mainak@ubuntu:~/mne-python$ nosetests mne/tests /home/mainak/mne-python/mne/datasets/sample/sample.py:134: UserWarning: Sample dataset (version 0.6) is older than mne-python (version 0.6.git). If the examples fail, you may need to update the sample dataset by using force_update=True % (sample_version, mne_version)) Qt: Session management error: Authentication Rejected, reason : None of the authentication protocols specified are supported and host-based authentication failed Test IO for noise covariance matrices ... ok Test estimation from raw on continuous recordings (typically empty room) ... ok Test estimation from raw with triggers ... ok Test arithmetic with noise covariance matrices ... ok Test cov regularization ... ok Test whitening of evoked data ... ok Test IO for .dip files ... ok Test epochs from raw files with IO as fif file ... ok Test handling projection (apply proj in Raw or in Epochs) ... ok Test arithmetic of evoked data ... ok Test IO of evoked data made from epochs ... ok Test calculation and read/write of standard error ... ok Test of epochs rejection ... ok Test preload of epochs ... ok Test of indexing and slicing operations ... ok Test of average obtained vs C code ... ok Test epochs Pandas exporter ... ok Test of crop of epochs ... ok Test of resample of epochs ... [Parallel(n_jobs=2)]: Done 1 out of 170 | elapsed: 0.0s remaining: 1.9s [Parallel(n_jobs=2)]: Done 150 out of 752 | elapsed: 0.2s remaining: 0.9s [Parallel(n_jobs=2)]: Done 301 out of 752 | elapsed: 0.4s remaining: 0.6s [Parallel(n_jobs=2)]: Done 452 out of 752 | elapsed: 0.6s remaining: 0.4s [Parallel(n_jobs=2)]: Done 603 out of 752 | elapsed: 0.8s remaining: 0.2s [Parallel(n_jobs=2)]: Done 752 out of 752 | elapsed: 1.0s finished ok Test detrending of epochs ... ok Test of bootstrapping of epochs ... ok Test copy epochs ... ok Test test_to_nitime ... ok Test epoch count equalization and condition combining ... ok Test accessing epochs by event name ... ok Test SSP proj methods from ProjMixin class ... ok Test IO for events ... ok Test find events in raw file ... ok Test making events of a fixed length ... ok Test defining response events ... ok Test notch filters ... ok Test low-, band-, high-pass, and band-stop filters plus resampling ... 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SKIP: Skipping test: test_cuda CUDA not initialized Test zeroth and first order detrending ... ok Test numpy.in1d() replacement ... ok Test numpy.tril_indices() replacement ... ok Test numpy.unravel_index() replacement ... ok Test numpy.copysign() replacement ... ok Test firwin2 backport ... ok Test IIR filtfilt replacement ... ok Test IO for forward solutions ... FAIL Test projection of source space data to sensor space ... ok Test restriction of source space to source SourceEstimate ... ok Test restriction of source space to label ... ok Test averaging forward solutions ... ok Test making forward solution from python ... FAIL Test label subject name extraction ... ok Test label addition ... ok Test IO for label + stc files ... ok Test IO of label files ... ok Test reading labels from parcellation ... ok Test reading labels from parc. by comparing with mne_annot2labels ... ERROR Test stc_to_label ... ok Test inter-subject label morphing ... [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.3s remaining: 0.0s [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.3s finished [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.4s remaining: 0.0s [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.4s finished [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.3s remaining: 0.0s [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.3s finished [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.4s remaining: 0.0s [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.4s finished [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.3s remaining: 0.0s [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.3s finished [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.4s remaining: 0.0s [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.4s finished [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.3s remaining: 0.0s [Parallel(n_jobs=2)]: Done 1 out of 1 | elapsed: 0.3s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.1s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.1s finished ok Test generation of circular source labels ... ok Test extracting label data from SourceEstimate ... ok Test parsing of .ave file ... ok Test sensitivity map computation ... ok Test SSP computation on epochs ... [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.0s [Parallel(n_jobs=1)]: Done 7 out of 7 | elapsed: 0.3s finished [Parallel(n_jobs=2)]: Done 1 out of 7 | elapsed: 0.1s remaining: 0.6s [Parallel(n_jobs=2)]: Done 3 out of 7 | elapsed: 0.2s remaining: 0.2s [Parallel(n_jobs=2)]: Done 5 out of 7 | elapsed: 0.2s remaining: 0.1s [Parallel(n_jobs=2)]: Done 7 out of 7 | elapsed: 0.3s finished ok Test SSP computation on raw ... [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.0s [Parallel(n_jobs=1)]: Done 16 out of 16 | elapsed: 0.3s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.1s [Parallel(n_jobs=1)]: Done 6 out of 6 | elapsed: 0.4s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.2s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.4s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.5s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.5s finished [Parallel(n_jobs=2)]: Done 1 out of 214 | elapsed: 0.0s remaining: 2.8s [Parallel(n_jobs=2)]: Done 74 out of 376 | elapsed: 0.1s remaining: 0.4s [Parallel(n_jobs=2)]: Done 150 out of 376 | elapsed: 0.2s remaining: 0.3s [Parallel(n_jobs=2)]: Done 226 out of 376 | elapsed: 0.3s remaining: 0.2s [Parallel(n_jobs=2)]: Done 302 out of 376 | elapsed: 0.3s remaining: 0.1s [Parallel(n_jobs=2)]: Done 376 out of 376 | elapsed: 0.4s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.2s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.4s finished ok Test reading of selections ... ok Test reading and writing volume STCs ... ok Test stc expansion ... ok Test IO for STC files ... ok Test IO for w files ... ok Test arithmetic for STC files ... ok Test stc methods lh_data, rh_data, bin(), center_of_mass(), resample() ... 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[Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.2s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.4s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.9s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.9s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.9s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.9s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.2s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.4s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.9s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.9s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.9s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.9s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.9s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.9s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.9s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.9s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.9s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.9s finished [Parallel(n_jobs=1)]: Done 1 jobs | elapsed: 0.9s [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.9s finished ok Test applying linear (time) transform to data ... ok Test that modifying the stc data removes the kernel and sensor data ... ok Test spatio-temporal connectivity from triangles ... ok Test spatio-temporal connectivity from source spaces ... ok Test reading of source space meshes ... ok Test writing and reading of source spaces ... ok Test conversion of vertices to MNI coordinates ... ok Test equivalence of vert_to_mni for nibabel and freesurfer ... ok Test reading of bem surfaces ... ok Test reading and writing of Freesurfer surface mesh files ... ok Test logging (to file) ... ok Test mne-python config file support ... ok Test show_fiff ... ok Test plotting of ERP topography ... ok Test plotting of TFR ... ok Test plotting of power ... ok Test plotting of epochs image topography ... ok Test plotting of evoked ... ok Test plotting of (sparse) source estimates ... ok Test plotting of covariances ... ok Test plotting of ICA panel ... ok Test plotting of epochs image ... ok Test plotting connectivity circle ... ok Test plotting a drop log ... ok Test plotting of raw data ... ok Test comparing fiff files ... ok ====================================================================== ERROR: Test reading labels from parc. by comparing with mne_annot2labels ---------------------------------------------------------------------- Traceback (most recent call last): File "/usr/local/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest self.test(*self.arg) File "/usr/lib/python2.7/dist-packages/numpy/testing/decorators.py", line 146, in skipper_func return f(*args, **kwargs) File "/home/mainak/mne-python/mne/tests/test_label.py", line 201, in test_labels_from_parc_annot2labels labels_mne = _mne_annot2labels('sample', subjects_dir, 'aparc') File "/home/mainak/mne-python/mne/tests/test_label.py", line 190, in _mne_annot2labels % st) RuntimeError: mne_annot2labels non-zero exit status 256 -------------------- >> begin captured stdout << --------------------- Reading labels from parcellation.. read 34 labels from /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/label/lh.aparc.annot read 34 labels from /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/label/rh.aparc.annot [done] --------------------- >> end captured stdout << ---------------------- -------------------- >> begin captured logging << -------------------- mne: INFO: Reading labels from parcellation.. mne: INFO: read 34 labels from /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/label/lh.aparc.annot mne: INFO: read 34 labels from /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/label/rh.aparc.annot mne: INFO: [done] --------------------- >> end captured logging << --------------------- ====================================================================== FAIL: Test IO for forward solutions ---------------------------------------------------------------------- Traceback (most recent call last): File "/usr/local/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest self.test(*self.arg) File "/home/mainak/mne-python/mne/tests/test_forward.py", line 45, in test_io_forward assert_equal(leadfield.shape, (306, 22494)) File "/usr/lib/python2.7/dist-packages/numpy/testing/utils.py", line 251, in assert_equal assert_equal(actual[k], desired[k], 'item=%r\n%s' % (k,err_msg), verbose) File "/usr/lib/python2.7/dist-packages/numpy/testing/utils.py", line 313, in assert_equal raise AssertionError(msg) AssertionError: Items are not equal: item=1 ACTUAL: 22488 DESIRED: 22494 >> raise AssertionError('\nItems are not equal:\nitem=1\n\n ACTUAL: 22488\n DESIRED: 22494') -------------------- >> begin captured stdout << --------------------- Reading forward solution from /home/mainak/mne-python/examples/MNE-sample-data/MEG/sample/sample_audvis-meg-oct-6-fwd.fif... Reading a source space... Computing patch statistics... Patch information added... Distance information added... [done] Reading a source space... Computing patch statistics... Patch information added... Distance information added... [done] 2 source spaces read Desired named matrix (kind = 3523) not available Read MEG forward solution (7496 sources, 306 channels, free orientations) Source spaces transformed to the forward solution coordinate frame Cartesian source orientations... [done] Reading forward solution from /home/mainak/mne-python/examples/MNE-sample-data/MEG/sample/sample_audvis-meg-oct-6-fwd.fif... Reading a source space... Computing patch statistics... Patch information added... Distance information added... [done] Reading a source space... Computing patch statistics... Patch information added... Distance information added... [done] 2 source spaces read Desired named matrix (kind = 3523) not available Read MEG forward solution (7496 sources, 306 channels, free orientations) Source spaces transformed to the forward solution coordinate frame Converting to surface-based source orientations... Average patch normals will be employed in the rotation to the local surface coordinates.... [done] --------------------- >> end captured stdout << ---------------------- -------------------- >> begin captured logging << -------------------- mne: INFO: Reading forward solution from /home/mainak/mne-python/examples/MNE-sample-data/MEG/sample/sample_audvis-meg-oct-6-fwd.fif... mne: INFO: Reading a source space... mne: INFO: Computing patch statistics... mne: INFO: Patch information added... mne: INFO: Distance information added... mne: INFO: [done] mne: INFO: Reading a source space... mne: INFO: Computing patch statistics... mne: INFO: Patch information added... mne: INFO: Distance information added... mne: INFO: [done] mne: INFO: 2 source spaces read mne: INFO: Desired named matrix (kind = 3523) not available mne: INFO: Read MEG forward solution (7496 sources, 306 channels, free orientations) mne: INFO: Source spaces transformed to the forward solution coordinate frame mne: INFO: Cartesian source orientations... mne: INFO: [done] mne: INFO: Reading forward solution from /home/mainak/mne-python/examples/MNE-sample-data/MEG/sample/sample_audvis-meg-oct-6-fwd.fif... mne: INFO: Reading a source space... mne: INFO: Computing patch statistics... mne: INFO: Patch information added... mne: INFO: Distance information added... mne: INFO: [done] mne: INFO: Reading a source space... mne: INFO: Computing patch statistics... mne: INFO: Patch information added... mne: INFO: Distance information added... mne: INFO: [done] mne: INFO: 2 source spaces read mne: INFO: Desired named matrix (kind = 3523) not available mne: INFO: Read MEG forward solution (7496 sources, 306 channels, free orientations) mne: INFO: Source spaces transformed to the forward solution coordinate frame mne: INFO: Converting to surface-based source orientations... mne: INFO: Average patch normals will be employed in the rotation to the local surface coordinates.... mne: INFO: [done] --------------------- >> end captured logging << --------------------- ====================================================================== FAIL: Test making forward solution from python ---------------------------------------------------------------------- Traceback (most recent call last): File "/usr/local/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest self.test(*self.arg) File "/usr/lib/python2.7/dist-packages/numpy/testing/decorators.py", line 146, in skipper_func return f(*args, **kwargs) File "/home/mainak/mne-python/mne/tests/test_forward.py", line 312, in test_do_forward_solution assert_equal(fwd_py['sol']['data'].shape, (306, 22494)) File "/usr/lib/python2.7/dist-packages/numpy/testing/utils.py", line 251, in assert_equal assert_equal(actual[k], desired[k], 'item=%r\n%s' % (k,err_msg), verbose) File "/usr/lib/python2.7/dist-packages/numpy/testing/utils.py", line 313, in assert_equal raise AssertionError(msg) AssertionError: Items are not equal: item=1 ACTUAL: 22488 DESIRED: 22494 >> raise AssertionError('\nItems are not equal:\nitem=1\n\n ACTUAL: 22488\n DESIRED: 22494') -------------------- >> begin captured stdout << --------------------- Opening raw data file /home/mainak/mne-python/mne/tests/../fiff/tests/data/test_raw.fif... Read a total of 3 projection items: PCA-v1 (1 x 102) idle PCA-v2 (1 x 102) idle PCA-v3 (1 x 102) idle Range : 25800 ... 40199 = 42.956 ... 66.930 secs Ready. Overwriting existing file. Running forward solution generation command: ['mne_do_forward_solution', '--subject', 'sample', '--meas', '/home/mainak/mne-python/mne/tests/../fiff/tests/data/test_raw.fif', '--fwd', 'test.fif', '--destdir', '/tmp/tmpl661XG', '--trans', u'/home/mainak/mne-python/examples/MNE-sample-data/MEG/sample/sample_audvis_raw-trans.fif', '--overwrite'] and subjects_dir /host/Users/Mainak/Desktop/Python/GSoc/Tools/freesurfer/subjects Adding average EEG reference projection. Created an SSP operator (subspace dimension = 4) 1 matching events found Reading 0 ... 601 = 0.000 ... 1.001 secs... [done] Applying baseline correction ... (mode: mean) Running forward solution generation command: ['mne_do_forward_solution', '--subject', 'sample', '--meas', '/tmp/tmprCVBPP/evoked.fif', '--fwd', 'temp-fwd.fif', '--destdir', '/tmp/tmprCVBPP', '--spacing', 'oct-6', '--mindist', '5', '--bem', 'sample-5120', '--mri', u'/home/mainak/mne-python/examples/MNE-sample-data/MEG/sample/sample_audvis_raw-trans.fif', '--megonly'] and subjects_dir /home/mainak/mne-python/examples/MNE-sample-data/subjects Stdout: Stderr: mne_forward_solution version 2.9 compiled at Apr 16 2013 04:18:00 Source space : /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/bem/sample-oct-6-src.fif MRI -> head transform source : /home/mainak/mne-python/examples/MNE-sample-data/MEG/sample/sample_audvis_raw-trans.fif Measurement data : /tmp/tmprCVBPP/evoked.fif BEM model : /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/bem/sample-5120-bem.fif Accurate field computations Do computations in head coordinates. Free source orientations Destination for the solution : /tmp/tmprCVBPP/temp-fwd.fif Reading /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/bem/sample-oct-6-src.fif... Read 2 source spaces a total of 8196 active source locations Coordinate transformation: MRI (surface RAS) -> head 0.999310 0.009985 -0.035787 -3.17 mm 0.012759 0.812405 0.582954 6.86 mm 0.034894 -0.583009 0.811716 28.88 mm 0.000000 0.000000 0.000000 1.00 Read 306 MEG channels from /tmp/tmprCVBPP/evoked.fif Read 60 EEG channels from /tmp/tmprCVBPP/evoked.fif Coordinate transformation: MEG device -> head 0.991420 -0.039936 -0.124467 -6.13 mm 0.060661 0.984012 0.167456 0.06 mm 0.115790 -0.173570 0.977991 64.74 mm 0.000000 0.000000 0.000000 1.00 EEG not requested. EEG channels omitted. 57 coil definitions read Head coordinate coil definitions created. Source spaces are now in head coordinates. Setting up the BEM model using /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/bem/sample-5120-bem-sol.fif... Loading surfaces... Triangle normals and neighboring triangles...[done] Vertex neighbors...[done] Distances between neighboring vertices...[15360 distances done] Homogeneous model surface loaded. Loading the solution matrix... Loaded linear collocation BEM solution from /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/bem/sample-5120-bem-sol.fif Employing the head->MRI coordinate transform with the BEM model. BEM model /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/bem/sample-5120-bem-sol.fif is now set up Source spaces are in head coordinates. Checking that the sources are inside the inner skull and at least 5.0 mm away (will take a few...) 2 source space points omitted because they are outside the inner skull surface. 366 source space points omitted because of the 5.0-mm distance limit. 1 source space points omitted because they are outside the inner skull surface. 331 source space points omitted because of the 5.0-mm distance limit. Thank you for waiting. Setting up compensation data... No compensation set. Nothing more to do. Composing the field computation matrix...[done] 2 processors. I will use one thread for each of the 2 source spaces. Computing MEG at 7496 source locations (free orientations)...done. writing /tmp/tmprCVBPP/temp-fwd.fif...done Finished. Reading forward solution from /tmp/tmprCVBPP/temp-fwd.fif... Reading a source space... [done] Reading a source space... [done] 2 source spaces read Desired named matrix (kind = 3523) not available Read MEG forward solution (7496 sources, 306 channels, free orientations) Source spaces transformed to the forward solution coordinate frame Cartesian source orientations... [done] Reading forward solution from /home/mainak/mne-python/examples/MNE-sample-data/MEG/sample/sample_audvis-meg-oct-6-fwd.fif... Reading a source space... Computing patch statistics... Patch information added... Distance information added... [done] Reading a source space... Computing patch statistics... Patch information added... Distance information added... [done] 2 source spaces read Desired named matrix (kind = 3523) not available Read MEG forward solution (7496 sources, 306 channels, free orientations) Source spaces transformed to the forward solution coordinate frame Cartesian source orientations... [done] --------------------- >> end captured stdout << ---------------------- -------------------- >> begin captured logging << -------------------- mne: INFO: Opening raw data file /home/mainak/mne-python/mne/tests/../fiff/tests/data/test_raw.fif... mne: INFO: Read a total of 3 projection items: mne: INFO: PCA-v1 (1 x 102) idle mne: INFO: PCA-v2 (1 x 102) idle mne: INFO: PCA-v3 (1 x 102) idle mne: INFO: Range : 25800 ... 40199 = 42.956 ... 66.930 secs mne: INFO: Ready. mne: INFO: Overwriting existing file. mne: INFO: Running forward solution generation command: ['mne_do_forward_solution', '--subject', 'sample', '--meas', '/home/mainak/mne-python/mne/tests/../fiff/tests/data/test_raw.fif', '--fwd', 'test.fif', '--destdir', '/tmp/tmpl661XG', '--trans', u'/home/mainak/mne-python/examples/MNE-sample-data/MEG/sample/sample_audvis_raw-trans.fif', '--overwrite'] and subjects_dir /host/Users/Mainak/Desktop/Python/GSoc/Tools/freesurfer/subjects mne: INFO: Adding average EEG reference projection. mne: INFO: Created an SSP operator (subspace dimension = 4) mne: INFO: 1 matching events found mne: INFO: Reading 0 ... 601 = 0.000 ... 1.001 secs... mne: INFO: [done] mne: INFO: Applying baseline correction ... (mode: mean) mne: INFO: Running forward solution generation command: ['mne_do_forward_solution', '--subject', 'sample', '--meas', '/tmp/tmprCVBPP/evoked.fif', '--fwd', 'temp-fwd.fif', '--destdir', '/tmp/tmprCVBPP', '--spacing', 'oct-6', '--mindist', '5', '--bem', 'sample-5120', '--mri', u'/home/mainak/mne-python/examples/MNE-sample-data/MEG/sample/sample_audvis_raw-trans.fif', '--megonly'] and subjects_dir /home/mainak/mne-python/examples/MNE-sample-data/subjects mne: INFO: Stdout: mne: INFO: Stderr: mne_forward_solution version 2.9 compiled at Apr 16 2013 04:18:00 Source space : /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/bem/sample-oct-6-src.fif MRI -> head transform source : /home/mainak/mne-python/examples/MNE-sample-data/MEG/sample/sample_audvis_raw-trans.fif Measurement data : /tmp/tmprCVBPP/evoked.fif BEM model : /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/bem/sample-5120-bem.fif Accurate field computations Do computations in head coordinates. Free source orientations Destination for the solution : /tmp/tmprCVBPP/temp-fwd.fif Reading /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/bem/sample-oct-6-src.fif... Read 2 source spaces a total of 8196 active source locations Coordinate transformation: MRI (surface RAS) -> head 0.999310 0.009985 -0.035787 -3.17 mm 0.012759 0.812405 0.582954 6.86 mm 0.034894 -0.583009 0.811716 28.88 mm 0.000000 0.000000 0.000000 1.00 Read 306 MEG channels from /tmp/tmprCVBPP/evoked.fif Read 60 EEG channels from /tmp/tmprCVBPP/evoked.fif Coordinate transformation: MEG device -> head 0.991420 -0.039936 -0.124467 -6.13 mm 0.060661 0.984012 0.167456 0.06 mm 0.115790 -0.173570 0.977991 64.74 mm 0.000000 0.000000 0.000000 1.00 EEG not requested. EEG channels omitted. 57 coil definitions read Head coordinate coil definitions created. Source spaces are now in head coordinates. Setting up the BEM model using /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/bem/sample-5120-bem-sol.fif... Loading surfaces... Triangle normals and neighboring triangles...[done] Vertex neighbors...[done] Distances between neighboring vertices...[15360 distances done] Homogeneous model surface loaded. Loading the solution matrix... Loaded linear collocation BEM solution from /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/bem/sample-5120-bem-sol.fif Employing the head->MRI coordinate transform with the BEM model. BEM model /home/mainak/mne-python/examples/MNE-sample-data/subjects/sample/bem/sample-5120-bem-sol.fif is now set up Source spaces are in head coordinates. Checking that the sources are inside the inner skull and at least 5.0 mm away (will take a few...) 2 source space points omitted because they are outside the inner skull surface. 366 source space points omitted because of the 5.0-mm distance limit. 1 source space points omitted because they are outside the inner skull surface. 331 source space points omitted because of the 5.0-mm distance limit. Thank you for waiting. Setting up compensation data... No compensation set. Nothing more to do. Composing the field computation matrix...[done] 2 processors. I will use one thread for each of the 2 source spaces. Computing MEG at 7496 source locations (free orientations)...done. writing /tmp/tmprCVBPP/temp-fwd.fif...done Finished. mne: INFO: Reading forward solution from /tmp/tmprCVBPP/temp-fwd.fif... mne: INFO: Reading a source space... mne: INFO: [done] mne: INFO: Reading a source space... mne: INFO: [done] mne: INFO: 2 source spaces read mne: INFO: Desired named matrix (kind = 3523) not available mne: INFO: Read MEG forward solution (7496 sources, 306 channels, free orientations) mne: INFO: Source spaces transformed to the forward solution coordinate frame mne: INFO: Cartesian source orientations... mne: INFO: [done] mne: INFO: Reading forward solution from /home/mainak/mne-python/examples/MNE-sample-data/MEG/sample/sample_audvis-meg-oct-6-fwd.fif... mne: INFO: Reading a source space... mne: INFO: Computing patch statistics... mne: INFO: Patch information added... mne: INFO: Distance information added... mne: INFO: [done] mne: INFO: Reading a source space... mne: INFO: Computing patch statistics... mne: INFO: Patch information added... mne: INFO: Distance information added... mne: INFO: [done] mne: INFO: 2 source spaces read mne: INFO: Desired named matrix (kind = 3523) not available mne: INFO: Read MEG forward solution (7496 sources, 306 channels, free orientations) mne: INFO: Source spaces transformed to the forward solution coordinate frame mne: INFO: Cartesian source orientations... mne: INFO: [done] --------------------- >> end captured logging << --------------------- Name Stmts Miss Cover Missing --------------------------------------------------------------- mne 35 1 97% 68 mne.baseline 37 6 84% 54, 72-73, 77-79 mne.beamformer 1 0 100% mne.beamformer._lcmv 105 2 98% 134, 328 mne.connectivity 2 0 100% mne.connectivity.spectral 420 23 95% 34, 37, 40, 43, 310, 320, 349, 359, 366, 423, 653, 663, 670, 733, 736, 750, 812-814, 837, 849, 879, 937, 941 mne.connectivity.utils 14 2 86% 11, 14 mne.cov 317 21 93% 29, 32, 83-85, 109, 113, 121-123, 177, 270, 354, 366, 374, 376, 448, 480-483, 613, 678 mne.cuda 165 112 32% 9-10, 45-104, 156-190, 217-224, 280-316, 361-386 mne.datasets 2 0 100% mne.datasets.megsim 1 0 100% mne.datasets.megsim.megsim 68 58 15% 68-132, 184-195 mne.datasets.megsim.urls 25 9 64% 150-160 mne.datasets.sample 1 0 100% mne.datasets.sample.sample 73 33 55% 58, 70-103, 107-116, 126-127 mne.dipole 19 1 95% 41 mne.epochs 685 66 90% 214, 216, 219, 221, 252, 260, 263, 266-268, 281, 333, 368, 371, 380, 387, 396, 406, 463, 495, 536, 545, 550, 583, 590-602, 634, 693, 730, 762, 767, 769-771, 774, 776-778, 823, 931-932, 1020-1021, 1097, 1154, 1157, 1159, 1162, 1209, 1224, 1292, 1341-1342, 1346-1347, 1366-1367, 1392, 1395-1396, 1449 mne.event 266 28 89% 52, 61, 106, 121-123, 135, 145-146, 158, 220, 230, 312, 315-317, 496-497, 511, 564-565, 601, 649-654, 662, 665, 676 mne.fiff 8 0 100% mne.fiff.channels 12 0 100% mne.fiff.compensator 15 1 93% 21 mne.fiff.constants 506 0 100% mne.fiff.cov 89 8 91% 52, 64, 69, 79, 86, 107-109 mne.fiff.ctf 129 17 87% 19, 49-54, 60, 68, 74, 81, 87, 94, 99, 138, 161, 183, 186, 196, 199 mne.fiff.evoked 324 52 84% 98, 107-108, 112-113, 120-121, 148-149, 156, 176-184, 187, 191-206, 224-225, 241-242, 250-253, 256-257, 300-304, 411-412, 448-449, 539-540, 578-579 mne.fiff.matrix 59 10 83% 59-62, 67, 74, 79, 108-111 mne.fiff.meas_info 243 20 92% 52, 54, 59, 61, 124, 127, 130, 133, 156, 158, 182-184, 201, 210-213, 217-219, 340 mne.fiff.open 103 8 92% 67, 70, 73, 78, 134, 170-171, 193 mne.fiff.pick 165 29 82% 42, 49-62, 172-177, 181, 203, 205, 211, 216, 257, 285, 291, 390, 409-411, 448 mne.fiff.proj 230 16 93% 99, 126-128, 239, 245, 258, 264, 270, 276, 285, 377, 383, 393, 403, 558, 613 mne.fiff.raw 722 80 89% 81-83, 140-141, 174-176, 179, 210-212, 224-225, 231, 240-244, 250, 259-260, 270-274, 318, 337, 342, 348, 416, 420, 560, 562, 565-574, 676, 678, 732, 798, 800, 802, 882-884, 901, 907, 937-940, 1033-1037, 1122, 1129, 1327-1328, 1393-1394, 1448, 1465, 1475, 1505, 1507, 1509, 1593, 1770, 1773, 1787-1790, 1810, 1822, 1825, 1827, 1832, 1834-1837 mne.fiff.tag 245 43 82% 42-47, 50-59, 118, 152, 154, 156, 159, 221, 238, 247, 255-266, 279, 291-296, 307, 314, 317, 323, 350-354, 418, 437-440, 447 mne.fiff.tree 95 2 98% 23-24 mne.fiff.write 195 4 98% 66-68, 305 mne.filter 430 42 90% 79, 109, 112, 116, 470, 474, 487, 493, 580, 589, 681, 685, 694, 706, 709-713, 783, 866, 873, 981, 994-1001, 1075, 1146, 1210, 1213, 1217, 1243-1245, 1277, 1283, 1293, 1320-1321, 1336 mne.fixes 191 83 57% 27-44, 48-65, 76-81, 84-89, 99, 103-108, 114-116, 121, 126-131, 136, 144, 165, 170, 183, 196, 208, 216-224, 234-238, 243-244, 248-250, 261, 269, 368, 371, 375, 378, 381, 384, 394-395, 414, 425 mne.forward 746 124 83% 76, 81, 120, 151-152, 157-158, 163-164, 169-170, 177-180, 192-193, 196-200, 226-227, 238-239, 263-264, 271, 277-278, 284-288, 335-336, 341-342, 347-349, 362-363, 374, 384, 397-398, 407-411, 419, 427-428, 433-437, 464, 471-472, 477, 504-506, 518, 529, 541, 609-610, 620, 627, 635, 658-663, 671-689, 698, 731, 734-735, 778, 782, 787, 803, 810-821, 837, 847-848, 926, 1002, 1067, 1152, 1271, 1320-1321, 1334, 1342, 1364, 1376, 1380, 1382, 1384, 1439, 1456, 1462, 1465 mne.label 415 56 87% 72, 81-83, 136, 150, 161-163, 310, 312, 321, 325, 342, 371, 379-382, 393-399, 431, 444, 471, 520, 544, 558, 561, 593, 600, 613, 622, 631, 740, 744, 752, 805-811, 819, 822-833, 839 mne.layouts 1 0 100% mne.layouts.layout 100 5 95% 100, 144, 147, 201, 212 mne.minimum_norm 2 0 100% mne.minimum_norm.inverse 532 88 83% 49, 84-85, 93-94, 103-104, 111-112, 118-119, 128-129, 137-138, 148-149, 159-160, 163, 192, 207-208, 213-217, 233-234, 260-262, 313, 338, 392, 394, 398, 413, 420, 423, 450, 469, 489, 537-539, 601, 606, 625-626, 642-644, 646-648, 650-652, 655, 806, 884-890, 983-999, 1094-1096, 1117, 1119, 1125, 1128, 1255, 1259, 1263 mne.minimum_norm.time_frequency 238 12 95% 410, 430-431, 442, 498, 502, 522-524, 527, 565-567, 577 mne.misc 61 18 70% 28-29, 42, 66-67, 85-100 mne.mixed_norm 1 0 100% mne.mixed_norm.debiasing 48 1 98% 132 mne.mixed_norm.inverse 176 13 93% 44, 51, 68-69, 74, 162, 188-190, 217, 248, 261, 402 mne.mixed_norm.optim 307 7 98% 27, 29, 36, 67, 201, 385, 623 mne.parallel 39 13 67% 44-49, 75-78, 91-94 mne.preprocessing 5 0 100% mne.preprocessing.ecg 60 3 95% 136, 142, 146 mne.preprocessing.eog 43 12 72% 47-67 mne.preprocessing.ica 481 30 94% 208, 257-258, 304, 317-318, 425-427, 549, 605-612, 759, 766, 820, 827, 964, 983, 996-997, 1007, 1017, 1029, 1170, 1181, 1195, 1289-1290, 1375 mne.preprocessing.maxfilter 101 66 35% 48, 74, 90, 190-281 mne.preprocessing.peak_finder 85 17 80% 53, 93-95, 100-102, 142-144, 155-161, 170 mne.preprocessing.ssp 80 18 78% 26-27, 109, 139, 143-144, 154, 157, 160, 163, 165-176 mne.proj 151 15 90% 63-64, 66-67, 69-70, 126, 130, 141, 276, 280, 284, 286, 314, 345 mne.selection 40 5 88% 50, 60, 80-82, 98 mne.simulation 2 0 100% mne.simulation.evoked 34 2 94% 116, 118 mne.simulation.source 72 3 96% 75, 90, 149 mne.source_estimate 922 117 87% 77, 278-281, 287-290, 300, 315, 349, 389, 437, 441, 447, 451, 456, 503, 519, 526, 540, 576-577, 731, 734, 740, 749, 810, 840, 844, 860, 863, 882, 884, 1084, 1096, 1111-1112, 1115, 1191-1197, 1323-1324, 1347, 1350, 1447, 1467-1470, 1518, 1618, 1651-1656, 1712-1713, 1719, 1721, 1771, 1816, 1819, 1822, 1825, 1829, 1864, 1876, 1878, 1917-1919, 1976, 2008, 2027, 2050, 2116, 2146-2193, 2204, 2208, 2230, 2242, 2275, 2277, 2308 mne.source_space 408 40 90% 52, 59, 64, 77, 143, 216, 224, 254, 258, 274, 286, 290, 297, 301, 305, 309, 316, 320, 323, 330-332, 337, 341, 461, 483, 560, 582, 660, 664, 667, 670, 693, 720, 729-732, 754, 758 mne.stats 3 0 100% mne.stats.cluster_level 439 69 84% 31, 108, 133, 143, 228, 281, 289-297, 302, 312, 323, 328, 348-355, 373, 385, 389, 399, 403, 424, 444, 488, 505-509, 553, 562, 572, 584, 635, 652-655, 673, 676-679, 687, 807, 929, 1014, 1100, 1141-1146, 1161-1162, 1166-1172 mne.stats.multi_comp 33 2 94% 64, 70 mne.stats.parametric 25 0 100% mne.stats.permutations 48 0 100% mne.surface 207 56 73% 73-74, 82-83, 100, 130, 146-147, 153-154, 162, 172-173, 177-178, 184-187, 191-192, 196-197, 250-252, 257-267, 289-310, 320, 346, 386 mne.time_frequency 5 0 100% mne.time_frequency.ar 43 9 79% 54, 63, 65, 75, 148-152 mne.time_frequency.multitaper 164 16 90% 45, 59, 91, 157-160, 220, 224, 285, 288, 347, 483, 508-510, 525 mne.time_frequency.psd 32 2 94% 71, 78 mne.time_frequency.stft 89 12 87% 47, 50, 57, 60, 65, 69, 138, 142, 145, 149, 152, 156 mne.time_frequency.tfr 154 21 86% 57, 68, 113, 119, 127-129, 150, 153-155, 195, 324-326, 383-392 mne.transforms 1 0 100% mne.transforms.transforms 139 54 61% 39-41, 90-94, 142, 180, 225, 267-339 mne.utils 320 88 73% 46, 88-91, 131, 138, 216, 221-237, 247-248, 267, 331-332, 360-362, 365-366, 420, 510, 555, 564-565, 598, 602, 613-614, 624, 636-666, 671-683, 688-693, 699, 712, 717, 723 mne.viz 1065 263 75% 112-119, 182-206, 254-255, 263-266, 270, 274, 395, 401, 403, 470, 496, 500, 503, 558, 560, 631-635, 653, 655, 663-664, 668-673, 691, 758, 778-779, 791-792, 800, 815, 827, 848, 886, 921, 1012, 1018-1021, 1024, 1041-1042, 1048, 1063, 1068, 1075-1158, 1165-1182, 1228-1229, 1248-1249, 1342, 1345, 1363, 1368, 1371, 1437, 1439, 1441, 1474, 1503, 1509, 1586, 1592, 1597, 1600-1601, 1609-1610, 1613, 1618, 1641, 1746, 1784, 1877-1878, 1882, 1902, 1910, 1912-1919, 1931-1937, 2030, 2038-2039, 2046-2047, 2061-2063, 2070-2074, 2081-2082, 2135, 2167-2169, 2174-2185, 2190-2200, 2205-2247, 2263, 2282-2283, 2298-2299, 2318-2319, 2364, 2371 --------------------------------------------------------------- TOTAL 13914 2034 85% ---------------------------------------------------------------------- Ran 96 tests in 192.352s FAILED (SKIP=1, errors=1, failures=2)