def test_featurize_files_function(tmpdir): """Test featurize function for on-disk time series""" with sample_ts_files(size=4, labels=['A', 'B']) as ts_paths: fset, labels = featurize.featurize_ts_files( ts_paths, features_to_use=["std_err"], scheduler=dask.get) assert "std_err" in fset assert fset.shape == (4, 1) npt.assert_array_equal(labels, ['A', 'B', 'A', 'B'])
def test_featurize_files_function(tmpdir): """Test featurize function for on-disk time series""" with sample_ts_files(size=4) as ts_paths: fset = featurize.featurize_ts_files(ts_paths, features_to_use=["std_err"], scheduler=get_sync) assert "std_err" in fset assert fset.shape == (4, 1)
def test_featurize_files_function(tmpdir): """Test featurize function for on-disk time series""" with sample_ts_files(size=4, labels=['A', 'B']) as ts_paths: fset, labels = featurize.featurize_ts_files(ts_paths, features_to_use=["std_err"], scheduler=dask.get) assert "std_err" in fset assert fset.shape == (4, 1) npt.assert_array_equal(labels, ['A', 'B', 'A', 'B'])
def test_featurize_files_function_regression_data(): """Test featurize function for on-disk time series - regression data""" fset_path = pjoin(TEMP_DIR, 'output_featureset.nc') with sample_ts_files(size=4, targets=[1.0, 2.0]) as ts_paths: fset = featurize.featurize_ts_files(ts_paths, features_to_use=["std_err"], output_path=fset_path, scheduler=get_sync) assert("std_err" in fset.data_vars) assert(all(target in [1.0, 2.0] for target in fset['target'].values))
def test_featurize_files_function(): """Test featurize function for on-disk time series""" fset_path = pjoin(TEMP_DIR, 'output_featureset.nc') with sample_ts_files(size=4, targets=['class1', 'class2']) as ts_paths: fset = featurize.featurize_ts_files(ts_paths, features_to_use=["std_err"], output_path=fset_path, scheduler=get_sync) assert("std_err" in fset.data_vars) assert(all(class_name in ['class1', 'class2'] for class_name in fset['target'].values))