sciforge 0.0.3

A comprehensive scientific computing library in pure Rust with zero dependencies
Documentation 
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

use sciforge::hub::prelude::*;

fn run_maths(name: &str, params: Vec<(&str, ParameterValue)>) -> RunOutput {
    let mut exp = Experiment::new(DomainType::Maths, name);
    for (k, v) in params {
        exp = exp.param(k, v);
    }
    ExperimentRunner::new()
        .run(&exp)
        .unwrap_or_else(|_| panic!("dispatch '{name}' failed"))
}

fn scalar(o: RunOutput) -> f64 {
    match o {
        RunOutput::Scalar(v) => v,
        _ => panic!("expected Scalar, got {o:?}"),
    }
}

#[test]
fn prob_normal_pdf() {
    let v = scalar(run_maths(
        "prob_normal_pdf",
        vec![
            ("x", ParameterValue::Scalar(0.0)),
            ("mu", ParameterValue::Scalar(0.0)),
            ("sigma", ParameterValue::Scalar(1.0)),
        ],
    ));
    let expected = 1.0 / (2.0 * std::f64::consts::PI).sqrt();
    assert!((v - expected).abs() < 1e-6, "N(0;0,1)≈0.3989, got {v}");
}

#[test]
fn prob_exponential_cdf() {
    let v = scalar(run_maths(
        "prob_exponential_cdf",
        vec![
            ("x", ParameterValue::Scalar(0.0)),
            ("lambda", ParameterValue::Scalar(1.0)),
        ],
    ));
    assert!(v.abs() < 1e-8, "CDF(0)=0, got {v}");
}

#[test]
fn monte_carlo_pi() {
    let v = scalar(run_maths(
        "monte_carlo_pi",
        vec![
            ("n", ParameterValue::Integer(100000)),
            ("seed", ParameterValue::Integer(42)),
        ],
    ));
    assert!((v - std::f64::consts::PI).abs() < 0.1, "pi≈3.14, got {v}");
}