def test_reverse_transform_rounding_negative_rounding_int(self):
"""Test ``reverse_transform`` when ``rounding`` is a negative int
The data should round to the number set in the ``_rounding_digits``
attribute and remain ints.
Input:
- Array with with floats above 100
Output:
- Same array rounded to the provided number of 0s
- Array should be of type int
"""
# Setup
data = np.array([2000.0, 120.0, 3100.0, 40100.0])
# Run
transformer = NumericalTransformer(dtype=np.int, nan=None)
transformer._dtype = np.int
transformer._rounding_digits = -3
result = transformer.reverse_transform(data)
# Assert
expected_data = np.array([2000, 0, 3000, 40000])
np.testing.assert_array_equal(result, expected_data)
assert result.dtype == np.int
def test_reverse_transform_rounding_none_with_nulls(self):
"""Test ``reverse_transform`` when ``rounding`` is ``None`` and there are nulls.
The data should not be rounded at all.
Input:
- 2d Array of multiple float values with decimals and a column setting at least 1 null.
Output:
- First column of the input array as entered, replacing the indicated value with a Nan.
"""
# Setup
data = np.array([
[0., 0.],
[1.2, 0.],
[3.45, 1.],
[6.789, 0.],
])
# Run
transformer = NumericalTransformer()
null_transformer = Mock()
null_transformer.reverse_transform.return_value = np.array(
[0., 1.2, np.nan, 6.789])
transformer.null_transformer = null_transformer
transformer._rounding_digits = None
transformer._dtype = np.float
result = transformer.reverse_transform(data)
# Assert
expected = np.array([0., 1.2, np.nan, 6.789])
np.testing.assert_array_equal(result, expected)
def test_reverse_transform_rounding_none_with_nulls_dtype_int(self):
"""Test ``reverse_transform`` when rounding is None, dtype is int and there are nulls.
The data should be rounded to 0 decimals and returned as float values with
nulls in the right place.
Input:
- 2d Array of multiple float values with decimals and a column setting at least 1 null.
Output:
- First column of the input array rounded, replacing the indicated value with a Nan,
and kept as float values.
"""
# Setup
data = np.array([
[0., 0.],
[1.2, 0.],
[3.45, 1.],
[6.789, 0.],
])
# Run
transformer = NumericalTransformer()
null_transformer = Mock()
null_transformer.reverse_transform.return_value = np.array(
[0., 1.2, np.nan, 6.789])
transformer.null_transformer = null_transformer
transformer._rounding_digits = None
transformer._dtype = np.int
result = transformer.reverse_transform(data)
# Assert
expected = np.array([0., 1., np.nan, 7.])
np.testing.assert_array_equal(result, expected)
def test_reverse_transform_rounding_none_integer(self):
"""Test ``reverse_transform`` when ``rounding`` is ``None`` and the dtype is integer.
The data should be rounded to 0 decimals and returned as integer values.
Input:
- Array of multiple float values with decimals.
Output:
- Input array rounded an converted to integers.
"""
# Setup
data = np.array([0., 1.2, 3.45, 6.789])
# Run
transformer = NumericalTransformer(dtype=np.int64, nan=None)
transformer._rounding_digits = None
transformer._dtype = np.int64
result = transformer.reverse_transform(data)
# Assert
expected = np.array([0, 1, 3, 7])
np.testing.assert_array_equal(result, expected)