diff --git a/Lib/statistics.py b/Lib/statistics.py index 758b5b58848fb9..7ccd8d862cb7bf 100644 --- a/Lib/statistics.py +++ b/Lib/statistics.py @@ -1206,7 +1206,13 @@ def quantiles(data, *, n=4, method='exclusive'): result = [] for i in range(1, n): j, delta = divmod(i * m, n) - interpolated = (data[j] * (n - delta) + data[j + 1] * delta) / n + a, b = data[j], data[j + 1] + if a == b and type(a) is type(b): + interpolated = a / 1 + elif 2 * delta <= n: + interpolated = a + (b - a) * delta / n + else: + interpolated = b - (b - a) * (n - delta) / n result.append(interpolated) return result @@ -1217,7 +1223,13 @@ def quantiles(data, *, n=4, method='exclusive'): j = i * m // n # rescale i to m/n j = 1 if j < 1 else ld-1 if j > ld-1 else j # clamp to 1 .. ld-1 delta = i*m - j*n # exact integer math - interpolated = (data[j - 1] * (n - delta) + data[j] * delta) / n + a, b = data[j - 1], data[j] + if a == b and type(a) is type(b): + interpolated = a / 1 + elif 2 * delta <= n: + interpolated = a + (b - a) * delta / n + else: + interpolated = b - (b - a) * (n - delta) / n result.append(interpolated) return result diff --git a/Lib/test/test_statistics.py b/Lib/test/test_statistics.py index 700c5ac304f717..50fd1a43bd727d 100644 --- a/Lib/test/test_statistics.py +++ b/Lib/test/test_statistics.py @@ -2647,6 +2647,42 @@ def test_equal_inputs(self): self.assertEqual(quantiles(data, method='inclusive'), [10.0, 10.0, 10.0]) + def test_monotonic_with_duplicate_floats(self): + quantiles = statistics.quantiles + for x in (3.141592653589793, # irrational-ish + 1/3, # repeating binary fraction + 0.1, # non-exact decimal + 2.0, # exact power of two + 1e300, # large magnitude + 1e-300, # small magnitude + float.fromhex('0x1.fffffffffffffp+1023'), # near max float + sys.float_info.min, # smallest normal + float('inf'), + float('-inf'), + ): + for method in ('exclusive', 'inclusive'): + for n in range(2, 20): + with self.subTest(x=x, n=n, method=method): + result = quantiles([x, x], n=n, method=method) + self.assertEqual(result, sorted(result)) + self.assertTrue(all(v == x for v in result)) + + result = quantiles([0.09999999999999999, 0.1, 0.1], + n=9, method='inclusive') + self.assertEqual(result, sorted(result)) + + def test_mixed_types(self): + data = [Fraction(1, 2), 0.5, 2.0] + for method, expected in [ + ('inclusive', [0.5, 0.5, 0.8, 1.4]), + ('exclusive', [0.5, 0.5, 1.1, 2.3]), + ]: + with self.subTest(method=method): + self.assertEqual( + statistics.quantiles(data, n=5, method=method), + expected, + ) + def test_equal_sized_groups(self): quantiles = statistics.quantiles total = 10_000 diff --git a/Misc/NEWS.d/next/Library/2026-05-23-23-14-26.gh-issue-150318.Utah1I.rst b/Misc/NEWS.d/next/Library/2026-05-23-23-14-26.gh-issue-150318.Utah1I.rst new file mode 100644 index 00000000000000..e24e2f49a8db0d --- /dev/null +++ b/Misc/NEWS.d/next/Library/2026-05-23-23-14-26.gh-issue-150318.Utah1I.rst @@ -0,0 +1,2 @@ +Fix :func:`statistics.quantiles` returning unsorted cut points for duplicate +floats.