nalgebra/src/core/componentwise.rs

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// Non-convensional componentwise operators.
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use std::ops::{Add, Mul};
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use num::{Signed, Zero};
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use alga::general::{ClosedDiv, ClosedMul};
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use core::{DefaultAllocator, Matrix, MatrixMN, MatrixSum, Scalar};
use core::dimension::Dim;
use core::storage::{Storage, StorageMut};
use core::allocator::{Allocator, SameShapeAllocator};
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use core::constraint::{SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
/// The type of the result of a matrix componentwise operation.
pub type MatrixComponentOp<N, R1, C1, R2, C2> = MatrixSum<N, R1, C1, R2, C2>;
impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
/// Computes the componentwise absolute value.
#[inline]
pub fn abs(&self) -> MatrixMN<N, R, C>
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where
N: Signed,
DefaultAllocator: Allocator<N, R, C>,
{
let mut res = self.clone_owned();
for e in res.iter_mut() {
*e = e.abs();
}
res
}
// FIXME: add other operators like component_ln, component_pow, etc. ?
}
macro_rules! component_binop_impl(
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($($binop: ident, $binop_mut: ident, $binop_assign: ident, $cmpy: ident, $Trait: ident . $op: ident . $op_assign: ident, $desc:expr, $desc_cmpy:expr, $desc_mut:expr);* $(;)*) => {$(
impl<N: Scalar, R1: Dim, C1: Dim, SA: Storage<N, R1, C1>> Matrix<N, R1, C1, SA> {
#[doc = $desc]
#[inline]
pub fn $binop<R2, C2, SB>(&self, rhs: &Matrix<N, R2, C2, SB>) -> MatrixComponentOp<N, R1, C1, R2, C2>
where N: $Trait,
R2: Dim, C2: Dim,
SB: Storage<N, R2, C2>,
DefaultAllocator: SameShapeAllocator<N, R1, C1, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
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assert_eq!(self.shape(), rhs.shape(), "Componentwise mul/div: mismatched matrix dimensions.");
let mut res = self.clone_owned_sum();
for j in 0 .. res.ncols() {
for i in 0 .. res.nrows() {
unsafe {
res.get_unchecked_mut(i, j).$op_assign(*rhs.get_unchecked(i, j));
}
}
}
res
}
}
impl<N: Scalar, R1: Dim, C1: Dim, SA: StorageMut<N, R1, C1>> Matrix<N, R1, C1, SA> {
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// componentwise binop plus Y.
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#[doc = $desc_cmpy]
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#[inline]
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pub fn $cmpy<R2, C2, SB, R3, C3, SC>(&mut self, alpha: N, a: &Matrix<N, R2, C2, SB>, b: &Matrix<N, R3, C3, SC>, beta: N)
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where N: $Trait + Zero + Mul<N, Output = N> + Add<N, Output = N>,
R2: Dim, C2: Dim,
R3: Dim, C3: Dim,
SB: Storage<N, R2, C2>,
SC: Storage<N, R3, C3>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> +
SameNumberOfRows<R1, R3> + SameNumberOfColumns<C1, C3> {
assert_eq!(self.shape(), a.shape(), "Componentwise mul/div: mismatched matrix dimensions.");
assert_eq!(self.shape(), b.shape(), "Componentwise mul/div: mismatched matrix dimensions.");
if beta.is_zero() {
for j in 0 .. self.ncols() {
for i in 0 .. self.nrows() {
unsafe {
let res = alpha * a.get_unchecked(i, j).$op(*b.get_unchecked(i, j));
*self.get_unchecked_mut(i, j) = res;
}
}
}
}
else {
for j in 0 .. self.ncols() {
for i in 0 .. self.nrows() {
unsafe {
let res = alpha * a.get_unchecked(i, j).$op(*b.get_unchecked(i, j));
*self.get_unchecked_mut(i, j) = beta * *self.get_unchecked(i, j) + res;
}
}
}
}
}
#[doc = $desc_mut]
#[inline]
pub fn $binop_assign<R2, C2, SB>(&mut self, rhs: &Matrix<N, R2, C2, SB>)
where N: $Trait,
R2: Dim,
C2: Dim,
SB: Storage<N, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
assert_eq!(self.shape(), rhs.shape(), "Componentwise mul/div: mismatched matrix dimensions.");
for j in 0 .. self.ncols() {
for i in 0 .. self.nrows() {
unsafe {
self.get_unchecked_mut(i, j).$op_assign(*rhs.get_unchecked(i, j));
}
}
}
}
#[doc = $desc_mut]
#[inline]
#[deprecated(note = "This is renamed using the `_assign` sufix instead of the `_mut` suffix.")]
pub fn $binop_mut<R2, C2, SB>(&mut self, rhs: &Matrix<N, R2, C2, SB>)
where N: $Trait,
R2: Dim,
C2: Dim,
SB: Storage<N, R2, C2>,
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2> {
self.$binop_assign(rhs)
}
}
)*}
);
component_binop_impl!(
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component_mul, component_mul_mut, component_mul_assign, cmpy, ClosedMul.mul.mul_assign,
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"Componentwise matrix multiplication.",
"Computes componentwise `self[i] = alpha * a[i] * b[i] + beta * self[i]",
"Inplace componentwise matrix multiplication.";
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component_div, component_div_mut, component_div_assign, cdpy, ClosedDiv.div.div_assign,
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"Componentwise matrix division.",
"Computes componentwise `self[i] = alpha * a[i] / b[i] + beta * self[i]",
"Inplace componentwise matrix division.";
// FIXME: add other operators like bitshift, etc. ?
);