(self)
| 2534 | class TestQuantiles(unittest.TestCase): |
| 2535 | |
| 2536 | def test_specific_cases(self): |
| 2537 | # Match results computed by hand and cross-checked |
| 2538 | # against the PERCENTILE.EXC function in MS Excel. |
| 2539 | quantiles = statistics.quantiles |
| 2540 | data = [120, 200, 250, 320, 350] |
| 2541 | random.shuffle(data) |
| 2542 | for n, expected in [ |
| 2543 | (1, []), |
| 2544 | (2, [250.0]), |
| 2545 | (3, [200.0, 320.0]), |
| 2546 | (4, [160.0, 250.0, 335.0]), |
| 2547 | (5, [136.0, 220.0, 292.0, 344.0]), |
| 2548 | (6, [120.0, 200.0, 250.0, 320.0, 350.0]), |
| 2549 | (8, [100.0, 160.0, 212.5, 250.0, 302.5, 335.0, 357.5]), |
| 2550 | (10, [88.0, 136.0, 184.0, 220.0, 250.0, 292.0, 326.0, 344.0, 362.0]), |
| 2551 | (12, [80.0, 120.0, 160.0, 200.0, 225.0, 250.0, 285.0, 320.0, 335.0, |
| 2552 | 350.0, 365.0]), |
| 2553 | (15, [72.0, 104.0, 136.0, 168.0, 200.0, 220.0, 240.0, 264.0, 292.0, |
| 2554 | 320.0, 332.0, 344.0, 356.0, 368.0]), |
| 2555 | ]: |
| 2556 | self.assertEqual(expected, quantiles(data, n=n)) |
| 2557 | self.assertEqual(len(quantiles(data, n=n)), n - 1) |
| 2558 | # Preserve datatype when possible |
| 2559 | for datatype in (float, Decimal, Fraction): |
| 2560 | result = quantiles(map(datatype, data), n=n) |
| 2561 | self.assertTrue(all(type(x) == datatype) for x in result) |
| 2562 | self.assertEqual(result, list(map(datatype, expected))) |
| 2563 | # Quantiles should be idempotent |
| 2564 | if len(expected) >= 2: |
| 2565 | self.assertEqual(quantiles(expected, n=n), expected) |
| 2566 | # Cross-check against method='inclusive' which should give |
| 2567 | # the same result after adding in minimum and maximum values |
| 2568 | # extrapolated from the two lowest and two highest points. |
| 2569 | sdata = sorted(data) |
| 2570 | lo = 2 * sdata[0] - sdata[1] |
| 2571 | hi = 2 * sdata[-1] - sdata[-2] |
| 2572 | padded_data = data + [lo, hi] |
| 2573 | self.assertEqual( |
| 2574 | quantiles(data, n=n), |
| 2575 | quantiles(padded_data, n=n, method='inclusive'), |
| 2576 | (n, data), |
| 2577 | ) |
| 2578 | # Invariant under translation and scaling |
| 2579 | def f(x): |
| 2580 | return 3.5 * x - 1234.675 |
| 2581 | exp = list(map(f, expected)) |
| 2582 | act = quantiles(map(f, data), n=n) |
| 2583 | self.assertTrue(all(math.isclose(e, a) for e, a in zip(exp, act))) |
| 2584 | # Q2 agrees with median() |
| 2585 | for k in range(2, 60): |
| 2586 | data = random.choices(range(100), k=k) |
| 2587 | q1, q2, q3 = quantiles(data) |
| 2588 | self.assertEqual(q2, statistics.median(data)) |
| 2589 | |
| 2590 | def test_specific_cases_inclusive(self): |
| 2591 | # Match results computed by hand and cross-checked |
nothing calls this directly
no test coverage detected