def test__flatten_dict_missing_keys_gh_89(self):
"""flatten_dict will only ignore keys that don't have dict or list values.
https://github.com/HDI-Project/SDV/issues/89
"""
# Setup
nested_dict = {
'covariance': [
[1.4999999999999991, 1.4999999999999991, 1.4999999999999991],
[1.4999999999999991, 1.4999999999999991, 1.4999999999999991],
[1.4999999999999991, 1.4999999999999991, 1.4999999999999991]],
'distribs': {
'type': {
'type': 'copulas.univariate.gaussian.GaussianUnivariate',
'fitted': True,
'mean': 4.0,
'std': 2.449489742783178
},
'distribution': {
'type': 'copulas.univariate.gaussian.GaussianUnivariate',
'fitted': True,
'mean': 5.0,
'std': 2.449489742783178
},
'fitted': {
'type': 'copulas.univariate.gaussian.GaussianUnivariate',
'fitted': True,
'mean': 6.0,
'std': 2.449489742783178
}
},
'type': 'copulas.multivariate.gaussian.GaussianMultivariate',
'fitted': True,
'distribution': 'copulas.univariate.gaussian.GaussianUnivariate'
}
expected_result = {
'covariance__0__0': 1.4999999999999991,
'covariance__0__1': 1.4999999999999991,
'covariance__0__2': 1.4999999999999991,
'covariance__1__0': 1.4999999999999991,
'covariance__1__1': 1.4999999999999991,
'covariance__1__2': 1.4999999999999991,
'covariance__2__0': 1.4999999999999991,
'covariance__2__1': 1.4999999999999991,
'covariance__2__2': 1.4999999999999991,
'distribs__type__mean': 4.0,
'distribs__type__std': 2.449489742783178,
'distribs__distribution__mean': 5.0,
'distribs__distribution__std': 2.449489742783178,
'distribs__fitted__mean': 6.0,
'distribs__fitted__std': 2.449489742783178
}
# Run
result = Modeler._flatten_dict(nested_dict)
# Check
assert result == expected_result
def test__flatten_dict_flat_dict(self):
"""_flatten_dict don't modify flat dicts."""
# Setup
nested_dict = {'a': 1, 'b': 2}
expected_result = {'a': 1, 'b': 2}
# Run
result = Modeler._flatten_dict(nested_dict)
# Check
assert result == expected_result
def test__flatten_dict_nested_dict(self):
"""_flatten_dict flatten nested dicts respecting the prefixes."""
# Setup
nested_dict = {'first_key': {'a': 1, 'b': 2}, 'second_key': {'x': 0}}
expected_result = {
'first_key__a': 1,
'first_key__b': 2,
'second_key__x': 0
}
# Run
result = Modeler._flatten_dict(nested_dict)
# Check
assert result == expected_result
def test__flatten_dict(self):
"""Test get flatten dict with some result"""
# Run
nested = {
'foo': 'value',
'bar': {
'bar_dict': 'value_bar_dict'
},
'tar': ['value_tar_list_0', 'value_tar_list_1'],
'fitted': 'value_1',
'distribution': 'value_2',
'type': 'value_3'
}
result = Modeler._flatten_dict(nested, prefix='test')
# Asserts
expected = {
'test__foo': 'value',
'test__bar__bar_dict': 'value_bar_dict',
'test__tar__0': 'value_tar_list_0',
'test__tar__1': 'value_tar_list_1'
}
assert result == expected
