[MRG] Be more precise about warnings (round 2) (#5428)

* more descriptive 'match=xxxxxxxxx'

* Unify do not warn

* pep8

mne/beamformer/tests/test_dics.py

@@ -335,9 +335,9 @@ def test_apply_dics_timeseries():
     # Sanity checks on the resulting STC after applying DICS on epochs.
     # Also test here that no warnings are thrown - implemented to check whether
     # src should not be None warning occurs
-    with pytest.warns(None) as wrn:
+    with pytest.warns(None) as w:
         stcs = apply_dics_epochs(epochs, filters)
-    assert len(wrn) == 0
+    assert len(w) == 0
 
     assert isinstance(stcs, list)
     assert len(stcs) == 1

mne/beamformer/tests/test_lcmv.py

@@ -341,9 +341,9 @@ def test_lcmv():
     # this channel from the data
     # also test here that no warnings are thrown - implemented to check whether
     # src should not be None warning occurs
-    with pytest.warns(None) as wrn:
+    with pytest.warns(None) as w:
         stc = apply_lcmv(evoked, filters, max_ori_out='signed')
-    assert len(wrn) == 0
+    assert len(w) == 0
     # the result should be equal to applying this filter to a dataset without
     # this channel:
     stc_ch = apply_lcmv(evoked_ch, filters, max_ori_out='signed')
@@ -593,7 +593,8 @@ def test_tf_lcmv():
 
     # Pass only one epoch to test if subtracting evoked
     # responses yields zeros
-    with pytest.warns(RuntimeWarning, match='samples'):
+    with pytest.warns(RuntimeWarning,
+                      match='Too few samples .* estimate may be unreliable'):
         stcs = tf_lcmv(epochs[0], forward, noise_covs, tmin, tmax, tstep,
                        win_lengths, freq_bins, subtract_evoked=True, reg=reg,
                        label=label, raw=raw)
@@ -635,7 +636,8 @@ def test_lcmv_ctf_comp():
     epochs = mne.Epochs(raw, events, tmin=0., tmax=0.2)
     evoked = epochs.average()
 
-    with pytest.warns(RuntimeWarning, match='samples'):
+    with pytest.warns(RuntimeWarning,
+                      match='Too few samples .* estimate may be unreliable'):
         data_cov = mne.compute_covariance(epochs)
     fwd = mne.make_forward_solution(evoked.info, None,
                                     mne.setup_volume_source_space(pos=15.0),

mne/channels/tests/test_interpolation.py

@@ -115,7 +115,7 @@ def test_interpolation():
     # check that interpolation works when non M/EEG channels are present
     # before MEG channels
     raw.rename_channels({'MEG 0113': 'TRIGGER'})
-    with pytest.warns(RuntimeWarning, match='unit'):  # change of units
+    with pytest.warns(RuntimeWarning, match='unit .* changed from .* to .*'):
         raw.set_channel_types({'TRIGGER': 'stim'})
     raw.info['bads'] = [raw.info['ch_names'][1]]
     raw.load_data()

mne/channels/tests/test_montage.py

@@ -396,7 +396,7 @@ def test_read_dig_montage():
                 else:
                     # extra column
                     fout.write(line.rstrip() + b' 0.0 0.0 0.0\n')
-    with pytest.warns(RuntimeWarning, match='columns'):
+    with pytest.warns(RuntimeWarning, match='Found .* columns instead of 3'):
         montage_extra = read_dig_montage(extra_hsp, hpi, elp, names)
     assert_allclose(montage_extra.hsp, montage.hsp)
     assert_allclose(montage_extra.elp, montage.elp)

mne/decoding/tests/test_transformer.py

@@ -112,7 +112,7 @@ def test_filterestimator():
 
     filt = FilterEstimator(epochs.info, l_freq=1, h_freq=1)
     y = epochs.events[:, -1]
-    with pytest.warns(RuntimeWarning, match='longer than'):
+    with pytest.warns(RuntimeWarning, match='longer than the signal'):
         pytest.raises(ValueError, filt.fit_transform, epochs_data, y)
 
     filt = FilterEstimator(epochs.info, l_freq=40, h_freq=None,

mne/io/ctf/tests/test_ctf.py

@@ -57,7 +57,7 @@ def test_read_ctf():
     os.mkdir(op.join(temp_dir, 'randpos'))
     ctf_eeg_fname = op.join(temp_dir, 'randpos', ctf_fname_catch)
     shutil.copytree(op.join(ctf_dir, ctf_fname_catch), ctf_eeg_fname)
-    with pytest.warns(RuntimeWarning, match='MISC channel'):
+    with pytest.warns(RuntimeWarning, match='RMSP .* changed to a MISC ch'):
         raw = _test_raw_reader(read_raw_ctf, directory=ctf_eeg_fname)
     picks = pick_types(raw.info, meg=False, eeg=True)
     pos = np.random.RandomState(42).randn(len(picks), 3)
@@ -73,7 +73,7 @@ def test_read_ctf():
                 '%0.5f' % x for x in 100 * pos[ii])  # convert to cm
             fid.write(('\t'.join(args) + '\n').encode('ascii'))
     pos_read_old = np.array([raw.info['chs'][p]['loc'][:3] for p in picks])
-    with pytest.warns(RuntimeWarning, match='MISC channel'):
+    with pytest.warns(RuntimeWarning, match='RMSP .* changed to a MISC ch'):
         raw = read_raw_ctf(ctf_eeg_fname)  # read modified data
     pos_read = np.array([raw.info['chs'][p]['loc'][:3] for p in picks])
     assert_allclose(apply_trans(raw.info['ctf_head_t'], pos), pos_read,

mne/io/edf/tests/test_edf.py

@@ -100,7 +100,7 @@ def test_bdf_stim_channel():
 @testing.requires_testing_data
 def test_edf_overlapping_annotations():
     """Test EDF with overlapping annotations."""
-    with pytest.warns(RuntimeWarning, match='overlapping'):
+    with pytest.warns(RuntimeWarning, match='overlapping.* not fully support'):
         read_raw_edf(edf_overlap_annot_path, preload=True, stim_channel='auto',
                      verbose=True)
 
@@ -156,7 +156,8 @@ def test_edf_data():
         fid_out.write(rbytes[:236])
         fid_out.write(bytes('-1      '.encode()))
         fid_out.write(rbytes[244:])
-    with pytest.warns(RuntimeWarning, match='record'):
+    with pytest.warns(RuntimeWarning,
+                      match='records .* not match the file size'):
         raw = read_raw_edf(broken_fname, preload=True, stim_channel='auto')
         read_raw_edf(broken_fname, exclude=raw.ch_names[:132], preload=True,
                      stim_channel='auto')
@@ -200,11 +201,12 @@ def test_stim_channel():
     pytest.raises(RuntimeError, read_raw_edf, edf_path, preload=False,
                   stim_channel=-1)
 
-    with pytest.warns(RuntimeWarning, match='jitter'):
+    with pytest.warns(RuntimeWarning,
+                      match='Interpolating stim .* Events may jitter'):
         raw = read_raw_edf(edf_stim_resamp_path, verbose=True, stim_channel=-1)
-    with pytest.warns(None) as record:
+    with pytest.warns(None) as w:
         raw[:]
-    assert len(record) == 0
+    assert len(w) == 0
 
     events = raw_py.find_edf_events()
     assert (len(events) == 0)

mne/io/fiff/tests/test_raw_fiff.py

@@ -642,7 +642,7 @@ def test_io_complex():
         raw_cp = raw.copy()
         raw_cp._data = np.array(raw_cp._data, dtype)
         raw_cp._data[picks, start:stop] += imag_rand
-        with pytest.warns(RuntimeWarning, match='complex'):
+        with pytest.warns(RuntimeWarning, match='Saving .* complex data.'):
             raw_cp.save(op.join(tempdir, 'raw.fif'), picks, tmin=0, tmax=5,
                         overwrite=True)
 
@@ -1254,7 +1254,7 @@ def test_annotation_crop():
     sfreq = raw.info['sfreq']
     annot = Annotations([0., raw.times[-1]], [2., 2.], 'test',
                         raw.info['meas_date'] + raw.first_samp / sfreq - 1.)
-    with pytest.warns(RuntimeWarning, match='data range'):
+    with pytest.warns(RuntimeWarning, match='Limited .* expanding outside'):
         raw.set_annotations(annot)
     assert_allclose(raw.annotations.duration,
                     [1., 1. + 1. / raw.info['sfreq']], atol=1e-3)

mne/io/kit/tests/test_kit.py

@@ -236,7 +236,8 @@ def test_decimate():
     np.savetxt(sphere_hsp_path, hsp_mm)
 
     # read in raw data using spherical hsp, and extract new hsp
-    with pytest.warns(RuntimeWarning, match='more than'):
+    with pytest.warns(RuntimeWarning,
+                      match='was automatically downsampled .* FastScan'):
         raw = read_raw_kit(sqd_path, mrk_path, elp_txt_path, sphere_hsp_path)
     # collect headshape from raw (should now be in m)
     hsp_dec = np.array([dig['r'] for dig in raw.info['dig']])[8:]

mne/io/tests/test_raw.py

@@ -148,8 +148,8 @@ def test_time_index():
 
 def test_annotation_property_deprecation_warning():
     """Test that assigning annotations warns and nowhere else."""
-    with pytest.warns(None) as record:
+    with pytest.warns(None) as w:
         raw = RawArray(np.random.rand(1, 1), create_info(1, 1))
-    assert len(record) is 0
+    assert len(w) is 0
     with pytest.warns(DeprecationWarning, match='by assignment is deprecated'):
         raw.annotations = None

mne/io/tests/test_reference.py

@@ -415,7 +415,7 @@ def test_add_reference():
     # create epochs in delayed mode, allowing removal of CAR when re-reffing
     epochs = Epochs(raw, events=events, event_id=1, tmin=-0.2, tmax=0.5,
                     picks=picks_eeg, preload=True, proj='delayed')
-    with pytest.warns(RuntimeWarning, match='ignored'):
+    with pytest.warns(RuntimeWarning, match='ignored .set to zero.'):
         epochs_ref = add_reference_channels(epochs, ['M1', 'M2'], copy=True)
     assert_equal(epochs_ref._data.shape[1], epochs._data.shape[1] + 2)
     _check_channel_names(epochs_ref, ['M1', 'M2'])
@@ -455,7 +455,7 @@ def test_add_reference():
     epochs = Epochs(raw, events=events, event_id=1, tmin=-0.2, tmax=0.5,
                     picks=picks_eeg, preload=True, proj='delayed')
     evoked = epochs.average()
-    with pytest.warns(RuntimeWarning, match='ignored'):
+    with pytest.warns(RuntimeWarning, match='ignored .set to zero.'):
         evoked_ref = add_reference_channels(evoked, ['M1', 'M2'], copy=True)
     assert_equal(evoked_ref.data.shape[0], evoked.data.shape[0] + 2)
     _check_channel_names(evoked_ref, ['M1', 'M2'])

mne/preprocessing/tests/test_ica.py

@@ -428,7 +428,7 @@ def test_ica_additional(method):
     for cov in (None, test_cov):
         ica = ICA(noise_cov=cov, n_components=2, max_pca_components=4,
                   n_pca_components=4, method=method, max_iter=1)
-        with pytest.warns(None):
+        with pytest.warns(None):  # ICA does not converge
             ica.fit(raw, picks=picks[:10], start=start, stop=stop2)
         sources = ica.get_sources(epochs).get_data()
         assert (ica.mixing_matrix_.shape == (2, 2))