def test_reverse_transform_min_an_max_with_nulls(self):
"""Test reverse_transform with nulls and ``min_value`` and ``max_value`` set
The ``reverse_transform`` method should clip any values above
the ``max_value`` and any values below the ``min_value``. Null values
should be replaced with ``np.nan``.
Input:
- 2d array where second column has some values over 0.5 representing null values
Output:
- Array with out of bounds values clipped and null values injected
"""
# Setup
data = np.array([[-np.inf, 0], [-5000, 0.1], [-301, 0.8], [-250, 0.4],
[0, 0], [125, 1], [401, 0.2], [np.inf, 0.5]])
clipped_data = np.array([[-300, 0], [-300, 0.1], [-300, 0.8],
[-250, 0.4], [0, 0], [125, 1], [400, 0.2],
[400, 0.5]])
expected_data = np.array(
[-300, -300, np.nan, -250, 0, np.nan, 400, 400])
# Run
transformer = NumericalTransformer(dtype=np.float, nan='nan')
transformer._max_value = 400
transformer._min_value = -300
transformer.null_transformer = Mock()
transformer.null_transformer.reverse_transform.return_value = expected_data
result = transformer.reverse_transform(data)
# Asserts
null_transformer_calls = transformer.null_transformer.reverse_transform.mock_calls
np.testing.assert_array_equal(null_transformer_calls[0][1][0],
clipped_data)
np.testing.assert_array_equal(result, expected_data)
def test_reverse_transform_min_no_max(self):
"""Test reverse_transform with ``min_value`` set
The ``reverse_transform`` method should clip any values below
the ``min_value`` if it is set.
Input:
- Array with values below the min and infinitely high values
Output:
- Array with low values clipped to min
"""
# Setup
data = np.array([-np.inf, -5000, -301, -250, 0, 125, 400, np.inf])
# Run
transformer = NumericalTransformer(dtype=np.float, nan=None)
transformer._min_value = -300
result = transformer.reverse_transform(data)
# Asserts
expected_data = np.array([-300, -300, -300, -250, 0, 125, 400, np.inf])
np.testing.assert_array_equal(result, expected_data)
def test_reverse_transform_min_and_max(self):
"""Test reverse_transform with ``min_value`` and ``max_value`` set
The ``reverse_transform`` method should clip any values above
the ``max_value`` and any values below the ``min_value``.
Input:
- Array with values above the max and below the min
Output:
- Array with out of bound values clipped to min and max
"""
# Setup
data = np.array([-np.inf, -5000, -301, -250, 0, 125, 401, np.inf])
# Run
transformer = NumericalTransformer(dtype=np.float, nan=None)
transformer._max_value = 400
transformer._min_value = -300
result = transformer.reverse_transform(data)
# Asserts
np.testing.assert_array_equal(
result, np.array([-300, -300, -300, -250, 0, 125, 400, 400]))