def test_reverse_transform(self):
"""Test the ``GreaterThan.reverse_transform`` method.
The ``GreaterThan.reverse_transform`` method is expected to:
- Return the original table data.
Input:
- Table data transformed (pandas.DataFrame)
Output:
- Table data (pandas.DataFrame)
Side effects:
- Since ``reverse_transform`` uses the class variable ``_dtype``, the ``fit`` method
must be called as well.
"""
# Setup
table_data = pd.DataFrame({
'a': [1, 2, 3],
'b': [4, 5, 6],
'c': [7, 8, 9]
})
instance = GreaterThan(low='a', high='b', strict=True)
instance.fit(table_data)
# Run
out = instance.reverse_transform(table_data)
# Assert
expected_out = pd.DataFrame({
'a': [1, 2, 3],
'b': [55, 149, 405],
'c': [7, 8, 9],
})
pd.testing.assert_frame_equal(out, expected_out)
def test_fit_float(self):
"""Test the ``GreaterThan.fit`` method.
The ``GreaterThan.fit`` method should only learn and store the
``dtype`` of the ``high`` column as the ``_dtype`` attribute.
Input:
- Table that contains two constrained columns with the high one
being made of float values.
Side Effect:
- The _dtype attribute gets `float` as the value even if the low
column has a different dtype.
"""
# Setup
instance = GreaterThan(low='a', high='b')
# Run
table_data = pd.DataFrame({
'a': [1, 2, 3],
'b': [4., 5., 6.],
'c': [7, 8, 9]
})
instance.fit(table_data)
# Asserts
assert instance._dtype.kind == 'f'
def test_fit_datetime(self):
"""Test the ``GreaterThan.fit`` method.
The ``GreaterThan.fit`` method should only learn and store the
``dtype`` of the ``high`` column as the ``_dtype`` attribute.
Input:
- Table that contains two constrained columns of datetimes.
Side Effect:
- The _dtype attribute gets `datetime` as the value.
"""
# Setup
instance = GreaterThan(low='a', high='b')
# Run
table_data = pd.DataFrame({
'a': pd.to_datetime(['2020-01-01']),
'b': pd.to_datetime(['2020-01-02'])
})
instance.fit(table_data)
# Asserts
assert instance._dtype.kind == 'M'
def test_fit(self):
"""Test the ``GreaterThan.fit`` method.
It is expected to return the dtype of the ``high`` column.
Input:
- Table data (pandas.DataFrame)
Output:
- dtype of the ``high`` column.
"""
# Setup
instance = GreaterThan(low='a', high='b')
# Run
table_data = pd.DataFrame({
'a': [1, 2, 3],
'b': [4, 5, 6],
'c': [7, 8, 9]
})
instance.fit(table_data)
# Asserts
expected = table_data['b'].dtype
assert instance._dtype == expected