def test_different_pipelines():
random_seed = 1233
X_train, y_train = load_gunpoint(return_X_y=True)
steps = [
('segment', RandomIntervalSegmenter(n_intervals='sqrt')),
('transform',
FeatureUnion([
('mean',
RowwiseTransformer(
FunctionTransformer(func=np.mean, validate=False))),
('std',
RowwiseTransformer(
FunctionTransformer(func=np.std, validate=False))),
('slope',
RowwiseTransformer(
FunctionTransformer(func=time_series_slope,
validate=False))),
])),
]
pipe = Pipeline(steps, random_state=random_seed)
a = pipe.fit_transform(X_train)
tran = RandomIntervalFeatureExtractor(
n_intervals='sqrt',
features=[np.mean, np.std, time_series_slope],
random_state=random_seed)
b = tran.fit_transform(X_train)
np.testing.assert_array_equal(a, b)
np.testing.assert_array_equal(pipe.steps[0][1].intervals_, tran.intervals_)
def test_different_implementations():
random_seed = 1233
X_train, y_train = load_gunpoint(return_X_y=True)
# Compare with chained transformations.
tran1 = RandomIntervalSegmenter(n_intervals='sqrt',
random_state=random_seed)
tran2 = RowwiseTransformer(
FunctionTransformer(func=np.mean, validate=False))
A = tran2.fit_transform(tran1.fit_transform(X_train))
tran = RandomIntervalFeatureExtractor(n_intervals='sqrt',
features=[np.mean],
random_state=random_seed)
B = tran.fit_transform(X_train)
np.testing.assert_array_equal(A, B)
# Compare with transformer pipeline using TSFeatureUnion.
steps = [
('segment',
RandomIntervalSegmenter(n_intervals='sqrt', check_input=False)),
('transform',
FeatureUnion([
('mean',
RowwiseTransformer(
FunctionTransformer(func=np.mean, validate=False))),
('std',
RowwiseTransformer(
FunctionTransformer(func=np.std, validate=False))),
])),
]
pipe = Pipeline(steps, random_state=random_seed)
a = pipe.fit_transform(X_train)
n_ints = a.shape[1] // 2 # Rename columns for comparing re-ordered arrays.
a.columns = [
*a.columns[:n_ints] + '_mean', *a.columns[n_ints:n_ints * 2] + '_std'
]
a = a.reindex(np.sort(a.columns), axis=1)
tran = RandomIntervalFeatureExtractor(n_intervals='sqrt',
features=[np.mean, np.std],
random_state=random_seed)
b = tran.fit_transform(X_train)
b = b.reindex(np.sort(b.columns), axis=1)
np.testing.assert_array_equal(a, b)