def test_frozen_featurizer_1(data):
ff = FrozenFeaturizer(data[0])
ff_features = ff.fit_transform(data[1])
assert ff_features.shape == (10, 11)
ff_features = ff.fit_transform(data[1], depth=1)
assert ff_features.shape == (10, 4)
ff_features = ff.fit_transform(data[1])
assert ff_features.shape == (10, 11)
def test_frozen_featurizer_3(data):
ff = FrozenFeaturizer(data[0])
try:
ff.feature_labels
except ValueError:
assert True
else:
assert False, 'should got ValueError'
ff.fit_transform(data[2])
try:
ff.feature_labels
except ValueError:
assert False
def test_frozen_featurizer_2(data):
ff = FrozenFeaturizer(data[0])
ff_features = ff.fit_transform(data[2])
assert ff_features.shape == (10, 11)
assert isinstance(ff_features, pd.DataFrame)
assert ff_features.index.tolist() == list(data[3])
_hlayers = [7, 4]
labels = [
'L(' + str(i - len(_hlayers)) + ')_' + str(j + 1) for i in range(2)
for j in range(_hlayers[i])
]
assert ff_features.columns.tolist() == list(labels)
def test_frozen_featurizer_5(data):
ff = FrozenFeaturizer(data[0])
with pytest.warns(
UserWarning,
match='is over the max depth of hidden layers starting at the given'
):
ff_features = ff.fit_transform(data[1], depth=2, n_layer=3)
assert ff_features.shape == (10, 11)
with pytest.warns(UserWarning,
match='is greater than the max depth of hidden layers'):
ff_features = ff.fit_transform(data[4], depth=3, n_layer=2)
assert ff_features.shape == (20, 11)
ff = FrozenFeaturizer(data[5])
ff_features = ff.transform(data[1], depth=2, return_type='df')
desc_ori = []
for i in [1, 2]:
desc_ori.append(ff_features[ff_features.columns[[
f'L(-{i})' in s for s in ff_features.columns.values
]]])
desc_new = []
for i in [1, 2]:
for j in [1, 2]:
desc_new.append(
ff.transform(data[1], depth=j, n_layer=i, return_type='df'))
for i in range(2):
tmp = desc_new[i] == desc_ori[i]
assert all(tmp.all())
def test_frozen_featurizer_3(data):
ff = FrozenFeaturizer(data[0])
with pytest.raises(ValueError):
ff.feature_labels
ff.fit_transform(data[2])
ff.feature_labels
ff = FrozenFeaturizer(data[5])
with pytest.raises(ValueError):
ff.feature_labels
ff.fit_transform(data[2])
ff.feature_labels
def test_frozen_featurizer_4(data):
ff = FrozenFeaturizer(data[0])
ff_features = ff.fit_transform(data[1])
assert ff_features.shape == (10, 11)
ff_features = ff.fit_transform(data[4])
assert ff_features.shape == (20, 11)
ff = FrozenFeaturizer(data[5])
ff_features = ff.fit_transform(data[1])
assert ff_features.shape == (10, 11)
ff_features = ff.fit_transform(data[4])
assert ff_features.shape == (20, 11)