nalgebra/src/base/conversion.rs

427 lines
14 KiB
Rust
Raw Normal View History

use alga::general::{SubsetOf, SupersetOf};
2017-07-25 23:04:12 +08:00
#[cfg(feature = "mint")]
use mint;
use std::convert::{AsMut, AsRef, From, Into};
use std::mem;
use std::ptr;
use generic_array::ArrayLength;
use std::ops::Mul;
use typenum::Prod;
use base::allocator::{Allocator, SameShapeAllocator};
use base::constraint::{SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
use base::dimension::{
2019-02-03 22:16:50 +08:00
Dim, DimName, U1, U10, U11, U12, U13, U14, U15, U16, U2, U3, U4, U5, U6, U7, U8, U9,
};
2019-02-03 22:16:50 +08:00
#[cfg(any(feature = "std", feature = "alloc"))]
use base::dimension::Dynamic;
use base::iter::{MatrixIter, MatrixIterMut};
use base::storage::{ContiguousStorage, ContiguousStorageMut, Storage, StorageMut};
#[cfg(any(feature = "std", feature = "alloc"))]
use base::VecStorage;
use base::{DefaultAllocator, Matrix, ArrayStorage, MatrixMN, MatrixSlice, MatrixSliceMut, Scalar};
// FIXME: too bad this won't work allo slice conversions.
impl<N1, N2, R1, C1, R2, C2> SubsetOf<MatrixMN<N2, R2, C2>> for MatrixMN<N1, R1, C1>
2018-02-02 19:26:35 +08:00
where
R1: Dim,
C1: Dim,
R2: Dim,
C2: Dim,
N1: Scalar,
N2: Scalar + SupersetOf<N1>,
DefaultAllocator:
Allocator<N2, R2, C2> + Allocator<N1, R1, C1> + SameShapeAllocator<N1, R1, C1, R2, C2>,
2018-02-02 19:26:35 +08:00
ShapeConstraint: SameNumberOfRows<R1, R2> + SameNumberOfColumns<C1, C2>,
{
#[inline]
fn to_superset(&self) -> MatrixMN<N2, R2, C2> {
let (nrows, ncols) = self.shape();
let nrows2 = R2::from_usize(nrows);
let ncols2 = C2::from_usize(ncols);
let mut res = unsafe { MatrixMN::<N2, R2, C2>::new_uninitialized_generic(nrows2, ncols2) };
2018-02-02 19:26:35 +08:00
for i in 0..nrows {
for j in 0..ncols {
2018-12-03 04:00:08 +08:00
unsafe { *res.get_unchecked_mut((i, j)) = N2::from_subset(self.get_unchecked((i, j))) }
}
}
res
}
#[inline]
fn is_in_subset(m: &MatrixMN<N2, R2, C2>) -> bool {
m.iter().all(|e| e.is_in_subset())
}
#[inline]
unsafe fn from_superset_unchecked(m: &MatrixMN<N2, R2, C2>) -> Self {
let (nrows2, ncols2) = m.shape();
let nrows = R1::from_usize(nrows2);
let ncols = C1::from_usize(ncols2);
let mut res = Self::new_uninitialized_generic(nrows, ncols);
2018-02-02 19:26:35 +08:00
for i in 0..nrows2 {
for j in 0..ncols2 {
2018-12-03 04:00:08 +08:00
*res.get_unchecked_mut((i, j)) = m.get_unchecked((i, j)).to_subset_unchecked()
}
}
res
}
}
2017-02-18 20:28:22 +08:00
impl<'a, N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> IntoIterator for &'a Matrix<N, R, C, S> {
2018-02-02 19:26:35 +08:00
type Item = &'a N;
type IntoIter = MatrixIter<'a, N, R, C, S>;
#[inline]
fn into_iter(self) -> Self::IntoIter {
self.iter()
}
}
2018-02-02 19:26:35 +08:00
impl<'a, N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> IntoIterator
for &'a mut Matrix<N, R, C, S>
{
2018-02-02 19:26:35 +08:00
type Item = &'a mut N;
type IntoIter = MatrixIterMut<'a, N, R, C, S>;
#[inline]
fn into_iter(self) -> Self::IntoIter {
self.iter_mut()
}
}
2017-02-18 20:28:22 +08:00
macro_rules! impl_from_into_asref_1D(
($(($NRows: ident, $NCols: ident) => $SZ: expr);* $(;)*) => {$(
impl<N> From<[N; $SZ]> for MatrixMN<N, $NRows, $NCols>
2017-02-18 20:28:22 +08:00
where N: Scalar,
DefaultAllocator: Allocator<N, $NRows, $NCols> {
2017-02-18 20:28:22 +08:00
#[inline]
fn from(arr: [N; $SZ]) -> Self {
unsafe {
let mut res = Self::new_uninitialized();
ptr::copy_nonoverlapping(&arr[0], res.data.ptr_mut(), $SZ);
res
}
}
}
impl<N, S> Into<[N; $SZ]> for Matrix<N, $NRows, $NCols, S>
2017-02-18 20:28:22 +08:00
where N: Scalar,
S: ContiguousStorage<N, $NRows, $NCols> {
2017-02-18 20:28:22 +08:00
#[inline]
fn into(self) -> [N; $SZ] {
unsafe {
let mut res: [N; $SZ] = mem::uninitialized();
ptr::copy_nonoverlapping(self.data.ptr(), &mut res[0], $SZ);
res
}
}
}
impl<N, S> AsRef<[N; $SZ]> for Matrix<N, $NRows, $NCols, S>
2017-02-18 20:28:22 +08:00
where N: Scalar,
S: ContiguousStorage<N, $NRows, $NCols> {
2017-02-18 20:28:22 +08:00
#[inline]
fn as_ref(&self) -> &[N; $SZ] {
unsafe {
mem::transmute(self.data.ptr())
}
}
}
impl<N, S> AsMut<[N; $SZ]> for Matrix<N, $NRows, $NCols, S>
2017-02-18 20:28:22 +08:00
where N: Scalar,
S: ContiguousStorageMut<N, $NRows, $NCols> {
2017-02-18 20:28:22 +08:00
#[inline]
fn as_mut(&mut self) -> &mut [N; $SZ] {
unsafe {
mem::transmute(self.data.ptr_mut())
}
}
}
)*}
);
// Implement for vectors of dimension 1 .. 16.
2017-02-18 20:28:22 +08:00
impl_from_into_asref_1D!(
// Row vectors.
(U1, U1 ) => 1; (U1, U2 ) => 2; (U1, U3 ) => 3; (U1, U4 ) => 4;
(U1, U5 ) => 5; (U1, U6 ) => 6; (U1, U7 ) => 7; (U1, U8 ) => 8;
(U1, U9 ) => 9; (U1, U10) => 10; (U1, U11) => 11; (U1, U12) => 12;
(U1, U13) => 13; (U1, U14) => 14; (U1, U15) => 15; (U1, U16) => 16;
// Column vectors.
(U2 , U1) => 2; (U3 , U1) => 3; (U4 , U1) => 4;
(U5 , U1) => 5; (U6 , U1) => 6; (U7 , U1) => 7; (U8 , U1) => 8;
(U9 , U1) => 9; (U10, U1) => 10; (U11, U1) => 11; (U12, U1) => 12;
(U13, U1) => 13; (U14, U1) => 14; (U15, U1) => 15; (U16, U1) => 16;
2017-02-18 20:28:22 +08:00
);
macro_rules! impl_from_into_asref_2D(
($(($NRows: ty, $NCols: ty) => ($SZRows: expr, $SZCols: expr));* $(;)*) => {$(
impl<N: Scalar> From<[[N; $SZRows]; $SZCols]> for MatrixMN<N, $NRows, $NCols>
where DefaultAllocator: Allocator<N, $NRows, $NCols> {
2017-02-18 20:28:22 +08:00
#[inline]
fn from(arr: [[N; $SZRows]; $SZCols]) -> Self {
unsafe {
let mut res = Self::new_uninitialized();
ptr::copy_nonoverlapping(&arr[0][0], res.data.ptr_mut(), $SZRows * $SZCols);
res
}
}
}
impl<N: Scalar, S> Into<[[N; $SZRows]; $SZCols]> for Matrix<N, $NRows, $NCols, S>
where S: ContiguousStorage<N, $NRows, $NCols> {
2017-02-18 20:28:22 +08:00
#[inline]
fn into(self) -> [[N; $SZRows]; $SZCols] {
unsafe {
let mut res: [[N; $SZRows]; $SZCols] = mem::uninitialized();
ptr::copy_nonoverlapping(self.data.ptr(), &mut res[0][0], $SZRows * $SZCols);
res
}
}
}
impl<N: Scalar, S> AsRef<[[N; $SZRows]; $SZCols]> for Matrix<N, $NRows, $NCols, S>
where S: ContiguousStorage<N, $NRows, $NCols> {
2017-02-18 20:28:22 +08:00
#[inline]
fn as_ref(&self) -> &[[N; $SZRows]; $SZCols] {
unsafe {
mem::transmute(self.data.ptr())
}
}
}
impl<N: Scalar, S> AsMut<[[N; $SZRows]; $SZCols]> for Matrix<N, $NRows, $NCols, S>
where S: ContiguousStorageMut<N, $NRows, $NCols> {
2017-02-18 20:28:22 +08:00
#[inline]
fn as_mut(&mut self) -> &mut [[N; $SZRows]; $SZCols] {
unsafe {
mem::transmute(self.data.ptr_mut())
}
}
}
)*}
);
// Implement for matrices with shape 2x2 .. 6x6.
2017-02-18 20:28:22 +08:00
impl_from_into_asref_2D!(
(U2, U2) => (2, 2); (U2, U3) => (2, 3); (U2, U4) => (2, 4); (U2, U5) => (2, 5); (U2, U6) => (2, 6);
(U3, U2) => (3, 2); (U3, U3) => (3, 3); (U3, U4) => (3, 4); (U3, U5) => (3, 5); (U3, U6) => (3, 6);
(U4, U2) => (4, 2); (U4, U3) => (4, 3); (U4, U4) => (4, 4); (U4, U5) => (4, 5); (U4, U6) => (4, 6);
(U5, U2) => (5, 2); (U5, U3) => (5, 3); (U5, U4) => (5, 4); (U5, U5) => (5, 5); (U5, U6) => (5, 6);
(U6, U2) => (6, 2); (U6, U3) => (6, 3); (U6, U4) => (6, 4); (U6, U5) => (6, 5); (U6, U6) => (6, 6);
2017-02-18 20:28:22 +08:00
);
2017-07-25 23:04:12 +08:00
#[cfg(feature = "mint")]
macro_rules! impl_from_into_mint_1D(
($($NRows: ident => $VT:ident [$SZ: expr]);* $(;)*) => {$(
2017-10-10 01:58:09 +08:00
impl<N> From<mint::$VT<N>> for MatrixMN<N, $NRows, U1>
2017-07-25 23:04:12 +08:00
where N: Scalar,
2017-10-10 01:58:09 +08:00
DefaultAllocator: Allocator<N, $NRows, U1> {
2017-07-25 23:04:12 +08:00
#[inline]
fn from(v: mint::$VT<N>) -> Self {
unsafe {
let mut res = Self::new_uninitialized();
ptr::copy_nonoverlapping(&v.x, res.data.ptr_mut(), $SZ);
res
}
}
}
impl<N, S> Into<mint::$VT<N>> for Matrix<N, $NRows, U1, S>
where N: Scalar,
2017-10-10 01:58:09 +08:00
S: ContiguousStorage<N, $NRows, U1> {
2017-07-25 23:04:12 +08:00
#[inline]
fn into(self) -> mint::$VT<N> {
unsafe {
let mut res: mint::$VT<N> = mem::uninitialized();
ptr::copy_nonoverlapping(self.data.ptr(), &mut res.x, $SZ);
res
}
}
}
impl<N, S> AsRef<mint::$VT<N>> for Matrix<N, $NRows, U1, S>
where N: Scalar,
2017-10-10 01:58:09 +08:00
S: ContiguousStorage<N, $NRows, U1> {
2017-07-25 23:04:12 +08:00
#[inline]
fn as_ref(&self) -> &mint::$VT<N> {
unsafe {
mem::transmute(self.data.ptr())
}
}
}
impl<N, S> AsMut<mint::$VT<N>> for Matrix<N, $NRows, U1, S>
where N: Scalar,
2017-10-10 01:58:09 +08:00
S: ContiguousStorageMut<N, $NRows, U1> {
2017-07-25 23:04:12 +08:00
#[inline]
fn as_mut(&mut self) -> &mut mint::$VT<N> {
unsafe {
mem::transmute(self.data.ptr_mut())
}
}
}
)*}
);
// Implement for vectors of dimension 2 .. 4.
#[cfg(feature = "mint")]
2017-07-26 00:27:18 +08:00
impl_from_into_mint_1D!(
2017-07-25 23:04:12 +08:00
U2 => Vector2[2];
U3 => Vector3[3];
U4 => Vector4[4];
);
2017-07-26 00:27:18 +08:00
#[cfg(feature = "mint")]
macro_rules! impl_from_into_mint_2D(
($(($NRows: ty, $NCols: ty) => $MV:ident{ $($component:ident),* }[$SZRows: expr]);* $(;)*) => {$(
2017-10-10 01:58:09 +08:00
impl<N> From<mint::$MV<N>> for MatrixMN<N, $NRows, $NCols>
2017-07-26 00:27:18 +08:00
where N: Scalar,
2017-10-10 01:58:09 +08:00
DefaultAllocator: Allocator<N, $NRows, $NCols> {
2017-07-26 00:27:18 +08:00
#[inline]
fn from(m: mint::$MV<N>) -> Self {
unsafe {
let mut res = Self::new_uninitialized();
let mut ptr = res.data.ptr_mut();
$(
ptr::copy_nonoverlapping(&m.$component.x, ptr, $SZRows);
ptr = ptr.offset($SZRows);
)*
let _ = ptr;
res
}
}
}
2017-10-10 01:58:09 +08:00
impl<N> Into<mint::$MV<N>> for MatrixMN<N, $NRows, $NCols>
2017-07-26 00:27:18 +08:00
where N: Scalar,
2017-10-10 01:58:09 +08:00
DefaultAllocator: Allocator<N, $NRows, $NCols> {
2017-07-26 00:27:18 +08:00
#[inline]
fn into(self) -> mint::$MV<N> {
unsafe {
let mut res: mint::$MV<N> = mem::uninitialized();
let mut ptr = self.data.ptr();
$(
ptr::copy_nonoverlapping(ptr, &mut res.$component.x, $SZRows);
ptr = ptr.offset($SZRows);
)*
let _ = ptr;
res
}
}
}
)*}
);
// Implement for matrices with shape 2x2 .. 4x4.
#[cfg(feature = "mint")]
impl_from_into_mint_2D!(
(U2, U2) => ColumnMatrix2{x, y}[2];
(U2, U3) => ColumnMatrix2x3{x, y}[2];
2017-07-26 00:27:18 +08:00
(U3, U3) => ColumnMatrix3{x, y, z}[3];
(U3, U4) => ColumnMatrix3x4{x, y, z}[3];
2017-07-26 00:27:18 +08:00
(U4, U4) => ColumnMatrix4{x, y, z, w}[4];
);
impl<'a, N, R, C, RStride, CStride> From<MatrixSlice<'a, N, R, C, RStride, CStride>>
for Matrix<N, R, C, ArrayStorage<N, R, C>>
where
N: Scalar,
R: DimName,
C: DimName,
RStride: Dim,
CStride: Dim,
R::Value: Mul<C::Value>,
Prod<R::Value, C::Value>: ArrayLength<N>,
{
fn from(matrix_slice: MatrixSlice<'a, N, R, C, RStride, CStride>) -> Self {
matrix_slice.into_owned()
}
}
#[cfg(any(feature = "std", feature = "alloc"))]
impl<'a, N, C, RStride, CStride> From<MatrixSlice<'a, N, Dynamic, C, RStride, CStride>>
for Matrix<N, Dynamic, C, VecStorage<N, Dynamic, C>>
where
N: Scalar,
C: Dim,
RStride: Dim,
CStride: Dim,
{
fn from(matrix_slice: MatrixSlice<'a, N, Dynamic, C, RStride, CStride>) -> Self {
matrix_slice.into_owned()
}
}
#[cfg(any(feature = "std", feature = "alloc"))]
impl<'a, N, R, RStride, CStride> From<MatrixSlice<'a, N, R, Dynamic, RStride, CStride>>
for Matrix<N, R, Dynamic, VecStorage<N, R, Dynamic>>
where
N: Scalar,
R: DimName,
RStride: Dim,
CStride: Dim,
{
fn from(matrix_slice: MatrixSlice<'a, N, R, Dynamic, RStride, CStride>) -> Self {
matrix_slice.into_owned()
}
}
impl<'a, N, R, C, RStride, CStride> From<MatrixSliceMut<'a, N, R, C, RStride, CStride>>
for Matrix<N, R, C, ArrayStorage<N, R, C>>
where
N: Scalar,
R: DimName,
C: DimName,
RStride: Dim,
CStride: Dim,
R::Value: Mul<C::Value>,
Prod<R::Value, C::Value>: ArrayLength<N>,
{
fn from(matrix_slice: MatrixSliceMut<'a, N, R, C, RStride, CStride>) -> Self {
matrix_slice.into_owned()
}
}
#[cfg(any(feature = "std", feature = "alloc"))]
impl<'a, N, C, RStride, CStride> From<MatrixSliceMut<'a, N, Dynamic, C, RStride, CStride>>
for Matrix<N, Dynamic, C, VecStorage<N, Dynamic, C>>
where
N: Scalar,
C: Dim,
RStride: Dim,
CStride: Dim,
{
fn from(matrix_slice: MatrixSliceMut<'a, N, Dynamic, C, RStride, CStride>) -> Self {
matrix_slice.into_owned()
}
}
#[cfg(any(feature = "std", feature = "alloc"))]
impl<'a, N, R, RStride, CStride> From<MatrixSliceMut<'a, N, R, Dynamic, RStride, CStride>>
for Matrix<N, R, Dynamic, VecStorage<N, R, Dynamic>>
where
N: Scalar,
R: DimName,
RStride: Dim,
CStride: Dim,
{
fn from(matrix_slice: MatrixSliceMut<'a, N, R, Dynamic, RStride, CStride>) -> Self {
matrix_slice.into_owned()
}
}