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test_aggregators.py
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test_aggregators.py
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import aggregators
import numpy as np
import unittest
class TestAggregators(unittest.TestCase):
frames = np.array([1,1,4,2,1,2])
start_indices = np.array([0,0,0,0,1,1])
expected_means = np.array([1,1,2,2,2,2])
expected_maxes = np.array([1,1,4,4,4,4])
expected_mins = np.array([ 1,1,1,1,1,1])
def test_quick_windowed_means(self):
computed_means = aggregators.quick_windowed_means(self.frames, self.start_indices)
self.assertTrue(np.all(self.expected_means ==computed_means))
def test_quick_windowed_max(self):
computed_max = aggregators.quick_windowed_max(self.frames, self.start_indices)
print computed_max
self.assertTrue(np.all(self.expected_maxes ==computed_max))
def test_quick_windowed_min(self):
computed_mins = aggregators.quick_windowed_min(self.frames, self.start_indices)
print computed_mins
self.assertTrue(np.all(self.expected_mins ==computed_mins))
def test_index_weighted_sum(self):
x = np.array([2,0,2,4])
# expected result = (2*1 + 0*2 + 2*3 + 4*4)/10 = 2.4
result = aggregators.index_weighted_sum(x)
self.assertEqual(result , 2.4)
def test_ols(self):
t = np.array([1,2,3,4,5,6])
actual_slope = 2
y = actual_slope * t + 1
computed_slope = aggregators.ols(t, y)
self.assertEqual(actual_slope, computed_slope)
def test_mean_cross_rate(self):
result = aggregators.mean_crossing_rate(self.frames)
# mean of frames is 1.8333, so expecting 3 crossings of 6 frames
self.assertApproxEqual(result, 0.5)