def test_compute_mean_curve_invalid_weights(self):
curves = [
[1.0, 0.85, 0.67, 0.3],
[0.87, 0.76, 0.59, 0.21],
[0.62, 0.41, 0.37, 0.0],
]
weights = [0.6, None, 0.4]
with self.assertRaises(TypeError):
# None is not a valid weight
mean_curve(curves, weights)
def test_mean_std(self):
values = [[5, 4], [10, 9], [8, 7]]
weights = [.2, .3, .5]
mean = mean_curve(values, weights)
std = std_curve(values, weights)
aaae(mean, [8, 7])
aaae(std, [1.73205081, 1.73205081])
def test_mean_std(self):
values = [[5, 4], [10, 9], [8, 7]]
weights = [.2, .3, .5]
mean = mean_curve(values, weights)
std = std_curve(values, weights)
aaae(mean, [8, 7])
aaae(std, [1.73205081, 1.73205081])
def test_compute_mean_curve(self):
curves = [
[1.0, 0.85, 0.67, 0.3],
[0.87, 0.76, 0.59, 0.21],
[0.62, 0.41, 0.37, 0.0],
]
expected_mean_curve = numpy.array([0.83, 0.67333333, 0.54333333, 0.17])
numpy.testing.assert_allclose(expected_mean_curve, mean_curve(curves))
def test_compute_mean_curve_weighted(self):
curves = [
[1.0, 0.85, 0.67, 0.3],
[0.87, 0.76, 0.59, 0.21],
[0.62, 0.41, 0.37, 0.0],
]
weights = [0.5, 0.3, 0.2]
expected_mean_curve = numpy.array([0.885, 0.735, 0.586, 0.213])
numpy.testing.assert_allclose(
expected_mean_curve, mean_curve(curves, weights=weights))
def test_compute_mean_curve_weights_None(self):
# If all weight values are None, ignore the weights altogether
curves = [
[1.0, 0.85, 0.67, 0.3],
[0.87, 0.76, 0.59, 0.21],
[0.62, 0.41, 0.37, 0.0],
]
weights = None
expected_mean_curve = numpy.array([0.83, 0.67333333, 0.54333333, 0.17])
numpy.testing.assert_allclose(
expected_mean_curve, mean_curve(curves, weights=weights))
