nalgebra/src/tests/mat.rs
Vincent Barrielle 2fd880a62d implemented QR factorization
this is a first sketch, the algorithm is not yet initialized and relies
on knowledge of DMat internals. A next step would be to implement this
algorithm in a more generic manner.
2014-05-09 18:59:26 +02:00

230 lines
4.4 KiB
Rust

use std::num::{Float, abs};
use rand::random;
use na::{Vec1, Vec3, Mat1, Mat2, Mat3, Mat4, Mat5, Mat6, Rot3, DMat, DVec, Indexable};
use na;
use na::decomp_qr;
macro_rules! test_inv_mat_impl(
($t: ty) => (
for _ in range(0, 10000) {
let randmat : $t = random();
assert!(na::approx_eq(&(na::inv(&randmat).unwrap() * randmat), &na::one()));
}
);
)
macro_rules! test_transpose_mat_impl(
($t: ty) => (
for _ in range(0, 10000) {
let randmat : $t = random();
assert!(na::transpose(&na::transpose(&randmat)) == randmat);
}
);
)
#[test]
fn test_transpose_mat1() {
test_transpose_mat_impl!(Mat1<f64>);
}
#[test]
fn test_transpose_mat2() {
test_transpose_mat_impl!(Mat2<f64>);
}
#[test]
fn test_transpose_mat3() {
test_transpose_mat_impl!(Mat3<f64>);
}
#[test]
fn test_transpose_mat4() {
test_transpose_mat_impl!(Mat4<f64>);
}
#[test]
fn test_transpose_mat5() {
test_transpose_mat_impl!(Mat5<f64>);
}
#[test]
fn test_transpose_mat6() {
test_transpose_mat_impl!(Mat6<f64>);
}
#[test]
fn test_inv_mat1() {
test_inv_mat_impl!(Mat1<f64>);
}
#[test]
fn test_inv_mat2() {
test_inv_mat_impl!(Mat2<f64>);
}
#[test]
fn test_inv_mat3() {
test_inv_mat_impl!(Mat3<f64>);
}
#[test]
fn test_inv_mat4() {
test_inv_mat_impl!(Mat4<f64>);
}
#[test]
fn test_inv_mat5() {
test_inv_mat_impl!(Mat5<f64>);
}
#[test]
fn test_inv_mat6() {
test_inv_mat_impl!(Mat6<f64>);
}
#[test]
fn test_rotation2() {
for _ in range(0, 10000) {
let randmat: na::Rot2<f64> = na::one();
let ang = Vec1::new(abs::<f64>(random()) % Float::pi());
assert!(na::approx_eq(&na::rotation(&na::append_rotation(&randmat, &ang)), &ang));
}
}
#[test]
fn test_index_mat2() {
let mat: Mat2<f64> = random();
assert!(mat.at((0, 1)) == na::transpose(&mat).at((1, 0)));
}
#[test]
fn test_inv_rotation3() {
for _ in range(0, 10000) {
let randmat: Rot3<f64> = na::one();
let dir: Vec3<f64> = random();
let ang = na::normalize(&dir) * (abs::<f64>(random()) % Float::pi());
let rot = na::append_rotation(&randmat, &ang);
assert!(na::approx_eq(&(na::transpose(&rot) * rot), &na::one()));
}
}
#[test]
fn test_mean_dmat() {
let mat = DMat::from_row_vec(
3,
3,
[
1.0f64, 2.0, 3.0,
4.0f64, 5.0, 6.0,
7.0f64, 8.0, 9.0,
]
);
assert!(na::approx_eq(&na::mean(&mat), &DVec::from_vec(3, [4.0f64, 5.0, 6.0])));
}
#[test]
fn test_cov_dmat() {
let mat = DMat::from_row_vec(
5,
3,
[
4.0, 2.0, 0.60,
4.2, 2.1, 0.59,
3.9, 2.0, 0.58,
4.3, 2.1, 0.62,
4.1, 2.2, 0.63
]
);
let expected = DMat::from_row_vec(
3,
3,
[
0.025, 0.0075, 0.00175,
0.0075, 0.007, 0.00135,
0.00175, 0.00135, 0.00043
]
);
assert!(na::approx_eq(&na::cov(&mat), &expected));
}
#[test]
fn test_transpose_dmat() {
let mat = DMat::from_row_vec(
8,
4,
[
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
]
);
assert!(na::transpose(&na::transpose(&mat)) == mat);
}
#[test]
fn test_dmat_from_vec() {
let mat1 = DMat::from_row_vec(
8,
4,
[
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
]
);
let mat2 = DMat::from_col_vec(
8,
4,
[
1, 5, 9, 13, 17, 21, 25, 29,
2, 6, 10, 14, 18, 22, 26, 30,
3, 7, 11, 15, 19, 23, 27, 31,
4, 8, 12, 16, 20, 24, 28, 32
]
);
println!("mat1: {:?}, mat2: {:?}", mat1, mat2);
assert!(mat1 == mat2);
}
#[test]
fn test_decomp_qr() {
let mat = DMat::from_row_vec(
5,
3,
[
4.0, 2.0, 0.60,
4.2, 2.1, 0.59,
3.9, 2.0, 0.58,
4.3, 2.1, 0.62,
4.1, 2.2, 0.63
]
);
let (q, r) = decomp_qr(&mat);
let mat_ = q * r;
assert!(na::approx_eq(&mat_, &mat));
}