diff --git a/tests/test_twopoint_difference.py b/tests/test_twopoint_difference.py index 303c425d3..5810f0e54 100644 --- a/tests/test_twopoint_difference.py +++ b/tests/test_twopoint_difference.py @@ -132,7 +132,6 @@ def test_5grps_cr2_nframe2(setup_cube): assert(np.array_equal([0, 4, 4, 0, 0], out_gdq[0, :, 100, 100])) -@pytest.mark.xfail def test_4grps_twocrs_2nd_4th(setup_cube): ngroups = 4 data, gdq, nframes, read_noise, rej_threshold = setup_cube(ngroups) @@ -611,7 +610,7 @@ def test_6grps_satat6_crat1(setup_cube): assert (np.array_equal([0, DQFLAGS['JUMP_DET'], 0, 0, 0, DQFLAGS['SATURATED']], out_gdq[0, :, 100, 100])) -@pytest.mark.xfail +@pytest.mark.xfail() def test_6grps_satat6_crat1_flagadjpixels(setup_cube): ngroups = 6 # crmag = 1000 @@ -1019,10 +1018,13 @@ def test_median_func(): arr = np.zeros(4 * 2 * 2).reshape(4, 2, 2) arr[:, 0, 0] = np.array([-1., -2., np.nan, np.nan]) assert calc_med_first_diffs(arr)[0, 0] == -1 -@pytest.mark.skip("Used for local testing") -def test_sigma_clip(): + + +# TODO: The input data for this is missing, need to find it +@pytest.mark.xfail(reason="Missing Input Data") +def test_sigma_clip(tmp_path, data_path): # hdul = fits.open('TSOjump_sc__refpix.fits') - hdul = fits.open('lrs_TSOjump_sigmaclip5_00_refpix.fits') + hdul = fits.open(data_path / 'lrs_TSOjump_sigmaclip5_00_refpix.fits') data = hdul['SCI'].data * 4.0 gdq = hdul['GROUPDQ'].data indata = data[:53, :, :, :] @@ -1038,9 +1040,10 @@ def test_sigma_clip(): after_jump_flag_e2=0.0, after_jump_flag_n2=0, copy_arrs=True, minimum_groups=3, minimum_sigclip_groups=50,) - fits.writeto("outgdq.fits", gdq, overwrite=True) -@pytest.mark.skip("Used for local testing") -def test_first_grp_flag_issue(): + fits.writeto(tmp_path / "outgdq.fits", gdq, overwrite=True) + + +def test_first_grp_flag_issue(tmp_path): nints = 8 nrows = 2 ncols = 2 @@ -1059,9 +1062,10 @@ def test_first_grp_flag_issue(): after_jump_flag_e1=0.0, after_jump_flag_n1=0, after_jump_flag_e2=0.0, after_jump_flag_n2=0, copy_arrs=True, minimum_groups=3, minimum_sigclip_groups=50) - fits.writeto("outgdq.fits",gdq, overwrite=True) -@pytest.mark.skip("Used for local testing") -def test_5grp_TSO(): + fits.writeto(tmp_path / "outgdq.fits",gdq, overwrite=True) + + +def test_5grp_TSO(tmp_path): nints=20 nrows = 2 ncols = 2 @@ -1082,10 +1086,13 @@ def test_5grp_TSO(): after_jump_flag_e1=0.0, after_jump_flag_n1=0, after_jump_flag_e2=0.0, after_jump_flag_n2=0, copy_arrs=True, minimum_groups=3, minimum_sigclip_groups=5000) - fits.writeto("new_gdq.fits", gdq, overwrite=True) -@pytest.mark.skip("Used for local testing") -def test_5grp_realTSO(): - hdul = fits.open("obs2508_cutout_jump.fits") + fits.writeto(tmp_path / "new_gdq.fits", gdq, overwrite=True) + + +# TODO: The input data for this is missing, need to find it +@pytest.mark.xfail(reason="Missing Input Data") +def test_5grp_realTSO(tmp_path, data_path): + hdul = fits.open(data_path / "obs2508_cutout_jump.fits") gdq = hdul['groupdq'].data data = hdul['sci'].data readnoise = 25 @@ -1096,10 +1103,13 @@ def test_5grp_realTSO(): after_jump_flag_e1=0.0, after_jump_flag_n1=0, after_jump_flag_e2=0.0, after_jump_flag_n2=0, copy_arrs=True, minimum_groups=3, minimum_sigclip_groups=15000) - fits.writeto("new_gdq_cutout.fits", gdq, overwrite=True) -@pytest.mark.skip("Used for local testing") -def test_5grp_allTSO(): - hdul = fits.open("obs2508_noshower_sigclip_base_00_dark_current.fits") + fits.writeto(tmp_path / "new_gdq_cutout.fits", gdq, overwrite=True) + + +# TODO: The input data for this is missing, need to find it +@pytest.mark.xfail(reason="Missing Input Data") +def test_5grp_allTSO(tmp_path, data_path): + hdul = fits.open(data_path / "obs2508_noshower_sigclip_base_00_dark_current.fits") gdq = hdul['groupdq'].data data = hdul['sci'].data * 5.5 readnoise = 5.5 * 6 @@ -1110,11 +1120,13 @@ def test_5grp_allTSO(): after_jump_flag_e1=0.0, after_jump_flag_n1=0, after_jump_flag_e2=0.0, after_jump_flag_n2=0, copy_arrs=True, minimum_groups=3, minimum_sigclip_groups=15000) - fits.writeto("new_no_sigma_clip_gdq.fits", gdq, overwrite=True) + fits.writeto(tmp_path / "new_no_sigma_clip_gdq.fits", gdq, overwrite=True) + -@pytest.mark.skip("Used for local testing") -def test_1059(): - hdul = fits.open("data/nircam_1059_00_dark_current.fits") +# TODO: The input data for this is missing, need to find it +@pytest.mark.xfail(reason="Missing Input Data") +def test_1059(tmp_path, data_path): + hdul = fits.open(data_path / "nircam_1059_00_dark_current.fits") gdq = hdul['groupdq'].data data = hdul['sci'].data * 5.5 readnoise = 5.5 * 6 @@ -1125,11 +1137,13 @@ def test_1059(): after_jump_flag_e1=0.0, after_jump_flag_n1=0, after_jump_flag_e2=0.0, after_jump_flag_n2=0, copy_arrs=True, minimum_groups=3, minimum_sigclip_groups=15000) - fits.writeto("new_no_sigma_clip_gdq.fits", gdq, overwrite=True) + fits.writeto(tmp_path / "new_no_sigma_clip_gdq.fits", gdq, overwrite=True) + -@pytest.mark.skip("Used for local testing") -def test_1952(): - hdul = fits.open("data/obs1952_sc_shower_00_dark_current.fits") +# TODO: The input data for this is missing, need to find it +@pytest.mark.xfail(reason="Missing Input Data") +def test_1952(tmp_path, data_path): + hdul = fits.open(data_path / "obs1952_sc_shower_00_dark_current.fits") gdq = hdul['groupdq'].data data = hdul['sci'].data * 5.5 readnoise = 5.5 * 6 @@ -1140,4 +1154,4 @@ def test_1952(): after_jump_flag_e1=100.0 * gain, after_jump_flag_n1=20/2.77, after_jump_flag_e2=3000.0 * gain, after_jump_flag_n2=1000/2.77, copy_arrs=True, minimum_groups=3, minimum_sigclip_groups=150) - fits.writeto("new_obs1952_gdq.fits", gdq, overwrite=True) + fits.writeto(tmp_path / "new_obs1952_gdq.fits", gdq, overwrite=True)