def test_blend_percentiles(self):
"""Test blend_percentile function works"""
weights = np.array([0.38872692, 0.33041788, 0.2808552])
percentiles = np.array(
[0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0]
)
result = PercentileBlendingAggregator.blend_percentiles(
PERCENTILE_VALUES, percentiles, weights
)
expected_result_array = np.array(
[
12.70237152,
16.65161847,
17.97408712,
18.86356829,
19.84089805,
20.77406153,
21.39078426,
21.73778353,
22.22440125,
23.53863876,
24.64542338,
]
)
self.assertArrayAlmostEqual(result, expected_result_array)
def test_only_one_point_to_blend(self):
"""Test case where there is only one point in the coordinate we are
blending over."""
weights = np.array([1.0])
percentiles = np.array([20.0, 50.0, 80.0])
percentile_values = np.array([[5.0, 6.0, 7.0]])
result = PercentileBlendingAggregator.blend_percentiles(
percentile_values, percentiles, weights)
expected_result = np.array([5.0, 6.0, 7.0])
self.assertArrayAlmostEqual(result, expected_result)
def test_three_percentiles_symmetric_case(self):
"""Test that when three percentiles are provided the correct values
are returned, not a simple average"""
weights = np.array([0.5, 0.5])
percentiles = np.array([20.0, 50.0, 80.0])
percentile_values = np.array([[5.0, 6.0, 7.0], [5.0, 6.5, 7.0]])
result = PercentileBlendingAggregator.blend_percentiles(
percentile_values, percentiles, weights)
expected_result = np.array([5.0, 6.2, 7.0])
self.assertArrayAlmostEqual(result, expected_result)
def test_two_percentiles(self):
"""Test that when two percentiles are provided, the extreme values in
the set of thresholds we are blending are returned"""
weights = np.array([0.5, 0.5])
percentiles = np.array([30., 60.])
percentile_values = np.array([[5.0, 8.0], [6.0, 7.0]])
result = PercentileBlendingAggregator.blend_percentiles(
percentile_values, percentiles, weights)
expected_result = np.array([5.0, 8.0])
self.assertArrayAlmostEqual(result, expected_result)