393 lines
11 KiB
Rust
393 lines
11 KiB
Rust
#![no_std]
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#![feature(const_fn_floating_point_arithmetic)]
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use float::Float;
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use num_traits::identities::Zero;
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/// A row-major matrix
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#[derive(Debug, Clone, PartialEq, Eq, Hash)]
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#[repr(transparent)]
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pub struct Matrix<T, const M: usize, const N: usize> {
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pub data: [[T; N]; M],
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}
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pub type RowVector<T, const N: usize> = Matrix<T, 1, N>;
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pub type ColVector<T, const N: usize> = Matrix<T, N, 1>;
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impl<T: Copy + Default, const M: usize, const N: usize> Default for Matrix<T, M, N> {
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fn default() -> Self {
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Self {
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data: [[T::default(); N]; M],
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}
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}
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}
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impl<T: Copy + Zero + PartialEq, const M: usize, const N: usize> Zero for Matrix<T, M, N> {
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fn zero() -> Self {
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Self {
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data: [[T::zero(); N]; M],
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}
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}
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fn is_zero(&self) -> bool {
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self.iter().all(|x| x.is_zero())
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}
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}
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impl<T, const M: usize, const N: usize> core::ops::Index<(usize, usize)> for Matrix<T, M, N> {
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type Output = T;
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#[inline(always)]
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fn index(&self, (i, j): (usize, usize)) -> &Self::Output {
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&self.data[i][j]
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}
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}
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impl<T, const M: usize, const N: usize> core::ops::IndexMut<(usize, usize)> for Matrix<T, M, N> {
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#[inline(always)]
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fn index_mut(&mut self, (i, j): (usize, usize)) -> &mut Self::Output {
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&mut self.data[i][j]
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}
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}
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impl<T, const M: usize, const N: usize> core::ops::Index<usize> for Matrix<T, M, N> {
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type Output = [T; N];
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#[inline(always)]
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fn index(&self, i: usize) -> &Self::Output {
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&self.data[i]
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}
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}
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impl<T, const M: usize, const N: usize> core::ops::IndexMut<usize> for Matrix<T, M, N> {
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#[inline(always)]
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fn index_mut(&mut self, i: usize) -> &mut Self::Output {
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&mut self.data[i]
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}
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}
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impl<T, const M: usize, const N: usize> Matrix<T, M, N> {
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pub const fn new(data: [[T; N]; M]) -> Self {
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Self { data }
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}
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#[inline(always)]
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pub const fn nrows(&self) -> usize {
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M
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}
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#[inline(always)]
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pub const fn ncols(&self) -> usize {
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N
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}
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#[inline(always)]
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pub fn iter(&self) -> impl Iterator<Item = &T> {
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self.data.iter().flatten()
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}
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#[inline(always)]
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pub fn iter_mut(&mut self) -> impl Iterator<Item = &mut T> {
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self.data.iter_mut().flatten()
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}
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#[inline(always)]
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pub fn iter_rows(
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&self,
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) -> impl ExactSizeIterator<Item = &[T; N]> + DoubleEndedIterator<Item = &[T; N]> {
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self.data.iter()
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}
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#[inline(always)]
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pub const fn row(&self, idx: usize) -> &[T; N] {
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&self.data[idx]
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}
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}
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impl<T, const N: usize> ColVector<T, N> {
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#[inline(always)]
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pub fn map_to_col(slice: &[T; N]) -> &ColVector<T, N> {
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unsafe { &*(slice.as_ptr().cast()) }
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}
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#[inline(always)]
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pub fn map_to_col_mut(slice: &mut [T; N]) -> &mut ColVector<T, N> {
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unsafe { &mut *(slice.as_mut_ptr().cast()) }
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}
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}
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impl<T, const N: usize> RowVector<T, N> {
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pub fn map_to_row(slice: &[T; N]) -> &Self {
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unsafe { &*(slice.as_ptr().cast()) }
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}
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pub fn map_to_row_mut(slice: &mut [T; N]) -> &mut Self {
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unsafe { &mut *(slice.as_mut_ptr().cast()) }
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}
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}
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impl<const M: usize, const P: usize> Matrix<Float, M, P> {
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/// A specialised matmul for Float, using fma
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pub fn matmul_float_into<const N: usize>(
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&mut self,
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lhs: &Matrix<Float, M, N>,
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rhs: &Matrix<Float, N, P>,
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) {
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for i in 0..M {
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for j in 0..P {
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// Slightly cheaper to do first computation separately
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// rather than store zero and issue all ops as fma
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let mut t = if N == 0 {
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0.0
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} else {
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lhs[(i, 0)] * rhs[(0, j)]
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};
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for k in 1..N {
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t = Float::mul_add(lhs[(i, k)], rhs[(k, j)], t);
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}
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self[(i, j)] = t;
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}
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}
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}
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}
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impl<T, const M: usize, const P: usize> Matrix<T, M, P> {
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pub fn matmul_into<const N: usize>(&mut self, lhs: &Matrix<T, M, N>, rhs: &Matrix<T, N, P>)
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where
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T: Default + Copy + core::ops::Mul<Output = T> + core::ops::Add<Output = T>,
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T: 'static,
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{
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for i in 0..M {
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for j in 0..P {
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let mut t = T::default();
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for k in 0..N {
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t = t + lhs[(i, k)] * rhs[(k, j)];
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}
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self[(i, j)] = t;
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}
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}
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}
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}
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macro_rules! impl_op_mul_mul {
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($lhs:ty, $rhs:ty) => {
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impl<T, const N: usize, const M: usize, const P: usize> core::ops::Mul<$rhs> for $lhs
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where
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T: Copy + Default + core::ops::Add<Output = T> + core::ops::Mul<Output = T>,
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T: 'static,
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{
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type Output = Matrix<T, M, P>;
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fn mul(self, lhs: $rhs) -> Self::Output {
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let mut out = Matrix::default();
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out.matmul_into(&self, &lhs);
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out
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}
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}
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};
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}
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impl_op_mul_mul! { Matrix<T, M, N>, Matrix<T, N, P> }
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impl_op_mul_mul! { &Matrix<T, M, N>, Matrix<T, N, P> }
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impl_op_mul_mul! { Matrix<T, M, N>, &Matrix<T, N, P> }
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impl_op_mul_mul! { &Matrix<T, M, N>, &Matrix<T, N, P> }
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impl<T, const M: usize, const N: usize> core::ops::MulAssign<T> for Matrix<T, M, N>
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where
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T: Copy + core::ops::MulAssign<T>,
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{
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#[inline(always)]
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fn mul_assign(&mut self, other: T) {
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self.iter_mut().for_each(|x| *x *= other)
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}
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}
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impl<T, const N: usize, const M: usize> core::ops::Add<Matrix<T, M, N>> for Matrix<T, M, N>
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where
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T: Copy + Zero + core::ops::Add<Output = T> + PartialEq,
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{
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type Output = Self;
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fn add(self, lhs: Self) -> Self::Output {
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let mut out = Matrix::zero();
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for i in 0..M {
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for j in 0..N {
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out[(i, j)] = self[(i, j)] + lhs[(i, j)];
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}
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}
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out
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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#[test]
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fn construct_copy_type() {
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let _m0 = Matrix::<i32, 4, 3>::default();
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let _m1: Matrix<u8, 8, 8> = Matrix::default();
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let _m2 = Matrix::new([[1, 2], [3, 4]]);
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}
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#[test]
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fn matmul() {
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let m1 = Matrix::new([[1_u8, 2, 3], [4, 5, 6]]);
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let m2 = Matrix::new([[7_u8, 8, 9, 10], [11, 12, 13, 14], [15, 16, 17, 18]]);
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let m3 = m1 * m2;
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assert_eq!(m3, Matrix::new([[74, 80, 86, 92], [173, 188, 203, 218]]));
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}
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#[test]
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fn iter() {
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let m = Matrix::new([[1_u8, 2, 3], [4, 5, 6]]);
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let mut iter = m.iter();
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assert_eq!(iter.next(), Some(&1));
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assert_eq!(iter.next(), Some(&2));
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assert_eq!(iter.next(), Some(&3));
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assert_eq!(iter.next(), Some(&4));
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assert_eq!(iter.next(), Some(&5));
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assert_eq!(iter.next(), Some(&6));
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assert_eq!(iter.next(), None);
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}
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}
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#[cfg(feature = "approx")]
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mod approx {
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use super::Matrix;
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use ::approx::{AbsDiffEq, RelativeEq, UlpsEq};
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impl<T, const M: usize, const N: usize> AbsDiffEq for Matrix<T, M, N>
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where
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T: AbsDiffEq,
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{
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type Epsilon = T::Epsilon;
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fn default_epsilon() -> Self::Epsilon {
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T::default_epsilon()
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}
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fn abs_diff_eq(&self, other: &Self, epsilon: Self::Epsilon) -> bool {
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self.iter()
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.zip(other.iter())
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.all(|(r, l)| r.abs_diff_eq(l, T::default_epsilon()))
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}
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}
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impl<T, const M: usize, const N: usize> RelativeEq for Matrix<T, M, N>
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where
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T: RelativeEq,
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Self::Epsilon: Copy,
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{
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fn default_max_relative() -> Self::Epsilon {
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T::default_max_relative()
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}
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fn relative_eq(
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&self,
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other: &Self,
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epsilon: Self::Epsilon,
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max_relative: Self::Epsilon,
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) -> bool {
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self.iter()
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.zip(other.iter())
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.all(|(r, l)| r.relative_eq(l, epsilon, max_relative))
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}
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}
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impl<T, const M: usize, const N: usize> UlpsEq for Matrix<T, M, N>
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where
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T: UlpsEq,
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Self::Epsilon: Copy,
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{
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fn default_max_ulps() -> u32 {
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T::default_max_ulps()
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}
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fn ulps_eq(&self, other: &Self, epsilon: Self::Epsilon, max_ulps: u32) -> bool {
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self.iter()
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.zip(other.iter())
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.all(|(r, l)| r.ulps_eq(l, epsilon, max_ulps))
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}
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}
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}
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impl<const M: usize, const N: usize> Matrix<Float, M, N> {
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pub const fn flip_ud(&self) -> Self {
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let mut m = Self::new([[0.0; N]; M]);
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let mut i = 0;
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while i < M {
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m.data[M - 1 - i] = self.data[i];
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i += 1;
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}
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m
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}
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pub const fn flip_lr(&self) -> Self {
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let mut m = Self::new([[0.0; N]; M]);
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let mut i = 0;
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while i < M {
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let mut j = 0;
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while j < N {
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m.data[i][N - 1 - j] = self.data[i][j];
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j += 1;
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}
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i += 1;
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}
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m
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}
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/// Flip all sign bits
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pub const fn flip_sign(&self) -> Self {
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let mut m = Self::new([[0.0; N]; M]);
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let mut i = 0;
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while i < M {
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let mut j = 0;
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while j < N {
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m.data[i][j] = -self.data[i][j];
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j += 1;
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}
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i += 1;
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}
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m
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}
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/// Zero extends if larger than self
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pub const fn resize<const M2: usize, const N2: usize>(&self) -> Matrix<Float, M2, N2> {
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let mut m = Matrix::new([[0.0; N2]; M2]);
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let m_min = if M < M2 { M } else { M2 };
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let n_min = if N < N2 { N } else { N2 };
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let mut i = 0;
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while i < m_min {
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let mut j = 0;
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while j < n_min {
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m.data[i][j] = self.data[i][j];
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j += 1;
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}
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i += 1;
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}
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m
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}
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}
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#[cfg(test)]
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mod flipping {
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use super::*;
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#[test]
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fn flip_lr_test() {
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let m = Matrix::new([[1.0, 2.0, 3.0, 4.0]]);
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let flipped = m.flip_lr();
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assert_eq!(flipped, Matrix::new([[4.0, 3.0, 2.0, 1.0]]));
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let m = Matrix::new([[1.0, 2.0, 3.0, 4.0, 5.0]]);
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let flipped = m.flip_lr();
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assert_eq!(flipped, Matrix::new([[5.0, 4.0, 3.0, 2.0, 1.0]]));
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}
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#[test]
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fn flip_ud_test() {
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let m = Matrix::new([[1.0], [2.0], [3.0], [4.0]]);
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let flipped = m.flip_ud();
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assert_eq!(flipped, Matrix::new([[4.0], [3.0], [2.0], [1.0]]));
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let m = Matrix::new([[1.0], [2.0], [3.0], [4.0], [5.0]]);
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let flipped = m.flip_ud();
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assert_eq!(flipped, Matrix::new([[5.0], [4.0], [3.0], [2.0], [1.0]]));
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}
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#[test]
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fn assert_castability_of_alignment() {
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let m = Matrix::new([[1.0], [2.0], [3.0], [4.0_f64]]);
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assert_eq!(core::mem::align_of_val(&m), core::mem::align_of::<f64>());
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let m = Matrix::new([[1.0], [2.0], [3.0], [4.0_f32]]);
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assert_eq!(core::mem::align_of_val(&m), core::mem::align_of::<f32>());
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let m = Matrix::new([[1], [2], [3], [4_i32]]);
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assert_eq!(core::mem::align_of_val(&m), core::mem::align_of::<i32>());
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let m = Matrix::new([[1], [2], [3], [4_u64]]);
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assert_eq!(core::mem::align_of_val(&m), core::mem::align_of::<u64>());
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let m = Matrix::new([[1], [2], [3], [4_u128]]);
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assert_eq!(core::mem::align_of_val(&m), core::mem::align_of::<u128>());
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}
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}
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