def test_reverse_transform_rounding_none(self):
"""Test ``reverse_transform`` when ``rounding`` is ``None``
The data should not be rounded at all.
Input:
- Random array of floats between 0 and 1
Output:
- Input array
"""
# Setup
data = np.random.random(10)
# Run
transformer = NumericalTransformer(dtype=np.float, nan=None)
transformer._rounding_digits = None
result = transformer.reverse_transform(data)
# Assert
np.testing.assert_array_equal(result, data)
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)
def test_reverse_transform_rounding_zero(self):
"""Test ``reverse_transform`` when ``rounding`` is a negative int
The data should round to the number set in the ``_rounding_digits``
attribute.
Input:
- Array with with larger numbers
Output:
- Same array rounded to the provided number of 0s
"""
# Setup
data = np.array([2000.554, 120.2, 3101, 4010])
# Run
transformer = NumericalTransformer(dtype=np.float, nan=None)
transformer._rounding_digits = 0
result = transformer.reverse_transform(data)
# Assert
expected_data = np.array([2001, 120, 3101, 4010])
np.testing.assert_array_equal(result, expected_data)
def test_reverse_transform_rounding_positive_rounding(self):
"""Test ``reverse_transform`` when ``rounding`` is a positive int
The data should round to the maximum number of decimal places
set in the ``_rounding_digits`` value.
Input:
- Array with decimals
Output:
- Same array rounded to the provided number of decimal places
"""
# Setup
data = np.array([1.1111, 2.2222, 3.3333, 4.44444, 5.555555])
# Run
transformer = NumericalTransformer(dtype=np.float, nan=None)
transformer._rounding_digits = 2
result = transformer.reverse_transform(data)
# Assert
expected_data = np.array([1.11, 2.22, 3.33, 4.44, 5.56])
np.testing.assert_array_equal(result, expected_data)