Fix mint tests.
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@ -6,7 +6,7 @@ if [ -z "$NO_STD" ]; then
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if [ -z "$LAPACK" ]; then
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cargo test --verbose;
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cargo test --verbose "arbitrary";
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cargo test --verbose "debug arbitrary mint serde-serialize abomonation-serialize";
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cargo test --verbose --all-features;
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cd nalgebra-glm; cargo test --verbose;
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else
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cd nalgebra-lapack; cargo test --verbose;
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@ -331,9 +331,9 @@ macro_rules! impl_from_into_mint_2D(
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#[cfg(feature = "mint")]
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impl_from_into_mint_2D!(
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(U2, U2) => ColumnMatrix2{x, y}[2];
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(U2, U3) => ColumnMatrix2x3{x, y}[2];
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(U2, U3) => ColumnMatrix2x3{x, y, z}[2];
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(U3, U3) => ColumnMatrix3{x, y, z}[3];
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(U3, U4) => ColumnMatrix3x4{x, y, z}[3];
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(U3, U4) => ColumnMatrix3x4{x, y, z, w}[3];
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(U4, U4) => ColumnMatrix4{x, y, z, w}[4];
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);
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@ -3,6 +3,7 @@
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use na::{DMatrix, Matrix2, Matrix3x5, Matrix4, Matrix5x3};
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use core::helper::{RandScalar, RandComplex};
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quickcheck! {
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fn bidiagonal(m: DMatrix<RandComplex<f64>>) -> bool {
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let m = m.map(|e| e.0);
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@ -63,3 +64,26 @@ quickcheck! {
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relative_eq!(m, &u * d * &v_t, epsilon = 1.0e-7)
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}
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}
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#[test]
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fn bidiagonal_identity() {
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let m = DMatrix::<f64>::identity(10, 10);
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let bidiagonal = m.clone().bidiagonalize();
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let (u, d, v_t) = bidiagonal.unpack();
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println!("u, s, v_t: {}{}{}", u, d, v_t);
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println!("recomp: {}", &u * &d * &v_t);
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assert_eq!(m, &u * d * &v_t);
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let m = DMatrix::<f64>::identity(10, 15);
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let bidiagonal = m.clone().bidiagonalize();
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let (u, d, v_t) = bidiagonal.unpack();
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println!("u, s, v_t: {}{}{}", u, d, v_t);
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assert_eq!(m, &u * d * &v_t);
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let m = DMatrix::<f64>::identity(15, 10);
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let bidiagonal = m.clone().bidiagonalize();
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let (u, d, v_t) = bidiagonal.unpack();
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println!("u, s, v_t: {}{}{}", u, d, v_t);
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assert_eq!(m, &u * d * &v_t);
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}
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@ -105,11 +105,11 @@ fn symmetric_eigen_singular_24x24() {
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let eig = m.clone().symmetric_eigen();
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let recomp = eig.recompose();
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assert!(relative_eq!(
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assert_relative_eq!(
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m.lower_triangle(),
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recomp.lower_triangle(),
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epsilon = 1.0e-5
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));
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);
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}
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// #[cfg(feature = "arbitrary")]
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@ -199,7 +199,7 @@ fn svd_singular() {
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assert!(s.iter().all(|e| *e >= 0.0));
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assert!(u.is_orthogonal(1.0e-5));
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assert!(v_t.is_orthogonal(1.0e-5));
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assert!(relative_eq!(m, &u * ds * &v_t, epsilon = 1.0e-5));
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assert_relative_eq!(m, &u * ds * &v_t, epsilon = 1.0e-5);
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}
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// Same as the previous test but with one additional row.
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@ -238,7 +238,7 @@ fn svd_singular_vertical() {
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let ds = DMatrix::from_diagonal(&s);
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assert!(s.iter().all(|e| *e >= 0.0));
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assert!(relative_eq!(m, &u * ds * &v_t, epsilon = 1.0e-5));
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assert_relative_eq!(m, &u * ds * &v_t, epsilon = 1.0e-5);
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}
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// Same as the previous test but with one additional column.
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@ -275,7 +275,7 @@ fn svd_singular_horizontal() {
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let ds = DMatrix::from_diagonal(&s);
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assert!(s.iter().all(|e| *e >= 0.0));
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assert!(relative_eq!(m, &u * ds * &v_t, epsilon = 1.0e-5));
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assert_relative_eq!(m, &u * ds * &v_t, epsilon = 1.0e-5);
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}
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#[test]
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@ -314,7 +314,7 @@ fn svd_with_delimited_subproblem() {
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m[(8,8)] = 16.0; m[(3,9)] = 17.0;
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m[(9,9)] = 18.0;
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let svd = m.clone().svd(true, true);
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assert!(relative_eq!(m, svd.recompose().unwrap(), epsilon = 1.0e-7));
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assert_relative_eq!(m, svd.recompose().unwrap(), epsilon = 1.0e-7);
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// Rectangular versions.
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let mut m = DMatrix::<f64>::from_element(15, 10, 0.0);
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@ -329,10 +329,10 @@ fn svd_with_delimited_subproblem() {
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m[(8,8)] = 16.0; m[(3,9)] = 17.0;
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m[(9,9)] = 18.0;
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let svd = m.clone().svd(true, true);
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assert!(relative_eq!(m, svd.recompose().unwrap(), epsilon = 1.0e-7));
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assert_relative_eq!(m, svd.recompose().unwrap(), epsilon = 1.0e-7);
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let svd = m.transpose().svd(true, true);
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assert!(relative_eq!(m.transpose(), svd.recompose().unwrap(), epsilon = 1.0e-7));
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assert_relative_eq!(m.transpose(), svd.recompose().unwrap(), epsilon = 1.0e-7);
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}
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#[test]
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@ -350,7 +350,7 @@ fn svd_fail() {
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println!("v: {:.5}", svd.v_t.unwrap());
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let recomp = svd.recompose().unwrap();
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println!("{:.5}{:.5}", m, recomp);
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assert!(relative_eq!(m, recomp, epsilon = 1.0e-5));
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assert_relative_eq!(m, recomp, epsilon = 1.0e-5);
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}
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#[test]
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