num_complex/
crand.rs
1use crate::Complex;
4use num_traits::Num;
5use rand::distributions::Standard;
6use rand::prelude::*;
7
8impl<T> Distribution<Complex<T>> for Standard
9where
10 T: Num + Clone,
11 Standard: Distribution<T>,
12{
13 fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Complex<T> {
14 Complex::new(self.sample(rng), self.sample(rng))
15 }
16}
17
18#[derive(Clone, Copy, Debug)]
20pub struct ComplexDistribution<Re, Im = Re> {
21 re: Re,
22 im: Im,
23}
24
25impl<Re, Im> ComplexDistribution<Re, Im> {
26 pub fn new(re: Re, im: Im) -> Self {
29 ComplexDistribution { re, im }
30 }
31}
32
33impl<T, Re, Im> Distribution<Complex<T>> for ComplexDistribution<Re, Im>
34where
35 T: Num + Clone,
36 Re: Distribution<T>,
37 Im: Distribution<T>,
38{
39 fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Complex<T> {
40 Complex::new(self.re.sample(rng), self.im.sample(rng))
41 }
42}
43
44#[cfg(test)]
45fn test_rng() -> impl RngCore {
46 struct XorShiftStar {
48 a: u64,
49 }
50
51 impl RngCore for XorShiftStar {
52 fn next_u32(&mut self) -> u32 {
53 self.next_u64() as u32
54 }
55
56 fn next_u64(&mut self) -> u64 {
57 self.a ^= self.a >> 12;
59 self.a ^= self.a << 25;
60 self.a ^= self.a >> 27;
61 self.a.wrapping_mul(0x2545_F491_4F6C_DD1D)
62 }
63
64 fn fill_bytes(&mut self, dest: &mut [u8]) {
65 for chunk in dest.chunks_mut(8) {
66 let bytes = self.next_u64().to_le_bytes();
67 let slice = &bytes[..chunk.len()];
68 chunk.copy_from_slice(slice)
69 }
70 }
71
72 fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), rand::Error> {
73 Ok(self.fill_bytes(dest))
74 }
75 }
76
77 XorShiftStar {
78 a: 0x0123_4567_89AB_CDEF,
79 }
80}
81
82#[test]
83fn standard_f64() {
84 let mut rng = test_rng();
85 for _ in 0..100 {
86 let c: Complex<f64> = rng.gen();
87 assert!(c.re >= 0.0 && c.re < 1.0);
88 assert!(c.im >= 0.0 && c.im < 1.0);
89 }
90}
91
92#[test]
93fn generic_standard_f64() {
94 let mut rng = test_rng();
95 let dist = ComplexDistribution::new(Standard, Standard);
96 for _ in 0..100 {
97 let c: Complex<f64> = rng.sample(&dist);
98 assert!(c.re >= 0.0 && c.re < 1.0);
99 assert!(c.im >= 0.0 && c.im < 1.0);
100 }
101}
102
103#[test]
104fn generic_uniform_f64() {
105 use rand::distributions::Uniform;
106
107 let mut rng = test_rng();
108 let re = Uniform::new(-100.0, 0.0);
109 let im = Uniform::new(0.0, 100.0);
110 let dist = ComplexDistribution::new(re, im);
111 for _ in 0..100 {
112 let c = rng.sample(&dist);
114 assert!(c.re >= -100.0 && c.re < 0.0);
115 assert!(c.im >= 0.0 && c.im < 100.0);
116 }
117}
118
119#[test]
120fn generic_mixed_f64() {
121 use rand::distributions::Uniform;
122
123 let mut rng = test_rng();
124 let re = Uniform::new(-100.0, 0.0);
125 let dist = ComplexDistribution::new(re, Standard);
126 for _ in 0..100 {
127 let c = rng.sample(&dist);
129 assert!(c.re >= -100.0 && c.re < 0.0);
130 assert!(c.im >= 0.0 && c.im < 1.0);
131 }
132}
133
134#[test]
135fn generic_uniform_i32() {
136 use rand::distributions::Uniform;
137
138 let mut rng = test_rng();
139 let re = Uniform::new(-100, 0);
140 let im = Uniform::new(0, 100);
141 let dist = ComplexDistribution::new(re, im);
142 for _ in 0..100 {
143 let c = rng.sample(&dist);
145 assert!(c.re >= -100 && c.re < 0);
146 assert!(c.im >= 0 && c.im < 100);
147 }
148}