def test__rebuild_gaussian_copula(self):
"""Test the ``GaussianCopula._rebuild_gaussian_copula`` method.
The ``test__rebuild_gaussian_copula`` method is expected to:
- Rebuild a square covariance matrix out of a triangular one.
Input:
- numpy array, Triangular covariance matrix
Expected Output:
- numpy array, Square covariance matrix
"""
# Setup
gaussian_copula = Mock(autospec=GaussianCopula)
gaussian_copula._rebuild_covariance_matrix.return_value = [[0.4, 0.17],
[
0.17,
0.07
]]
gaussian_copula._distribution = {'foo': 'GaussianUnivariate'}
# Run
model_parameters = {
'univariates': {
'foo': {
'scale': 0.0,
'loc': 5
},
},
'covariance': [[0.1], [0.4, 0.1]],
'distribution': 'GaussianUnivariate',
}
result = GaussianCopula._rebuild_gaussian_copula(
gaussian_copula, model_parameters)
# Asserts
expected = {
'univariates': [{
'scale': 1.0,
'loc': 5,
'type': 'GaussianUnivariate'
}],
'columns': ['foo'],
'distribution': 'GaussianUnivariate',
'covariance': [[0.4, 0.17], [0.17, 0.07]]
}
assert result == expected
def test__rebuild_gaussian_copula(self):
"""Test the ``GaussianCopula._rebuild_gaussian_copula`` method.
The ``test__rebuild_gaussian_copula`` method is expected to:
- Rebuild a square covariance matrix out of a triangular one.
Input:
- numpy array, Triangular correlation matrix
Expected Output:
- numpy array, Square correlation matrix
"""
# Setup
gaussian_copula = GaussianCopula()
gaussian_copula._field_distributions = {
'foo': 'GaussianUnivariate',
'bar': 'GaussianUnivariate',
'baz': 'GaussianUnivariate',
}
# Run
model_parameters = {
'univariates': {
'foo': {
'scale': 0.0,
'loc': 0.0
},
'bar': {
'scale': 1.0,
'loc': 1.0
},
'baz': {
'scale': 2.0,
'loc': 2.0
},
},
'covariance': [[0.1], [0.2, 0.3]],
'distribution': 'GaussianUnivariate',
}
result = GaussianCopula._rebuild_gaussian_copula(
gaussian_copula, model_parameters)
# Asserts
expected = {
'univariates': [
{
'scale': 0.0,
'loc': 0.0,
'type': 'GaussianUnivariate'
},
{
'scale': 1.0,
'loc': 1.0,
'type': 'GaussianUnivariate'
},
{
'scale': 2.0,
'loc': 2.0,
'type': 'GaussianUnivariate'
},
],
'covariance': [[1.0, 0.1, 0.2], [0.1, 1.0, 0.3], [0.2, 0.3, 1.0]],
'distribution':
'GaussianUnivariate',
'columns': ['foo', 'bar', 'baz'],
}
assert result == expected
