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import unittest, numpy |
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from mock import Mock |
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from datetime import datetime |
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from tests.test_basefile import BaseFileTests |
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class FifTests(BaseFileTests): |
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def setUp(self): |
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super(FifTests, self).setUp() |
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self.libs = Mock() |
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self.libs.hasDependency.return_value = True |
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self.libs.mne.io.read_raw_fif.side_effect = ValueError |
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self.libs.mne.read_cov.side_effect = ValueError |
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self.libs.mne.read_epochs.side_effect = ValueError |
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self.libs.mne.read_evokeds.side_effect = ValueError |
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self.libs.mne.read_forward_solution.side_effect = ValueError |
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self.libs.mne.read_trans.side_effect = ValueError |
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self.dependencies.getLibraries.return_value = self.libs |
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from niprov.fif import FifFile |
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self.constructor = FifFile |
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self.file = FifFile(self.path, dependencies=self.dependencies) |
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def test_Gets_basic_info_from_mne_and_returns_it(self): |
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self.setupRawFile() |
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out = self.file.inspect() |
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self.assertEqual(out['subject'], 'John Doeish') |
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self.assertEqual(out['project'], 'worlddom') |
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self.assertEqual(out['acquired'], self.acquired) |
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def test_Gets_dimensions(self): |
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self.setupRawFile() |
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out = self.file.inspect() |
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self.assertEqual(out['dimensions'], [123, 91]) |
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self.assertEqual(out['sampling-frequency'], 200) |
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self.assertEqual(out['duration'], 91/200.) |
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def test_Attach_method(self): |
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self.setupRawFile() |
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self.file.getProvenance = Mock() |
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self.file.getProvenance.return_value = 'serial prov' |
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self.file.attach('json') |
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self.file.getProvenance.assert_called_with('json') |
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self.assertIn('existing bla bla ', #original string+added space |
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self.img.info['description']) |
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self.assertIn('NIPROV:'+'serial prov', |
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self.img.info['description']) |
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self.libs.mne.io.write_info.assert_called_with(self.file.path, |
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self.img.info) |
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def test_Determines_modality(self): |
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out = self.file.inspect() |
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self.assertEqual(out['modality'], 'MEG') |
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def test_Preserves_modality_if_inherited(self): |
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pass # Doesn't have to preserve |
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def test_Tries_different_mne_access_functions_or_fails_silently(self): |
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out = self.file.inspect() |
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self.libs.mne.io.read_raw_fif.assert_called_with(self.path, |
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allow_maxshield=True) |
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self.libs.mne.read_cov.assert_called_with(self.path) |
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self.libs.mne.read_epochs.assert_called_with(self.path) |
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self.libs.mne.read_evokeds.assert_called_with(self.path) |
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self.libs.mne.read_forward_solution.assert_called_with(self.path) |
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self.libs.mne.read_trans.assert_called_with(self.path) |
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self.assertEqual(out['fif-type'], 'other') |
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def test_epochs(self): |
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self.setupEpochsFile() |
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out = self.file.inspect() |
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self.assertEqual(out['fif-type'], 'epo') |
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self.assertEqual(out['lowpass'],40.0) |
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self.assertEqual(out['highpass'],0.10000000149) |
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self.assertEqual(out['bad-channels'],['MEG666', 'ECG999']) |
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self.assertEqual(out['dimensions'], [7, 455]) |
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def test_evokeds(self): |
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self.setupEvokedsFile() |
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out = self.file.inspect() |
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self.assertEqual(out['fif-type'], 'ave') |
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self.assertEqual(out['dimensions'], [3, 306, 455]) |
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def test_covariance(self): |
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self.setupCovarianceFile() |
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out = self.file.inspect() |
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self.assertEqual(out['fif-type'], 'cov') |
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self.assertEqual(out['dimensions'], [365, 365]) |
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def test_forward(self): |
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self.setupForwardFile() |
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out = self.file.inspect() |
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self.assertEqual(out['fif-type'], 'fwd') |
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def test_trans(self): |
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self.setupTransFile() |
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out = self.file.inspect() |
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self.assertEqual(out['fif-type'], 'trans') |
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def setupRawFile(self): |
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TS = 1422522595.76096 |
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self.acquired = datetime.fromtimestamp(TS) |
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self.img = Mock() |
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self.img.info = { |
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'meas_date':(TS,), |
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'proj_name':'worlddom', |
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'subject_info':{'first_name':'John','last_name':'Doeish'}, |
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'nchan':123, |
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'sfreq':200, |
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'description':'existing bla bla'} |
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self.img.first_samp = 10 |
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self.img.last_samp = 100 |
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self.libs.mne.io.read_raw_fif.side_effect = None |
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self.libs.mne.io.read_raw_fif.return_value = self.img |
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self.libs.mne.io.read_info.return_value = self.img.info |
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def setupEpochsFile(self): |
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self.img = Mock() |
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self.img.info = { |
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'lowpass': 40.0, |
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'highpass': 0.10000000149, |
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'bads': ['MEG666', 'ECG999']} |
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self.img.events = numpy.zeros((7,3)) |
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self.img.times = numpy.zeros((455,1)) |
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self.libs.mne.read_epochs.side_effect = None |
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self.libs.mne.read_epochs.return_value = self.img |
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def setupEvokedsFile(self): |
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self.img = Mock() |
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self.img.info = {} |
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self.img.data = numpy.zeros((306,455)) |
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self.libs.mne.read_evokeds.side_effect = None |
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self.libs.mne.read_evokeds.return_value = [self.img, self.img, self.img] |
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def setupCovarianceFile(self): |
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self.img = Mock() |
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self.img.data = numpy.zeros((365,365)) |
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self.libs.mne.read_cov.side_effect = None |
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self.libs.mne.read_cov.return_value = self.img |
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def setupForwardFile(self): |
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self.img = Mock() |
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self.libs.mne.read_forward_solution.side_effect = None |
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self.libs.mne.read_forward_solution.return_value = self.img |
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def setupTransFile(self): |
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self.img = Mock() |
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self.libs.mne.read_trans.side_effect = None |
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self.libs.mne.read_trans.return_value = self.img |
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ilogue /
niprov
