def test_min_max_indicator_inplace_false(self, data_frame):
""" Test that not setting inplace rules equates to more columns after the transformation"""
test_feature = MinMaxNormalizer(
columns=TestMinMaxNormalizer.price_columns, inplace=False)
test_feature.reset()
transformed = test_feature.transform(data_frame)
assert transformed is not None
assert len(data_frame.columns) != len(transformed.columns)
def test_min_max_indicator(self, data_frame, reference_frame):
""" Check that the min-max indicator is to be expected. """
test_feature = MinMaxNormalizer(
columns=TestMinMaxNormalizer.price_columns)
test_feature.reset()
roundable = 4
transformed = test_feature.transform(data_frame)
assert transformed is not None
transformed = transformed.round(roundable)
reference_frame = reference_frame.round(roundable)
close_1 = transformed.Close.values
close_2 = reference_frame.Close.values
is_valid = (close_1 == close_2).all()
assert is_valid