def test_manifest_check_download(tmpdir, n_have, monkeypatch):
"""Test our manifest downloader."""
monkeypatch.setattr(datasets.utils, '_fetch_file', _fake_zip_fetch)
destination = op.join(str(tmpdir), 'empty')
manifest_path = op.join(str(tmpdir), 'manifest.txt')
with open(manifest_path, 'w') as fid:
for fname in _zip_fnames:
fid.write('%s\n' % fname)
assert n_have in range(len(_zip_fnames) + 1)
assert not op.isdir(destination)
if n_have > 0:
os.makedirs(op.join(destination, 'foo'))
assert op.isdir(op.join(destination, 'foo'))
for fname in _zip_fnames:
assert not op.isfile(op.join(destination, fname))
for fname in _zip_fnames[:n_have]:
with open(op.join(destination, fname), 'w'):
pass
with catch_logging() as log:
with use_log_level(True):
url = hash_ = '' # we mock the _fetch_file so these are not used
_manifest_check_download(manifest_path, destination, url, hash_)
log = log.getvalue()
n_missing = 3 - n_have
assert ('%d file%s missing from' % (n_missing, _pl(n_missing))) in log
for want in ('Extracting missing', 'Successfully '):
if n_missing > 0:
assert want in log
else:
assert want not in log
assert op.isdir(destination)
for fname in _zip_fnames:
assert op.isfile(op.join(destination, fname))
def test_manifest_check_download(tmpdir, n_have, monkeypatch):
"""Test our manifest downloader."""
monkeypatch.setattr(datasets.utils, '_fetch_file', _fake_zip_fetch)
destination = op.join(str(tmpdir), 'empty')
manifest_path = op.join(str(tmpdir), 'manifest.txt')
with open(manifest_path, 'w') as fid:
for fname in _zip_fnames:
fid.write('%s\n' % fname)
assert n_have in range(len(_zip_fnames) + 1)
assert not op.isdir(destination)
if n_have > 0:
os.makedirs(op.join(destination, 'foo'))
assert op.isdir(op.join(destination, 'foo'))
for fname in _zip_fnames:
assert not op.isfile(op.join(destination, fname))
for fname in _zip_fnames[:n_have]:
with open(op.join(destination, fname), 'w'):
pass
with catch_logging() as log:
with use_log_level(True):
url = hash_ = '' # we mock the _fetch_file so these are not used
_manifest_check_download(manifest_path, destination, url, hash_)
log = log.getvalue()
n_missing = 3 - n_have
assert ('%d file%s missing from' % (n_missing, _pl(n_missing))) in log
for want in ('Extracting missing', 'Successfully '):
if n_missing > 0:
assert want in log
else:
assert want not in log
assert op.isdir(destination)
for fname in _zip_fnames:
assert op.isfile(op.join(destination, fname))
def test_docstring_parameters():
"""Test module docstring formatting."""
# skip modules that require mayavi if mayavi is not installed
public_modules_ = public_modules[:]
try:
import mayavi # noqa: F401 analysis:ignore
public_modules_.append('mne.gui')
except ImportError:
pass
incorrect = []
for name in public_modules_:
# Assert that by default we import all public names with `import mne`
if name not in ('mne', 'mne.gui'):
extra = name.split('.')[1]
assert hasattr(mne, extra)
with pytest.warns(None): # traits warnings
module = __import__(name, globals())
for submod in name.split('.')[1:]:
module = getattr(module, submod)
classes = inspect.getmembers(module, inspect.isclass)
for cname, cls in classes:
if cname.startswith('_'):
continue
incorrect += check_parameters_match(cls)
functions = inspect.getmembers(module, inspect.isfunction)
for fname, func in functions:
if fname.startswith('_'):
continue
incorrect += check_parameters_match(func)
incorrect = sorted(list(set(incorrect)))
msg = '\n' + '\n'.join(incorrect)
msg += '\n%d error%s' % (len(incorrect), _pl(incorrect))
if len(incorrect) > 0:
raise AssertionError(msg)
def test_docstring_parameters():
"""Test module docstring formatting."""
from numpydoc import docscrape
# skip modules that require mayavi if mayavi is not installed
public_modules_ = public_modules[:]
try:
import mayavi # noqa: F401 analysis:ignore
public_modules_.append('mne.gui')
except ImportError:
pass
incorrect = []
for name in public_modules_:
# Assert that by default we import all public names with `import mne`
if name not in ('mne', 'mne.gui'):
extra = name.split('.')[1]
assert hasattr(mne, extra)
with pytest.warns(None): # traits warnings
module = __import__(name, globals())
for submod in name.split('.')[1:]:
module = getattr(module, submod)
classes = inspect.getmembers(module, inspect.isclass)
# XXX eventually this should be public
if name == 'mne.viz':
from mne.viz._brain import _Brain
classes.append(('Brain', _Brain))
for cname, cls in classes:
if cname.startswith('_'):
continue
incorrect += check_parameters_match(cls)
cdoc = docscrape.ClassDoc(cls)
for method_name in cdoc.methods:
method = getattr(cls, method_name)
incorrect += check_parameters_match(method, cls=cls)
if hasattr(cls, '__call__') and \
'of type object' not in str(cls.__call__):
incorrect += check_parameters_match(cls.__call__, cls)
functions = inspect.getmembers(module, inspect.isfunction)
for fname, func in functions:
if fname.startswith('_'):
continue
incorrect += check_parameters_match(func)
incorrect = sorted(list(set(incorrect)))
msg = '\n' + '\n'.join(incorrect)
msg += '\n%d error%s' % (len(incorrect), _pl(incorrect))
if len(incorrect) > 0:
raise AssertionError(msg)
def test_docstring_parameters():
"""Test module docstring formatting."""
from numpydoc import docscrape
incorrect = []
for name in public_modules:
# Assert that by default we import all public names with `import mne`
if name not in ('mne', 'mne.gui'):
extra = name.split('.')[1]
assert hasattr(mne, extra)
with _record_warnings(): # traits warnings
module = __import__(name, globals())
for submod in name.split('.')[1:]:
module = getattr(module, submod)
classes = inspect.getmembers(module, inspect.isclass)
for cname, cls in classes:
if cname.startswith('_'):
continue
incorrect += check_parameters_match(cls)
cdoc = docscrape.ClassDoc(cls)
for method_name in cdoc.methods:
method = getattr(cls, method_name)
incorrect += check_parameters_match(method, cls=cls)
if hasattr(cls, '__call__') and \
'of type object' not in str(cls.__call__) and \
'of ABCMeta object' not in str(cls.__call__):
incorrect += check_parameters_match(cls.__call__, cls)
functions = inspect.getmembers(module, inspect.isfunction)
for fname, func in functions:
if fname.startswith('_'):
continue
incorrect += check_parameters_match(func)
incorrect = sorted(list(set(incorrect)))
msg = '\n' + '\n'.join(incorrect)
msg += '\n%d error%s' % (len(incorrect), _pl(incorrect))
if len(incorrect) > 0:
raise AssertionError(msg)
def _proj_fig(fname, info, proj_nums, proj_meg, kind):
import matplotlib.pyplot as plt
proj_nums = np.array(proj_nums, int)
assert proj_nums.shape == (3,)
projs = read_proj(fname)
epochs = fname.replace('-proj.fif', '-epo.fif')
n_col = proj_nums.max()
rs_topo = 3
if op.isfile(epochs):
epochs = mne.read_epochs(epochs)
evoked = epochs.average()
rs_trace = 2
else:
rs_trace = 0
n_row = proj_nums.astype(bool).sum() * (rs_topo + rs_trace)
shape = (n_row, n_col)
fig = plt.figure(figsize=(n_col * 2, n_row * 0.75))
used = np.zeros(len(projs), int)
ri = 0
for count, ch_type in zip(proj_nums, ('grad', 'mag', 'eeg')):
if count == 0:
continue
if ch_type == 'eeg':
meg, eeg = False, True
else:
meg, eeg = ch_type, False
ch_names = [info['ch_names'][pick]
for pick in mne.pick_types(info, meg=meg, eeg=eeg)]
idx = np.where([np.in1d(ch_names, proj['data']['col_names']).all()
for proj in projs])[0]
if len(idx) != count:
raise RuntimeError('Expected %d %s projector%s for channel type '
'%s based on proj_nums but got %d in %s'
% (count, kind, _pl(count), ch_type, len(idx),
fname))
if proj_meg == 'separate':
assert not used[idx].any()
else:
assert (used[idx] <= 1).all()
used[idx] += 1
these_projs = [deepcopy(projs[ii]) for ii in idx]
for proj in these_projs:
sub_idx = [proj['data']['col_names'].index(name)
for name in ch_names]
proj['data']['data'] = proj['data']['data'][:, sub_idx]
proj['data']['col_names'] = ch_names
topo_axes = [plt.subplot2grid(
shape, (ri * (rs_topo + rs_trace), ci),
rowspan=rs_topo) for ci in range(count)]
# topomaps
with warnings.catch_warnings(record=True):
plot_projs_topomap(these_projs, info=info, show=False,
axes=topo_axes)
plt.setp(topo_axes, title='', xlabel='')
topo_axes[0].set(ylabel=ch_type)
if rs_trace:
trace_axes = [plt.subplot2grid(
shape, (ri * (rs_topo + rs_trace) + rs_topo, ci),
rowspan=rs_trace) for ci in range(count)]
for proj, ax in zip(these_projs, trace_axes):
this_evoked = evoked.copy().pick_channels(ch_names)
p = proj['data']['data']
assert p.shape == (1, len(this_evoked.data))
with warnings.catch_warnings(record=True): # tight_layout
this_evoked.plot(
picks=np.arange(len(this_evoked.data)), axes=[ax])
ax.texts = []
trace = np.dot(p, this_evoked.data)[0]
trace *= 0.8 * (np.abs(ax.get_ylim()).max() /
np.abs(trace).max())
ax.plot(this_evoked.times, trace, color='#9467bd')
ax.set(title='', ylabel='', xlabel='')
ri += 1
assert used.all() and (used <= 2).all()
fig.subplots_adjust(0.1, 0.1, 0.95, 1, 0.3, 0.3)
return fig
