diff options
Diffstat (limited to 'Lib/test/test_statistics.py')
| -rw-r--r-- | Lib/test/test_statistics.py | 32 |
1 files changed, 17 insertions, 15 deletions
diff --git a/Lib/test/test_statistics.py b/Lib/test/test_statistics.py index 946c742..ed2f657 100644 --- a/Lib/test/test_statistics.py +++ b/Lib/test/test_statistics.py @@ -2326,18 +2326,18 @@ class TestNormalDist(unittest.TestCase): nd = statistics.NormalDist(300, 23) with self.assertRaises(TypeError): vars(nd) - self.assertEqual(tuple(nd.__slots__), ('mu', 'sigma')) + self.assertEqual(tuple(nd.__slots__), ('_mu', '_sigma')) def test_instantiation_and_attributes(self): nd = statistics.NormalDist(500, 17) - self.assertEqual(nd.mu, 500) - self.assertEqual(nd.sigma, 17) + self.assertEqual(nd.mean, 500) + self.assertEqual(nd.stdev, 17) self.assertEqual(nd.variance, 17**2) # default arguments nd = statistics.NormalDist() - self.assertEqual(nd.mu, 0) - self.assertEqual(nd.sigma, 1) + self.assertEqual(nd.mean, 0) + self.assertEqual(nd.stdev, 1) self.assertEqual(nd.variance, 1**2) # error case: negative sigma @@ -2520,10 +2520,7 @@ class TestNormalDist(unittest.TestCase): with self.assertRaises(statistics.StatisticsError): iq.inv_cdf(1.1) # p over one with self.assertRaises(statistics.StatisticsError): - iq.sigma = 0.0 # sigma is zero - iq.inv_cdf(0.5) - with self.assertRaises(statistics.StatisticsError): - iq.sigma = -0.1 # sigma under zero + iq = NormalDist(100, 0) # sigma is zero iq.inv_cdf(0.5) # Special values @@ -2544,8 +2541,8 @@ class TestNormalDist(unittest.TestCase): def overlap_numeric(X, Y, *, steps=8_192, z=5): 'Numerical integration cross-check for overlap() ' fsum = math.fsum - center = (X.mu + Y.mu) / 2.0 - width = z * max(X.sigma, Y.sigma) + center = (X.mean + Y.mean) / 2.0 + width = z * max(X.stdev, Y.stdev) start = center - width dx = 2.0 * width / steps x_arr = [start + i*dx for i in range(steps)] @@ -2626,12 +2623,12 @@ class TestNormalDist(unittest.TestCase): X = NormalDist(100, 12) Y = +X self.assertIsNot(X, Y) - self.assertEqual(X.mu, Y.mu) - self.assertEqual(X.sigma, Y.sigma) + self.assertEqual(X.mean, Y.mean) + self.assertEqual(X.stdev, Y.stdev) Y = -X self.assertIsNot(X, Y) - self.assertEqual(X.mu, -Y.mu) - self.assertEqual(X.sigma, Y.sigma) + self.assertEqual(X.mean, -Y.mean) + self.assertEqual(X.stdev, Y.stdev) def test_equality(self): NormalDist = statistics.NormalDist @@ -2682,6 +2679,11 @@ class TestNormalDist(unittest.TestCase): nd3 = pickle.loads(pickle.dumps(nd)) self.assertEqual(nd, nd3) + def test_hashability(self): + ND = statistics.NormalDist + s = {ND(100, 15), ND(100.0, 15.0), ND(100, 10), ND(95, 15), ND(100, 15)} + self.assertEqual(len(s), 3) + def test_repr(self): nd = statistics.NormalDist(37.5, 5.625) self.assertEqual(repr(nd), 'NormalDist(mu=37.5, sigma=5.625)') |