def test_nested_fold():
splitter_subjects = [(range(5), range(5, 10))]
splitter_runs = [([0], [1])]
class FoldFxStore(object):
def __init__(self):
self.train = []
self.test = []
self.calls = 0
def __call__(self, data_train, data_test):
self.calls += 1
self.train.append(data_train)
self.test.append(data_test)
return data_train.samples, data_test.samples
mock_foldfx = FoldFxStore()
scores = reproducibility(dss, [splitter_subjects, splitter_runs],
WardClusterMethod(),
spaces=['sa.subjects', 'sa.runs'],
fold_fx=mock_foldfx,
ks=[2],
ground_truth=ground_truth, verbose=0)
assert_equal(mock_foldfx.calls, 1)
assert_array_equal(np.unique(mock_foldfx.train[0].sa.subjects), splitter_subjects[0][0])
assert_array_equal(np.unique(mock_foldfx.train[0].sa.runs), splitter_runs[0][0])
assert_array_equal(np.unique(mock_foldfx.test[0].sa.subjects), splitter_subjects[0][1])
assert_array_equal(np.unique(mock_foldfx.test[0].sa.runs), splitter_runs[0][1])
def test_nested_fold():
splitter_subjects = [(range(5), range(5, 10))]
splitter_runs = [([0], [1])]
class FoldFxStore(object):
def __init__(self):
self.train = []
self.test = []
self.calls = 0
def __call__(self, data_train, data_test):
self.calls += 1
self.train.append(data_train)
self.test.append(data_test)
return data_train.samples, data_test.samples
mock_foldfx = FoldFxStore()
scores = reproducibility(dss, [splitter_subjects, splitter_runs],
WardClusterMethod(),
spaces=['sa.subjects', 'sa.runs'],
fold_fx=mock_foldfx,
ks=[2],
ground_truth=ground_truth,
verbose=0)
assert_equal(mock_foldfx.calls, 1)
assert_array_equal(np.unique(mock_foldfx.train[0].sa.subjects),
splitter_subjects[0][0])
assert_array_equal(np.unique(mock_foldfx.train[0].sa.runs),
splitter_runs[0][0])
assert_array_equal(np.unique(mock_foldfx.test[0].sa.subjects),
splitter_subjects[0][1])
assert_array_equal(np.unique(mock_foldfx.test[0].sa.runs),
splitter_runs[0][1])
def test_run_method():
scores = reproducibility(dss, fake_splitter, WardClusterMethod(),
ks=np.arange(2, 21),
ground_truth=ground_truth, verbose=0)
for key, value in scores.items():
assert_array_equal(value[0], np.arange(2, 21))
if not key.endswith('_gt'):
# this works only with ARI and AMI -- default
assert_array_equal(value[1], np.ones(value[1].shape))
else:
# only the first is 1.
assert_equal(value[1, 0], 1.)
def test_run_method():
scores = reproducibility(dss,
fake_splitter,
WardClusterMethod(),
ks=np.arange(2, 21),
ground_truth=ground_truth,
verbose=0)
for key, value in scores.items():
assert_array_equal(value[0], np.arange(2, 21))
if not key.endswith('_gt'):
# this works only with ARI and AMI -- default
assert_array_equal(value[1], np.ones(value[1].shape))
else:
# only the first is 1.
assert_equal(value[1, 0], 1.)
