def test_add_features_to_only_a_part(self):
augmenter = FeatureAugmenter(column_value="val",
column_id="id",
column_sort="sort",
column_kind="kind",
settings=self.settings)
augmenter.set_timeseries_container(self.test_df)
X_with_not_all_ids = pd.DataFrame([{"feature_1": 1}], index=[1])
X_transformed = augmenter.transform(X_with_not_all_ids)
for i in X_transformed.index:
self.assertIn(i, X_with_not_all_ids.index)
for i in X_with_not_all_ids.index:
self.assertIn(i, X_transformed.index)
self.assertEqual(X_transformed.shape, (1, 3))
self.assertEqual(X_transformed.index, [1])
# Features are not allowed to be NaN
for index, row in X_transformed.iterrows():
print(index, row)
self.assertFalse(np.isnan(row["a__length"]))
self.assertFalse(np.isnan(row["b__length"]))
def test_fit_and_transform(self):
augmenter = FeatureAugmenter(column_value="val", column_id="id", column_sort="sort",
column_kind="kind",
kind_to_fc_parameters=self.kind_to_fc_parameters)
# Fit should do nothing
returned_df = augmenter.fit()
six.assertCountEqual(self, returned_df.__dict__, augmenter.__dict__)
self.assertRaises(RuntimeError, augmenter.transform, None)
augmenter.set_timeseries_container(self.test_df)
# Add features to all time series
X_with_index = pd.DataFrame([{"feature_1": 1}]*2, index=[10, 500])
X_transformed = augmenter.transform(X_with_index)
# Require same shape
for i in X_transformed.index:
self.assertIn(i, X_with_index.index)
for i in X_with_index.index:
self.assertIn(i, X_transformed.index)
self.assertEqual(X_transformed.shape, (2, 3))
# Preserve old features
six.assertCountEqual(self, list(X_transformed.columns), ["feature_1", "a__length", "b__length"])
# Features are not allowed to be NaN
for index, row in X_transformed.iterrows():
print((index, row))
self.assertFalse(np.isnan(row["a__length"]))
self.assertFalse(np.isnan(row["b__length"]))
def test_add_features_to_only_a_part(self):
augmenter = FeatureAugmenter(column_value="val", column_id="id", column_sort="sort",
column_kind="kind",
kind_to_fc_parameters=self.kind_to_fc_parameters,
n_jobs=0,
disable_progressbar = True)
augmenter.set_timeseries_container(self.test_df)
X_with_not_all_ids = pd.DataFrame([{"feature_1": 1}], index=[10])
X_transformed = augmenter.transform(X_with_not_all_ids)
for i in X_transformed.index:
self.assertIn(i, X_with_not_all_ids.index)
for i in X_with_not_all_ids.index:
self.assertIn(i, X_transformed.index)
self.assertEqual(X_transformed.shape, (1, 3))
self.assertEqual(X_transformed.index, [10])
# Features are not allowed to be NaN
for index, row in X_transformed.iterrows():
print((index, row))
self.assertFalse(np.isnan(row["a__length"]))
self.assertFalse(np.isnan(row["b__length"]))