forked from M-Labs/nalgebra
2fd880a62d
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.
230 lines
4.4 KiB
Rust
230 lines
4.4 KiB
Rust
use std::num::{Float, abs};
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use rand::random;
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use na::{Vec1, Vec3, Mat1, Mat2, Mat3, Mat4, Mat5, Mat6, Rot3, DMat, DVec, Indexable};
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use na;
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use na::decomp_qr;
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macro_rules! test_inv_mat_impl(
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($t: ty) => (
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for _ in range(0, 10000) {
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let randmat : $t = random();
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assert!(na::approx_eq(&(na::inv(&randmat).unwrap() * randmat), &na::one()));
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}
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);
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)
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macro_rules! test_transpose_mat_impl(
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($t: ty) => (
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for _ in range(0, 10000) {
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let randmat : $t = random();
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assert!(na::transpose(&na::transpose(&randmat)) == randmat);
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}
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);
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)
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#[test]
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fn test_transpose_mat1() {
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test_transpose_mat_impl!(Mat1<f64>);
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}
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#[test]
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fn test_transpose_mat2() {
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test_transpose_mat_impl!(Mat2<f64>);
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}
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#[test]
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fn test_transpose_mat3() {
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test_transpose_mat_impl!(Mat3<f64>);
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}
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#[test]
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fn test_transpose_mat4() {
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test_transpose_mat_impl!(Mat4<f64>);
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}
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#[test]
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fn test_transpose_mat5() {
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test_transpose_mat_impl!(Mat5<f64>);
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}
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#[test]
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fn test_transpose_mat6() {
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test_transpose_mat_impl!(Mat6<f64>);
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}
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#[test]
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fn test_inv_mat1() {
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test_inv_mat_impl!(Mat1<f64>);
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}
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#[test]
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fn test_inv_mat2() {
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test_inv_mat_impl!(Mat2<f64>);
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}
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#[test]
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fn test_inv_mat3() {
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test_inv_mat_impl!(Mat3<f64>);
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}
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#[test]
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fn test_inv_mat4() {
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test_inv_mat_impl!(Mat4<f64>);
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}
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#[test]
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fn test_inv_mat5() {
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test_inv_mat_impl!(Mat5<f64>);
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}
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#[test]
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fn test_inv_mat6() {
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test_inv_mat_impl!(Mat6<f64>);
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}
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#[test]
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fn test_rotation2() {
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for _ in range(0, 10000) {
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let randmat: na::Rot2<f64> = na::one();
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let ang = Vec1::new(abs::<f64>(random()) % Float::pi());
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assert!(na::approx_eq(&na::rotation(&na::append_rotation(&randmat, &ang)), &ang));
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}
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}
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#[test]
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fn test_index_mat2() {
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let mat: Mat2<f64> = random();
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assert!(mat.at((0, 1)) == na::transpose(&mat).at((1, 0)));
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}
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#[test]
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fn test_inv_rotation3() {
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for _ in range(0, 10000) {
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let randmat: Rot3<f64> = na::one();
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let dir: Vec3<f64> = random();
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let ang = na::normalize(&dir) * (abs::<f64>(random()) % Float::pi());
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let rot = na::append_rotation(&randmat, &ang);
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assert!(na::approx_eq(&(na::transpose(&rot) * rot), &na::one()));
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}
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}
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#[test]
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fn test_mean_dmat() {
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let mat = DMat::from_row_vec(
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3,
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3,
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[
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1.0f64, 2.0, 3.0,
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4.0f64, 5.0, 6.0,
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7.0f64, 8.0, 9.0,
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]
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);
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assert!(na::approx_eq(&na::mean(&mat), &DVec::from_vec(3, [4.0f64, 5.0, 6.0])));
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}
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#[test]
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fn test_cov_dmat() {
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let mat = DMat::from_row_vec(
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5,
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3,
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[
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4.0, 2.0, 0.60,
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4.2, 2.1, 0.59,
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3.9, 2.0, 0.58,
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4.3, 2.1, 0.62,
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4.1, 2.2, 0.63
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]
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);
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let expected = DMat::from_row_vec(
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3,
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3,
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[
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0.025, 0.0075, 0.00175,
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0.0075, 0.007, 0.00135,
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0.00175, 0.00135, 0.00043
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]
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);
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assert!(na::approx_eq(&na::cov(&mat), &expected));
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}
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#[test]
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fn test_transpose_dmat() {
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let mat = DMat::from_row_vec(
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8,
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4,
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[
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1, 2, 3, 4,
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5, 6, 7, 8,
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9, 10, 11, 12,
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13, 14, 15, 16,
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17, 18, 19, 20,
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21, 22, 23, 24,
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25, 26, 27, 28,
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29, 30, 31, 32
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]
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);
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assert!(na::transpose(&na::transpose(&mat)) == mat);
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}
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#[test]
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fn test_dmat_from_vec() {
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let mat1 = DMat::from_row_vec(
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8,
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4,
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[
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1, 2, 3, 4,
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5, 6, 7, 8,
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9, 10, 11, 12,
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13, 14, 15, 16,
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17, 18, 19, 20,
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21, 22, 23, 24,
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25, 26, 27, 28,
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29, 30, 31, 32
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]
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);
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let mat2 = DMat::from_col_vec(
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8,
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4,
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[
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1, 5, 9, 13, 17, 21, 25, 29,
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2, 6, 10, 14, 18, 22, 26, 30,
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3, 7, 11, 15, 19, 23, 27, 31,
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4, 8, 12, 16, 20, 24, 28, 32
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]
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);
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println!("mat1: {:?}, mat2: {:?}", mat1, mat2);
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assert!(mat1 == mat2);
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}
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#[test]
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fn test_decomp_qr() {
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let mat = DMat::from_row_vec(
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5,
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3,
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[
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4.0, 2.0, 0.60,
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4.2, 2.1, 0.59,
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3.9, 2.0, 0.58,
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4.3, 2.1, 0.62,
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4.1, 2.2, 0.63
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]
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);
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let (q, r) = decomp_qr(&mat);
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let mat_ = q * r;
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assert!(na::approx_eq(&mat_, &mat));
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}
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