def test__bootstrap__computation(self): """ Result of bootstrap() equals expected result. """ # Computing bootstrap result1 = statx.bootstrap(self.samples.temperature, [0], min_observations=1) # Checking if lower percentile of result2 is correct self.assertAlmostEqual(result1[0][2.5], 98.1220, 2) # Checking if upper percentile of result2 is correct self.assertAlmostEqual(result1[0][97.5], 98.3708, 2) # Checking if no bootstrap data was passed self.assertIsNone(result1[1]) # Defining data and computing bootstrap zero_3 = np.array([0., 0., 0.]) one_3 = np.array([1., 1., 1.]) result2 = statx.bootstrap(zero_3, one_3, min_observations=3) # Checking if lower percentile of result2 is correct self.assertEqual(result2[0][2.5], -1.0) # Checking if upper percentile of result2 is correct self.assertEqual(result2[0][97.5], -1.0) # Checking if no bootstrap data was passed self.assertIsNone(result2[1]) # Defining data and computing bootstrap sample1 = self.samples.temperature[self.samples.gender == 1] sample2 = self.samples.temperature[self.samples.gender == 2] result3 = statx.bootstrap(sample1, sample2) # Checking if lower percentile of result3 is correct self.assertAlmostEqual(result3[0][2.5], -0.53384615384615619) # Checking if upper percentile of result3 is correct self.assertAlmostEqual(result3[0][97.5], -0.049192307692299965) # Checking if no bootstrap data was passed self.assertIsNone(result3[1])