def test_collate_effect_size_2_power(self): # The known effect is used as a reference elsewhere test_means, test_bounds = collate_effect_size(counts=self.counts, powers=self.power2, alpha=self.alpha) npt.assert_almost_equal(self.effects, test_means, 4) npt.assert_almost_equal(self.bounds, test_bounds, 4)
def test_collate_effect_size_1_power(self): known_means = np.array([0.72374193, 0.5795861]) known_bounds = np.array([0.17654622, 0.06264818]) test_means, test_bounds = collate_effect_size(counts=self.counts, powers=self.power1, alpha=self.alpha) npt.assert_almost_equal(known_means, test_means, 4) npt.assert_almost_equal(known_bounds, test_bounds, 4)
def test_collate_effect_size_nan(self): power = [count * 0 for count in self.counts] test_mean, test_bounds = collate_effect_size(counts=self.counts, powers=power, alpha=self.alpha) self.assertTrue(np.isnan(test_mean[0])) self.assertTrue(np.isnan(test_bounds[0]))
def test_collate_effect_size_nan(self): power = [count*0 for count in self.counts] test_mean, test_bounds = collate_effect_size(counts=self.counts, powers=power, alpha=self.alpha) self.assertTrue(np.isnan(test_mean[0])) self.assertTrue(np.isnan(test_bounds[0]))
def test_collate_effect_size_count_for_power_2d(self): with self.assertRaises(ValueError): collate_effect_size(counts=[self.counts[0]], powers=self.power2[1], alpha=0.05)
def test_collate_effect_size_count_shape_error(self): with self.assertRaises(TypeError): collate_effect_size(counts=self.power2, powers=self.power2, alpha=self.alpha)
def test_collate_effect_size_unequal_counts_error(self): with self.assertRaises(ValueError): collate_effect_size(counts=[np.array([1, 2, 3])], powers=self.power2, alpha=self.alpha)