def test_feature_rep():
# multivariate ts
frep = transform.FeatureRep(features=all_features())
X = np.random.rand(100, 10, 5)
y = np.ones(100)
frep.fit(X, y)
Xt = frep.transform(X)
assert Xt.shape[0] == len(X)
assert len(frep.f_labels) == Xt.shape[1]
# univariate ts
X = np.random.rand(100, 10)
y = np.ones(100)
frep.fit(X, y)
Xt = frep.transform(X)
assert Xt.shape[0] == len(X)
assert len(frep.f_labels) == Xt.shape[1]
# single feature
frep = transform.FeatureRep(features={'mean': mean})
frep.fit(X, y)
Xt = frep.transform(X)
assert Xt.shape[0] == len(X)
assert len(frep.f_labels) == Xt.shape[1]
assert Xt.shape[1] == 1
# ts with multivariate contextual data
frep = transform.FeatureRep(features=all_features())
X = TS_Data(np.random.rand(100, 10, 5), np.random.rand(100, 3))
y = np.ones(100)
frep.fit(X, y)
Xt = frep.transform(X)
assert Xt.shape[0] == len(X)
assert len(frep.f_labels) == Xt.shape[1]
# ts with univariate contextual data
X = TS_Data(np.random.rand(100, 10, 5), np.random.rand(100))
y = np.ones(100)
frep.fit(X, y)
Xt = frep.transform(X)
assert Xt.shape[0] == len(X)
assert len(frep.f_labels) == Xt.shape[1]
def test_feature_rep_mix():
union = transform.FeatureRepMix([
('a', transform.FeatureRep(features={'mean': mean}), 0),
('b', transform.FeatureRep(features={'mean': mean}), 1),
('c', transform.FeatureRep(features={'mean': mean}), [2, 3]),
('d', transform.FeatureRep(features={'mean': mean}), slice(0, 2)),
('e', transform.FeatureRep(features={'mean': mean}),
[False, False, True, True]),
])
# multivariate ts
X = np.random.rand(100, 10, 4)
y = np.ones(100)
union.fit(X, y)
Xt = union.transform(X)
assert Xt.shape[0] == len(X)
assert len(union.f_labels) == Xt.shape[1]
# ts with multivariate contextual data
X = TS_Data(np.random.rand(100, 10, 4), np.random.rand(100, 3))
y = np.ones(100)
union.fit(X, y)
Xt = union.transform(X)
assert Xt.shape[0] == len(X)
assert len(union.f_labels) == Xt.shape[1]
# ts with univariate contextual data
X = TS_Data(np.random.rand(100, 10, 4), np.random.rand(100))
y = np.ones(100)
union.fit(X, y)
Xt = union.transform(X)
assert Xt.shape[0] == len(X)
assert len(union.f_labels) == Xt.shape[1]
# univariate ts
uni_union = transform.FeatureRepMix([
('a', transform.FeatureRep(features={'mean': mean}), 0),
('b', transform.FeatureRep(features={'mean': mean}), [0]),
('c', transform.FeatureRep(features={'mean': mean}), slice(0, 1)),
('d', transform.FeatureRep(features={'mean': mean}), [True]),
])
X = np.random.rand(100, 10)
y = np.ones(100)
uni_union.fit(X, y)
Xt = uni_union.transform(X)
assert Xt.shape[0] == len(X)
assert len(uni_union.f_labels) == Xt.shape[1]
