def test_returns_correct_values(self):
"""Test it returns the correct values. """
weights_in = np.array([6.0, 3.0, 1.0])
result = WeightsUtilities.normalise_weights(weights_in)
expected_result = np.array([0.6, 0.3, 0.1])
self.assertArrayAlmostEqual(result, expected_result)
def test_fails_sum_equals_zero(self):
"""Test it fails if sum of input weights is zero. """
weights_in = np.array([0.0, 0.0, 0.0])
msg = ('Sum of weights must be > 0.0')
with self.assertRaisesRegexp(ValueError, msg):
WeightsUtilities.normalise_weights(weights_in)
def test_array_sum_equals_one(self):
"""Test that the resulting weights add up to one. """
weights_in = np.array([1.0, 2.0, 3.0])
result = WeightsUtilities.normalise_weights(weights_in)
self.assertAlmostEquals(result.sum(), 1.0)
def test_fails_weight_less_than_zero(self):
"""Test it fails if weight less than zero. """
weights_in = np.array([-1.0, 0.1])
msg = ('Weights must be positive')
with self.assertRaisesRegexp(ValueError, msg):
WeightsUtilities.normalise_weights(weights_in)
def test_basic(self):
"""Test that the function returns an array of weights. """
weights_in = np.array([1.0, 2.0, 3.0])
result = WeightsUtilities.normalise_weights(weights_in)
self.assertIsInstance(result, np.ndarray)