def test_manual_report_2d(tmpdir, invisible_fig):
"""Simulate user manually creating report by adding one file at a time."""
from sklearn.exceptions import ConvergenceWarning
r = Report(title='My Report')
raw = read_raw_fif(raw_fname)
raw.pick_channels(raw.ch_names[:6]).crop(10, None)
raw.info.normalize_proj()
cov = read_cov(cov_fname)
cov = pick_channels_cov(cov, raw.ch_names)
events = read_events(events_fname)
epochs = Epochs(raw=raw, events=events, baseline=None)
evokeds = read_evokeds(evoked_fname)
evoked = evokeds[0].pick('eeg')
with pytest.warns(ConvergenceWarning, match='did not converge'):
ica = (ICA(n_components=2, max_iter=1, random_state=42)
.fit(inst=raw.copy().crop(tmax=1)))
ica_ecg_scores = ica_eog_scores = np.array([3, 0])
ica_ecg_evoked = ica_eog_evoked = epochs.average()
r.add_raw(raw=raw, title='my raw data', tags=('raw',), psd=True,
projs=False)
r.add_events(events=events_fname, title='my events',
sfreq=raw.info['sfreq'])
r.add_epochs(epochs=epochs, title='my epochs', tags=('epochs',), psd=False,
projs=False)
r.add_evokeds(evokeds=evoked, noise_cov=cov_fname,
titles=['my evoked 1'], tags=('evoked',), projs=False,
n_time_points=2)
r.add_projs(info=raw_fname, projs=ecg_proj_fname, title='my proj',
tags=('ssp', 'ecg'))
r.add_ica(ica=ica, title='my ica', inst=None)
with pytest.raises(RuntimeError, match='not preloaded'):
r.add_ica(ica=ica, title='ica', inst=raw)
r.add_ica(
ica=ica, title='my ica with inst',
inst=raw.copy().load_data(),
picks=[0],
ecg_evoked=ica_ecg_evoked,
eog_evoked=ica_eog_evoked,
ecg_scores=ica_ecg_scores,
eog_scores=ica_eog_scores
)
r.add_covariance(cov=cov, info=raw_fname, title='my cov')
r.add_forward(forward=fwd_fname, title='my forward', subject='sample',
subjects_dir=subjects_dir)
r.add_html(html='<strong>Hello</strong>', title='Bold')
r.add_code(code=__file__, title='my code')
r.add_sys_info(title='my sysinfo')
fname = op.join(tmpdir, 'report.html')
r.save(fname=fname, open_browser=False)
def test_sorting(tmp_path):
"""Test that automated ordering based on tags works."""
r = Report()
r.add_code(code='E = m * c**2', title='intelligence >9000', tags=('bem', ))
r.add_code(code='a**2 + b**2 = c**2',
title='Pythagoras',
tags=('evoked', ))
r.add_code(code='🧠',
title='source of truth',
tags=('source-estimate', ))
r.add_code(code='🥦', title='veggies', tags=('raw', ))
# Check that repeated calls of add_* actually continuously appended to
# the report
orig_order = ['bem', 'evoked', 'source-estimate', 'raw']
assert [c.tags[0] for c in r._content] == orig_order
# Now check the actual sorting
content_sorted = r._sort(content=r._content, order=CONTENT_ORDER)
expected_order = ['raw', 'evoked', 'bem', 'source-estimate']
assert content_sorted != r._content
assert [c.tags[0] for c in content_sorted] == expected_order
r.save(fname=op.join(tmp_path, 'report.html'),
sort_content=True,
open_browser=False)
def test_tags(tags, not_a_collection, wrong_dtype, invalid_chars):
"""Test handling of invalid tags."""
r = Report()
if not_a_collection:
with pytest.raises(TypeError, match='must be a collection of str'):
r.add_code(code='foo', title='bar', tags=tags)
elif wrong_dtype:
with pytest.raises(TypeError, match='must be strings'):
r.add_code(code='foo', title='bar', tags=tags)
elif invalid_chars:
with pytest.raises(ValueError, match='contained invalid characters'):
r.add_code(code='foo', title='bar', tags=tags)
else:
r.add_code(code='foo', title='bar', tags=tags)
def test_tags(tags, str_or_array, wrong_dtype, invalid_chars):
"""Test handling of invalid tags."""
r = Report()
if not str_or_array:
with pytest.raises(TypeError, match='must be a string.*or an array.*'):
r.add_code(code='foo', title='bar', tags=tags)
elif wrong_dtype:
with pytest.raises(TypeError, match='tags must be strings'):
r.add_code(code='foo', title='bar', tags=tags)
elif invalid_chars:
with pytest.raises(ValueError, match='contained invalid characters'):
r.add_code(code='foo', title='bar', tags=tags)
else:
r.add_code(code='foo', title='bar', tags=tags)
def test_manual_report_2d(tmp_path, invisible_fig):
"""Simulate user manually creating report by adding one file at a time."""
from sklearn.exceptions import ConvergenceWarning
r = Report(title='My Report')
raw = read_raw_fif(raw_fname)
raw.pick_channels(raw.ch_names[:6]).crop(10, None)
raw.info.normalize_proj()
cov = read_cov(cov_fname)
cov = pick_channels_cov(cov, raw.ch_names)
events = read_events(events_fname)
event_id = {
'auditory/left': 1,
'auditory/right': 2,
'visual/left': 3,
'visual/right': 4,
'face': 5,
'buttonpress': 32
}
metadata, metadata_events, metadata_event_id = make_metadata(
events=events,
event_id=event_id,
tmin=-0.2,
tmax=0.5,
sfreq=raw.info['sfreq'])
epochs_without_metadata = Epochs(raw=raw,
events=events,
event_id=event_id,
baseline=None)
epochs_with_metadata = Epochs(raw=raw,
events=metadata_events,
event_id=metadata_event_id,
baseline=None,
metadata=metadata)
evokeds = read_evokeds(evoked_fname)
evoked = evokeds[0].pick('eeg')
with pytest.warns(ConvergenceWarning, match='did not converge'):
ica = (ICA(n_components=2, max_iter=1,
random_state=42).fit(inst=raw.copy().crop(tmax=1)))
ica_ecg_scores = ica_eog_scores = np.array([3, 0])
ica_ecg_evoked = ica_eog_evoked = epochs_without_metadata.average()
r.add_raw(raw=raw,
title='my raw data',
tags=('raw', ),
psd=True,
projs=False)
r.add_raw(raw=raw,
title='my raw data 2',
psd=False,
projs=False,
butterfly=1)
r.add_events(events=events_fname,
title='my events',
sfreq=raw.info['sfreq'])
r.add_epochs(epochs=epochs_without_metadata,
title='my epochs',
tags=('epochs', ),
psd=False,
projs=False)
r.add_epochs(epochs=epochs_without_metadata,
title='my epochs 2',
psd=1,
projs=False)
r.add_epochs(epochs=epochs_without_metadata,
title='my epochs 2',
psd=True,
projs=False)
assert 'Metadata' not in r.html[-1]
# Try with metadata
r.add_epochs(epochs=epochs_with_metadata,
title='my epochs with metadata',
psd=False,
projs=False)
assert 'Metadata' in r.html[-1]
with pytest.raises(ValueError,
match='requested to calculate PSD on a duration'):
r.add_epochs(epochs=epochs_with_metadata,
title='my epochs 2',
psd=100000000,
projs=False)
r.add_evokeds(evokeds=evoked,
noise_cov=cov_fname,
titles=['my evoked 1'],
tags=('evoked', ),
projs=False,
n_time_points=2)
r.add_projs(info=raw_fname,
projs=ecg_proj_fname,
title='my proj',
tags=('ssp', 'ecg'))
r.add_ica(ica=ica, title='my ica', inst=None)
with pytest.raises(RuntimeError, match='not preloaded'):
r.add_ica(ica=ica, title='ica', inst=raw)
r.add_ica(ica=ica,
title='my ica with inst',
inst=raw.copy().load_data(),
picks=[0],
ecg_evoked=ica_ecg_evoked,
eog_evoked=ica_eog_evoked,
ecg_scores=ica_ecg_scores,
eog_scores=ica_eog_scores)
r.add_covariance(cov=cov, info=raw_fname, title='my cov')
r.add_forward(forward=fwd_fname,
title='my forward',
subject='sample',
subjects_dir=subjects_dir)
r.add_html(html='<strong>Hello</strong>', title='Bold')
r.add_code(code=__file__, title='my code')
r.add_sys_info(title='my sysinfo')
# drop locations (only EEG channels in `evoked`)
evoked_no_ch_locs = evoked.copy()
for ch in evoked_no_ch_locs.info['chs']:
ch['loc'][:3] = np.nan
with pytest.warns(RuntimeWarning, match='No EEG channel locations'):
r.add_evokeds(evokeds=evoked_no_ch_locs,
titles=['evoked no chan locs'],
tags=('evoked', ),
projs=True,
n_time_points=1)
assert 'Time course' not in r._content[-1].html
assert 'Topographies' not in r._content[-1].html
assert evoked.info['projs'] # only then the following test makes sense
assert 'SSP' not in r._content[-1].html
assert 'Global field power' in r._content[-1].html
# Drop locations from Info used for projs
info_no_ch_locs = raw.info.copy()
for ch in info_no_ch_locs['chs']:
ch['loc'][:3] = np.nan
with pytest.warns(RuntimeWarning, match='No channel locations found'):
r.add_projs(info=info_no_ch_locs, title='Projs no chan locs')
# Drop locations from ICA
ica_no_ch_locs = ica.copy()
for ch in ica_no_ch_locs.info['chs']:
ch['loc'][:3] = np.nan
with pytest.warns(RuntimeWarning,
match='No Magnetometers channel locations'):
r.add_ica(ica=ica_no_ch_locs,
picks=[0],
inst=raw.copy().load_data(),
title='ICA')
assert 'ICA component properties' not in r._content[-1].html
assert 'ICA component topographies' not in r._content[-1].html
assert 'Original and cleaned signal' in r._content[-1].html
fname = op.join(tmp_path, 'report.html')
r.save(fname=fname, open_browser=False)