def test_custom_trans_primitives(self):
""" Test changing the default trans primitives. """
feat = feature.Creator(data, target, features)
feat.transform(trans_primitives=["add_numeric"])
custom_n_cols = len(feat._x.columns)
feat = feature.Creator(data, target, features)
feat.transform(trans_primitives=None)
default_n_cols = len(feat._x.columns)
assert default_n_cols > custom_n_cols
def test_custom_max_depth(self):
""" Test changing the default trans primitives. """
feat = feature.Creator(data, target, features)
feat.transform(trans_primitives=["greater_than", "and"], max_depth=1)
depth1_n_cols = len(feat._x.columns)
feat = feature.Creator(data, target, features)
feat.transform(trans_primitives=["greater_than", "and"], max_depth=2)
depth2_n_cols = len(feat._x.columns)
assert depth2_n_cols > depth1_n_cols
def test_not_all_nan(self):
""" Test that no NA features are created. """
feat = feature.Creator(data, target, features)
feat.transform(trans_primitives=["greater_than"])
before = len(feat._x.columns)
after = len(feat._x.dropna(1, how="all").columns)
assert before == after
def test_create(self):
""" Test creating variables. """
feat = feature.Creator(data, target, features)
old_n_cols = len(feat._x.columns)
feat.transform()
new_n_cols = len(feat._x.columns)
assert new_n_cols > old_n_cols
def test_export_files(self):
""" Test if files are exported accordingly. """
feat = feature.Creator(data, target, features)
feat.transform(
trans_primitives=["greater_than"],
entity_set_folder_name="entityset",
features_file_name="features.json",
)
assert os.path.exists("entityset") and os.path.exists("features.json")
def test_export_files(self):
""" Test if files are exported accordingly. """
feat = feature.Creator(data, target, features)
feat.transform(
trans_primitives=["greater_than"],
entity_set_folder_name="entityset",
features_file_name="features.json",
)
feat_matrix = feature.load("entityset", "features.json")
pd.testing.assert_frame_equal(feat._x, feat_matrix)
def setup_class(cls):
cls.feat = feature.Creator(data, target, features)
def test_not_single_value(self):
""" Test that no single values features are created. """
feat = feature.Creator(data, target, features)
feat.transform(trans_primitives=["greater_than"])
uniques_count = [len(feat._x[col].unique()) for col in feat._x.columns]
assert 1 not in uniques_count