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_uv_feature_functions():
''' test feature functions with univariate data '''
N = 20
W = 30
uv_data = np.random.rand(N, W)
ftr_funcs = feature_functions.all_features()
for f in ftr_funcs:
uvf = ftr_funcs[f](uv_data)
assert len(uvf) == N
def test_mv_feature_functions():
''' test feature functions with multivariate data '''
# sliding window data is shape [n_segments, width, variables]
N = 20
W = 30
mv_data = np.random.rand(N, W, 3)
ftr_funcs = feature_functions.all_features()
for f in ftr_funcs:
mvf = ftr_funcs[f](mv_data)
assert len(mvf) == N
def test_uv_feature_functions():
""" test feature functions with univariate data """
N = 20
W = 30
uv_data = np.random.rand(N, W)
ftr_funcs = {}
ftr_funcs.update(feature_functions.all_features())
ftr_funcs.update(feature_functions.base_features())
ftr_funcs.update(feature_functions.hudgins_features())
ftr_funcs.update(feature_functions.emg_features())
for f in ftr_funcs:
uvf = ftr_funcs[f](uv_data)
assert len(uvf) == N
def test_mv_feature_functions():
""" test feature functions with multivariate data """
# sliding window data is shape [n_segments, width, variables]
N = 20
W = 30
mv_data = np.random.rand(N, W, 3)
ftr_funcs = {}
ftr_funcs.update(feature_functions.all_features())
ftr_funcs.update(feature_functions.base_features())
ftr_funcs.update(feature_functions.hudgins_features())
ftr_funcs.update(feature_functions.emg_features())
for f in ftr_funcs:
mvf = ftr_funcs[f](mv_data)
assert len(mvf) == N
