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