// Non-conventional componentwise operators. use num::{Signed, Zero}; use std::ops::{Add, Mul}; use alga::general::{ClosedDiv, ClosedMul}; use base::allocator::{Allocator, SameShapeAllocator}; use base::constraint::{SameNumberOfColumns, SameNumberOfRows, ShapeConstraint}; use base::dimension::Dim; use base::storage::{Storage, StorageMut}; use base::{DefaultAllocator, Matrix, MatrixMN, MatrixSum, Scalar}; /// The type of the result of a matrix component-wise operation. pub type MatrixComponentOp = MatrixSum; impl> Matrix { /// Computes the component-wise absolute value. /// /// # Example /// /// ``` /// # use nalgebra::Matrix2; /// let a = Matrix2::new(0.0, 1.0, /// -2.0, -3.0); /// assert_eq!(a.abs(), Matrix2::new(0.0, 1.0, 2.0, 3.0)) /// ``` #[inline] pub fn abs(&self) -> MatrixMN where N: Signed, DefaultAllocator: Allocator, { 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( ($($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> Matrix { #[doc = $desc] #[inline] pub fn $binop(&self, rhs: &Matrix) -> MatrixComponentOp where N: $Trait, R2: Dim, C2: Dim, SB: Storage, DefaultAllocator: SameShapeAllocator, ShapeConstraint: SameNumberOfRows + SameNumberOfColumns { assert_eq!(self.shape(), rhs.shape(), "Componentwise mul/div: mismatched matrix dimensions."); let mut res = self.clone_owned_sum(); for j in 0 .. res.ncols() { for i in 0 .. res.nrows() { unsafe { res.get_unchecked_mut((i, j)).$op_assign(*rhs.get_unchecked((i, j))); } } } res } } impl> Matrix { // componentwise binop plus Y. #[doc = $desc_cmpy] #[inline] pub fn $cmpy(&mut self, alpha: N, a: &Matrix, b: &Matrix, beta: N) where N: $Trait + Zero + Mul + Add, R2: Dim, C2: Dim, R3: Dim, C3: Dim, SB: Storage, SC: Storage, ShapeConstraint: SameNumberOfRows + SameNumberOfColumns + SameNumberOfRows + SameNumberOfColumns { assert_eq!(self.shape(), a.shape(), "Componentwise mul/div: mismatched matrix dimensions."); assert_eq!(self.shape(), b.shape(), "Componentwise mul/div: mismatched matrix dimensions."); if beta.is_zero() { for j in 0 .. self.ncols() { for i in 0 .. self.nrows() { unsafe { let res = alpha * a.get_unchecked((i, j)).$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(&mut self, rhs: &Matrix) where N: $Trait, R2: Dim, C2: Dim, SB: Storage, ShapeConstraint: SameNumberOfRows + SameNumberOfColumns { assert_eq!(self.shape(), rhs.shape(), "Componentwise mul/div: mismatched matrix dimensions."); for j in 0 .. self.ncols() { for i in 0 .. self.nrows() { unsafe { self.get_unchecked_mut((i, j)).$op_assign(*rhs.get_unchecked((i, j))); } } } } #[doc = $desc_mut] #[inline] #[deprecated(note = "This is renamed using the `_assign` suffix instead of the `_mut` suffix.")] pub fn $binop_mut(&mut self, rhs: &Matrix) where N: $Trait, R2: Dim, C2: Dim, SB: Storage, ShapeConstraint: SameNumberOfRows + SameNumberOfColumns { self.$binop_assign(rhs) } } )*} ); component_binop_impl!( component_mul, component_mul_mut, component_mul_assign, cmpy, ClosedMul.mul.mul_assign, r" Componentwise matrix or vector multiplication. # Example ``` # use nalgebra::Matrix2; let a = Matrix2::new(0.0, 1.0, 2.0, 3.0); let b = Matrix2::new(4.0, 5.0, 6.0, 7.0); let expected = Matrix2::new(0.0, 5.0, 12.0, 21.0); assert_eq!(a.component_mul(&b), expected); ``` ", r" Computes componentwise `self[i] = alpha * a[i] * b[i] + beta * self[i]`. # Example ``` # use nalgebra::Matrix2; let mut m = Matrix2::new(0.0, 1.0, 2.0, 3.0); let a = Matrix2::new(0.0, 1.0, 2.0, 3.0); let b = Matrix2::new(4.0, 5.0, 6.0, 7.0); let expected = (a.component_mul(&b) * 5.0) + m * 10.0; m.cmpy(5.0, &a, &b, 10.0); assert_eq!(m, expected); ``` ", r" Inplace componentwise matrix or vector multiplication. # Example ``` # use nalgebra::Matrix2; let mut a = Matrix2::new(0.0, 1.0, 2.0, 3.0); let b = Matrix2::new(4.0, 5.0, 6.0, 7.0); let expected = Matrix2::new(0.0, 5.0, 12.0, 21.0); a.component_mul_assign(&b); assert_eq!(a, expected); ``` "; component_div, component_div_mut, component_div_assign, cdpy, ClosedDiv.div.div_assign, r" Componentwise matrix or vector division. # Example ``` # use nalgebra::Matrix2; let a = Matrix2::new(0.0, 1.0, 2.0, 3.0); let b = Matrix2::new(4.0, 5.0, 6.0, 7.0); let expected = Matrix2::new(0.0, 1.0 / 5.0, 2.0 / 6.0, 3.0 / 7.0); assert_eq!(a.component_div(&b), expected); ``` ", r" Computes componentwise `self[i] = alpha * a[i] / b[i] + beta * self[i]`. # Example ``` # use nalgebra::Matrix2; let mut m = Matrix2::new(0.0, 1.0, 2.0, 3.0); let a = Matrix2::new(4.0, 5.0, 6.0, 7.0); let b = Matrix2::new(4.0, 5.0, 6.0, 7.0); let expected = (a.component_div(&b) * 5.0) + m * 10.0; m.cdpy(5.0, &a, &b, 10.0); assert_eq!(m, expected); ``` ", r" Inplace componentwise matrix or vector division. # Example ``` # use nalgebra::Matrix2; let mut a = Matrix2::new(0.0, 1.0, 2.0, 3.0); let b = Matrix2::new(4.0, 5.0, 6.0, 7.0); let expected = Matrix2::new(0.0, 1.0 / 5.0, 2.0 / 6.0, 3.0 / 7.0); a.component_div_assign(&b); assert_eq!(a, expected); ``` "; // FIXME: add other operators like bitshift, etc. ? );