From 889ba4db991a33491c154cb4d6126b91bf8e99f8 Mon Sep 17 00:00:00 2001 From: Raymond Hettinger Date: Sun, 5 May 2024 00:07:57 -0500 Subject: [PATCH] Simplify and tighten the distribution test --- Lib/test/test_statistics.py | 21 +++++++++++---------- 1 file changed, 11 insertions(+), 10 deletions(-) diff --git a/Lib/test/test_statistics.py b/Lib/test/test_statistics.py index fe6c59c30dae28..a60791e9b6e1f5 100644 --- a/Lib/test/test_statistics.py +++ b/Lib/test/test_statistics.py @@ -2482,29 +2482,30 @@ def test_kde_random(self): # Approximate distribution test: Compare a random sample to the expected distribution data = [-2.1, -1.3, -0.4, 1.9, 5.1, 6.2, 7.8, 14.3, 15.1, 15.3, 15.8, 17.0] + xarr = [x / 10 for x in range(-100, 250)] n = 1_000_000 h = 1.75 dx = 0.1 - def p_expected(x): - return F_hat(x + dx) - F_hat(x - dx) - def p_observed(x): - # P(x-dx <= X < x+dx) / (2*dx) - i = bisect.bisect_left(big_sample, x - dx) - j = bisect.bisect_right(big_sample, x + dx) + # P(x <= X < x+dx) + i = bisect.bisect_left(big_sample, x) + j = bisect.bisect_left(big_sample, x + dx) return (j - i) / len(big_sample) + def p_expected(x): + # P(x <= X < x+dx) + return F_hat(x + dx) - F_hat(x) + for kernel in kernels: with self.subTest(kernel=kernel): - F_hat = statistics.kde(data, h, kernel, cumulative=True) rand = kde_random(data, h, kernel, seed=8675309**2) big_sample = sorted([rand() for i in range(n)]) + F_hat = statistics.kde(data, h, kernel, cumulative=True) - for x in range(-40, 190): - x /= 10 - self.assertTrue(math.isclose(p_observed(x), p_expected(x), abs_tol=0.001)) + for x in xarr: + self.assertTrue(math.isclose(p_observed(x), p_expected(x), abs_tol=0.0005)) class TestQuantiles(unittest.TestCase):