def test_one_division(self):
assembly = np.random.rand(100, 3)
assembly = NeuroidAssembly(
assembly,
coords={'neuroid': list(range(len(assembly))), 'division_coord': list(range(assembly.shape[1]))},
dims=['neuroid', 'division_coord'])
transformation = CartesianProduct(dividers=['division_coord'])
placeholder = self.MetricPlaceholder()
transformation(assembly, apply=placeholder)
assert len(assembly['division_coord']) == len(placeholder.assemblies)
targets = [assembly.sel(division_coord=i) for i in assembly['division_coord'].values]
for target in targets:
match = any([actual == target] for actual in placeholder.assemblies)
assert match, "expected divided assembly not found: {target}"
def __init__(self, identifier):
self._logger = logging.getLogger(fullname(self))
self._identifier = identifier
assembly = LazyLoad(self._load_assembly)
self._target_assembly = assembly
regression = linear_regression(xarray_kwargs=dict(
stimulus_coord='word_id', neuroid_coord='subject_id'))
correlation = pearsonr_correlation(xarray_kwargs=dict(
correlation_coord='word_id', neuroid_coord='subject_id'))
self._metric = CrossRegressedCorrelation(
regression=regression,
correlation=correlation,
crossvalidation_kwargs=dict(splits=5,
kfold=True,
split_coord='word_id',
stratification_coord='sentence_id'))
self._cross = CartesianProduct(dividers=['subject_id'])
self._ceiler = self.ManySubjectExtrapolationCeiling(
subject_column='subject_id')
def test_no_expand_raw_level(self):
assembly = np.random.rand(3, 100)
assembly = NeuroidAssembly(
assembly,
coords={'neuroid': list(range(assembly.shape[1])), 'division_coord': list(range(assembly.shape[0]))},
dims=['division_coord', 'neuroid'])
transformation = CartesianProduct(dividers=['division_coord'])
class RawMetricPlaceholder(Metric):
def __call__(self, assembly, *args, **kwargs):
result = Score([assembly.values[0]], dims=['dim'])
raw = result.copy()
raw['dim_id'] = 'dim', [assembly.values[1]]
raw['division_coord'] = 'dim', [assembly.values[2]]
result.attrs['raw'] = raw
return result
metric = RawMetricPlaceholder()
result = transformation(assembly, apply=metric)
assert hasattr(result, 'raw')
assert 'division_coord' not in result.raw # no dimension
assert hasattr(result.raw, 'division_coord') # but a level
def __init__(self, identifier, metric):
super(_Fedorenko2016V3SubjectWise,
self).__init__(identifier=identifier, metric=metric)
self._ceiler.extrapolation_dimension = 'subject_UID'
self._cross = CartesianProduct(dividers=['subject_UID'])
def __init__(self, **kwargs):
super(_PereiraSubjectWise, self).__init__(**kwargs)
self._cross = CartesianProduct(dividers=['experiment', 'atlas', 'subject'])
self._ceiler = self.PereiraSubjectWiseExtrapolationCeiling(
extrapolation_dimension='subject', subject_column='subject', num_bootstraps=self._ceiler.num_bootstraps)
def __init__(self, bold_shift=4):
assemblies = self._load_rdms(bold_shift_seconds=bold_shift)
assemblies = {story: rdm for story, rdm in assemblies.items() if story != 'Elvis'}
self._target_assemblies = assemblies
self._metric = RDMSimilarityCrossValidated()
self._cross_region = CartesianProduct(dividers=['region'])