first upload into public SAMI repository

sami_examples/DemoOne_BehavEmotionRating.txt

@@ -0,0 +1,24 @@
+s07t21v1.c3d,1,1,1,1,1,1,2,1,1,1,1,1,1,1,1,1,1,1,1
+s07t20v2.c3d,1,1,1,2,2,1,1,1,1,1,1,1,1,1,1,1,1,1,1
+s03t26v1.c3d,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
+s08t12v1.c3d,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
+s05t12v2.c3d,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,1,1,1
+s11t07v1.c3d,1,1,1,1,1,1,2,1,1,1,1,1,1,1,1,1,1,1,1
+s08t17v2.c3d,2,2,2,2,2,2,2,1,3,2,2,3,2,2,3,2,2,2,2
+s10t20v2.c3d,2,2,2,1,2,2,2,2,2,2,2,1,2,2,1,1,2,2,2
+s03t22v2.c3d,2,2,2,2,2,2,2,2,1,2,2,1,2,2,2,2,3,2,2
+s03t28v1.c3d,1,1,2,1,2,2,2,1,2,2,1,1,2,2,1,1,1,4,2
+s03t19v2.c3d,1,1,2,2,2,2,2,2,2,1,2,1,2,2,1,2,3,2,2
+s07t26v3.c3d,3,2,2,1,2,2,2,2,3,1,3,2,2,1,1,1,2,2,2
+s11t20v2.c3d,3,3,3,3,3,3,3,3,3,3,3,3,3,1,3,3,3,3,3
+s03t32v1.c3d,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,3,3
+s10t25v2.c3d,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3
+s07t34v2.c3d,3,3,3,3,3,3,3,3,3,3,3,1,3,3,3,3,3,3,3
+s07t31v2.c3d,3,3,3,3,3,3,3,3,3,3,3,1,3,3,3,3,3,3,3
+s07t35v1.c3d,3,3,1,3,3,3,3,3,3,3,3,3,3,3,3,3,2,3,3
+s10t06v1.c3d,4,4,4,4,4,4,4,3,4,4,4,4,4,4,4,4,4,4,4
+s10t08v1.c3d,4,4,4,4,4,4,1,4,4,4,4,4,4,4,4,4,4,4,4
+s07t03v1.c3d,4,4,4,4,4,4,1,4,4,4,4,4,1,4,4,4,4,4,4
+s07t32v1.c3d,4,3,4,4,3,4,4,3,4,4,4,4,4,4,4,4,4,4,4
+s05t05v2.c3d,4,4,1,4,4,4,3,4,4,4,4,4,4,4,4,4,3,4,4
+s10t04v2.c3d,4,3,4,4,3,4,4,3,4,4,3,4,4,4,4,4,1,4,3

sami_examples/DemoOne_BehavValenceRating.txt

@@ -0,0 +1,24 @@
+s07t21v1.c3d,2,4,5,3,5,4,5,5,3,5,5,5,4,4,4,2,3,3,3
+s07t20v2.c3d,2,5,5,3,3,3,5,4,4,4,4,5,4,2,5,2,3,3,3
+s03t26v1.c3d,2,2,4,3,2,3,5,4,3,3,4,3,4,4,3,4,3,3,2
+s08t12v1.c3d,3,5,5,2,4,4,5,5,4,3,4,2,3,3,4,1,2,4,1
+s05t12v2.c3d,3,2,2,3,2,3,5,4,3,4,4,2,3,3,1,1,3,3,2
+s11t07v1.c3d,2,2,3,2,3,3,5,4,2,4,4,1,3,3,3,3,2,3,1
+s08t17v2.c3d,2,3,2,2,2,5,5,2,-1,2,4,-1,2,4,1,5,3,2,3
+s10t20v2.c3d,2,2,4,2,2,4,4,4,3,3,3,2,3,2,3,1,3,3,2
+s03t22v2.c3d,1,3,3,2,2,2,5,2,1,3,4,3,4,3,1,1,-3,4,2
+s03t28v1.c3d,2,2,3,1,5,3,5,2,3,4,3,2,3,5,3,2,3,-2,2
+s03t19v2.c3d,2,1,3,3,1,2,5,2,2,2,2,1,1,4,0,2,2,3,4
+s07t26v3.c3d,-2,1,3,1,1,1,4,1,-2,0,-2,2,1,2,1,2,3,1,1
+s11t20v2.c3d,-2,-3,-5,-2,-5,-1,-5,-5,-4,-3,-4,-5,-4,2,-5,-2,-3,-5,-4
+s03t32v1.c3d,-2,-2,-5,-4,-5,-2,-5,-5,-3,-4,-4,-5,-4,-5,-5,-5,2,-3,-2
+s10t25v2.c3d,-3,-3,-5,-3,-4,-1,-5,-3,-2,-2,-3,-3,-3,-2,-5,-3,-2,-3,-3
+s07t34v2.c3d,-3,-2,-2,-2,-4,-3,-5,-2,-3,-3,-2,0,-3,-2,-3,-3,-3,-2,-2
+s07t31v2.c3d,-2,-3,-2,-2,-4,-4,-5,-2,-1,-2,-4,0,-2,-4,-3,-1,-3,-1,-2
+s07t35v1.c3d,-4,-1,-3,-2,-3,-2,-4,-1,-2,-4,-3,-4,-2,-3,-2,-2,1,-1,-1
+s10t06v1.c3d,-2,-2,-2,-3,-3,-2,-5,-1,-2,-5,-2,-2,-3,-2,-3,-1,-3,-2,-2
+s10t08v1.c3d,-1,-4,-5,-3,-4,-1,3,-2,-4,-3,-4,-5,-1,-4,-1,-1,-3,-2,-2
+s07t03v1.c3d,-2,-3,-4,-1,-2,-3,2,-3,-3,-3,-3,-4,1,-3,-1,-2,-3,-3,-2
+s07t32v1.c3d,-2,-2,-3,-2,-3,-2,-3,-2,-2,-2,-2,-4,-2,-3,-2,-3,-2,-2,-1
+s05t05v2.c3d,-1,-3,0,-3,-3,-4,-2,-2,-2,-2,-2,-3,-2,-3,-1,-3,-2,-2,-1
+s10t04v2.c3d,-1,-1,-3,-2,-3,-2,-3,-3,-2,-2,0,-2,-4,-3,-2,-2,2,-2,-1

sami_examples/DemoOne_SAMI.m

@@ -0,0 +1,92 @@
+%% example script
+clear all; close all;
+
+% add toolbox to path
+returnHere = pwd;
+cd ../sami_toolbox;
+addpath(genpath(pwd));
+cd(returnHere)
+
+% +++ obligatory: loading userOptions / initializing SAMItoolbox +++++++++++++++++++++++++
+userOptions = DemoOne_defineUserOptions();
+userOptions = sami.initSAMI(userOptions,'c');
+
+redo = 0;
+if redo == 1
+    % +++ loading c3d-files and checking them ++++++++++++++++++++++++++++++++++++++++++++
+    c3dData = sami.c3d.importFiles(userOptions);
+
+    % +++ calculate features +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+    feat_idv = sami.calcFeatures(c3dData, 'idv', userOptions);
+    feat_itx = sami.calcFeatures(c3dData, 'itx', userOptions);
+else
+    load(fullfile(userOptions.rootPath,'c3dData.mat'));
+
+    load(fullfile(userOptions.rootPath,'features_idv.mat'));
+    load(fullfile(userOptions.rootPath,'features_itx.mat'));
+end
+
+% +++ create feature_RDMs ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+RDMs_idv = sami.createFeatureRDMs(feat_idv, userOptions);
+RDMs_itx = sami.createFeatureRDMs(feat_itx, userOptions);
+
+% +++ create model RDMs ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+modelThis = {'emotion','valence'};
+RDMs_stim_models_categorical = sami.createCategoryRDMs(modelThis, 'binary', userOptions);
+
+% +++ create behavioral RDMs +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+[RDMs_behav_val_subj, behav_val_data] = sami.createBehavioralRDMs('DemoOne_BehavValenceRating.txt', 'Valence', 'distance',  userOptions);
+[RDMs_behav_emo_subj, behav_emo_data] = sami.createBehavioralRDMs('DemoOne_BehavEmotionRating.txt', 'Emotion', 'binary', userOptions);
+
+% average across subjects
+RDMs_behav_val = sami.rdm.averageRDMs(RDMs_behav_val_subj,'mean_val_RDM',[1 0 0]);
+RDMs_behav_emo = sami.rdm.averageRDMs(RDMs_behav_emo_subj,'mean_emo_RDM',[1 0 0]);
+
+%% display RDMs/MDS plots
+% +++ show RDMs ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+sami.plotRDMs([RDMs_stim_models_categorical RDMs_idv],userOptions);
+sami.plotRDMs([RDMs_stim_models_categorical RDMs_itx],userOptions);
+sami.plotRDMs([RDMs_behav_val_subj RDMs_behav_val],userOptions);
+sami.plotRDMs([RDMs_behav_emo_subj RDMs_behav_emo],userOptions);
+
+% +++ MDS of Stimuli +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+sami.MDSofStimuli(RDMs_idv(1), 'emotion', userOptions);
+sami.MDSofStimuli(RDMs_idv(1), 'valence', userOptions);
+
+% +++ 2nd order - RDM correlation matrix and MDS +++++++++++++++++++++++++++++++++++++++++
+sami.RDMsPairwiseCorrelations([RDMs_stim_models_categorical RDMs_idv], userOptions, 'CAT and IDV');
+sami.RDMsPairwiseCorrelations([RDMs_stim_models_categorical RDMs_itx], userOptions, 'CAT and ITX');
+sami.RDMsPairwiseCorrelations([RDMs_behav_val RDMs_behav_emo RDMs_idv], userOptions, 'BEHAV and IDV');
+sami.RDMsPairwiseCorrelations([RDMs_behav_val RDMs_behav_emo RDMs_itx], userOptions, 'BEHAV and ITX');
+
+sami.MDSofRDMs([RDMs_stim_models_categorical RDMs_idv], userOptions,'CategoricalModels and IDV');
+sami.MDSofRDMs([RDMs_stim_models_categorical RDMs_itx], userOptions,'CategoricalModels and ITX');
+sami.MDSofRDMs([RDMs_behav_val RDMs_behav_emo RDMs_stim_models_categorical RDMs_idv], userOptions,'Behavior and CategoricalModels and IDV');
+sami.MDSofRDMs([RDMs_behav_val RDMs_behav_emo RDMs_stim_models_categorical RDMs_itx], userOptions,'Behavior and CategoricalModels and ITX');
+
+%% do some statistical analyses, like RSA or ANOVA...
+% +++ compare METRIC behavioral data +++++++++++++++++++++++++++++++++++++++++++++++++++++
+sami.compareBehavData(behav_val_data, 'emotion', 'Valence', userOptions);
+
+% +++ compare CATEGORICAL behavioral data ++++++++++++++++++++++++++++++++++++++++++++++++
+sami.compareBehavCategoricalData(behav_emo_data, 'emotion', 'Emotion', userOptions);
+
+% +++ compare average feature-values between specific categories +++++++++++++++++++++++++
+sami.compareFeatValues(feat_idv, 'emotion', 'IDV', userOptions);
+sami.compareFeatValues(feat_idv, 'valence', 'IDV', userOptions);
+sami.compareFeatValues(feat_itx, 'emotion', 'ITX', userOptions);
+sami.compareFeatValues(feat_itx, 'valence', 'ITX', userOptions);
+
+% +++ compare categoryRDMs with movement RDMs ++++++++++++++++++++++++++++++++++++++++++++
+sami.compareCatRDMs2FeatRDMs(RDMs_stim_models_categorical,RDMs_idv,'Categorical vs IDV',userOptions);
+sami.compareCatRDMs2FeatRDMs(RDMs_stim_models_categorical,RDMs_itx,'Categorical vs ITX',userOptions);
+
+% +++ compare behavioralRDMs with movement RDMs ++++++++++++++++++++++++++++++++++++++++++
+userOptions.rdms_pairWiseCorr = 'Pearson';
+statsA = sami.compareBehavRDMs2FeatRDMs(RDMs_behav_val_subj, RDMs_idv, 'Valence', 'IDV', userOptions);
+statsB = sami.compareBehavRDMs2FeatRDMs(RDMs_behav_val_subj, RDMs_itx, 'Valence', 'ITX', userOptions);
+
+userOptions.rdms_pairWiseCorr = 'Kendall_taua';
+statsC = sami.compareBehavRDMs2FeatRDMs(RDMs_behav_emo_subj, RDMs_idv, 'Emotion', 'IDV', userOptions);
+statsD = sami.compareBehavRDMs2FeatRDMs(RDMs_behav_emo_subj, RDMs_itx, 'Emotion', 'ITX', userOptions);
+

sami_examples/DemoOne_defineUserOptions.m

@@ -0,0 +1,168 @@
+function userOptions = DemoOne_defineUserOptions()
+%  defineUserOptions is a nullary function which initialises a struct
+%  containing the preferences and details for a particular project.
+%  It should be edited to taste before a project is run, and a new
+%  one created for each substantially different project.
+%
+%  For a guide to how to fill out the fields in this file, consult
+%  the documentation folder (particularly the userOptions_guide.m)
+%
+%  A. Zabicki 09-2020
+%__________________________________________________________________________
+
+userOptions.debug = true; % will save and/or display some more information during execution of several functions
+
+%% **********************************************************
+% Project details
+% **********************************************************
+% *** edit how needed *********************
+
+% This name identifies a collection of files which all belong to the same run of a project.
+userOptions.analysisName = 'DemoOne_sami';
+
+% The path leading to where the c3d files are stored.
+userOptions.c3dPath = fullfile(pwd,'DemoOne_c3d');
+
+% *** no need to change here anything *******************************
+% This is the root directory of the project.
+userOptions.rootPath = fullfile(pwd,userOptions.analysisName);
+% *******************************************************************
+
+
+%% **********************************************************
+% c3d file and label settings
+% **********************************************************
+
+% if "Vicon Plug-in Gait" Modell is used and markers are named according to Plug-in Gait
+% and _c3d_personIdentifier, sami_toolbox will transform data automatically
+userOptions.c3d_ViconPluginGait = false;
+
+% if markers are available, but named differently, use this to rename labels of "ownMarker" 
+% into "samiMarker" [Head, LSHO, LELB, LWRI, LHIP, LKNE, LANK, RSHO, RELB, RWRI, RHIP, RKNE, RANK]
+userOptions.c3d_OwnMarker = true;
+userOptions.c3d_MarkerMatching = {...
+    'ownMarker','samiMarker';...
+    'HAND','WRI';...
+    };
+% if specified, user is able to keep own indiviuum identifications,
+% otherwise markers will be renamed, e.g. 'p1HEAD' and 'p2HEAD", automatically
+% userOptions.c3d_personIdentifier = '[[marker]][[person]]';
+
+
+%% **********************************************************
+% descriptions of stimuli: regarding their categories, and how to sort them
+% **********************************************************
+% set category which is used to sort the stimuli according to
+userOptions.stimuli_sorting = 'emotion';
+
+% if filename is specified: "stimulus_settings" will be loaded from this file
+userOptions.stimuli_settings_filename = 'DemoOne_stimuli_settings.txt';
+% else: stimulus_settings have to be defined here
+userOptions.stimuli_settings = {};
+
+% providing labels for each category describing the stimuli
+userOptions.stimuli_naming_key(1).name = 'emotion';
+userOptions.stimuli_naming_key(1).condition = {'happiness','affection','sadness','anger'};
+userOptions.stimuli_naming_key(1).color = {[0 .5 1],[.1 .8 .1],[1 .5 0],[1 0 0]};
+userOptions.stimuli_naming_key(2).name = 'valence';
+userOptions.stimuli_naming_key(2).condition = {'positive','negative'};
+userOptions.stimuli_naming_key(2).color = {[0 .5 1],[1 .5 0]};
+
+% stimuli_labels for MDS plots 
+%    ---> !!! same order as in first column in userOptions.stimuli_settings_filename !!!
+% [userOptions.stimuli_MDS_labels{1:size(userOptions.stimuli_settings,1)-1}] = deal(' ');
+
+%% **********************************************************
+% calculating individual/interaction movement-features 
+%    -> comparing movement-features between stimuli-categories 
+%    -> creating movement/feature-RDMs for stimulus-set
+% **********************************************************
+% set alpha and correction method which will be applied in post-hoc multiple comparisons of feature values
+userOptions.feat_threshold = 0.05;               % default: 0.05
+userOptions.feat_multipleTesting = 'bonferroni'; % ['bonferroni'] | 'tukey-kramer' | 'hsd' | 'lsd' | 'dunn-sidak' | 'scheffe'
+
+% which distance measure to use when calculating feature-RDMs.
+userOptions.feat_distance = 'euclidean';        % input into pdist function, default: 'euclidean'
+
+% should feature-RDM-entries be rank transformed into [0,1] before they're displayed?
+userOptions.feat_rankTransform = false; % !!!!!!!! NOT YET IMPLEMENTED !!!!!!!!!!!!
+
+%% **********************************************************
+% behavioral data: 
+%    -> comparing average behavioral ratings between stimuli-categories
+%    -> creating behavioral-RDMs for each subject
+% **********************************************************
+% set alpha and correction method which will be applied in post-hoc multiple comparisons of behavioral ratings
+userOptions.behav_threshold = 0.05;                 % default: 0.05
+userOptions.behav_multipleTesting = 'bonferroni';   % ['bonferroni'] | 'tukey-kramer' | 'hsd' | 'lsd' | 'dunn-sidak' | 'scheffe'
+
+% which distance measure to use between stimuli-rating-values when calculating subjects behavioral-RDMs
+userOptions.behav_distanceMeasure = 'euclidean';    % input into pdist function, default: 'euclidean'
+
+%% **********************************************************
+% MDS plots
+% **********************************************************
+% what criterion to be minimised in MDS calculation?
+userOptions.MDS_criterion = 'metricstress'; % default: 'metricstress'
+
+% style
+userOptions.MDS_plotLabels = true;  % show labels in MDS-Plot
+userOptions.MDS_plotLegend = true;  % show color-legend in MDS-plot -> useful for "stimuliMDS()"
+userOptions.MDS_dotSize = 20;       % default: 20
+userOptions.MDS_fontSize = 9;       % default: 9
+
+%% **********************************************************
+% second-order-analysis of RDMs
+% **********************************************************
+% which similarity-measure is used for the pair-wise comparison of RDMs
+userOptions.rdms_pairWiseCorr = 'Kendall_taua';
+
+% for 'compareCatRDMs2FeatRDMs' function
+% set alpha and correction method to be applied in pairwise-RDM-correlation analysis
+userOptions.rdms_pairWiseCorrThreshold = 0.05;          % default: 0.05
+userOptions.rdms_pairWiseCorrMultipleTesting = 'holm';  % ['holm'] | 'bonferroni' | 'FDR'
+
+% for 'compareBehavRDMs2FeatRDMs' function
+% set test, alpha and correction method for analysing relatedness of features and behavioral RDMs
+userOptions.rdms_relatednessTest = 'signedRank';        % ['signedRank'] | 'randomisation'
+userOptions.rdms_relatednessThreshold = 0.05;           % default: 0.05
+userOptions.rdms_relatednessMultipleTesting = 'FDR';    % ['FDR'] | 'bonferroni' | 'holm'
+
+% set test, alpha and correction method for analysing relatedness of features and behavioral RDMs
+userOptions.rdms_differencesTest = 'signedRank';        % ['signedRank'] | 'conditionBootstrap'
+userOptions.rdms_differencesThreshold = 0.05;           % default: 0.05
+userOptions.rdms_differencesMultipleTesting = 'FDR';    % ['FDR'] | 'bonferroni' | 'holm'
+
+% some set test, alpha and correction method for analysing relatedness of features and behavioral RDMs
+userOptions.rdms_orderByCorr = true;                    % sort features by height of relatedness? default: true
+userOptions.rdms_nRandomisations = 50000;               % default: 50000 (min. 10,000 highly recommended)
+userOptions.rdms_nBootstrap = 1000;                     % default: 1000
+
+%% **********************************************************
+% everything else, my be set or not 
+%       (here, defaults are used to show what can be edited)
+% **********************************************************
+userOptions.default_modelRDMcolor = [.5 .5 .5];
+userOptions.default_behavRDMcolor = [.9 .2 .1];
+
+% threshold: minimal number of datapoints for parametric group-comparisons (ANOVA, t-test)
+userOptions.stats_minNforSubjectRFXtests = 12;
+% threshold: minimal number of datapoints for NON-parametric group-comparisons (Wilcoxon, Kruskall-Walis)
+userOptions.stats_minNforNonParamTests = 5;
+
+%% **********************************************************
+% handling figures
+% **********************************************************
+% generall displaying all figures?
+userOptions.fig_display = true;     % default: true
+
+% How should figures be outputted?
+userOptions.fig_saveFIG = true;    % default: false
+userOptions.fig_savePDF = true;    % default: false
+userOptions.fig_saveSVG = true;    % default: false
+userOptions.fig_saveTIF = true;    % default: false
+
+% Which dots per inch resolution do we output?
+userOptions.fig_dpi = 300;
+
+end

sami_examples/DemoOne_stimuli_settings.txt

@@ -0,0 +1,25 @@
+filename,emotion,valence
+s07t21v1.c3d,1,1
+s07t20v2.c3d,1,1
+s03t26v1.c3d,1,1
+s08t12v1.c3d,1,1
+s05t12v2.c3d,1,1
+s11t07v1.c3d,1,1
+s08t17v2.c3d,2,1
+s10t20v2.c3d,2,1
+s03t22v2.c3d,2,1
+s03t28v1.c3d,2,1
+s03t19v2.c3d,2,1
+s07t26v3.c3d,2,1
+s11t20v2.c3d,3,2
+s03t32v1.c3d,3,2
+s10t25v2.c3d,3,2
+s07t34v2.c3d,3,2
+s07t31v2.c3d,3,2
+s07t35v1.c3d,3,2
+s10t06v1.c3d,4,2
+s10t08v1.c3d,4,2
+s07t03v1.c3d,4,2
+s07t32v1.c3d,4,2
+s05t05v2.c3d,4,2
+s10t04v2.c3d,4,2