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@ -2,10 +2,59 @@ use generic_parameterize::parameterize;
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use num_traits::real::Real;
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use num_traits::Zero;
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use std::fmt::Debug;
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use std::iter::{Product, Sum};
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use std::iter::{zip, Product, Sum};
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use std::ops;
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use vector_victor::{LUSolve, Matrix, Vector};
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macro_rules! scalar_eq {
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($left:expr, $right:expr $(,)?) => {
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match (&$left, &$right) {
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(_left_val, _right_val) => {
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scalar_eq!($left, $right, "Difference is less than epsilon")
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}
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}
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};
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($left:expr, $right:expr, $($arg:tt)+) => {
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match (&$left, &$right) {
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(left_val, right_val) => {
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let epsilon = f32::epsilon() as f64;
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let lf : f64 = (*left_val).into();
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let rf : f64 = (*right_val).into();
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let diff : f64 = (lf - rf).abs();
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if diff >= epsilon {
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assert_eq!(left_val, right_val, $($arg)+) // done this way to get nice errors
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}
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}
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}
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};
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}
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macro_rules! matrix_eq {
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($left:expr, $right:expr $(,)?) => {
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match (&$left, &$right) {
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(_left_val, _right_val) => {
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matrix_eq!($left, $right, "Difference is less than epsilon")
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}
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}
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};
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($left:expr, $right:expr, $($arg:tt)+) => {
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match (&$left, &$right) {
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(left_val, right_val) => {
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let epsilon = f32::epsilon() as f64;
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for (l, r) in zip(left_val.elements(), right_val.elements()) {
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let lf : f64 = (*l).into();
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let rf : f64 = (*r).into();
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let diff : f64 = (lf - rf).abs();
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if diff >= epsilon {
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assert_eq!($left, $right, $($arg)+) // done this way to get nice errors
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}
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}
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}
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}
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};
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}
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#[parameterize(S = (i32, f32, u32), M = [1,4], N = [1,4])]
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#[test]
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fn test_add<S: Copy + From<u16> + PartialEq + Debug, const M: usize, const N: usize>()
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@ -22,7 +71,7 @@ where
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#[parameterize(S = (f32, f64), M = [1,2,3,4])]
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#[test]
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fn test_lu_identity<S: Default + Real + Debug + Product + Sum, const M: usize>() {
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fn test_lu_identity<S: Default + Real + Debug + Product + Sum + Into<f64>, const M: usize>() {
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// let a: Matrix<f32, 3, 3> = Matrix::<f32, 3, 3>::identity();
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let i = Matrix::<S, M, M>::identity();
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let ones = Vector::<S, M>::fill(S::one());
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@ -33,8 +82,8 @@ fn test_lu_identity<S: Default + Real + Debug + Product + Sum, const M: usize>()
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(0..M).eq(idx.elements().cloned()),
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"Incorrect permutation matrix",
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);
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assert_eq!(d, S::one(), "Incorrect permutation parity");
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assert_eq!(i.det(), S::one());
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scalar_eq!(d, S::one(), "Incorrect permutation parity");
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scalar_eq!(i.det(), S::one());
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assert_eq!(i.inverse(), Some(i));
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assert_eq!(i.solve(&ones), Some(ones));
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assert_eq!(decomp.separate(), (i, i));
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@ -58,22 +107,42 @@ fn test_lu_singular<S: Default + Real + Debug + Product + Sum, const M: usize>()
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fn test_lu_2x2() {
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let a = Matrix::new([[1.0, 2.0], [3.0, 0.0]]);
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let decomp = a.lu().expect("Singular matrix encountered");
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let (lu, idx, d) = decomp;
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let (_lu, idx, _d) = decomp;
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// the decomposition is non-unique, due to the combination of lu and idx.
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// Instead of checking the exact value, we only check the results.
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// Also check if they produce the same results with both methods, since the
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// Matrix<> methods use shortcuts the decomposition methods don't
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let (l, u) = decomp.separate();
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assert_eq!(l.mmul(&u), a.permute_rows(&idx));
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matrix_eq!(l.mmul(&u), a.permute_rows(&idx));
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scalar_eq!(a.det(), -6.0);
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scalar_eq!(a.det(), decomp.det());
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matrix_eq!(
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a.inverse().unwrap(),
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Matrix::new([[0.0, 2.0], [3.0, -1.0]]) * (1.0 / 6.0)
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);
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matrix_eq!(a.inverse().unwrap(), decomp.inverse());
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matrix_eq!(a.inverse().unwrap().inverse().unwrap(), a)
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}
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#[test]
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fn test_lu_3x3() {
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let a = Matrix::new([[1.0, -5.0, 8.0], [1.0, -2.0, 1.0], [2.0, -1.0, -4.0]]);
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let decomp = a.lu().expect("Singular matrix encountered");
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let (_lu, idx, _d) = decomp;
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let (l, u) = decomp.separate();
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matrix_eq!(l.mmul(&u), a.permute_rows(&idx));
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assert_eq!(a.det(), -6.0);
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assert_eq!(a.det(), decomp.det());
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scalar_eq!(a.det(), 3.0);
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scalar_eq!(a.det(), decomp.det());
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assert_eq!(
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a.inverse(),
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Some(Matrix::new([[0.0, 2.0], [3.0, -1.0]]) * (1.0 / 6.0))
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matrix_eq!(
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a.inverse().unwrap(),
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Matrix::new([[9.0, -28.0, 11.0], [6.0, -20.0, 7.0], [3.0, -9.0, 3.0]]) * (1.0 / 3.0)
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);
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assert_eq!(a.inverse(), Some(decomp.inverse()));
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assert_eq!(a.inverse().unwrap().inverse().unwrap(), a)
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matrix_eq!(a.inverse().unwrap(), decomp.inverse());
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matrix_eq!(a.inverse().unwrap().inverse().unwrap(), a)
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}
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