Fix Vector::axpy for noncommutative cases
One example would be performing simple matrix multiplication over a division algebra such as quaternions.
This commit is contained in:
Jakub Konka
parent
bde8fbe10f
commit
d0fa79f6e1
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@ -473,7 +473,7 @@ where N: Scalar + Zero + ClosedAdd + ClosedMul {
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for i in 0..len {
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unsafe {
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let y = y.get_unchecked_mut(i * stride1);
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*y = a * *x.get_unchecked(i * stride2) + beta * *y;
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*y = *x.get_unchecked(i * stride2) * a + *y * beta;
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}
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}
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}
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@ -482,7 +482,7 @@ fn array_ax<N>(y: &mut [N], a: N, x: &[N], stride1: usize, stride2: usize, len:
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where N: Scalar + Zero + ClosedAdd + ClosedMul {
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for i in 0..len {
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unsafe {
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*y.get_unchecked_mut(i * stride1) = a * *x.get_unchecked(i * stride2);
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*y.get_unchecked_mut(i * stride1) = *x.get_unchecked(i * stride2) * a;
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}
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}
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}
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@ -579,13 +579,13 @@ where
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// FIXME: avoid bound checks.
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let col2 = a.column(0);
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let val = unsafe { *x.vget_unchecked(0) };
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self.axpy(alpha * val, &col2, beta);
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self.axpy(val * alpha, &col2, beta);
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for j in 1..ncols2 {
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let col2 = a.column(j);
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let val = unsafe { *x.vget_unchecked(j) };
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self.axpy(alpha * val, &col2, N::one());
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self.axpy(val * alpha, &col2, N::one());
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}
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}
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@ -624,7 +624,7 @@ where
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// FIXME: avoid bound checks.
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let col2 = a.column(0);
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let val = unsafe { *x.vget_unchecked(0) };
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self.axpy(alpha * val, &col2, beta);
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self.axpy(val * alpha, &col2, beta);
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self[0] += alpha * dot(&a.slice_range(1.., 0), &x.rows_range(1..));
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for j in 1..dim2 {
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@ -637,7 +637,7 @@ where
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*self.vget_unchecked_mut(j) += alpha * dot;
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}
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self.rows_range_mut(j + 1..)
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.axpy(alpha * val, &col2.rows_range(j + 1..), N::one());
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.axpy(val * alpha, &col2.rows_range(j + 1..), N::one());
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}
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}
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@ -890,7 +890,7 @@ where N: Scalar + Zero + ClosedAdd + ClosedMul
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for j in 0..ncols1 {
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// FIXME: avoid bound checks.
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let val = unsafe { conjugate(*y.vget_unchecked(j)) };
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self.column_mut(j).axpy(alpha * val, x, beta);
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self.column_mut(j).axpy(val * alpha, x, beta);
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}
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}
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@ -1256,7 +1256,7 @@ where N: Scalar + Zero + ClosedAdd + ClosedMul
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let subdim = Dynamic::new(dim1 - j);
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// FIXME: avoid bound checks.
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self.generic_slice_mut((j, j), (subdim, U1)).axpy(
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alpha * val,
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val * alpha,
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&x.rows_range(j..),
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beta,
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);
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@ -1,105 +1,129 @@
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#![cfg(feature = "arbitrary")]
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use na::{geometry::Quaternion, Matrix2, Vector3};
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use num_traits::{One, Zero};
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use na::{DMatrix, DVector};
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use std::cmp;
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#[test]
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fn gemm_noncommutative() {
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type Qf64 = Quaternion<f64>;
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let i = Qf64::from_imag(Vector3::new(1.0, 0.0, 0.0));
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let j = Qf64::from_imag(Vector3::new(0.0, 1.0, 0.0));
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let k = Qf64::from_imag(Vector3::new(0.0, 0.0, 1.0));
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quickcheck! {
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/*
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*
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* Symmetric operators.
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*
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*/
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fn gemv_symm(n: usize, alpha: f64, beta: f64) -> bool {
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let n = cmp::max(1, cmp::min(n, 50));
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let a = DMatrix::<f64>::new_random(n, n);
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let a = &a * a.transpose();
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let m1 = Matrix2::new(k, Qf64::zero(), j, i);
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// this is the inverse of m1
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let m2 = Matrix2::new(-k, Qf64::zero(), Qf64::one(), -i);
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let x = DVector::new_random(n);
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let mut y1 = DVector::new_random(n);
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let mut y2 = y1.clone();
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let mut res: Matrix2<Qf64> = Matrix2::zero();
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res.gemm(Qf64::one(), &m1, &m2, Qf64::zero());
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assert_eq!(res, Matrix2::identity());
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y1.gemv(alpha, &a, &x, beta);
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y2.sygemv(alpha, &a.lower_triangle(), &x, beta);
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let mut res: Matrix2<Qf64> = Matrix2::identity();
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res.gemm(k, &m1, &m2, -k);
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assert_eq!(res, Matrix2::zero());
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}
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if !relative_eq!(y1, y2, epsilon = 1.0e-10) {
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return false;
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#[cfg(feature = "arbitrary")]
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mod blas_quickcheck {
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use na::{DMatrix, DVector};
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use std::cmp;
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quickcheck! {
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/*
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*
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* Symmetric operators.
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*
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*/
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fn gemv_symm(n: usize, alpha: f64, beta: f64) -> bool {
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let n = cmp::max(1, cmp::min(n, 50));
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let a = DMatrix::<f64>::new_random(n, n);
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let a = &a * a.transpose();
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let x = DVector::new_random(n);
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let mut y1 = DVector::new_random(n);
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let mut y2 = y1.clone();
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y1.gemv(alpha, &a, &x, beta);
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y2.sygemv(alpha, &a.lower_triangle(), &x, beta);
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if !relative_eq!(y1, y2, epsilon = 1.0e-10) {
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return false;
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}
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y1.gemv(alpha, &a, &x, 0.0);
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y2.sygemv(alpha, &a.lower_triangle(), &x, 0.0);
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relative_eq!(y1, y2, epsilon = 1.0e-10)
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}
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y1.gemv(alpha, &a, &x, 0.0);
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y2.sygemv(alpha, &a.lower_triangle(), &x, 0.0);
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fn gemv_tr(n: usize, alpha: f64, beta: f64) -> bool {
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let n = cmp::max(1, cmp::min(n, 50));
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let a = DMatrix::<f64>::new_random(n, n);
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let x = DVector::new_random(n);
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let mut y1 = DVector::new_random(n);
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let mut y2 = y1.clone();
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relative_eq!(y1, y2, epsilon = 1.0e-10)
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}
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y1.gemv(alpha, &a, &x, beta);
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y2.gemv_tr(alpha, &a.transpose(), &x, beta);
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fn gemv_tr(n: usize, alpha: f64, beta: f64) -> bool {
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let n = cmp::max(1, cmp::min(n, 50));
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let a = DMatrix::<f64>::new_random(n, n);
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let x = DVector::new_random(n);
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let mut y1 = DVector::new_random(n);
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let mut y2 = y1.clone();
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if !relative_eq!(y1, y2, epsilon = 1.0e-10) {
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return false;
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}
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y1.gemv(alpha, &a, &x, beta);
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y2.gemv_tr(alpha, &a.transpose(), &x, beta);
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y1.gemv(alpha, &a, &x, 0.0);
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y2.gemv_tr(alpha, &a.transpose(), &x, 0.0);
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if !relative_eq!(y1, y2, epsilon = 1.0e-10) {
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return false;
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relative_eq!(y1, y2, epsilon = 1.0e-10)
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}
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y1.gemv(alpha, &a, &x, 0.0);
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y2.gemv_tr(alpha, &a.transpose(), &x, 0.0);
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fn ger_symm(n: usize, alpha: f64, beta: f64) -> bool {
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let n = cmp::max(1, cmp::min(n, 50));
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let a = DMatrix::<f64>::new_random(n, n);
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let mut a1 = &a * a.transpose();
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let mut a2 = a1.lower_triangle();
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relative_eq!(y1, y2, epsilon = 1.0e-10)
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}
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let x = DVector::new_random(n);
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let y = DVector::new_random(n);
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fn ger_symm(n: usize, alpha: f64, beta: f64) -> bool {
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let n = cmp::max(1, cmp::min(n, 50));
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let a = DMatrix::<f64>::new_random(n, n);
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let mut a1 = &a * a.transpose();
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let mut a2 = a1.lower_triangle();
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a1.ger(alpha, &x, &y, beta);
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a2.syger(alpha, &x, &y, beta);
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let x = DVector::new_random(n);
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let y = DVector::new_random(n);
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if !relative_eq!(a1.lower_triangle(), a2) {
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return false;
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}
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a1.ger(alpha, &x, &y, beta);
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a2.syger(alpha, &x, &y, beta);
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a1.ger(alpha, &x, &y, 0.0);
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a2.syger(alpha, &x, &y, 0.0);
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if !relative_eq!(a1.lower_triangle(), a2) {
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return false;
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relative_eq!(a1.lower_triangle(), a2)
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}
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a1.ger(alpha, &x, &y, 0.0);
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a2.syger(alpha, &x, &y, 0.0);
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fn quadform(n: usize, alpha: f64, beta: f64) -> bool {
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let n = cmp::max(1, cmp::min(n, 50));
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let rhs = DMatrix::<f64>::new_random(6, n);
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let mid = DMatrix::<f64>::new_random(6, 6);
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let mut res = DMatrix::new_random(n, n);
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relative_eq!(a1.lower_triangle(), a2)
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}
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let expected = &res * beta + rhs.transpose() * &mid * &rhs * alpha;
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fn quadform(n: usize, alpha: f64, beta: f64) -> bool {
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let n = cmp::max(1, cmp::min(n, 50));
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let rhs = DMatrix::<f64>::new_random(6, n);
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let mid = DMatrix::<f64>::new_random(6, 6);
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let mut res = DMatrix::new_random(n, n);
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res.quadform(alpha, &mid, &rhs, beta);
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let expected = &res * beta + rhs.transpose() * &mid * &rhs * alpha;
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println!("{}{}", res, expected);
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res.quadform(alpha, &mid, &rhs, beta);
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relative_eq!(res, expected, epsilon = 1.0e-7)
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}
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println!("{}{}", res, expected);
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fn quadform_tr(n: usize, alpha: f64, beta: f64) -> bool {
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let n = cmp::max(1, cmp::min(n, 50));
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let lhs = DMatrix::<f64>::new_random(6, n);
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let mid = DMatrix::<f64>::new_random(n, n);
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let mut res = DMatrix::new_random(6, 6);
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relative_eq!(res, expected, epsilon = 1.0e-7)
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}
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let expected = &res * beta + &lhs * &mid * lhs.transpose() * alpha;
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fn quadform_tr(n: usize, alpha: f64, beta: f64) -> bool {
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let n = cmp::max(1, cmp::min(n, 50));
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let lhs = DMatrix::<f64>::new_random(6, n);
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let mid = DMatrix::<f64>::new_random(n, n);
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let mut res = DMatrix::new_random(6, 6);
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res.quadform_tr(alpha, &lhs, &mid , beta);
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let expected = &res * beta + &lhs * &mid * lhs.transpose() * alpha;
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println!("{}{}", res, expected);
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res.quadform_tr(alpha, &lhs, &mid , beta);
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println!("{}{}", res, expected);
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relative_eq!(res, expected, epsilon = 1.0e-7)
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relative_eq!(res, expected, epsilon = 1.0e-7)
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}
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}
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}
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