4 use self::test::test::Bencher;
6 use std::io::prelude::*;
8 // Test vectors generated from R, using the script src/etc/stat-test-vectors.r.
10 macro_rules! assert_approx_eq {
11 ($a: expr, $b: expr) => {{
12 let (a, b) = (&$a, &$b);
13 assert!((*a - *b).abs() < 1.0e-6, "{} is not approximately equal to {}", *a, *b);
17 fn check(samples: &[f64], summ: &Summary) {
18 let summ2 = Summary::new(samples);
20 let mut w = io::sink();
22 (write!(w, "\n")).unwrap();
24 assert_eq!(summ.sum, summ2.sum);
25 assert_eq!(summ.min, summ2.min);
26 assert_eq!(summ.max, summ2.max);
27 assert_eq!(summ.mean, summ2.mean);
28 assert_eq!(summ.median, summ2.median);
30 // We needed a few more digits to get exact equality on these
31 // but they're within float epsilon, which is 1.0e-6.
32 assert_approx_eq!(summ.var, summ2.var);
33 assert_approx_eq!(summ.std_dev, summ2.std_dev);
34 assert_approx_eq!(summ.std_dev_pct, summ2.std_dev_pct);
35 assert_approx_eq!(summ.median_abs_dev, summ2.median_abs_dev);
36 assert_approx_eq!(summ.median_abs_dev_pct, summ2.median_abs_dev_pct);
38 assert_eq!(summ.quartiles, summ2.quartiles);
39 assert_eq!(summ.iqr, summ2.iqr);
43 fn test_min_max_nan() {
44 let xs = &[1.0, 2.0, f64::NAN, 3.0, 4.0];
45 let summary = Summary::new(xs);
46 assert_eq!(summary.min, 1.0);
47 assert_eq!(summary.max, 4.0);
52 let val = &[958.0000000000, 924.0000000000];
58 median: 941.0000000000,
60 std_dev: 24.0416305603,
61 std_dev_pct: 2.5549022912,
62 median_abs_dev: 25.2042000000,
63 median_abs_dev_pct: 2.6784484591,
64 quartiles: (932.5000000000, 941.0000000000, 949.5000000000),
70 fn test_norm10narrow() {
88 median: 970.5000000000,
89 var: 16050.7111111111,
90 std_dev: 126.6914010938,
91 std_dev_pct: 12.6742097933,
92 median_abs_dev: 102.2994000000,
93 median_abs_dev_pct: 10.5408964451,
94 quartiles: (956.7500000000, 970.5000000000, 1078.7500000000),
100 fn test_norm10medium() {
113 let summ = &Summary {
114 sum: 8653.0000000000,
116 max: 1084.0000000000,
117 mean: 865.3000000000,
118 median: 911.5000000000,
119 var: 48628.4555555556,
120 std_dev: 220.5186059170,
121 std_dev_pct: 25.4846418487,
122 median_abs_dev: 195.7032000000,
123 median_abs_dev_pct: 21.4704552935,
124 quartiles: (771.0000000000, 911.5000000000, 1017.2500000000),
130 fn test_norm10wide() {
143 let summ = &Summary {
144 sum: 9349.0000000000,
146 max: 1591.0000000000,
147 mean: 934.9000000000,
148 median: 913.5000000000,
149 var: 239208.9888888889,
150 std_dev: 489.0899599142,
151 std_dev_pct: 52.3146817750,
152 median_abs_dev: 611.5725000000,
153 median_abs_dev_pct: 66.9482758621,
154 quartiles: (567.2500000000, 913.5000000000, 1331.2500000000),
160 fn test_norm25verynarrow() {
188 let summ = &Summary {
189 sum: 24926.0000000000,
191 max: 1040.0000000000,
192 mean: 997.0400000000,
193 median: 998.0000000000,
195 std_dev: 19.8294393937,
196 std_dev_pct: 1.9888308788,
197 median_abs_dev: 22.2390000000,
198 median_abs_dev_pct: 2.2283567134,
199 quartiles: (983.0000000000, 998.0000000000, 1013.0000000000),
218 let summ = &Summary {
223 median: 11.5000000000,
225 std_dev: 16.9643416875,
226 std_dev_pct: 101.5828843560,
227 median_abs_dev: 13.3434000000,
228 median_abs_dev_pct: 116.0295652174,
229 quartiles: (4.2500000000, 11.5000000000, 22.5000000000),
248 let summ = &Summary {
253 median: 24.5000000000,
255 std_dev: 19.5848580967,
256 std_dev_pct: 74.4671410520,
257 median_abs_dev: 22.9803000000,
258 median_abs_dev_pct: 93.7971428571,
259 quartiles: (9.5000000000, 24.5000000000, 36.5000000000),
278 let summ = &Summary {
283 median: 22.0000000000,
285 std_dev: 21.4050876611,
286 std_dev_pct: 88.4507754589,
287 median_abs_dev: 21.4977000000,
288 median_abs_dev_pct: 97.7168181818,
289 quartiles: (7.7500000000, 22.0000000000, 35.0000000000),
323 let summ = &Summary {
328 median: 19.0000000000,
330 std_dev: 24.5161851301,
331 std_dev_pct: 103.3565983562,
332 median_abs_dev: 19.2738000000,
333 median_abs_dev_pct: 101.4410526316,
334 quartiles: (6.0000000000, 19.0000000000, 31.0000000000),
368 let summ = &Summary {
373 median: 20.0000000000,
375 std_dev: 4.5650848842,
376 std_dev_pct: 22.2037202539,
377 median_abs_dev: 5.9304000000,
378 median_abs_dev_pct: 29.6520000000,
379 quartiles: (17.0000000000, 20.0000000000, 24.0000000000),
385 fn test_pois25lambda30() {
413 let summ = &Summary {
418 median: 32.0000000000,
420 std_dev: 5.1568724372,
421 std_dev_pct: 16.3814245145,
422 median_abs_dev: 5.9304000000,
423 median_abs_dev_pct: 18.5325000000,
424 quartiles: (28.0000000000, 32.0000000000, 34.0000000000),
430 fn test_pois25lambda40() {
458 let summ = &Summary {
459 sum: 1019.0000000000,
463 median: 42.0000000000,
465 std_dev: 5.8685603004,
466 std_dev_pct: 14.3978417577,
467 median_abs_dev: 5.9304000000,
468 median_abs_dev_pct: 14.1200000000,
469 quartiles: (37.0000000000, 42.0000000000, 45.0000000000),
475 fn test_pois25lambda50() {
503 let summ = &Summary {
504 sum: 1235.0000000000,
508 median: 50.0000000000,
510 std_dev: 5.6273143387,
511 std_dev_pct: 11.3913245723,
512 median_abs_dev: 4.4478000000,
513 median_abs_dev_pct: 8.8956000000,
514 quartiles: (44.0000000000, 50.0000000000, 52.0000000000),
548 let summ = &Summary {
549 sum: 1242.0000000000,
553 median: 45.0000000000,
554 var: 1015.6433333333,
555 std_dev: 31.8691595957,
556 std_dev_pct: 64.1488719719,
557 median_abs_dev: 45.9606000000,
558 median_abs_dev_pct: 102.1346666667,
559 quartiles: (29.0000000000, 45.0000000000, 79.0000000000),
567 assert_eq!([0.5f64, 3.2321f64, 1.5678f64].sum(), 5.2999);
570 fn test_sum_f64_between_ints_that_sum_to_0() {
571 assert_eq!([1e30f64, 1.2f64, -1e30f64].sum(), 1.2);
575 pub fn sum_three_items(b: &mut Bencher) {
577 [1e20f64, 1.5f64, -1e20f64].sum();
581 pub fn sum_many_f64(b: &mut Bencher) {
582 let nums = [-1e30f64, 1e60, 1e30, 1.0, -1e60];
583 let v = (0..500).map(|i| nums[i % 5]).collect::<Vec<_>>();
591 pub fn no_iter(_: &mut Bencher) {}