QR factorization for fixed size matrices.
The ColSlice implementation for fixed size matrices returns a DVec, while this is probably not optimal performance-wise, the dynamic nature of the result makes this necessary. Using a data type presenting the ImmutableVector trait would solve this, but it looks like a non-trivial change.
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@ -8,9 +8,10 @@ use traits::operations::ApproxEq;
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use std::slice::{Items, MutItems};
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use structs::vec::{Vec1, Vec2, Vec3, Vec4, Vec5, Vec6, Vec1MulRhs, Vec4MulRhs,
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Vec5MulRhs, Vec6MulRhs};
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use structs::dvec::DVec;
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use traits::structure::{Cast, Row, Col, Iterable, IterableMut, Dim, Indexable,
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Eye};
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Eye, ColSlice, RowSlice};
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use traits::operations::{Absolute, Transpose, Inv, Outer};
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use traits::geometry::{ToHomogeneous, FromHomogeneous};
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@ -119,6 +120,8 @@ transpose_impl!(Mat1, 1)
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approx_eq_impl!(Mat1)
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row_impl!(Mat1, Vec1, 1)
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col_impl!(Mat1, Vec1, 1)
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col_slice_impl!(Mat1, Vec1, 1)
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row_slice_impl!(Mat1, Vec1, 1)
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to_homogeneous_impl!(Mat1, Mat2, 1, 2)
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from_homogeneous_impl!(Mat1, Mat2, 1, 2)
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outer_impl!(Vec1, Mat1)
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@ -218,6 +221,8 @@ transpose_impl!(Mat2, 2)
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approx_eq_impl!(Mat2)
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row_impl!(Mat2, Vec2, 2)
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col_impl!(Mat2, Vec2, 2)
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col_slice_impl!(Mat2, Vec2, 2)
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row_slice_impl!(Mat2, Vec2, 2)
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to_homogeneous_impl!(Mat2, Mat3, 2, 3)
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from_homogeneous_impl!(Mat2, Mat3, 2, 3)
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outer_impl!(Vec2, Mat2)
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@ -331,6 +336,8 @@ transpose_impl!(Mat3, 3)
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approx_eq_impl!(Mat3)
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// (specialized) row_impl!(Mat3, Vec3, 3)
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// (specialized) col_impl!(Mat3, Vec3, 3)
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col_slice_impl!(Mat3, Vec3, 3)
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row_slice_impl!(Mat3, Vec3, 3)
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to_homogeneous_impl!(Mat3, Mat4, 3, 4)
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from_homogeneous_impl!(Mat3, Mat4, 3, 4)
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outer_impl!(Vec3, Mat3)
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@ -496,6 +503,8 @@ transpose_impl!(Mat4, 4)
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approx_eq_impl!(Mat4)
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row_impl!(Mat4, Vec4, 4)
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col_impl!(Mat4, Vec4, 4)
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col_slice_impl!(Mat4, Vec4, 4)
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row_slice_impl!(Mat4, Vec4, 4)
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to_homogeneous_impl!(Mat4, Mat5, 4, 5)
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from_homogeneous_impl!(Mat4, Mat5, 4, 5)
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outer_impl!(Vec4, Mat4)
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@ -677,6 +686,8 @@ transpose_impl!(Mat5, 5)
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approx_eq_impl!(Mat5)
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row_impl!(Mat5, Vec5, 5)
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col_impl!(Mat5, Vec5, 5)
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col_slice_impl!(Mat5, Vec5, 5)
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row_slice_impl!(Mat5, Vec5, 5)
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to_homogeneous_impl!(Mat5, Mat6, 5, 6)
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from_homogeneous_impl!(Mat5, Mat6, 5, 6)
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outer_impl!(Vec5, Mat5)
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@ -910,4 +921,6 @@ transpose_impl!(Mat6, 6)
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approx_eq_impl!(Mat6)
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row_impl!(Mat6, Vec6, 6)
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col_impl!(Mat6, Vec6, 6)
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col_slice_impl!(Mat6, Vec6, 6)
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row_slice_impl!(Mat6, Vec6, 6)
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outer_impl!(Vec6, Mat6)
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@ -225,6 +225,26 @@ macro_rules! indexable_impl(
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)
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)
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macro_rules! col_slice_impl(
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($t: ident, $tv: ident, $dim: expr) => (
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impl<N: Clone + Zero> ColSlice<DVec<N>> for $t<N> {
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fn col_slice(& self, cid: uint, rstart: uint, rend: uint) -> DVec<N> {
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assert!(cid < $dim);
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assert!(rstart < rend);
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assert!(rend <= $dim);
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let col = self.col(cid);
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let res = DVec::from_vec(
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rend - rstart,
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unsafe {
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cast::transmute::<&$tv<N>, & [N, ..$dim]>
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(&col).slice(rstart, rend)
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});
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res
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}
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}
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)
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)
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macro_rules! row_impl(
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($t: ident, $tv: ident, $dim: expr) => (
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impl<N: Clone + Zero> Row<$tv<N>> for $t<N> {
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@ -254,6 +274,26 @@ macro_rules! row_impl(
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)
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)
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macro_rules! row_slice_impl(
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($t: ident, $tv: ident, $dim: expr) => (
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impl<N: Clone + Zero> RowSlice<DVec<N>> for $t<N> {
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fn row_slice(& self, rid: uint, cstart: uint, cend: uint) -> DVec<N> {
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assert!(rid < $dim);
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assert!(cstart < cend);
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assert!(cend <= $dim);
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let row = self.row(rid);
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let res = DVec::from_vec(
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cend - cstart,
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unsafe {
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cast::transmute::<&$tv<N>, & [N, ..$dim]>
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(&row).slice(cstart, cend)
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});
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res
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}
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}
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)
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)
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macro_rules! col_impl(
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($t: ident, $tv: ident, $dim: expr) => (
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impl<N: Clone + Zero> Col<$tv<N>> for $t<N> {
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@ -3,6 +3,7 @@ use rand::random;
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use na::{Vec1, Vec3, Mat1, Mat2, Mat3, Mat4, Mat5, Mat6, Rot3, DMat, DVec, Indexable};
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use na;
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use na::decomp_qr;
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use std::cmp::{min, max};
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macro_rules! test_inv_mat_impl(
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($t: ty) => (
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@ -24,6 +25,19 @@ macro_rules! test_transpose_mat_impl(
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);
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)
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macro_rules! test_decomp_qr_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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let (q, r) = decomp_qr(&randmat);
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let recomp = q * r;
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assert!(na::approx_eq(&randmat, &recomp));
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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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@ -210,20 +224,45 @@ fn test_dmat_from_vec() {
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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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for _ in range(0, 10) {
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let dim1: uint = random();
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let dim2: uint = random();
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let rows = min(40, max(dim1, dim2));
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let cols = min(40, min(dim1, dim2));
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let randmat: DMat<f64> = DMat::new_random(rows, cols);
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let (q, r) = decomp_qr(&randmat);
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let recomp = q * r;
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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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assert!(na::approx_eq(&randmat, &recomp));
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}
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}
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#[test]
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fn test_decomp_qr_mat1() {
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test_decomp_qr_impl!(Mat1<f64>);
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}
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#[test]
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fn test_decomp_qr_mat2() {
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test_decomp_qr_impl!(Mat2<f64>);
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}
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#[test]
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fn test_decomp_qr_mat3() {
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test_decomp_qr_impl!(Mat3<f64>);
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}
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#[test]
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fn test_decomp_qr_mat4() {
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test_decomp_qr_impl!(Mat4<f64>);
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}
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#[test]
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fn test_decomp_qr_mat5() {
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test_decomp_qr_impl!(Mat5<f64>);
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}
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#[test]
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fn test_decomp_qr_mat6() {
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test_decomp_qr_impl!(Mat6<f64>);
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}
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