def test_bias_influence_array(self):
"""
This method tests the influence of the bias array. The results should be different.
"""
n = 8
k = 4
mu = 1
sigma = 0.5
challenges = tools.all_inputs(n)
weight_array = NoisyLTFArray.normal_weights(
n, k, mu=mu, sigma=sigma, random_instance=RandomState(0xBADA556))
bias_array = NoisyLTFArray.normal_weights(
1,
k,
mu=mu,
sigma=sigma * 2,
random_instance=RandomState(0xBADAFF1))
biased_ltf_array = NoisyLTFArray(
weight_array=weight_array,
transform=NoisyLTFArray.transform_id,
combiner=NoisyLTFArray.combiner_xor,
sigma_noise=sigma,
bias=bias_array,
)
ltf_array = NoisyLTFArray(
weight_array=weight_array,
transform=NoisyLTFArray.transform_id,
combiner=NoisyLTFArray.combiner_xor,
sigma_noise=sigma,
bias=None,
)
self.assertEqual(ltf_array.weight_array.shape,
biased_ltf_array.weight_array.shape)
bias_array = biased_ltf_array.weight_array[:, -1]
bias_array_compared = [
bias == bias_array[0] for bias in bias_array[1:]
]
# the bias values should be different for this test. It is possible that they are all equal but this chance is
# low.
self.assertFalse(array(bias_array_compared).all())
biased_responses = biased_ltf_array.eval(challenges)
responses = ltf_array.eval(challenges)
# The arithmetic mean of the res
self.assertFalse(array_equal(biased_responses, responses))
def test_bias_influence_value(self):
"""
This method tests the influence of the bias value. The results should be different.
"""
n = 8
k = 4
mu = 1
sigma = 0.5
challenges = array(list(tools.all_inputs(n)))
weight_array = NoisyLTFArray.normal_weights(n, k, mu=mu, sigma=sigma, random_instance=RandomState(0xBADA556))
bias_value = 2.5
biased_ltf_array = NoisyLTFArray(
weight_array=weight_array,
transform=NoisyLTFArray.transform_id,
combiner=NoisyLTFArray.combiner_xor,
sigma_noise=sigma,
bias=bias_value,
)
ltf_array = NoisyLTFArray(
weight_array=weight_array,
transform=NoisyLTFArray.transform_id,
combiner=NoisyLTFArray.combiner_xor,
sigma_noise=sigma,
bias=None,
)
# the second dimension of the weight_array plus one must be the number of elements in biased weight_array
self.assertEqual(shape(ltf_array.weight_array)[1]+1, shape(biased_ltf_array.weight_array)[1])
bias_array = biased_ltf_array.weight_array[:, -1]
bias_array_compared = [bias == bias_array[0] for bias in bias_array]
# the bias values should be equal for this test.
self.assertTrue(array(list(bias_array_compared)).all())
biased_responses = biased_ltf_array.eval(challenges)
responses = ltf_array.eval(challenges)
# The arithmetic mean of the res
self.assertFalse(array_equal(biased_responses, responses))