def test_lambda_for_no_bounded_weights(self):
# pylint: disable=protected-access,invalid-name
"""
Test the computation of lambda when there are no bounded weights
"""
cla = CLA(weight_bounds=(0, 1), calculate_expected_returns="mean")
cla.allocate(asset_prices=self.data, solution='min_volatility', asset_names=self.data.columns)
data = self.data.cov()
data = data.values
x, y = cla._compute_lambda(covar_f_inv=data,
covar_fb=data,
mean_f=cla.expected_returns,
w_b=None,
asset_index=1,
b_i=[[0], [1]])
assert isinstance(x, float)
assert isinstance(y, int)
def test_lambda_for_zero_matrices(self):
# pylint: disable=protected-access,invalid-name
"""
Test the computation of lambda when there are no bounded weights. The method
should return None, None
"""
cla = CLA(weight_bounds=(0, 1), calculate_expected_returns="mean")
cla.allocate(asset_prices=self.data, solution='min_volatility', asset_names=self.data.columns)
data = self.data.cov()
data = data.values
data[:, :] = 0
x, y = cla._compute_lambda(covar_f_inv=data,
covar_fb=data,
mean_f=cla.expected_returns,
w_b=None,
asset_index=1,
b_i=[[0], [1]])
assert not x
assert not y