7 Binary files /dev/null and b/Afni_proc_through_nipype/files/result_files.pklz differ diff --git a/Afni_proc_through_nipype/graph.json b/Afni_proc_through_nipype/graph.json new file mode 100644 index 00000000..a5c6c74e --- /dev/null +++ b/Afni_proc_through_nipype/graph.json @@ -0,0 +1,1520 @@ +[ + { + "group": 1, + "imports": [], + "name": "000_files", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "001_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "002_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "003_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "004_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "005_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "006_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "007_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "008_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "009_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "010_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "011_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "012_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "013_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "014_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "015_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "016_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "017_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "018_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "019_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "020_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "021_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "022_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "023_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "024_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "025_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "026_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "027_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "028_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "029_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "030_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "031_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "032_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "033_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "034_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "035_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "036_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "037_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "038_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "039_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "040_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "041_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "042_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "043_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "044_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "045_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "046_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "047_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "048_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "049_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "050_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "051_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "052_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "053_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "054_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "055_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "056_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "057_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "058_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "059_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "060_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "061_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "062_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "063_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "064_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "065_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "066_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "067_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "068_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "069_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "070_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "071_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "072_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "073_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "074_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "075_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "076_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "077_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "078_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "079_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "080_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "081_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "082_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "083_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "084_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "085_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "086_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "087_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "088_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "089_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "090_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "091_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "092_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "093_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "094_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "095_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "096_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "097_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "098_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "099_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "100_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "101_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "102_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "103_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "104_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "105_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "106_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "107_afni_proc", + "size": 1 + }, + { + "group": 1, + "imports": [ + "000_files" + ], + "name": "108_afni_proc", + "size": 1 + }, + { + "group": 2, + "imports": [], + "name": "109_create_stimuli", + "size": 1 + }, + { + "group": 3, + "imports": [], + "name": "110_create_stimuli", + "size": 1 + }, + { + "group": 4, + "imports": [], + "name": "111_create_stimuli", + "size": 1 + }, + { + "group": 5, + "imports": [], + "name": "112_create_stimuli", + "size": 1 + }, + { + "group": 6, + "imports": [], + "name": "113_create_stimuli", + "size": 1 + }, + { + "group": 7, + "imports": [], + "name": "114_create_stimuli", + "size": 1 + }, + { + "group": 8, + "imports": [], + "name": "115_create_stimuli", + "size": 1 + }, + { + "group": 9, + "imports": [], + "name": "116_create_stimuli", + "size": 1 + }, + { + "group": 10, + "imports": [], + "name": "117_create_stimuli", + "size": 1 + }, + { + "group": 11, + "imports": [], + "name": "118_create_stimuli", + "size": 1 + }, + { + "group": 12, + "imports": [], + "name": "119_create_stimuli", + "size": 1 + }, + { + "group": 13, + "imports": [], + "name": "120_create_stimuli", + "size": 1 + }, + { + "group": 14, + "imports": [], + "name": "121_create_stimuli", + "size": 1 + }, + { + "group": 15, + "imports": [], + "name": "122_create_stimuli", + "size": 1 + }, + { + "group": 16, + "imports": [], + "name": "123_create_stimuli", + "size": 1 + }, + { + "group": 17, + "imports": [], + "name": "124_create_stimuli", + "size": 1 + }, + { + "group": 18, + "imports": [], + "name": "125_create_stimuli", + "size": 1 + }, + { + "group": 19, + "imports": [], + "name": "126_create_stimuli", + "size": 1 + }, + { + "group": 20, + "imports": [], + "name": "127_create_stimuli", + "size": 1 + }, + { + "group": 21, + "imports": [], + "name": "128_create_stimuli", + "size": 1 + }, + { + "group": 22, + "imports": [], + "name": "129_create_stimuli", + "size": 1 + }, + { + "group": 23, + "imports": [], + "name": "130_create_stimuli", + "size": 1 + }, + { + "group": 24, + "imports": [], + "name": "131_create_stimuli", + "size": 1 + }, + { + "group": 25, + "imports": [], + "name": "132_create_stimuli", + "size": 1 + }, + { + "group": 26, + "imports": [], + "name": "133_create_stimuli", + "size": 1 + }, + { + "group": 27, + "imports": [], + "name": "134_create_stimuli", + "size": 1 + }, + { + "group": 28, + "imports": [], + "name": "135_create_stimuli", + "size": 1 + }, + { + "group": 29, + "imports": [], + "name": "136_create_stimuli", + "size": 1 + }, + { + "group": 30, + "imports": [], + "name": "137_create_stimuli", + "size": 1 + }, + { + "group": 31, + "imports": [], + "name": "138_create_stimuli", + "size": 1 + }, + { + "group": 32, + "imports": [], + "name": "139_create_stimuli", + "size": 1 + }, + { + "group": 33, + "imports": [], + "name": "140_create_stimuli", + "size": 1 + }, + { + "group": 34, + "imports": [], + "name": "141_create_stimuli", + "size": 1 + }, + { + "group": 35, + "imports": [], + "name": "142_create_stimuli", + "size": 1 + }, + { + "group": 36, + "imports": [], + "name": "143_create_stimuli", + "size": 1 + }, + { + "group": 37, + "imports": [], + "name": "144_create_stimuli", + "size": 1 + }, + { + "group": 38, + "imports": [], + "name": "145_create_stimuli", + "size": 1 + }, + { + "group": 39, + "imports": [], + "name": "146_create_stimuli", + "size": 1 + }, + { + "group": 40, + "imports": [], + "name": "147_create_stimuli", + "size": 1 + }, + { + "group": 41, + "imports": [], + "name": "148_create_stimuli", + "size": 1 + }, + { + "group": 42, + "imports": [], + "name": "149_create_stimuli", + "size": 1 + }, + { + "group": 43, + "imports": [], + "name": "150_create_stimuli", + "size": 1 + }, + { + "group": 44, + "imports": [], + "name": "151_create_stimuli", + "size": 1 + }, + { + "group": 45, + "imports": [], + "name": "152_create_stimuli", + "size": 1 + }, + { + "group": 46, + "imports": [], + "name": "153_create_stimuli", + "size": 1 + }, + { + "group": 47, + "imports": [], + "name": "154_create_stimuli", + "size": 1 + }, + { + "group": 48, + "imports": [], + "name": "155_create_stimuli", + "size": 1 + }, + { + "group": 49, + "imports": [], + "name": "156_create_stimuli", + "size": 1 + }, + { + "group": 50, + "imports": [], + "name": "157_create_stimuli", + "size": 1 + }, + { + "group": 51, + "imports": [], + "name": "158_create_stimuli", + "size": 1 + }, + { + "group": 52, + "imports": [], + "name": "159_create_stimuli", + "size": 1 + }, + { + "group": 53, + "imports": [], + "name": "160_create_stimuli", + "size": 1 + }, + { + "group": 54, + "imports": [], + "name": "161_create_stimuli", + "size": 1 + }, + { + "group": 55, + "imports": [], + "name": "162_create_stimuli", + "size": 1 + }, + { + "group": 56, + "imports": [], + "name": "163_create_stimuli", + "size": 1 + }, + { + "group": 57, + "imports": [], + "name": "164_create_stimuli", + "size": 1 + }, + { + "group": 58, + "imports": [], + "name": "165_create_stimuli", + "size": 1 + }, + { + "group": 59, + "imports": [], + "name": "166_create_stimuli", + "size": 1 + }, + { + "group": 60, + "imports": [], + "name": "167_create_stimuli", + "size": 1 + }, + { + "group": 61, + "imports": [], + "name": "168_create_stimuli", + "size": 1 + }, + { + "group": 62, + "imports": [], + "name": "169_create_stimuli", + "size": 1 + }, + { + "group": 63, + "imports": [], + "name": "170_create_stimuli", + "size": 1 + }, + { + "group": 64, + "imports": [], + "name": "171_create_stimuli", + "size": 1 + }, + { + "group": 65, + "imports": [], + "name": "172_create_stimuli", + "size": 1 + }, + { + "group": 66, + "imports": [], + "name": "173_create_stimuli", + "size": 1 + }, + { + "group": 67, + "imports": [], + "name": "174_create_stimuli", + "size": 1 + }, + { + "group": 68, + "imports": [], + "name": "175_create_stimuli", + "size": 1 + }, + { + "group": 69, + "imports": [], + "name": "176_create_stimuli", + "size": 1 + }, + { + "group": 70, + "imports": [], + "name": "177_create_stimuli", + "size": 1 + }, + { + "group": 71, + "imports": [], + "name": "178_create_stimuli", + "size": 1 + }, + { + "group": 72, + "imports": [], + "name": "179_create_stimuli", + "size": 1 + }, + { + "group": 73, + "imports": [], + "name": "180_create_stimuli", + "size": 1 + }, + { + "group": 74, + "imports": [], + "name": "181_create_stimuli", + "size": 1 + }, + { + "group": 75, + "imports": [], + "name": "182_create_stimuli", + "size": 1 + }, + { + "group": 76, + "imports": [], + "name": "183_create_stimuli", + "size": 1 + }, + { + "group": 77, + "imports": [], + "name": "184_create_stimuli", + "size": 1 + }, + { + "group": 78, + "imports": [], + "name": "185_create_stimuli", + "size": 1 + }, + { + "group": 79, + "imports": [], + "name": "186_create_stimuli", + "size": 1 + }, + { + "group": 80, + "imports": [], + "name": "187_create_stimuli", + "size": 1 + }, + { + "group": 81, + "imports": [], + "name": "188_create_stimuli", + "size": 1 + }, + { + "group": 82, + "imports": [], + "name": "189_create_stimuli", + "size": 1 + }, + { + "group": 83, + "imports": [], + "name": "190_create_stimuli", + "size": 1 + }, + { + "group": 84, + "imports": [], + "name": "191_create_stimuli", + "size": 1 + }, + { + "group": 85, + "imports": [], + "name": "192_create_stimuli", + "size": 1 + }, + { + "group": 86, + "imports": [], + "name": "193_create_stimuli", + "size": 1 + }, + { + "group": 87, + "imports": [], + "name": "194_create_stimuli", + "size": 1 + }, + { + "group": 88, + "imports": [], + "name": "195_create_stimuli", + "size": 1 + }, + { + "group": 89, + "imports": [], + "name": "196_create_stimuli", + "size": 1 + }, + { + "group": 90, + "imports": [], + "name": "197_create_stimuli", + "size": 1 + }, + { + "group": 91, + "imports": [], + "name": "198_create_stimuli", + "size": 1 + }, + { + "group": 92, + "imports": [], + "name": "199_create_stimuli", + "size": 1 + }, + { + "group": 93, + "imports": [], + "name": "200_create_stimuli", + "size": 1 + }, + { + "group": 94, + "imports": [], + "name": "201_create_stimuli", + "size": 1 + }, + { + "group": 95, + "imports": [], + "name": "202_create_stimuli", + "size": 1 + }, + { + "group": 96, + "imports": [], + "name": "203_create_stimuli", + "size": 1 + }, + { + "group": 97, + "imports": [], + "name": "204_create_stimuli", + "size": 1 + }, + { + "group": 98, + "imports": [], + "name": "205_create_stimuli", + "size": 1 + }, + { + "group": 99, + "imports": [], + "name": "206_create_stimuli", + "size": 1 + }, + { + "group": 100, + "imports": [], + "name": "207_create_stimuli", + "size": 1 + }, + { + "group": 101, + "imports": [], + "name": "208_create_stimuli", + "size": 1 + }, + { + "group": 102, + "imports": [], + "name": "209_create_stimuli", + "size": 1 + }, + { + "group": 103, + "imports": [], + "name": "210_create_stimuli", + "size": 1 + }, + { + "group": 104, + "imports": [], + "name": "211_create_stimuli", + "size": 1 + }, + { + "group": 105, + "imports": [], + "name": "212_create_stimuli", + "size": 1 + }, + { + "group": 106, + "imports": [], + "name": "213_create_stimuli", + "size": 1 + }, + { + "group": 107, + "imports": [], + "name": "214_create_stimuli", + "size": 1 + }, + { + "group": 108, + "imports": [], + "name": "215_create_stimuli", + "size": 1 + }, + { + "group": 109, + "imports": [], + "name": "216_create_stimuli", + "size": 1 + } +] \ No newline at end of file diff --git a/Afni_proc_through_nipype/graph1.json b/Afni_proc_through_nipype/graph1.json new file mode 100644 index 00000000..3df9fa6b --- /dev/null +++ b/Afni_proc_through_nipype/graph1.json @@ -0,0 +1,2722 @@ +{ + "groups": [ + { + "name": "Group_00001", + "procs": [ + 0, + 1, + 2, + 3, + 4, + 5, + 6, + 7, + 8, + 9, + 10, + 11, + 12, + 13, + 14, + 15, + 16, + 17, + 18, + 19, + 20, + 21, + 22, + 23, + 24, + 25, + 26, + 27, + 28, + 29, + 30, + 31, + 32, + 33, + 34, + 35, + 36, + 37, + 38, + 39, + 40, + 41, + 42, + 43, + 44, + 45, + 46, + 47, + 48, + 49, + 50, + 51, + 52, + 53, + 54, + 55, + 56, + 57, + 58, + 59, + 60, + 61, + 62, + 63, + 64, + 65, + 66, + 67, + 68, + 69, + 70, + 71, + 72, + 73, + 74, + 75, + 76, + 77, + 78, + 79, + 80, + 81, + 82, + 83, + 84, + 85, + 86, + 87, + 88, + 89, + 90, + 91, + 92, + 93, + 94, + 95, + 96, + 97, + 98, + 99, + 100, + 101, + 102, + 103, + 104, + 105, + 106, + 107, + 108 + ], + "total": 109 + }, + { + "name": "Group_00002", + "procs": [ + 109 + ], + "total": 1 + }, + { + "name": "Group_00003", + "procs": [ + 110 + ], + "total": 1 + }, + { + "name": "Group_00004", + "procs": [ + 111 + ], + "total": 1 + }, + { + "name": "Group_00005", + "procs": [ + 112 + ], + "total": 1 + }, + { + "name": "Group_00006", + "procs": [ + 113 + ], + "total": 1 + }, + { + "name": "Group_00007", + "procs": [ + 114 + ], + "total": 1 + }, + { + "name": "Group_00008", + "procs": [ + 115 + ], + "total": 1 + }, + { + "name": "Group_00009", + "procs": [ + 116 + ], + "total": 1 + }, + { + "name": "Group_00010", + "procs": [ + 117 + ], + "total": 1 + }, + { + "name": "Group_00011", + "procs": [ + 118 + ], + "total": 1 + }, + { + "name": "Group_00012", + "procs": [ + 119 + ], + "total": 1 + }, + { + "name": "Group_00013", + "procs": [ + 120 + ], + "total": 1 + }, + { + "name": "Group_00014", + "procs": [ + 121 + ], + "total": 1 + }, + { + "name": "Group_00015", + "procs": [ + 122 + ], + "total": 1 + }, + { + "name": "Group_00016", + "procs": [ + 123 + ], + "total": 1 + }, + { + "name": "Group_00017", + "procs": [ + 124 + ], + "total": 1 + }, + { + "name": "Group_00018", + "procs": [ + 125 + ], + "total": 1 + }, + { + "name": "Group_00019", + "procs": [ + 126 + ], + "total": 1 + }, + { + "name": "Group_00020", + "procs": [ + 127 + ], + "total": 1 + }, + { + "name": "Group_00021", + "procs": [ + 128 + ], + "total": 1 + }, + { + "name": "Group_00022", + "procs": [ + 129 + ], + "total": 1 + }, + { + "name": "Group_00023", + "procs": [ + 130 + ], + "total": 1 + }, + { + "name": "Group_00024", + "procs": [ + 131 + ], + "total": 1 + }, + { + "name": "Group_00025", + "procs": [ + 132 + ], + "total": 1 + }, + { + "name": "Group_00026", + "procs": [ + 133 + ], + "total": 1 + }, + { + "name": "Group_00027", + "procs": [ + 134 + ], + "total": 1 + }, + { + "name": "Group_00028", + "procs": [ + 135 + ], + "total": 1 + }, + { + "name": "Group_00029", + "procs": [ + 136 + ], + "total": 1 + }, + { + "name": "Group_00030", + "procs": [ + 137 + ], + "total": 1 + }, + { + "name": "Group_00031", + "procs": [ + 138 + ], + "total": 1 + }, + { + "name": "Group_00032", + "procs": [ + 139 + ], + "total": 1 + }, + { + "name": "Group_00033", + "procs": [ + 140 + ], + "total": 1 + }, + { + "name": "Group_00034", + "procs": [ + 141 + ], + "total": 1 + }, + { + "name": "Group_00035", + "procs": [ + 142 + ], + "total": 1 + }, + { + "name": "Group_00036", + "procs": [ + 143 + ], + "total": 1 + }, + { + "name": "Group_00037", + "procs": [ + 144 + ], + "total": 1 + }, + { + "name": "Group_00038", + "procs": [ + 145 + ], + "total": 1 + }, + { + "name": "Group_00039", + "procs": [ + 146 + ], + "total": 1 + }, + { + "name": "Group_00040", + "procs": [ + 147 + ], + "total": 1 + }, + { + "name": "Group_00041", + "procs": [ + 148 + ], + "total": 1 + }, + { + "name": "Group_00042", + "procs": [ + 149 + ], + "total": 1 + }, + { + "name": "Group_00043", + "procs": [ + 150 + ], + "total": 1 + }, + { + "name": "Group_00044", + "procs": [ + 151 + ], + "total": 1 + }, + { + "name": "Group_00045", + "procs": [ + 152 + ], + "total": 1 + }, + { + "name": "Group_00046", + "procs": [ + 153 + ], + "total": 1 + }, + { + "name": "Group_00047", + "procs": [ + 154 + ], + "total": 1 + }, + { + "name": "Group_00048", + "procs": [ + 155 + ], + "total": 1 + }, + { + "name": "Group_00049", + "procs": [ + 156 + ], + "total": 1 + }, + { + "name": "Group_00050", + "procs": [ + 157 + ], + "total": 1 + }, + { + "name": "Group_00051", + "procs": [ + 158 + ], + "total": 1 + }, + { + "name": "Group_00052", + "procs": [ + 159 + ], + "total": 1 + }, + { + "name": "Group_00053", + "procs": [ + 160 + ], + "total": 1 + }, + { + "name": "Group_00054", + "procs": [ + 161 + ], + "total": 1 + }, + { + "name": "Group_00055", + "procs": [ + 162 + ], + "total": 1 + }, + { + "name": "Group_00056", + "procs": [ + 163 + ], + "total": 1 + }, + { + "name": "Group_00057", + "procs": [ + 164 + ], + "total": 1 + }, + { + "name": "Group_00058", + "procs": [ + 165 + ], + "total": 1 + }, + { + "name": "Group_00059", + "procs": [ + 166 + ], + "total": 1 + }, + { + "name": "Group_00060", + "procs": [ + 167 + ], + "total": 1 + }, + { + "name": "Group_00061", + "procs": [ + 168 + ], + "total": 1 + }, + { + "name": "Group_00062", + "procs": [ + 169 + ], + "total": 1 + }, + { + "name": "Group_00063", + "procs": [ + 170 + ], + "total": 1 + }, + { + "name": "Group_00064", + "procs": [ + 171 + ], + "total": 1 + }, + { + "name": "Group_00065", + "procs": [ + 172 + ], + "total": 1 + }, + { + "name": "Group_00066", + "procs": [ + 173 + ], + "total": 1 + }, + { + "name": "Group_00067", + "procs": [ + 174 + ], + "total": 1 + }, + { + "name": "Group_00068", + "procs": [ + 175 + ], + "total": 1 + }, + { + "name": "Group_00069", + "procs": [ + 176 + ], + "total": 1 + }, + { + "name": "Group_00070", + "procs": [ + 177 + ], + "total": 1 + }, + { + "name": "Group_00071", + "procs": [ + 178 + ], + "total": 1 + }, + { + "name": "Group_00072", + "procs": [ + 179 + ], + "total": 1 + }, + { + "name": "Group_00073", + "procs": [ + 180 + ], + "total": 1 + }, + { + "name": "Group_00074", + "procs": [ + 181 + ], + "total": 1 + }, + { + "name": "Group_00075", + "procs": [ + 182 + ], + "total": 1 + }, + { + "name": "Group_00076", + "procs": [ + 183 + ], + "total": 1 + }, + { + "name": "Group_00077", + "procs": [ + 184 + ], + "total": 1 + }, + { + "name": "Group_00078", + "procs": [ + 185 + ], + "total": 1 + }, + { + "name": "Group_00079", + "procs": [ + 186 + ], + "total": 1 + }, + { + "name": "Group_00080", + "procs": [ + 187 + ], + "total": 1 + }, + { + "name": "Group_00081", + "procs": [ + 188 + ], + "total": 1 + }, + { + "name": "Group_00082", + "procs": [ + 189 + ], + "total": 1 + }, + { + "name": "Group_00083", + "procs": [ + 190 + ], + "total": 1 + }, + { + "name": "Group_00084", + "procs": [ + 191 + ], + "total": 1 + }, + { + "name": "Group_00085", + "procs": [ + 192 + ], + "total": 1 + }, + { + "name": "Group_00086", + "procs": [ + 193 + ], + "total": 1 + }, + { + "name": "Group_00087", + "procs": [ + 194 + ], + "total": 1 + }, + { + "name": "Group_00088", + "procs": [ + 195 + ], + "total": 1 + }, + { + "name": "Group_00089", + "procs": [ + 196 + ], + "total": 1 + }, + { + "name": "Group_00090", + "procs": [ + 197 + ], + "total": 1 + }, + { + "name": "Group_00091", + "procs": [ + 198 + ], + "total": 1 + }, + { + "name": "Group_00092", + "procs": [ + 199 + ], + "total": 1 + }, + { + "name": "Group_00093", + "procs": [ + 200 + ], + "total": 1 + }, + { + "name": "Group_00094", + "procs": [ + 201 + ], + "total": 1 + }, + { + "name": "Group_00095", + "procs": [ + 202 + ], + "total": 1 + }, + { + "name": "Group_00096", + "procs": [ + 203 + ], + "total": 1 + }, + { + "name": "Group_00097", + "procs": [ + 204 + ], + "total": 1 + }, + { + "name": "Group_00098", + "procs": [ + 205 + ], + "total": 1 + }, + { + "name": "Group_00099", + "procs": [ + 206 + ], + "total": 1 + }, + { + "name": "Group_00100", + "procs": [ + 207 + ], + "total": 1 + }, + { + "name": "Group_00101", + "procs": [ + 208 + ], + "total": 1 + }, + { + "name": "Group_00102", + "procs": [ + 209 + ], + "total": 1 + }, + { + "name": "Group_00103", + "procs": [ + 210 + ], + "total": 1 + }, + { + "name": "Group_00104", + "procs": [ + 211 + ], + "total": 1 + }, + { + "name": "Group_00105", + "procs": [ + 212 + ], + "total": 1 + }, + { + "name": "Group_00106", + "procs": [ + 213 + ], + "total": 1 + }, + { + "name": "Group_00107", + "procs": [ + 214 + ], + "total": 1 + }, + { + "name": "Group_00108", + "procs": [ + 215 + ], + "total": 1 + }, + { + "name": "Group_00109", + "procs": [ + 216 + ], + "total": 1 + } + ], + "links": [ + { + "source": 0, + "target": 1, + "value": 1 + }, + { + "source": 0, + "target": 2, + "value": 1 + }, + { + "source": 0, + "target": 3, + "value": 1 + }, + { + "source": 0, + "target": 4, + "value": 1 + }, + { + "source": 0, + "target": 5, + "value": 1 + }, + { + "source": 0, + "target": 6, + "value": 1 + }, + { + "source": 0, + "target": 7, + "value": 1 + }, + { + "source": 0, + "target": 8, + "value": 1 + }, + { + "source": 0, + "target": 9, + "value": 1 + }, + { + "source": 0, + "target": 10, + "value": 1 + }, + { + "source": 0, + "target": 11, + "value": 1 + }, + { + "source": 0, + "target": 12, + "value": 1 + }, + { + "source": 0, + "target": 13, + "value": 1 + }, + { + "source": 0, + "target": 14, + "value": 1 + }, + { + "source": 0, + "target": 15, + "value": 1 + }, + { + "source": 0, + "target": 16, + "value": 1 + }, + { + "source": 0, + "target": 17, + "value": 1 + }, + { + "source": 0, + "target": 18, + "value": 1 + }, + { + "source": 0, + "target": 19, + "value": 1 + }, + { + "source": 0, + "target": 20, + "value": 1 + }, + { + "source": 0, + "target": 21, + "value": 1 + }, + { + "source": 0, + "target": 22, + "value": 1 + }, + { + "source": 0, + "target": 23, + "value": 1 + }, + { + "source": 0, + "target": 24, + "value": 1 + }, + { + "source": 0, + "target": 25, + "value": 1 + }, + { + "source": 0, + "target": 26, + "value": 1 + }, + { + "source": 0, + "target": 27, + "value": 1 + }, + { + "source": 0, + "target": 28, + "value": 1 + }, + { + "source": 0, + "target": 29, + "value": 1 + }, + { + "source": 0, + "target": 30, + "value": 1 + }, + { + "source": 0, + "target": 31, + "value": 1 + }, + { + "source": 0, + "target": 32, + "value": 1 + }, + { + "source": 0, + "target": 33, + "value": 1 + }, + { + "source": 0, + "target": 34, + "value": 1 + }, + { + "source": 0, + "target": 35, + "value": 1 + }, + { + "source": 0, + "target": 36, + "value": 1 + }, + { + "source": 0, + "target": 37, + "value": 1 + }, + { + "source": 0, + "target": 38, + "value": 1 + }, + { + "source": 0, + "target": 39, + "value": 1 + }, + { + "source": 0, + "target": 40, + "value": 1 + }, + { + "source": 0, + "target": 41, + "value": 1 + }, + { + "source": 0, + "target": 42, + "value": 1 + }, + { + "source": 0, + "target": 43, + "value": 1 + }, + { + "source": 0, + "target": 44, + "value": 1 + }, + { + "source": 0, + "target": 45, + "value": 1 + }, + { + "source": 0, + "target": 46, + "value": 1 + }, + { + "source": 0, + "target": 47, + "value": 1 + }, + { + "source": 0, + "target": 48, + "value": 1 + }, + { + "source": 0, + "target": 49, + "value": 1 + }, + { + "source": 0, + "target": 50, + "value": 1 + }, + { + "source": 0, + "target": 51, + "value": 1 + }, + { + "source": 0, + "target": 52, + "value": 1 + }, + { + "source": 0, + "target": 53, + "value": 1 + }, + { + "source": 0, + "target": 54, + "value": 1 + }, + { + "source": 0, + "target": 55, + "value": 1 + }, + { + "source": 0, + "target": 56, + "value": 1 + }, + { + "source": 0, + "target": 57, + "value": 1 + }, + { + "source": 0, + "target": 58, + "value": 1 + }, + { + "source": 0, + "target": 59, + "value": 1 + }, + { + "source": 0, + "target": 60, + "value": 1 + }, + { + "source": 0, + "target": 61, + "value": 1 + }, + { + "source": 0, + "target": 62, + "value": 1 + }, + { + "source": 0, + "target": 63, + "value": 1 + }, + { + "source": 0, + "target": 64, + "value": 1 + }, + { + "source": 0, + "target": 65, + "value": 1 + }, + { + "source": 0, + "target": 66, + "value": 1 + }, + { + "source": 0, + "target": 67, + "value": 1 + }, + { + "source": 0, + "target": 68, + "value": 1 + }, + { + "source": 0, + "target": 69, + "value": 1 + }, + { + "source": 0, + "target": 70, + "value": 1 + }, + { + "source": 0, + "target": 71, + "value": 1 + }, + { + "source": 0, + "target": 72, + "value": 1 + }, + { + "source": 0, + "target": 73, + "value": 1 + }, + { + "source": 0, + "target": 74, + "value": 1 + }, + { + "source": 0, + "target": 75, + "value": 1 + }, + { + "source": 0, + "target": 76, + "value": 1 + }, + { + "source": 0, + "target": 77, + "value": 1 + }, + { + "source": 0, + "target": 78, + "value": 1 + }, + { + "source": 0, + "target": 79, + "value": 1 + }, + { + "source": 0, + "target": 80, + "value": 1 + }, + { + "source": 0, + "target": 81, + "value": 1 + }, + { + "source": 0, + "target": 82, + "value": 1 + }, + { + "source": 0, + "target": 83, + "value": 1 + }, + { + "source": 0, + "target": 84, + "value": 1 + }, + { + "source": 0, + "target": 85, + "value": 1 + }, + { + "source": 0, + "target": 86, + "value": 1 + }, + { + "source": 0, + "target": 87, + "value": 1 + }, + { + "source": 0, + "target": 88, + "value": 1 + }, + { + "source": 0, + "target": 89, + "value": 1 + }, + { + "source": 0, + "target": 90, + "value": 1 + }, + { + "source": 0, + "target": 91, + "value": 1 + }, + { + "source": 0, + "target": 92, + "value": 1 + }, + { + "source": 0, + "target": 93, + "value": 1 + }, + { + "source": 0, + "target": 94, + "value": 1 + }, + { + "source": 0, + "target": 95, + "value": 1 + }, + { + "source": 0, + "target": 96, + "value": 1 + }, + { + "source": 0, + "target": 97, + "value": 1 + }, + { + "source": 0, + "target": 98, + "value": 1 + }, + { + "source": 0, + "target": 99, + "value": 1 + }, + { + "source": 0, + "target": 100, + "value": 1 + }, + { + "source": 0, + "target": 101, + "value": 1 + }, + { + "source": 0, + "target": 102, + "value": 1 + }, + { + "source": 0, + "target": 103, + "value": 1 + }, + { + "source": 0, + "target": 104, + "value": 1 + }, + { + "source": 0, + "target": 105, + "value": 1 + }, + { + "source": 0, + "target": 106, + "value": 1 + }, + { + "source": 0, + "target": 107, + "value": 1 + }, + { + "source": 0, + "target": 108, + "value": 1 + } + ], + "maxN": 109, + "nodes": [ + { + "group": 1, + "name": "0_files", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/files/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/files/result_files.pklz" + }, + { + "group": 1, + "name": "1_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_082/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_082/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "2_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_013/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_013/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "3_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_021/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_021/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "4_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_089/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_089/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "5_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_004/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_004/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "6_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_002/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_002/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "7_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_046/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_046/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "8_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_043/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_043/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "9_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_038/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_038/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "10_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_092/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_092/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "11_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_029/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_029/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "12_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_118/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_118/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "13_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_053/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_053/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "14_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_077/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_077/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "15_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_008/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_008/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "16_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_016/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_016/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "17_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_011/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_011/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "18_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_123/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_123/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "19_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_058/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_058/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "20_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_069/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_069/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "21_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_093/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_093/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "22_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_076/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_076/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "23_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_071/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_071/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "24_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_003/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_003/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "25_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_010/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_010/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "26_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_096/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_096/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "27_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_055/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_055/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "28_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_018/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_018/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "29_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_026/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_026/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "30_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_061/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_061/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "31_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_005/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_005/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "32_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_121/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_121/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "33_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_041/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_041/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "34_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_110/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_110/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "35_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_049/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_049/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "36_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_079/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_079/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "37_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_057/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_057/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "38_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_108/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_108/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "39_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_040/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_040/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "40_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_047/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_047/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "41_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_106/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_106/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "42_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_033/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_033/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "43_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_116/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_116/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "44_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_105/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_105/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "45_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_085/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_085/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "46_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_066/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_066/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "47_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_020/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_020/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "48_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_075/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_075/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "49_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_114/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_114/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "50_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_072/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_072/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "51_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_044/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_044/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "52_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_102/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_102/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "53_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_099/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_099/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "54_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_088/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_088/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "55_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_064/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_064/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "56_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_063/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_063/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "57_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_017/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_017/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "58_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_117/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_117/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "59_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_056/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_056/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "60_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_019/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_019/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "61_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_022/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_022/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "62_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_024/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_024/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "63_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_090/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_090/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "64_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_124/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_124/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "65_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_067/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_067/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "66_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_094/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_094/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "67_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_039/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_039/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "68_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_074/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_074/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "69_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_030/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_030/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "70_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_050/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_050/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "71_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_001/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_001/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "72_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_119/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_119/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "73_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_032/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_032/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "74_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_100/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_100/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "75_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_015/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_015/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "76_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_103/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_103/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "77_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_045/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_045/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "78_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_084/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_084/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "79_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_059/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_059/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "80_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_025/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_025/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "81_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_112/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_112/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "82_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_009/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_009/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "83_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_115/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_115/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "84_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_073/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_073/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "85_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_027/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_027/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "86_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_104/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_104/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "87_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_083/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_083/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "88_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_095/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_095/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "89_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_037/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_037/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "90_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_051/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_051/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "91_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_107/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_107/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "92_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_052/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_052/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "93_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_087/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_087/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "94_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_060/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_060/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "95_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_035/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_035/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "96_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_070/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_070/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "97_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_081/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_081/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "98_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_120/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_120/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "99_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_109/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_109/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "100_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_036/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_036/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "101_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_006/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_006/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "102_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_098/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_098/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "103_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_014/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_014/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "104_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_062/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_062/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "105_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_113/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_113/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "106_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_068/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_068/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "107_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_054/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_054/afni_proc/result_afni_proc.pklz" + }, + { + "group": 1, + "name": "108_afni_proc", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_080/afni_proc/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_080/afni_proc/result_afni_proc.pklz" + }, + { + "group": 2, + "name": "109_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_082/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_082/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 3, + "name": "110_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_013/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_013/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 4, + "name": "111_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_021/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_021/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 5, + "name": "112_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_089/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_089/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 6, + "name": "113_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_004/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_004/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 7, + "name": "114_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_002/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_002/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 8, + "name": "115_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_046/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_046/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 9, + "name": "116_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_043/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_043/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 10, + "name": "117_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_038/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_038/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 11, + "name": "118_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_092/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_092/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 12, + "name": "119_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_029/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_029/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 13, + "name": "120_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_118/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_118/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 14, + "name": "121_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_053/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_053/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 15, + "name": "122_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_077/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_077/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 16, + "name": "123_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_008/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_008/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 17, + "name": "124_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_016/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_016/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 18, + "name": "125_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_011/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_011/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 19, + "name": "126_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_123/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_123/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 20, + "name": "127_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_058/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_058/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 21, + "name": "128_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_069/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_069/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 22, + "name": "129_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_093/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_093/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 23, + "name": "130_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_076/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_076/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 24, + "name": "131_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_071/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_071/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 25, + "name": "132_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_003/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_003/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 26, + "name": "133_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_010/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_010/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 27, + "name": "134_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_096/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_096/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 28, + "name": "135_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_055/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_055/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 29, + "name": "136_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_018/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_018/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 30, + "name": "137_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_026/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_026/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 31, + "name": "138_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_061/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_061/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 32, + "name": "139_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_005/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_005/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 33, + "name": "140_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_121/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_121/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 34, + "name": "141_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_041/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_041/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 35, + "name": "142_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_110/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_110/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 36, + "name": "143_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_049/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_049/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 37, + "name": "144_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_079/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_079/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 38, + "name": "145_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_057/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_057/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 39, + "name": "146_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_108/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_108/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 40, + "name": "147_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_040/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_040/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 41, + "name": "148_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_047/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_047/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 42, + "name": "149_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_106/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_106/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 43, + "name": "150_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_033/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_033/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 44, + "name": "151_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_116/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_116/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 45, + "name": "152_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_105/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_105/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 46, + "name": "153_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_085/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_085/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 47, + "name": "154_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_066/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_066/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 48, + "name": "155_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_020/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_020/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 49, + "name": "156_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_075/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_075/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 50, + "name": "157_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_114/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_114/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 51, + "name": "158_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_072/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_072/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 52, + "name": "159_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_044/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_044/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 53, + "name": "160_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_102/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_102/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 54, + "name": "161_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_099/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_099/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 55, + "name": "162_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_088/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_088/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 56, + "name": "163_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_064/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_064/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 57, + "name": "164_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_063/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_063/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 58, + "name": "165_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_017/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_017/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 59, + "name": "166_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_117/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_117/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 60, + "name": "167_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_056/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_056/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 61, + "name": "168_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_019/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_019/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 62, + "name": "169_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_022/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_022/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 63, + "name": "170_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_024/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_024/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 64, + "name": "171_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_090/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_090/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 65, + "name": "172_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_124/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_124/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 66, + "name": "173_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_067/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_067/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 67, + "name": "174_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_094/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_094/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 68, + "name": "175_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_039/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_039/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 69, + "name": "176_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_074/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_074/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 70, + "name": "177_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_030/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_030/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 71, + "name": "178_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_050/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_050/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 72, + "name": "179_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_001/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_001/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 73, + "name": "180_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_119/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_119/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 74, + "name": "181_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_032/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_032/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 75, + "name": "182_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_100/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_100/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 76, + "name": "183_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_015/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_015/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 77, + "name": "184_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_103/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_103/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 78, + "name": "185_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_045/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_045/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 79, + "name": "186_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_084/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_084/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 80, + "name": "187_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_059/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_059/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 81, + "name": "188_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_025/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_025/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 82, + "name": "189_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_112/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_112/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 83, + "name": "190_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_009/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_009/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 84, + "name": "191_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_115/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_115/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 85, + "name": "192_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_073/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_073/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 86, + "name": "193_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_027/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_027/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 87, + "name": "194_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_104/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_104/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 88, + "name": "195_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_083/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_083/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 89, + "name": "196_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_095/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_095/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 90, + "name": "197_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_037/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_037/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 91, + "name": "198_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_051/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_051/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 92, + "name": "199_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_107/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_107/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 93, + "name": "200_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_052/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_052/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 94, + "name": "201_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_087/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_087/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 95, + "name": "202_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_060/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_060/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 96, + "name": "203_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_035/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_035/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 97, + "name": "204_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_070/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_070/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 98, + "name": "205_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_081/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_081/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 99, + "name": "206_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_120/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_120/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 100, + "name": "207_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_109/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_109/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 101, + "name": "208_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_036/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_036/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 102, + "name": "209_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_006/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_006/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 103, + "name": "210_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_098/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_098/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 104, + "name": "211_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_014/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_014/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 105, + "name": "212_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_062/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_062/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 106, + "name": "213_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_113/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_113/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 107, + "name": "214_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_068/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_068/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 108, + "name": "215_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_054/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_054/create_stimuli/result_create_stimuli.pklz" + }, + { + "group": 109, + "name": "216_create_stimuli", + "report": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_080/create_stimuli/_report/report.rst", + "result": "/home/jlefortb/narps_open_pipelines/Afni_proc_through_nipype/_subject_id_080/create_stimuli/result_create_stimuli.pklz" + } + ] +} \ No newline at end of file diff --git a/Afni_proc_through_nipype/index.html b/Afni_proc_through_nipype/index.html new file mode 100644 index 00000000..3fb66b4a --- /dev/null +++ b/Afni_proc_through_nipype/index.html @@ -0,0 +1,264 @@ + + + + + + + + +

+ Flare imports
+ hierarchical edge bundling +

+
tension: +
+ + + + + diff --git a/narps_open/pipelines/team_27SS.firstlevel b/narps_open/pipelines/team_27SS.firstlevel new file mode 100755 index 00000000..9d1ba399 --- /dev/null +++ b/narps_open/pipelines/team_27SS.firstlevel @@ -0,0 +1,111 @@ +#!/bin/tcsh + +# Reproduction of 27SS pipeline by the Narps reproducibility team +# creation date: 13 February 2024 +# version afni used by the team: AFNI 18.3.12 +# version afni used by the reproducibility team: AFNI Version 23.0.02 Commodus + +# Store arguments (directory where to store results, subjects list, directory where data are stored) +set expdir="$1" # /home/jlefortb/narps_open_pipelines/data/results/team_27SS_afni/firstlevel/ +set subject="$2" # sub-001 +set datadir="$3" # /home/jlefortb/narps_open_pipelines/data/original/ds001734/ + +# In a terminal, path /home/jlefortb/narps_open_pipelines, run: +# /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_27SS.firstlevel /home/jlefortb/narps_open_pipelines/data/results/team_27SS_afni/firstlevel/, sub-001, /home/jlefortb/narps_open_pipelines/data/original/ds001734/ + + + + +# Store arguments (directory where to store results, subjects list, directory where data are stored) +set expdir="$1" +set subject="$2" +set datadir="$3" + + +afni_proc.py \ + # Spécification du script de sortie + -script ${expdir}/proc.${subject}.block \ + # Autoriser l'écrasement du script existant + -scr_overwrite \ + # Spécification de l'identifiant du sujet + -subj_id ${subject} \ + # Spécification du répertoire de sortie + -out_dir ${expdir}/${subject}.results.block \ + # Spécification des ensembles de données EPI + -dsets ${datadir}/${subject}/func/${subject}_task-MGT_run-01_bold.nii.gz \ + ${datadir}/${subject}/func/${subject}_task-MGT_run-02_bold.nii.gz \ + ${datadir}/${subject}/func/${subject}_task-MGT_run-03_bold.nii.gz \ + ${datadir}/${subject}/func/${subject}_task-MGT_run-04_bold.nii.gz \ + # Copie de l'image anatomique + -copy_anat ${datadir}/${subject}/anat/${subject}_T1w.nii.gz \ + # Spécification de la présence du crâne dans l'image anatomique + -anat_has_skull yes \ + # Blocs de prétraitement inclus dans le pipeline + -blocks despike tshift align tlrc volreg blur mask scale regress \ + # Option de déspike + -despike_new yes \ + # Spécification de la base TLRC + -tlrc_base MNI152_T1_2009c+tlrc \ + # Specify blur size + -blur_size 6.0 \ + # Options d'alignement + -align_opts_aea \ + # Déplacement géant + -giant_move \ + # Coût de l'alignement + -cost lpc+ZZ \ + # Options for temporal shift + -tshift_opts_ts -quintic \ + # Alignement des volumes EPI sur l'outlier minimal + -volreg_align_to MIN_OUTLIER \ + # Interpolation method for volume registration + -volreg_interp cubic \ + # Alignement EPI vers anatomique + -volreg_align_e2a \ + # Flou dans le masque automatique + -blur_in_automask \ + # Model motion per run + -regress_motion_per_run \ + # Censor motion outliers with framewise displacement greater than 1.5 mm + -regress_censor_motion 1.5 \ + # Specify the regressors and their corresponding labels + -regress_stim_times \ + ${datadir}/${subject}/func/times+gain.1D \ + ${datadir}/${subject}/func/times+loss.1D \ + -regress_stim_labels task nuisance \ + # Modélisation des régresseurs de stimulus + -regress_basis 'BLOCK(4,1)' \ + # Application du masque anatomique + -mask_apply anat \ + # Options supplémentaires pour 3dDeconvolve + -regress_opts_3dD \ + -GOFORIT 8 \ + -jobs 6 \ + -ortvec ${datadir}/${subject}/func/motion_parameters.1D motion_params \ + -allzero_OK \ + # Application des types de mouvement pour la régression + -regress_apply_mot_types demean \ + # Censure des premiers TRs + -regress_censor_first_trs 3 \ + # Estimation des erreurs de flou + # Estimate the blur epochs + -regress_est_blur_epits \ + # Estimate the blur error times + -regress_est_blur_errts \ + # Exécution du pipeline directement après création du script TCSH + + # No gradient distortion correction specified + # No distortion correction specified + # No intensity correction specified + # No intensity normalization specified + # No spatial smoothing specified + # Execute the pipeline script +# -execute + +# # extract beta values +# 3dbucket -prefix GAIN ${expdir}/${subject}.results.block/stats.sub-001+tlrc.BRIK[3] +# 3dbucket -prefix LOSS ${expdir}/${subject}.results.block/stats.sub-001+tlrc.BRIK[8] + +# # convert BRIK to nii +# 3dAFNItoNIFTI -prefix GAIN ${subject}_GAIN+tlrc +# 3dAFNItoNIFTI -prefix LOSS ${subject}_LOSS+tlrc \ No newline at end of file diff --git a/narps_open/pipelines/team_6VV2.firstlevel b/narps_open/pipelines/team_6VV2.firstlevel new file mode 100755 index 00000000..435d6324 --- /dev/null +++ b/narps_open/pipelines/team_6VV2.firstlevel @@ -0,0 +1,107 @@ +#!/bin/tcsh + +# created by team 6VV2, reproduced by Narps reproducibility team +# creation date: 22 June 2023 +# read and ran by team_6VV2.py script +# version afni used by the team : AFNI Version 19.0.01 Tiberius +# version afni used by the reproducibility team :AFNI Version 23.0.02 Commodus +# Last update: June 2023 + + +# exemple run: +# In a terminal, path /home/jlefortb/narps_open_pipelines, run: +# tcsh /home/jlefortb/narps_open_pipelines/narps_open/pipelines/team_6VV2.firstlevel /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/, sub-001, /home/jlefortb/narps_open_pipelines/data/original/ds001734/ + + + + +# Store arguments (directory where to store results, subjects list, directory where data are stored) +set expdir="$1" +set subject="$2" +set datadir="$3" + + +afni_proc.py \ + -script ${expdir}/proc.${subject}.block \ + -scr_overwrite \ + -subj_id ${subject} \ + -out_dir ${expdir}/${subject}.results.block \ + -dsets ${datadir}/${subject}/func/${subject}_task-MGT_run-01_bold.nii.gz \ + ${datadir}/${subject}/func/${subject}_task-MGT_run-02_bold.nii.gz \ + ${datadir}/${subject}/func/${subject}_task-MGT_run-03_bold.nii.gz \ + ${datadir}/${subject}/func/${subject}_task-MGT_run-04_bold.nii.gz \ + -copy_anat ${datadir}/${subject}/anat/${subject}_T1w.nii.gz \ + -anat_has_skull yes \ + -blocks despike tshift align tlrc volreg blur mask scale regress \ + -despike_new yes \ + -tlrc_base MNI152_T1_2009c+tlrc \ + -tlrc_NL_warp \ + -align_opts_aea \ + -giant_move \ + -cost lpc+ZZ \ + -volreg_align_to MIN_OUTLIER \ + -volreg_tlrc_warp \ + -volreg_align_e2a \ + -blur_in_automask \ + -regress_stim_times \ + ${datadir}/${subject}/func/times+gain.1D \ + ${datadir}/${subject}/func/times+loss.1D \ + -regress_stim_types AM2 \ + -regress_stim_labels \ + GAIN \ + LOSS \ + -regress_basis \ + 'BLOCK(4,1)' \ + -mask_apply anat \ + -regress_motion_per_run \ + -test_stim_files no \ + -regress_opts_3dD \ + -GOFORIT 8 \ + -jobs 6 \ + -regress_censor_motion 0.2 \ + -regress_apply_mot_types demean deriv \ + -regress_censor_first_trs 3 \ + -regress_est_blur_errts \ + -execute + + +# # extract beta values +# 3dbucket -prefix GAIN ${expdir}/${subject}.results.block/stats.sub-001+tlrc.BRIK[3] +# 3dbucket -prefix LOSS ${expdir}/${subject}.results.block/stats.sub-001+tlrc.BRIK[8] + +# # convert BRIK to nii +# 3dAFNItoNIFTI -prefix GAIN ${subject}_GAIN+tlrc +# 3dAFNItoNIFTI -prefix LOSS ${subject}_LOSS+tlrc + + + +# run this file with "tcsh 6VV2_afni_proc.simple" + +# create 1D stimuli file : +# import pandas as pd + +# df_run1 = pd.read_csv("/home/jlefortb/narps_open_pipelines/data/original/ds001734/sub-001/func/sub-001_task-MGT_run-01_events.tsv", sep="\t") +# df_run1 = df_run1[["onset", "gain", "loss"]].T +# df_run2 = pd.read_csv("/home/jlefortb/narps_open_pipelines/data/original/ds001734/sub-001/func/sub-001_task-MGT_run-02_events.tsv", sep="\t") +# df_run2 = df_run2[["onset", "gain", "loss"]].T +# df_run3 = pd.read_csv("/home/jlefortb/narps_open_pipelines/data/original/ds001734/sub-001/func/sub-001_task-MGT_run-03_events.tsv", sep="\t") +# df_run3 = df_run3[["onset", "gain", "loss"]].T +# df_run4 = pd.read_csv("/home/jlefortb/narps_open_pipelines/data/original/ds001734/sub-001/func/sub-001_task-MGT_run-04_events.tsv", sep="\t") +# df_run4 = df_run4[["onset", "gain", "loss"]].T + +# df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) +# df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] +# df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] +# df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] +# df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] +# df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) +# df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] +# df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] +# df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] +# df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + +# df_gain.to_csv('/home/jlefortb/narps_open_pipelines/data/original/ds001734/sub-001/func/times+gain.1D', +# sep='\t', index=False, header=False) +# df_loss.to_csv('/home/jlefortb/narps_open_pipelines/data/original/ds001734/sub-001/func/times+loss.1D', +# sep='\t', index=False, header=False) diff --git a/narps_open/pipelines/team_6VV2.secondlevel b/narps_open/pipelines/team_6VV2.secondlevel new file mode 100644 index 00000000..390b8b85 --- /dev/null +++ b/narps_open/pipelines/team_6VV2.secondlevel @@ -0,0 +1,232 @@ +#!/bin/tcsh + +# created by team 6VV2, reproduced by Narps reproducibility team +# creation date: 22 June 2023 +# read and ran by team_6VV2.py script +# version afni used by the team : AFNI Version 19.0.01 Tiberius +# version afni used by the reproducibility team :AFNI Version 23.0.02 Commodus +# Last update: June 2023 + + +# Store arguments (directory where to store results) +set expdir="$1" + +3dLME -prefix expdir -jobs 4 \ +-model 'group*cond' \ +-SS_type 3 \ +-ranEff '~1' \ +-num_glt 5 \ +-gltLabel 1 'GAIN_indiff' -gltCode 1 'group : 1*indiff cond : 1*GAIN' \ +-gltLabel 2 'GAIN_range' -gltCode 2 'group : 1*range cond : 1*GAIN' \ +-gltLabel 3 'LOSS_indiff' -gltCode 3 'group : 1*indiff cond : 1*LOSS' \ +-gltLabel 4 'LOSS_range' -gltCode 4 'group : 1*range cond : 1*LOSS' \ +-gltLabel 5 'LOSS_range-indiff' -gltCode 5 'group : 1*range -1*indiff cond : 1*LOSS' \ +-dataTable \ +Subj cond group InputFile \ +001 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-001.results.block/sub-001_GAIN.nii \ +001 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-001.results.block/sub-001_LOSS.nii \ +002 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-002.results.block/sub-002_GAIN.nii \ +002 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-002.results.block/sub-002_LOSS.nii \ +003 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-003.results.block/sub-003_GAIN.nii \ +003 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-003.results.block/sub-003_LOSS.nii \ +004 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-004.results.block/sub-004_GAIN.nii \ +004 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-004.results.block/sub-004_LOSS.nii \ +005 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-005.results.block/sub-005_GAIN.nii \ +005 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-005.results.block/sub-005_LOSS.nii \ +006 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-006.results.block/sub-006_GAIN.nii \ +006 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-006.results.block/sub-006_LOSS.nii \ +008 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-008.results.block/sub-008_GAIN.nii \ +008 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-008.results.block/sub-008_LOSS.nii \ +009 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-009.results.block/sub-009_GAIN.nii \ +009 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-009.results.block/sub-009_LOSS.nii \ +010 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-010.results.block/sub-010_GAIN.nii \ +010 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-010.results.block/sub-010_LOSS.nii \ +011 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-011.results.block/sub-011_GAIN.nii \ +011 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-011.results.block/sub-011_LOSS.nii \ +013 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-013.results.block/sub-013_GAIN.nii \ +013 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-013.results.block/sub-013_LOSS.nii \ +014 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-014.results.block/sub-014_GAIN.nii \ +014 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-014.results.block/sub-014_LOSS.nii \ +015 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-015.results.block/sub-015_GAIN.nii \ +015 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-015.results.block/sub-015_LOSS.nii \ +017 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-017.results.block/sub-017_GAIN.nii \ +017 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-017.results.block/sub-017_LOSS.nii \ +019 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-019.results.block/sub-019_GAIN.nii \ +019 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-019.results.block/sub-019_LOSS.nii \ +020 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-020.results.block/sub-020_GAIN.nii \ +020 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-020.results.block/sub-020_LOSS.nii \ +021 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-021.results.block/sub-021_GAIN.nii \ +021 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-021.results.block/sub-021_LOSS.nii \ +022 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-022.results.block/sub-022_GAIN.nii \ +022 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-022.results.block/sub-022_LOSS.nii \ +024 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-024.results.block/sub-024_GAIN.nii \ +024 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-024.results.block/sub-024_LOSS.nii \ +025 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-025.results.block/sub-025_GAIN.nii \ +025 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-025.results.block/sub-025_LOSS.nii \ +026 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-026.results.block/sub-026_GAIN.nii \ +026 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-026.results.block/sub-026_LOSS.nii \ +027 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-027.results.block/sub-027_GAIN.nii \ +027 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-027.results.block/sub-027_LOSS.nii \ +029 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-029.results.block/sub-029_GAIN.nii \ +029 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-029.results.block/sub-029_LOSS.nii \ +032 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-032.results.block/sub-032_GAIN.nii \ +032 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-032.results.block/sub-032_LOSS.nii \ +033 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-033.results.block/sub-033_GAIN.nii \ +033 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-033.results.block/sub-033_LOSS.nii \ +035 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-035.results.block/sub-035_GAIN.nii \ +035 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-035.results.block/sub-035_LOSS.nii \ +036 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-036.results.block/sub-036_GAIN.nii \ +036 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-036.results.block/sub-036_LOSS.nii \ +037 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-037.results.block/sub-037_GAIN.nii \ +037 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-037.results.block/sub-037_LOSS.nii \ +038 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-038.results.block/sub-038_GAIN.nii \ +038 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-038.results.block/sub-038_LOSS.nii \ +039 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-039.results.block/sub-039_GAIN.nii \ +039 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-039.results.block/sub-039_LOSS.nii \ +040 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-040.results.block/sub-040_GAIN.nii \ +040 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-040.results.block/sub-040_LOSS.nii \ +041 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-041.results.block/sub-041_GAIN.nii \ +041 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-041.results.block/sub-041_LOSS.nii \ +043 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-043.results.block/sub-043_GAIN.nii \ +043 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-043.results.block/sub-043_LOSS.nii \ +044 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-044.results.block/sub-044_GAIN.nii \ +044 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-044.results.block/sub-044_LOSS.nii \ +045 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-045.results.block/sub-045_GAIN.nii \ +045 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-045.results.block/sub-045_LOSS.nii \ +046 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-046.results.block/sub-046_GAIN.nii \ +046 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-046.results.block/sub-046_LOSS.nii \ +047 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-047.results.block/sub-047_GAIN.nii \ +047 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-047.results.block/sub-047_LOSS.nii \ +049 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-049.results.block/sub-049_GAIN.nii \ +049 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-049.results.block/sub-049_LOSS.nii \ +050 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-050.results.block/sub-050_GAIN.nii \ +050 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-050.results.block/sub-050_LOSS.nii \ +051 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-051.results.block/sub-051_GAIN.nii \ +051 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-051.results.block/sub-051_LOSS.nii \ +052 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-052.results.block/sub-052_GAIN.nii \ +052 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-052.results.block/sub-052_LOSS.nii \ +053 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-053.results.block/sub-053_GAIN.nii \ +053 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-053.results.block/sub-053_LOSS.nii \ +054 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-054.results.block/sub-054_GAIN.nii \ +054 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-054.results.block/sub-054_LOSS.nii \ +055 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-055.results.block/sub-055_GAIN.nii \ +055 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-055.results.block/sub-055_LOSS.nii \ +056 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-056.results.block/sub-056_GAIN.nii \ +056 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-056.results.block/sub-056_LOSS.nii \ +057 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-057.results.block/sub-057_GAIN.nii \ +057 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-057.results.block/sub-057_LOSS.nii \ +058 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-058.results.block/sub-058_GAIN.nii \ +058 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-058.results.block/sub-058_LOSS.nii \ +059 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-059.results.block/sub-059_GAIN.nii \ +059 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-059.results.block/sub-059_LOSS.nii \ +060 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-060.results.block/sub-060_GAIN.nii \ +060 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-060.results.block/sub-060_LOSS.nii \ +061 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-061.results.block/sub-061_GAIN.nii \ +061 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-061.results.block/sub-061_LOSS.nii \ +062 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-062.results.block/sub-062_GAIN.nii \ +062 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-062.results.block/sub-062_LOSS.nii \ +063 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-063.results.block/sub-063_GAIN.nii \ +063 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-063.results.block/sub-063_LOSS.nii \ +064 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-064.results.block/sub-064_GAIN.nii \ +064 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-064.results.block/sub-064_LOSS.nii \ +066 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-066.results.block/sub-066_GAIN.nii \ +066 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-066.results.block/sub-066_LOSS.nii \ +067 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-067.results.block/sub-067_GAIN.nii \ +067 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-067.results.block/sub-067_LOSS.nii \ +068 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-068.results.block/sub-068_GAIN.nii \ +068 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-068.results.block/sub-068_LOSS.nii \ +069 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-069.results.block/sub-069_GAIN.nii \ +069 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-069.results.block/sub-069_LOSS.nii \ +070 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-070.results.block/sub-070_GAIN.nii \ +070 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-070.results.block/sub-070_LOSS.nii \ +071 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-071.results.block/sub-071_GAIN.nii \ +071 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-071.results.block/sub-071_LOSS.nii \ +072 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-072.results.block/sub-072_GAIN.nii \ +072 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-072.results.block/sub-072_LOSS.nii \ +073 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-073.results.block/sub-073_GAIN.nii \ +073 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-073.results.block/sub-073_LOSS.nii \ +074 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-074.results.block/sub-074_GAIN.nii \ +074 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-074.results.block/sub-074_LOSS.nii \ +075 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-075.results.block/sub-075_GAIN.nii \ +075 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-075.results.block/sub-075_LOSS.nii \ +076 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-076.results.block/sub-076_GAIN.nii \ +076 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-076.results.block/sub-076_LOSS.nii \ +077 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-077.results.block/sub-077_GAIN.nii \ +077 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-077.results.block/sub-077_LOSS.nii \ +079 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-079.results.block/sub-079_GAIN.nii \ +079 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-079.results.block/sub-079_LOSS.nii \ +080 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-080.results.block/sub-080_GAIN.nii \ +080 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-080.results.block/sub-080_LOSS.nii \ +081 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-081.results.block/sub-081_GAIN.nii \ +081 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-081.results.block/sub-081_LOSS.nii \ +082 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-082.results.block/sub-082_GAIN.nii \ +082 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-082.results.block/sub-082_LOSS.nii \ +083 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-083.results.block/sub-083_GAIN.nii \ +083 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-083.results.block/sub-083_LOSS.nii \ +084 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-084.results.block/sub-084_GAIN.nii \ +084 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-084.results.block/sub-084_LOSS.nii \ +085 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-085.results.block/sub-085_GAIN.nii \ +085 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-085.results.block/sub-085_LOSS.nii \ +087 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-087.results.block/sub-087_GAIN.nii \ +087 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-087.results.block/sub-087_LOSS.nii \ +090 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-090.results.block/sub-090_GAIN.nii \ +090 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-090.results.block/sub-090_LOSS.nii \ +092 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-092.results.block/sub-092_GAIN.nii \ +092 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-092.results.block/sub-092_LOSS.nii \ +093 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-093.results.block/sub-093_GAIN.nii \ +093 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-093.results.block/sub-093_LOSS.nii \ +094 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-094.results.block/sub-094_GAIN.nii \ +094 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-094.results.block/sub-094_LOSS.nii \ +095 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-095.results.block/sub-095_GAIN.nii \ +095 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-095.results.block/sub-095_LOSS.nii \ +096 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-096.results.block/sub-096_GAIN.nii \ +096 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-096.results.block/sub-096_LOSS.nii \ +098 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-098.results.block/sub-098_GAIN.nii \ +098 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-098.results.block/sub-098_LOSS.nii \ +099 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-099.results.block/sub-099_GAIN.nii \ +099 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-099.results.block/sub-099_LOSS.nii \ +102 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-102.results.block/sub-102_GAIN.nii \ +102 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-102.results.block/sub-102_LOSS.nii \ +103 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-103.results.block/sub-103_GAIN.nii \ +103 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-103.results.block/sub-103_LOSS.nii \ +104 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-104.results.block/sub-104_GAIN.nii \ +104 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-104.results.block/sub-104_LOSS.nii \ +105 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-105.results.block/sub-105_GAIN.nii \ +105 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-105.results.block/sub-105_LOSS.nii \ +106 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-106.results.block/sub-106_GAIN.nii \ +106 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-106.results.block/sub-106_LOSS.nii \ +107 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-107.results.block/sub-107_GAIN.nii \ +107 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-107.results.block/sub-107_LOSS.nii \ +108 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-108.results.block/sub-108_GAIN.nii \ +108 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-108.results.block/sub-108_LOSS.nii \ +109 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-109.results.block/sub-109_GAIN.nii \ +109 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-109.results.block/sub-109_LOSS.nii \ +110 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-110.results.block/sub-110_GAIN.nii \ +110 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-110.results.block/sub-110_LOSS.nii \ +112 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-112.results.block/sub-112_GAIN.nii \ +112 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-112.results.block/sub-112_LOSS.nii \ +113 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-113.results.block/sub-113_GAIN.nii \ +113 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-113.results.block/sub-113_LOSS.nii \ +114 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-114.results.block/sub-114_GAIN.nii \ +114 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-114.results.block/sub-114_LOSS.nii \ +115 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-115.results.block/sub-115_GAIN.nii \ +115 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-115.results.block/sub-115_LOSS.nii \ +116 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-116.results.block/sub-116_GAIN.nii \ +116 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-116.results.block/sub-116_LOSS.nii \ +117 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-117.results.block/sub-117_GAIN.nii \ +117 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-117.results.block/sub-117_LOSS.nii \ +118 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-118.results.block/sub-118_GAIN.nii \ +118 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-118.results.block/sub-118_LOSS.nii \ +119 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-119.results.block/sub-119_GAIN.nii \ +119 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-119.results.block/sub-119_LOSS.nii \ +120 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-120.results.block/sub-120_GAIN.nii \ +120 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-120.results.block/sub-120_LOSS.nii \ +121 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-121.results.block/sub-121_GAIN.nii \ +121 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-121.results.block/sub-121_LOSS.nii \ +123 GAIN indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-123.results.block/sub-123_GAIN.nii \ +123 LOSS indifference /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-123.results.block/sub-123_LOSS.nii \ +124 GAIN range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-124.results.block/sub-124_GAIN.nii \ +124 LOSS range /home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-124.results.block/sub-124_LOSS.nii + + + diff --git a/narps_open/pipelines/team_6VV2_wip.py b/narps_open/pipelines/team_6VV2_wip.py new file mode 100644 index 00000000..201290af --- /dev/null +++ b/narps_open/pipelines/team_6VV2_wip.py @@ -0,0 +1,231 @@ +''' +created by team 6VV2, reproduced by Narps reproducibility team +creation date: 22 June 2023 +needs script "team_6VV2.firstlevel" and "team_6VV2.secondlevel" +the team : AFNI Version 19.0.01 Tiberius +version afni used by the reproducibility team :AFNI Version 23.0.02 Commodus +Participants not included 016, 018, 030, 088, 089, 100 +Last update: June 2023 +''' + +from nipype import Node, Function, Workflow,IdentityInterface +import subprocess +from nipype.interfaces.io import SelectFiles, DataSink +from os.path import abspath +from os.path import join as opj +import os +import pathlib +from glob import glob +from nilearn import plotting +import matplotlib.pyplot as plt +from nilearn import image +import pandas as pd + +######################################################################## +################## FIRST LEVEL ANALYSIS FOR TEAM 6VV2 ################## +######################################################################## + +# define environment for first level analysis +data_dir = "/home/jlefortb/narps_open_pipelines/data/original/ds001734/" +results_dir = "/home/jlefortb/narps_open_pipelines/data/results/derived/team_6VV2_afni/firstlevel/" + +path = pathlib.Path(results_dir) +path.mkdir(parents=True, exist_ok=True) + + + +# define subject ids +dir_list = os.listdir(data_dir) +# Subject list (to which we will do the analysis) +subject_list = [] +for dirs in dir_list: + if dirs[0:3] == 'sub': + subject_list.append(dirs[-3:]) + + + + +# Infosource Node - To iterate on subjects + get directoris paths +infosource = Node(interface=IdentityInterface(fields = ['subject_id', 'data_dir', 'results_dir'], + data_dir = data_dir, + results_dir = results_dir), + name = 'infosource') + +infosource.iterables = [('subject_id', subject_list)] + + +templates = {'command': abspath('narps_open/pipelines/team_6VV2.firstlevel')} +# Create SelectFiles node +files = Node(SelectFiles(templates), + name='files') +# Location of the dataset folder +files.inputs.base_directory = '.' + +# create stimuli file the afni way +def create_stimuli_file(subject, data_dir): + # create 1D stimuli file : + import pandas as pd + from os.path import join as opj + df_run1 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-01_events.tsv".format(subject, subject)), sep="\t") + df_run1 = df_run1[["onset", "gain", "loss"]].T + df_run2 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-02_events.tsv".format(subject, subject)), sep="\t") + df_run2 = df_run2[["onset", "gain", "loss"]].T + df_run3 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-03_events.tsv".format(subject, subject)), sep="\t") + df_run3 = df_run3[["onset", "gain", "loss"]].T + df_run4 = pd.read_csv(opj(data_dir, "sub-{}/func/sub-{}_task-MGT_run-04_events.tsv".format(subject, subject)), sep="\t") + df_run4 = df_run4[["onset", "gain", "loss"]].T + + df_gain = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_gain.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['gain']) for col in range(0, 64)] + df_gain.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['gain']) for col in range(0, 64)] + df_loss = pd.DataFrame(index=range(0,4), columns=range(0,64)) + df_loss.loc[0] = ["{}*{}".format(df_run1[col].loc['onset'], df_run1[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[1] = ["{}*{}".format(df_run2[col].loc['onset'], df_run2[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[2] = ["{}*{}".format(df_run3[col].loc['onset'], df_run3[col].loc['loss']) for col in range(0, 64)] + df_loss.loc[3] = ["{}*{}".format(df_run4[col].loc['onset'], df_run4[col].loc['loss']) for col in range(0, 64)] + + df_gain.to_csv(opj(data_dir, "sub-{}/func/times+gain.1D".format(subject)), + sep='\t', index=False, header=False) + df_loss.to_csv(opj(data_dir, "sub-{}/func/times+loss.1D".format(subject)), + sep='\t', index=False, header=False) + print("Done") + +create_stimuli = Node(Function(input_names=["subject", "data_dir"], + output_names=["Stimuli"], + function=create_stimuli_file), + name='create_stimuli') + + +# launch afni bash script +def run(command, results_dir, subject, data_dir): + import subprocess + subject= "sub-{}".format(subject) + subprocess.run([command, results_dir, subject, data_dir]) + print("Done") + +afni_proc = Node(Function(input_names=["command", "results_dir", "subject", "data_dir"], + output_names=["Adni_1stLevel"], + function=run), + name='afni_proc') + + +####### build workflow +wf_run = Workflow(base_dir = results_dir, name="Afni_proc_through_nipype") +wf_run.base_dir = '.' +wf_run.connect([(infosource, create_stimuli, [('subject_id', 'subject')]), + (infosource, create_stimuli, [("data_dir", "data_dir")]), + (infosource, afni_proc, [('subject_id', 'subject')]), + (infosource, afni_proc, [("results_dir", "results_dir")]), + (infosource, afni_proc, [("data_dir", "data_dir")]), + (files, afni_proc, [("command", "command")]) + ]) +# wf_run.write_graph() +wf_run.run() + +#### +# to do: relaunch sub 1 and launch sub 2, then launch part 2 to check which data are mandatory and which we can delete +# because taking a bunch of space (60G) +#### + +# convert BRIK to nii +command = "3dAFNItoNIFTI" +for Afni_file in glob("/home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-001.results.block/*.HEAD"): + file_name = Afni_file.split('/')[-1] + nifti_file_name = file_name[:-5] + results_dir = "/home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-001.results.block/results_as_nifti/" + prefixname = opj(results_dir, nifti_file_name) + subprocess.run([command, "-prefix", prefixname, Afni_file]) + +# visualise nifti +for nifi_file in glob("/home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/sub-001.results.block/results_as_nifti/*"): + shape = image.load_img(nifi_file).shape + print("shape: ", shape) + if len(shape) > 3: + plotting.plot_stat_map(image.index_img(nifi_file, 0), annotate=False, title=nifi_file.split('/')[-1] + " ind 0", colorbar=True, cut_coords=(-24, -10, 4, 18, 32, 52, 64), display_mode='z', cmap='coolwarm') + plotting.plot_stat_map(image.index_img(nifi_file, 30), annotate=False, title=nifi_file.split('/')[-1] + " ind 30", colorbar=True, cut_coords=(-24, -10, 4, 18, 32, 52, 64), display_mode='z', cmap='coolwarm') + plotting.plot_stat_map(image.index_img(nifi_file, 60), annotate=False, title=nifi_file.split('/')[-1] + " ind 60", colorbar=True, cut_coords=(-24, -10, 4, 18, 32, 52, 64), display_mode='z', cmap='coolwarm') + plt.show() + else: + plotting.plot_stat_map(nifi_file, annotate=False, title=nifi_file.split('/')[-1], colorbar=True, cut_coords=(-24, -10, 4, 18, 32, 52, 64), display_mode='z', cmap='coolwarm') + plt.show() + + +######################################################################## +################## SECOND LEVEL ANALYSIS FOR TEAM 6VV2 ################# +######################################################################## + +# define environment for second level analysis +data_dir_firstlevel = "/home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/firstlevel/" +results_dir_second_level = "/home/jlefortb/narps_open_pipelines/data/results/team_6VV2_afni/secondlevel/" +path = pathlib.Path(results_dir_second_level) +path.mkdir(parents=True, exist_ok=True) + +# Infosource Node - To iterate on subjects + get directoris paths +infosource = Node(interface=IdentityInterface(fields = ['results_dir_second_level'], + results_dir_second_level = results_dir_second_level), + name = 'infosource') + +templates = {'command': abspath('narps_open/pipelines/team_6VV2.secondlevel')} +# Create SelectFiles node +files = Node(SelectFiles(templates), + name='files') +# Location of the dataset folder +files.inputs.base_directory = '.' + + +# create datatable for afni_proc.py script +def create_dataTable(data_dir_firstlevel): + # subject not analyzed by the team, see pipelines information for more details + not_included = ["016","018","030","088","089","100"] + df_participant = pd.read_csv("data/original/ds001734/participants.tsv", sep="\t") + # replace equalRange and equalIndifference with range and indifference + df_participant["group"] = [i[5:].lower() for i in df_participant["group"].values] + df_participant["participant_id"] = [i[-3:] for i in df_participant["participant_id"].values] + df = pd.DataFrame(columns=["Subj", "cond", "group", "InputFile"]) + for sub in df_participant["participant_id"].values: + if sub in not_included: + continue + size_df = len(df) + sub_group = df_participant["group"][df_participant["participant_id"]==sub].values[0] + df.loc[size_df] = [sub, "GAIN", sub_group, "{}sub-{}/sub-{}_GAIN.nii".format(data_dir_firstlevel, sub, sub)] + size_df = len(df) + df.loc[size_df] = [sub, "LOSS", sub_group, "{}sub-{}/sub-{}_LOSS.nii".format(data_dir_firstlevel, sub, sub)] + dataTable = df + + """ + Should look like + + Subj cond group InputFile \ + 001 GAIN indiff results/sub-001.results.block/sub-001_GAIN.nii \ + 001 LOSS indiff results/sub-001.results.block/sub-001_LOSS.nii \ + … + 124 GAIN range results/sub-124.results.block/sub-124_GAIN.nii \ + 124 LOSS range results/sub-124.results.block/sub-124_LOSS.nii + + + """ + return dataTable + + +# launch afni bash script +def run_secondlevel(command, results_dir_second_level): + import subprocess + subprocess.run([command, results_dir_second_level]) + print("Done") + +afni_proc = Node(Function(input_names=["command", "results_dir_second_level"], + output_names=["Adni_2ndLevel"], + function=run_secondlevel), + name='afni_proc') + + +####### build workflow +wf_run = Workflow(base_dir = results_dir_second_level, name="Afni_proc_2nd_level_through_nipype") +wf_run.base_dir = '.' +wf_run.connect([(infosource, afni_proc, [("results_dir_second_level", "results_dir_second_level")]), + (files, afni_proc, [("command", "command")]) + ]) +# wf_run.write_graph() +wf_run.run() \ No newline at end of file diff --git a/narps_open/pipelines/team_I9D6.firstlevel b/narps_open/pipelines/team_I9D6.firstlevel new file mode 100644 index 00000000..438a85ae --- /dev/null +++ b/narps_open/pipelines/team_I9D6.firstlevel @@ -0,0 +1,175 @@ +#!/bin/tcsh + +# created by team I9D6, reproduced by Narps reproducibility team +# creation date: 22 June 2023 +# read and ran by team_I9D6.py script +# version afni used by the team : AFNI Version 19.0.24 Tiberius +# version afni used by the reproducibility team :AFNI Version 23.0.02 Commodus +# Last update: June 2023 + +# Store arguments (directory where to store results, subjects list, directory where data are stored) +set expdir="$1" +set subject="$2" +set datadir="$3" + +""" +https://osf.io/bvs2f + +Brain extraction and non-linear registration to the MNI152_2009 template were done with AFNI's @SSwarper script. Prior to brain extraction, the images were deobliqued with 3dWarp and intensity normalized with 3dUnifize, so @SSwarper was run with the -unifize_off flag. +1. AFNI's 3dWarp was used to apply the obliquity transformation to the T1's, needed to keep AFNI and FreeSurfer in register. +2. AFNI's 3dUnifize was run to uniform-ize the T1w volume intensities, to provide assistance to FreeSurfer. +3. Freesurfer processing of anatomical T1w datasets, to define white matter and other ROIs +4. AFNI's @SSwarper was applied to skull-strip each anatomical and to estimate a nonlinear warp to a standard space target (MNI152NLin2009cAsym). +5. AFNI's afni_proc.py blocks: +tshift: slice timing alignment on volumes, +align: linear affine alignment of EPI and anatomy, +tlrc: warp anat to standard space (using @SSwarper results), +volreg: EPI registration, plus concatenating and applying 'align' and 'tlrc' transformations to produce the final EPI time series in MNI space, +mask: create a 'brain' mask from the EPI data for later use, +scale: voxelwise scaling of each EPI run mean to 100, for each voxel , +regress: time series regression analysis. + +Freesurfer segmentation with -3T flag: +recon-all -all -sd $cwd -subjid $sid -3T \ + -i $indata_root/$sid/${sid}_T1w-deobl_nu.nii.gz + +The utilized “tissue classes” were specific ROIs selected from the list labeled by FS. These were the ROIs defined to be WM in AFNI’s @SUMA_renumber_FS: Left-Cerebral-White-Matter, Left-Cerebellum-White-Matter, Right-Cerebral-White-Matter, Right-Cerebellum-White-Matter, WM-hypointensities, CC_Posterior, CC_Mid_Posterior, CC_Central, CC_Mid_Anterior, CC_Anterior. (This WM mask was later used for the ANATICOR calculations.) + +Slice time correction done by AFNI's 3dTshift as setup by the tshift block in the afni_proc.py command, which uses 5th order Lagrange polynomial interpolation. This was done before motion correction. Slice #0 was used for the reference, to keep nominal volume times in sync with stimulus timing. + +Motion correction was done using 3dvolreg using 6-parameter rigid transformations. + +The reference scan is the “MIN_OUTLIER” volume (volume in the time series with fewest number of outliers detected using 3dToutcount, pre-motion correction, to minimize risk of selecting a high-motion time point). + +The similarity metric is weighted least squares, to determine the 6 rigid body motion parameters and the accompanying coordinate transformation matrix for each time point. + +Interpolation type is “cubic” when determining the motion parameters. The interpolation type of "wsinc5" (weighted sinc, ±5 voxel neighborhood) was applied to the EPI when the combined transformation to MNI space was applied: the EPI➝ref➝anat➝(NL)MNI template transformations were combined to allow a single interpolation from the original EPI time series to the MNI analysis space. + +Function-to-structure (T1w) registration done by AFNI's align_epi_anat.py script as setup by the align block in afni_proc.py, with these additional parameters: -giant_move -cost lpc+ZZ -check_flip. These options specify to search a larger range of rotations (giant_move), use a constrained local Pearson correlation cost function (lpc+ZZ: https://www.ncbi.nlm.nih.gov/pubmed/18976717), and check to see if the EPI has been flipped relative to the anatomical (this happens 😟). This transformation is a 12 parameter linear affine matrix. + +T1-weighted volumes were first deobliqued and intensity normalized before brain extraction and non-linear registration to the MNI152_2009 template MNI152NLin2009cAsym space) were done with AFNI's @SSwarper script. Both the subject T1 and template volumes were at 1 mm resolution. +@SSwarper -input \ + $indata_root/$sid/${sid}_T1w-deobl_nu.nii.gz \ + -unifize_off \ + -base MNI152_2009_template_SSW.nii.gz \ + -subid $sid \ + -odir . + +Here are the steps in the @SSwarper script: + #1: Uniform-ize the T1-weighted volume intensity (3dUnifize) - skipped (already done) + #2: Strip the skull (3dSkullStrip), with mildly aggressive settings. + #3: Nonlinearly warp (3dQwarp) the result from #1 to the skull-on + template, driving the warping to a medium level of refinement. + #4: Use a slightly dilated brain mask from the template to + crop off any non-brain tissue resulting from #3 (3dcalc). + #5: Warp the output of #4 back to original anatomical space, + along with the template brain mask, and combine those + with the output of #2 to get a better skull-stripped + result in original space (3dNwarpApply and 3dcalc). + #6: Restart the nonlinear warping, registering the output + of #5 to the skull-off template brain volume (3dQwarp). + #7: Use @snapshot_volreg3 to make pretty pictures for QC. +The nonlinear warp computed in 3dQwarp (and applied to the EPI data in 3dNwarpApply) is computed incrementally using a set of overlapping 3D polynomial patches. As the patches are refined, more parameters are introduced. However, the many thousands of parameters defining the polynomial patches are not saved; rather, the warp is stored as a non-parametric displacement field in a 3-volume NiFTI datasets. Program 3dNwarpApply uses such a warp dataset to transform other 3D datasets in the same fashion (and can catenate warps and matrices on-the-fly); its default interpolation method is weighted sinc, but lower order methods are also available (e.g., NN for warping ROI labels). + +We used AFNI's 3dUnifize for T1w intensity correction. Command: + 3dUnifize -GM -clfrac 0.4 -Urad 30 \ + -input ${sid}_T1w-deobl.nii.gz \ + -prefix ${sid}_T1w-deobl_nu.nii.gz + +We ran Freesurfer with the -3T flag which runs nu intensity correction, in the creation of a white matter mask for each subject. + +The “scale” block was utilized in afni_proc.py, which scales the mean of each EPI voxel time series to 100; that is, the voxels are scaled separately, not the volumes as a whole. The fluctuations in the resulting time series have an interpretation of local (BOLD) % signal change. Values are truncated to a range of [0,200]. + +Nuisance regression was done including the motion parameters and local white matter voxelwise regressors. +The 6 rigid-body motion parameters (estimated in 3dvolreg) were included, one set of 6 per run. + +Local white matter tissue signals were were included in the regression model set up by the afni_proc.py script as specified by the flags “-regress_anaticor_fast” and "-regress_anaticor_fwhm 20”. The local signal from the eroded white matter is computed summing each EPI volume over the nearby white matter voxels weighted by a Gaussian decay, in this case with a full width half max of 20 mm (https://www.ncbi.nlm.nih.gov/pubmed/20420926). Each EPI voxel time series thus gets a separate ANATICOR regressor, in addition to the usual (global) motion parameter regressors. (The time series regression analysis program 3dREMLfit can deal with voxelwise regressors.) + +Censoring is done with AFNI as part of the regress step +Criteria: ++ the Euclidean norm (enorm) of the 6 motion parameters first temporal differences is calculated, and where enorm is greater than a threshold (here, 0.3 ~mm), both that volume and the preceding one are censored. ++ the fraction of outliers in each (automasked) volume is calculated, and where the fraction is greater than a threshold (here, 0.05), that volume is censored from the regression model. +In most cases, censoring due to excessive “outliers” in a volume coincides with censoring due to excessive motion -- but not always. Both methods are used to be safe. + +No spatial smoothing was applied here during single subject processing. + +Spatial smoothing was applied later (to the individual subject-level effect size estimates “betas”) as part of AFNI's ETAC form of running 3dttest++ for group analysis and clustering, where it applied several different blurs (here, 0, 4, 6, and 8mm Gaussian FWHM applied inside the brain mask using an iterative approach), before combining those results to maintain an overall FPR. + +The list of subjects with number of retained TRs, percent of time points censored, and list of censored TRs is available in the spreadsheet here: +https://docs.google.com/spreadsheets/d/1_T_Y7xaaTV4O-AyUd-kN4hACCMJOAYuUFDqSy1WOcTw/edit?usp=sharing +The subjects not including in the group analysis were those shown in the output of: + gen_ss_review_table.py \ + -outlier_sep space \ + -report_outliers 'censor fraction' GE 0.1 \ + -report_outliers 'average censored motion' GE 0.1 \ + -report_outliers 'max censored displacement' GE 8 \ + -infiles sub*/s*.results/out.ss*.txt + + +We modelled the task using a canonical (only) basis function, AFNI's BLOCK model (an integrated gamma variate function), using response times as the individual event durations. HRF peaks varied, according to the convolution with the response times. +We used the following independent variables: +- for trials with a response, BLOCK, with duration equal to response time, and amplitude modulation parameters (leading to automatically generated parametrically modulated regressors) for gain and loss in dollars +- for trials without a response, BLOCK, with duration of 4 s (the total period in which a subject could respond) +Nuisance regressors: +- A Gaussian weighted local neighborhood of white matter (ANATICOR), leading to 1 voxel-dependent regressor +- Six motion parameters (degrees and mm) per run +- The baseline and temporal drift was modeled as Legendre polynomials of order 4, including 5 regressors per run. +- Generalized linear least squares (GLSQ) regression was carried out, with the temporal noise autocovariance modeled with voxelwise ARMA(1,1) parameters estimated from the GLSQ residuals at each voxel (i.e, REML). + + +The 9 hypotheses were evaluated with 4 group-level whole-brain two-sided t-tests and 1 between group test. The 4 whole-brain tests will be: + - Parametric effect of gain in the equal indifference group + - Parametric effect of gain in the equal range group + - Parametric effect of loss in the equal indifference group + - Parametric effect of loss in the equal range group +The between group test was a two-sided test of difference in the parametric effect of loss between the indifference group and the equal range group. + +""" + +afni_proc.py \ + -script ${expdir}/proc.${subject}.block \ + -scr_overwrite \ + -subj_id ${subject} \ + -out_dir ${expdir}/${subject}.results.block \ + -dsets ${datadir}/${subject}/func/${subject}_task-MGT_run-01_bold.nii.gz \ + ${datadir}/${subject}/func/${subject}_task-MGT_run-02_bold.nii.gz \ + ${datadir}/${subject}/func/${subject}_task-MGT_run-03_bold.nii.gz \ + ${datadir}/${subject}/func/${subject}_task-MGT_run-04_bold.nii.gz \ + -copy_anat ${datadir}/${subject}/anat/${subject}_T1w.nii.gz \ + -anat_has_skull yes \ + -blocks tshift align tlrc volreg mask scale regress \ + -despike_new yes \ + -tlrc_base MNI152_T1_2009c+tlrc \ + -tlrc_NL_warp \ + -align_opts_aea \ + -giant_move \ + -cost lpc+ZZ \ + -volreg_align_to MIN_OUTLIER \ + -volreg_tlrc_warp \ + -volreg_align_e2a \ + -blur_in_automask \ + -regress_stim_times \ + ${datadir}/${subject}/func/times+gain.1D \ + ${datadir}/${subject}/func/times+loss.1D \ + -regress_stim_types AM2 \ + -regress_stim_labels \ + GAIN \ + LOSS \ + -regress_basis \ + 'BLOCK(4,1)' \ + -mask_apply anat \ + -regress_motion_per_run \ + -test_stim_files no \ + -regress_opts_3dD \ + -GOFORIT 8 \ + -jobs 6 \ + -regress_censor_motion 0.2 \ + -regress_apply_mot_types demean deriv \ + -regress_censor_first_trs 3 \ + -regress_est_blur_errts \ + -execute + + + + + diff --git a/narps_open/pipelines/team_I9D6_wip.py b/narps_open/pipelines/team_I9D6_wip.py new file mode 100644 index 00000000..39db821c --- /dev/null +++ b/narps_open/pipelines/team_I9D6_wip.py @@ -0,0 +1,10 @@ +''' +created by team I9D6, reproduced by Narps reproducibility team +creation date: 27 June 2023 +needs script "team_I9D6.firstlevel" and "team_I9D6.secondlevel" +the team : AFNI Version 19.0.24 Tiberius +version afni used by the reproducibility team :AFNI Version 23.0.02 Commodus +Participants not included 016 +Last update: June 2023 +''' + diff --git a/notes.txt b/notes.txt new file mode 100644 index 00000000..8260c233 --- /dev/null +++ b/notes.txt @@ -0,0 +1 @@ +datalad get ./data/original/ds001734/sub-001