blob: c95607851acd17d21dad58a064335c77f921ade5 (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
|
//! Testing-only functionality, used elsewhere in this crate.
pub(crate) use imp::*;
/// Testing implementation helpers.
///
/// This module comes in two flavors: a stochastic and a non-stochastic one.
/// When stochastic testing is enabled, we use a real PRNG, and therefore
/// we require more iterations and broader tolerances.
///
/// The stochastic testing version of this module is on when the
/// `stochastic-tests` feature is enabled.
#[cfg(any(doc, not(feature = "stochastic-tests")))]
mod imp {
/// Return a new RNG -- possibly a pre-seeded one.
pub(crate) fn get_rng() -> impl rand::Rng {
// When stochastic tests aren't enabled, we use a RNG seeded
// with a fixed value and a small number of iterators for each test.
//
// XXXX: Note that the StdRng is not guaranteed to be
// reproducible across rust stdlib versions; an upgrade might break
// these tests.
use rand::SeedableRng;
rand::rngs::StdRng::from_seed(
// Fun facts:
// The Julius Tote was a mechanical computer and point-of-sale
// system from the 1920s that used horses as an RNG.
*b"George Alfred Julius Totalisator",
)
}
/// Return the number of iterations for which to run a randomized test.
pub(crate) fn get_iters() -> usize {
5000
}
/// Assert that a is close to b.
pub(crate) fn check_close(a: isize, b: isize) {
assert!((a - b).abs() <= (b / 20) + 5);
}
}
// ------ stochastic implementations of above features.
#[cfg(all(not(doc), feature = "stochastic-tests"))]
mod imp {
pub(crate) fn get_rng() -> impl rand::Rng {
rand::thread_rng()
}
#[cfg(all(not(doc), feature = "stochastic-tests"))]
pub(crate) fn get_iters() -> usize {
1000000
}
#[cfg(feature = "stochastic-tests")]
pub(crate) fn check_close(a: isize, b: isize) {
assert!((a - b).abs() <= (b / 100));
}
}
|
