forked from M-Labs/nalgebra
4a6022d9bf
There are two major additions in this commit. The first is a new storage trait, `ReshapableStorage`, that can be implemented for storage types that can be reshaped in-place. I have implemented this for both the `ArrayStorage` and `VecStorage` types, as they are the most common and they are just interpretations of a flat list. The second is a `Matrix::reshape_generic` method that allows matrices to be in-place reshaped provided that the underlying storage can handle it. In practice, this means that the standard matrix types (`MatrixMN` and `DMatrix`) can be resized to any size that has the same element count. Resizing between array and vector storage is not implemented due to `Storage` only being implemented for `VecStorage` variants where at least one dimension is `Dynamic`. Additionally, only the generic reshape function is added as it can be a basis for other reshaping functions (see the resizing functions) and I am not particularly in the mood to implement a variety of reshaping methods.
1118 lines
36 KiB
Rust
1118 lines
36 KiB
Rust
use num::{One, Zero};
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use std::cmp;
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#[cfg(any(feature = "std", feature = "alloc"))]
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use std::iter::ExactSizeIterator;
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#[cfg(any(feature = "std", feature = "alloc"))]
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use std::mem;
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use std::ptr;
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use crate::base::allocator::{Allocator, Reallocator};
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use crate::base::constraint::{DimEq, SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
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#[cfg(any(feature = "std", feature = "alloc"))]
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use crate::base::dimension::Dynamic;
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use crate::base::dimension::{
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Dim, DimAdd, DimDiff, DimMin, DimMinimum, DimName, DimSub, DimSum, U1,
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};
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use crate::base::storage::{ReshapableStorage, Storage, StorageMut};
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#[cfg(any(feature = "std", feature = "alloc"))]
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use crate::base::DMatrix;
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use crate::base::{DefaultAllocator, Matrix, MatrixMN, RowVector, Scalar, Vector};
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impl<N: Scalar + Zero, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
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/// Extracts the upper triangular part of this matrix (including the diagonal).
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#[inline]
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pub fn upper_triangle(&self) -> MatrixMN<N, R, C>
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where
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DefaultAllocator: Allocator<N, R, C>,
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{
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let mut res = self.clone_owned();
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res.fill_lower_triangle(N::zero(), 1);
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res
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}
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/// Extracts the lower triangular part of this matrix (including the diagonal).
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#[inline]
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pub fn lower_triangle(&self) -> MatrixMN<N, R, C>
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where
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DefaultAllocator: Allocator<N, R, C>,
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{
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let mut res = self.clone_owned();
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res.fill_upper_triangle(N::zero(), 1);
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res
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}
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/// Creates a new matrix by extracting the given set of rows from `self`.
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#[cfg(any(feature = "std", feature = "alloc"))]
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pub fn select_rows<'a, I>(&self, irows: I) -> MatrixMN<N, Dynamic, C>
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where
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I: IntoIterator<Item = &'a usize>,
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I::IntoIter: ExactSizeIterator + Clone,
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DefaultAllocator: Allocator<N, Dynamic, C>,
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{
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let irows = irows.into_iter();
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let ncols = self.data.shape().1;
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let mut res =
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unsafe { MatrixMN::new_uninitialized_generic(Dynamic::new(irows.len()), ncols) };
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// First, check that all the indices from irows are valid.
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// This will allow us to use unchecked access in the inner loop.
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for i in irows.clone() {
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assert!(*i < self.nrows(), "Row index out of bounds.")
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}
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for j in 0..ncols.value() {
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// FIXME: use unchecked column indexing
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let mut res = res.column_mut(j);
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let src = self.column(j);
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for (destination, source) in irows.clone().enumerate() {
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unsafe {
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*res.vget_unchecked_mut(destination) =
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src.vget_unchecked(*source).inlined_clone()
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}
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}
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}
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res
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}
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/// Creates a new matrix by extracting the given set of columns from `self`.
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#[cfg(any(feature = "std", feature = "alloc"))]
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pub fn select_columns<'a, I>(&self, icols: I) -> MatrixMN<N, R, Dynamic>
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where
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I: IntoIterator<Item = &'a usize>,
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I::IntoIter: ExactSizeIterator,
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DefaultAllocator: Allocator<N, R, Dynamic>,
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{
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let icols = icols.into_iter();
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let nrows = self.data.shape().0;
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let mut res =
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unsafe { MatrixMN::new_uninitialized_generic(nrows, Dynamic::new(icols.len())) };
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for (destination, source) in icols.enumerate() {
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res.column_mut(destination).copy_from(&self.column(*source))
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}
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res
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}
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}
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impl<N: Scalar, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
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/// Sets all the elements of this matrix to `val`.
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#[inline]
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pub fn fill(&mut self, val: N) {
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for e in self.iter_mut() {
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*e = val.inlined_clone()
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}
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}
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/// Fills `self` with the identity matrix.
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#[inline]
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pub fn fill_with_identity(&mut self)
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where
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N: Zero + One,
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{
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self.fill(N::zero());
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self.fill_diagonal(N::one());
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}
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/// Sets all the diagonal elements of this matrix to `val`.
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#[inline]
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pub fn fill_diagonal(&mut self, val: N) {
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let (nrows, ncols) = self.shape();
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let n = cmp::min(nrows, ncols);
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for i in 0..n {
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unsafe { *self.get_unchecked_mut((i, i)) = val.inlined_clone() }
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}
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}
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/// Sets all the elements of the selected row to `val`.
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#[inline]
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pub fn fill_row(&mut self, i: usize, val: N) {
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assert!(i < self.nrows(), "Row index out of bounds.");
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for j in 0..self.ncols() {
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unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
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}
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}
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/// Sets all the elements of the selected column to `val`.
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#[inline]
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pub fn fill_column(&mut self, j: usize, val: N) {
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assert!(j < self.ncols(), "Row index out of bounds.");
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for i in 0..self.nrows() {
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unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
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}
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}
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/// Fills the diagonal of this matrix with the content of the given vector.
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#[inline]
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pub fn set_diagonal<R2: Dim, S2>(&mut self, diag: &Vector<N, R2, S2>)
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where
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R: DimMin<C>,
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S2: Storage<N, R2>,
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ShapeConstraint: DimEq<DimMinimum<R, C>, R2>,
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{
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let (nrows, ncols) = self.shape();
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let min_nrows_ncols = cmp::min(nrows, ncols);
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assert_eq!(diag.len(), min_nrows_ncols, "Mismatched dimensions.");
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for i in 0..min_nrows_ncols {
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unsafe { *self.get_unchecked_mut((i, i)) = diag.vget_unchecked(i).inlined_clone() }
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}
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}
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/// Fills the diagonal of this matrix with the content of the given iterator.
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///
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/// This will fill as many diagonal elements as the iterator yields, up to the
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/// minimum of the number of rows and columns of `self`, and starting with the
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/// diagonal element at index (0, 0).
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#[inline]
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pub fn set_partial_diagonal(&mut self, diag: impl Iterator<Item = N>) {
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let (nrows, ncols) = self.shape();
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let min_nrows_ncols = cmp::min(nrows, ncols);
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for (i, val) in diag.enumerate().take(min_nrows_ncols) {
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unsafe { *self.get_unchecked_mut((i, i)) = val }
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}
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}
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/// Fills the selected row of this matrix with the content of the given vector.
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#[inline]
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pub fn set_row<C2: Dim, S2>(&mut self, i: usize, row: &RowVector<N, C2, S2>)
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where
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S2: Storage<N, U1, C2>,
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ShapeConstraint: SameNumberOfColumns<C, C2>,
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{
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self.row_mut(i).copy_from(row);
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}
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/// Fills the selected column of this matrix with the content of the given vector.
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#[inline]
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pub fn set_column<R2: Dim, S2>(&mut self, i: usize, column: &Vector<N, R2, S2>)
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where
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S2: Storage<N, R2, U1>,
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ShapeConstraint: SameNumberOfRows<R, R2>,
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{
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self.column_mut(i).copy_from(column);
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}
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/// Sets all the elements of the lower-triangular part of this matrix to `val`.
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///
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/// The parameter `shift` allows some subdiagonals to be left untouched:
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/// * If `shift = 0` then the diagonal is overwritten as well.
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/// * If `shift = 1` then the diagonal is left untouched.
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/// * If `shift > 1`, then the diagonal and the first `shift - 1` subdiagonals are left
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/// untouched.
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#[inline]
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pub fn fill_lower_triangle(&mut self, val: N, shift: usize) {
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for j in 0..self.ncols() {
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for i in (j + shift)..self.nrows() {
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unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
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}
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}
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}
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/// Sets all the elements of the lower-triangular part of this matrix to `val`.
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///
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/// The parameter `shift` allows some superdiagonals to be left untouched:
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/// * If `shift = 0` then the diagonal is overwritten as well.
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/// * If `shift = 1` then the diagonal is left untouched.
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/// * If `shift > 1`, then the diagonal and the first `shift - 1` superdiagonals are left
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/// untouched.
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#[inline]
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pub fn fill_upper_triangle(&mut self, val: N, shift: usize) {
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for j in shift..self.ncols() {
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// FIXME: is there a more efficient way to avoid the min ?
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// (necessary for rectangular matrices)
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for i in 0..cmp::min(j + 1 - shift, self.nrows()) {
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unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
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}
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}
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}
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/// Swaps two rows in-place.
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#[inline]
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pub fn swap_rows(&mut self, irow1: usize, irow2: usize) {
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assert!(irow1 < self.nrows() && irow2 < self.nrows());
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if irow1 != irow2 {
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// FIXME: optimize that.
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for i in 0..self.ncols() {
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unsafe { self.swap_unchecked((irow1, i), (irow2, i)) }
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}
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}
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// Otherwise do nothing.
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}
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/// Swaps two columns in-place.
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#[inline]
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pub fn swap_columns(&mut self, icol1: usize, icol2: usize) {
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assert!(icol1 < self.ncols() && icol2 < self.ncols());
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if icol1 != icol2 {
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// FIXME: optimize that.
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for i in 0..self.nrows() {
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unsafe { self.swap_unchecked((i, icol1), (i, icol2)) }
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}
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}
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// Otherwise do nothing.
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}
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}
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impl<N: Scalar, D: Dim, S: StorageMut<N, D, D>> Matrix<N, D, D, S> {
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/// Copies the upper-triangle of this matrix to its lower-triangular part.
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///
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/// This makes the matrix symmetric. Panics if the matrix is not square.
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pub fn fill_lower_triangle_with_upper_triangle(&mut self) {
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assert!(self.is_square(), "The input matrix should be square.");
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let dim = self.nrows();
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for j in 0..dim {
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for i in j + 1..dim {
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unsafe {
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*self.get_unchecked_mut((i, j)) = self.get_unchecked((j, i)).inlined_clone();
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}
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}
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}
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}
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/// Copies the upper-triangle of this matrix to its upper-triangular part.
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///
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/// This makes the matrix symmetric. Panics if the matrix is not square.
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pub fn fill_upper_triangle_with_lower_triangle(&mut self) {
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assert!(self.is_square(), "The input matrix should be square.");
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for j in 1..self.ncols() {
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for i in 0..j {
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unsafe {
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*self.get_unchecked_mut((i, j)) = self.get_unchecked((j, i)).inlined_clone();
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}
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}
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}
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}
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}
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/*
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*
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* FIXME: specialize all the following for slices.
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*
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*/
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impl<N: Scalar, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
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/*
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*
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* Column removal.
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*
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*/
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/// Removes the `i`-th column from this matrix.
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#[inline]
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pub fn remove_column(self, i: usize) -> MatrixMN<N, R, DimDiff<C, U1>>
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where
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C: DimSub<U1>,
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DefaultAllocator: Reallocator<N, R, C, R, DimDiff<C, U1>>,
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{
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self.remove_fixed_columns::<U1>(i)
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}
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/// Removes all columns in `indices`
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#[cfg(any(feature = "std", feature = "alloc"))]
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pub fn remove_columns_at(self, indices: &[usize]) -> MatrixMN<N, R, Dynamic>
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where
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C: DimSub<Dynamic, Output = Dynamic>,
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DefaultAllocator: Reallocator<N, R, C, R, Dynamic>,
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{
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let mut m = self.into_owned();
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let (nrows, ncols) = m.data.shape();
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let mut offset: usize = 0;
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let mut target: usize = 0;
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while offset + target < ncols.value() {
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if indices.contains(&(target + offset)) {
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offset += 1;
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} else {
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unsafe {
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let ptr_source = m
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.data
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.ptr()
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.offset(((target + offset) * nrows.value()) as isize);
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let ptr_target = m.data.ptr_mut().offset((target * nrows.value()) as isize);
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ptr::copy(ptr_source, ptr_target, nrows.value());
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target += 1;
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}
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}
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}
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unsafe {
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Matrix::from_data(DefaultAllocator::reallocate_copy(
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nrows,
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ncols.sub(Dynamic::from_usize(offset)),
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m.data,
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))
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}
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}
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/// Removes all rows in `indices`
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#[cfg(any(feature = "std", feature = "alloc"))]
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pub fn remove_rows_at(self, indices: &[usize]) -> MatrixMN<N, Dynamic, C>
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where
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R: DimSub<Dynamic, Output = Dynamic>,
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DefaultAllocator: Reallocator<N, R, C, Dynamic, C>,
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{
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let mut m = self.into_owned();
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let (nrows, ncols) = m.data.shape();
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let mut offset: usize = 0;
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let mut target: usize = 0;
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while offset + target < nrows.value() * ncols.value() {
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if indices.contains(&((target + offset) % nrows.value())) {
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offset += 1;
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} else {
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unsafe {
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let ptr_source = m.data.ptr().offset((target + offset) as isize);
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let ptr_target = m.data.ptr_mut().offset(target as isize);
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ptr::copy(ptr_source, ptr_target, 1);
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target += 1;
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}
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}
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}
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|
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unsafe {
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Matrix::from_data(DefaultAllocator::reallocate_copy(
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nrows.sub(Dynamic::from_usize(offset / ncols.value())),
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ncols,
|
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m.data,
|
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))
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}
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}
|
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|
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/// Removes `D::dim()` consecutive columns from this matrix, starting with the `i`-th
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/// (included).
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#[inline]
|
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pub fn remove_fixed_columns<D>(self, i: usize) -> MatrixMN<N, R, DimDiff<C, D>>
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where
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D: DimName,
|
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C: DimSub<D>,
|
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DefaultAllocator: Reallocator<N, R, C, R, DimDiff<C, D>>,
|
||
{
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self.remove_columns_generic(i, D::name())
|
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}
|
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|
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/// Removes `n` consecutive columns from this matrix, starting with the `i`-th (included).
|
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#[inline]
|
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#[cfg(any(feature = "std", feature = "alloc"))]
|
||
pub fn remove_columns(self, i: usize, n: usize) -> MatrixMN<N, R, Dynamic>
|
||
where
|
||
C: DimSub<Dynamic, Output = Dynamic>,
|
||
DefaultAllocator: Reallocator<N, R, C, R, Dynamic>,
|
||
{
|
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self.remove_columns_generic(i, Dynamic::new(n))
|
||
}
|
||
|
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/// Removes `nremove.value()` columns from this matrix, starting with the `i`-th (included).
|
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///
|
||
/// This is the generic implementation of `.remove_columns(...)` and
|
||
/// `.remove_fixed_columns(...)` which have nicer API interfaces.
|
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#[inline]
|
||
pub fn remove_columns_generic<D>(self, i: usize, nremove: D) -> MatrixMN<N, R, DimDiff<C, D>>
|
||
where
|
||
D: Dim,
|
||
C: DimSub<D>,
|
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DefaultAllocator: Reallocator<N, R, C, R, DimDiff<C, D>>,
|
||
{
|
||
let mut m = self.into_owned();
|
||
let (nrows, ncols) = m.data.shape();
|
||
assert!(
|
||
i + nremove.value() <= ncols.value(),
|
||
"Column index out of range."
|
||
);
|
||
|
||
if nremove.value() != 0 && i + nremove.value() < ncols.value() {
|
||
// The first `deleted_i * nrows` are left untouched.
|
||
let copied_value_start = i + nremove.value();
|
||
|
||
unsafe {
|
||
let ptr_in = m
|
||
.data
|
||
.ptr()
|
||
.offset((copied_value_start * nrows.value()) as isize);
|
||
let ptr_out = m.data.ptr_mut().offset((i * nrows.value()) as isize);
|
||
|
||
ptr::copy(
|
||
ptr_in,
|
||
ptr_out,
|
||
(ncols.value() - copied_value_start) * nrows.value(),
|
||
);
|
||
}
|
||
}
|
||
|
||
unsafe {
|
||
Matrix::from_data(DefaultAllocator::reallocate_copy(
|
||
nrows,
|
||
ncols.sub(nremove),
|
||
m.data,
|
||
))
|
||
}
|
||
}
|
||
|
||
/*
|
||
*
|
||
* Row removal.
|
||
*
|
||
*/
|
||
/// Removes the `i`-th row from this matrix.
|
||
#[inline]
|
||
pub fn remove_row(self, i: usize) -> MatrixMN<N, DimDiff<R, U1>, C>
|
||
where
|
||
R: DimSub<U1>,
|
||
DefaultAllocator: Reallocator<N, R, C, DimDiff<R, U1>, C>,
|
||
{
|
||
self.remove_fixed_rows::<U1>(i)
|
||
}
|
||
|
||
/// Removes `D::dim()` consecutive rows from this matrix, starting with the `i`-th (included).
|
||
#[inline]
|
||
pub fn remove_fixed_rows<D>(self, i: usize) -> MatrixMN<N, DimDiff<R, D>, C>
|
||
where
|
||
D: DimName,
|
||
R: DimSub<D>,
|
||
DefaultAllocator: Reallocator<N, R, C, DimDiff<R, D>, C>,
|
||
{
|
||
self.remove_rows_generic(i, D::name())
|
||
}
|
||
|
||
/// Removes `n` consecutive rows from this matrix, starting with the `i`-th (included).
|
||
#[inline]
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
pub fn remove_rows(self, i: usize, n: usize) -> MatrixMN<N, Dynamic, C>
|
||
where
|
||
R: DimSub<Dynamic, Output = Dynamic>,
|
||
DefaultAllocator: Reallocator<N, R, C, Dynamic, C>,
|
||
{
|
||
self.remove_rows_generic(i, Dynamic::new(n))
|
||
}
|
||
|
||
/// Removes `nremove.value()` rows from this matrix, starting with the `i`-th (included).
|
||
///
|
||
/// This is the generic implementation of `.remove_rows(...)` and `.remove_fixed_rows(...)`
|
||
/// which have nicer API interfaces.
|
||
#[inline]
|
||
pub fn remove_rows_generic<D>(self, i: usize, nremove: D) -> MatrixMN<N, DimDiff<R, D>, C>
|
||
where
|
||
D: Dim,
|
||
R: DimSub<D>,
|
||
DefaultAllocator: Reallocator<N, R, C, DimDiff<R, D>, C>,
|
||
{
|
||
let mut m = self.into_owned();
|
||
let (nrows, ncols) = m.data.shape();
|
||
assert!(
|
||
i + nremove.value() <= nrows.value(),
|
||
"Row index out of range."
|
||
);
|
||
|
||
if nremove.value() != 0 {
|
||
unsafe {
|
||
compress_rows(
|
||
&mut m.data.as_mut_slice(),
|
||
nrows.value(),
|
||
ncols.value(),
|
||
i,
|
||
nremove.value(),
|
||
);
|
||
}
|
||
}
|
||
|
||
unsafe {
|
||
Matrix::from_data(DefaultAllocator::reallocate_copy(
|
||
nrows.sub(nremove),
|
||
ncols,
|
||
m.data,
|
||
))
|
||
}
|
||
}
|
||
|
||
/*
|
||
*
|
||
* Columns insertion.
|
||
*
|
||
*/
|
||
/// Inserts a column filled with `val` at the `i-th` position.
|
||
#[inline]
|
||
pub fn insert_column(self, i: usize, val: N) -> MatrixMN<N, R, DimSum<C, U1>>
|
||
where
|
||
C: DimAdd<U1>,
|
||
DefaultAllocator: Reallocator<N, R, C, R, DimSum<C, U1>>,
|
||
{
|
||
self.insert_fixed_columns::<U1>(i, val)
|
||
}
|
||
|
||
/// Inserts `D::dim()` columns filled with `val` starting at the `i-th` position.
|
||
#[inline]
|
||
pub fn insert_fixed_columns<D>(self, i: usize, val: N) -> MatrixMN<N, R, DimSum<C, D>>
|
||
where
|
||
D: DimName,
|
||
C: DimAdd<D>,
|
||
DefaultAllocator: Reallocator<N, R, C, R, DimSum<C, D>>,
|
||
{
|
||
let mut res = unsafe { self.insert_columns_generic_uninitialized(i, D::name()) };
|
||
res.fixed_columns_mut::<D>(i).fill(val);
|
||
res
|
||
}
|
||
|
||
/// Inserts `n` columns filled with `val` starting at the `i-th` position.
|
||
#[inline]
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
pub fn insert_columns(self, i: usize, n: usize, val: N) -> MatrixMN<N, R, Dynamic>
|
||
where
|
||
C: DimAdd<Dynamic, Output = Dynamic>,
|
||
DefaultAllocator: Reallocator<N, R, C, R, Dynamic>,
|
||
{
|
||
let mut res = unsafe { self.insert_columns_generic_uninitialized(i, Dynamic::new(n)) };
|
||
res.columns_mut(i, n).fill(val);
|
||
res
|
||
}
|
||
|
||
/// Inserts `ninsert.value()` columns starting at the `i-th` place of this matrix.
|
||
///
|
||
/// The added column values are not initialized.
|
||
#[inline]
|
||
pub unsafe fn insert_columns_generic_uninitialized<D>(
|
||
self,
|
||
i: usize,
|
||
ninsert: D,
|
||
) -> MatrixMN<N, R, DimSum<C, D>>
|
||
where
|
||
D: Dim,
|
||
C: DimAdd<D>,
|
||
DefaultAllocator: Reallocator<N, R, C, R, DimSum<C, D>>,
|
||
{
|
||
let m = self.into_owned();
|
||
let (nrows, ncols) = m.data.shape();
|
||
let mut res = Matrix::from_data(DefaultAllocator::reallocate_copy(
|
||
nrows,
|
||
ncols.add(ninsert),
|
||
m.data,
|
||
));
|
||
|
||
assert!(i <= ncols.value(), "Column insertion index out of range.");
|
||
|
||
if ninsert.value() != 0 && i != ncols.value() {
|
||
let ptr_in = res.data.ptr().offset((i * nrows.value()) as isize);
|
||
let ptr_out = res
|
||
.data
|
||
.ptr_mut()
|
||
.offset(((i + ninsert.value()) * nrows.value()) as isize);
|
||
|
||
ptr::copy(ptr_in, ptr_out, (ncols.value() - i) * nrows.value())
|
||
}
|
||
|
||
res
|
||
}
|
||
|
||
/*
|
||
*
|
||
* Rows insertion.
|
||
*
|
||
*/
|
||
/// Inserts a row filled with `val` at the `i-th` position.
|
||
#[inline]
|
||
pub fn insert_row(self, i: usize, val: N) -> MatrixMN<N, DimSum<R, U1>, C>
|
||
where
|
||
R: DimAdd<U1>,
|
||
DefaultAllocator: Reallocator<N, R, C, DimSum<R, U1>, C>,
|
||
{
|
||
self.insert_fixed_rows::<U1>(i, val)
|
||
}
|
||
|
||
/// Inserts `D::dim()` rows filled with `val` starting at the `i-th` position.
|
||
#[inline]
|
||
pub fn insert_fixed_rows<D>(self, i: usize, val: N) -> MatrixMN<N, DimSum<R, D>, C>
|
||
where
|
||
D: DimName,
|
||
R: DimAdd<D>,
|
||
DefaultAllocator: Reallocator<N, R, C, DimSum<R, D>, C>,
|
||
{
|
||
let mut res = unsafe { self.insert_rows_generic_uninitialized(i, D::name()) };
|
||
res.fixed_rows_mut::<D>(i).fill(val);
|
||
res
|
||
}
|
||
|
||
/// Inserts `n` rows filled with `val` starting at the `i-th` position.
|
||
#[inline]
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
pub fn insert_rows(self, i: usize, n: usize, val: N) -> MatrixMN<N, Dynamic, C>
|
||
where
|
||
R: DimAdd<Dynamic, Output = Dynamic>,
|
||
DefaultAllocator: Reallocator<N, R, C, Dynamic, C>,
|
||
{
|
||
let mut res = unsafe { self.insert_rows_generic_uninitialized(i, Dynamic::new(n)) };
|
||
res.rows_mut(i, n).fill(val);
|
||
res
|
||
}
|
||
|
||
/// Inserts `ninsert.value()` rows at the `i-th` place of this matrix.
|
||
///
|
||
/// The added rows values are not initialized.
|
||
/// This is the generic implementation of `.insert_rows(...)` and
|
||
/// `.insert_fixed_rows(...)` which have nicer API interfaces.
|
||
#[inline]
|
||
pub unsafe fn insert_rows_generic_uninitialized<D>(
|
||
self,
|
||
i: usize,
|
||
ninsert: D,
|
||
) -> MatrixMN<N, DimSum<R, D>, C>
|
||
where
|
||
D: Dim,
|
||
R: DimAdd<D>,
|
||
DefaultAllocator: Reallocator<N, R, C, DimSum<R, D>, C>,
|
||
{
|
||
let m = self.into_owned();
|
||
let (nrows, ncols) = m.data.shape();
|
||
let mut res = Matrix::from_data(DefaultAllocator::reallocate_copy(
|
||
nrows.add(ninsert),
|
||
ncols,
|
||
m.data,
|
||
));
|
||
|
||
assert!(i <= nrows.value(), "Row insertion index out of range.");
|
||
|
||
if ninsert.value() != 0 {
|
||
extend_rows(
|
||
&mut res.data.as_mut_slice(),
|
||
nrows.value(),
|
||
ncols.value(),
|
||
i,
|
||
ninsert.value(),
|
||
);
|
||
}
|
||
|
||
res
|
||
}
|
||
|
||
/*
|
||
*
|
||
* Resizing.
|
||
*
|
||
*/
|
||
|
||
/// Resizes this matrix so that it contains `new_nrows` rows and `new_ncols` columns.
|
||
///
|
||
/// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
|
||
/// rows and/or columns than `self`, then the extra rows or columns are filled with `val`.
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
pub fn resize(self, new_nrows: usize, new_ncols: usize, val: N) -> DMatrix<N>
|
||
where
|
||
DefaultAllocator: Reallocator<N, R, C, Dynamic, Dynamic>,
|
||
{
|
||
self.resize_generic(Dynamic::new(new_nrows), Dynamic::new(new_ncols), val)
|
||
}
|
||
|
||
/// Resizes this matrix vertically, i.e., so that it contains `new_nrows` rows while keeping the same number of columns.
|
||
///
|
||
/// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
|
||
/// rows than `self`, then the extra rows are filled with `val`.
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
pub fn resize_vertically(self, new_nrows: usize, val: N) -> MatrixMN<N, Dynamic, C>
|
||
where
|
||
DefaultAllocator: Reallocator<N, R, C, Dynamic, C>,
|
||
{
|
||
let ncols = self.data.shape().1;
|
||
self.resize_generic(Dynamic::new(new_nrows), ncols, val)
|
||
}
|
||
|
||
/// Resizes this matrix horizontally, i.e., so that it contains `new_ncolumns` columns while keeping the same number of columns.
|
||
///
|
||
/// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
|
||
/// columns than `self`, then the extra columns are filled with `val`.
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
pub fn resize_horizontally(self, new_ncols: usize, val: N) -> MatrixMN<N, R, Dynamic>
|
||
where
|
||
DefaultAllocator: Reallocator<N, R, C, R, Dynamic>,
|
||
{
|
||
let nrows = self.data.shape().0;
|
||
self.resize_generic(nrows, Dynamic::new(new_ncols), val)
|
||
}
|
||
|
||
/// Resizes this matrix so that it contains `R2::value()` rows and `C2::value()` columns.
|
||
///
|
||
/// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
|
||
/// rows and/or columns than `self`, then the extra rows or columns are filled with `val`.
|
||
pub fn fixed_resize<R2: DimName, C2: DimName>(self, val: N) -> MatrixMN<N, R2, C2>
|
||
where
|
||
DefaultAllocator: Reallocator<N, R, C, R2, C2>,
|
||
{
|
||
self.resize_generic(R2::name(), C2::name(), val)
|
||
}
|
||
|
||
/// Resizes `self` such that it has dimensions `new_nrows × new_ncols`.
|
||
///
|
||
/// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
|
||
/// rows and/or columns than `self`, then the extra rows or columns are filled with `val`.
|
||
#[inline]
|
||
pub fn resize_generic<R2: Dim, C2: Dim>(
|
||
self,
|
||
new_nrows: R2,
|
||
new_ncols: C2,
|
||
val: N,
|
||
) -> MatrixMN<N, R2, C2>
|
||
where
|
||
DefaultAllocator: Reallocator<N, R, C, R2, C2>,
|
||
{
|
||
let (nrows, ncols) = self.shape();
|
||
let mut data = self.data.into_owned();
|
||
|
||
if new_nrows.value() == nrows {
|
||
let res = unsafe { DefaultAllocator::reallocate_copy(new_nrows, new_ncols, data) };
|
||
let mut res = Matrix::from_data(res);
|
||
if new_ncols.value() > ncols {
|
||
res.columns_range_mut(ncols..).fill(val);
|
||
}
|
||
|
||
res
|
||
} else {
|
||
let mut res;
|
||
|
||
unsafe {
|
||
if new_nrows.value() < nrows {
|
||
compress_rows(
|
||
&mut data.as_mut_slice(),
|
||
nrows,
|
||
ncols,
|
||
new_nrows.value(),
|
||
nrows - new_nrows.value(),
|
||
);
|
||
res = Matrix::from_data(DefaultAllocator::reallocate_copy(
|
||
new_nrows, new_ncols, data,
|
||
));
|
||
} else {
|
||
res = Matrix::from_data(DefaultAllocator::reallocate_copy(
|
||
new_nrows, new_ncols, data,
|
||
));
|
||
extend_rows(
|
||
&mut res.data.as_mut_slice(),
|
||
nrows,
|
||
new_ncols.value(),
|
||
nrows,
|
||
new_nrows.value() - nrows,
|
||
);
|
||
}
|
||
}
|
||
|
||
if new_ncols.value() > ncols {
|
||
res.columns_range_mut(ncols..).fill(val.inlined_clone());
|
||
}
|
||
|
||
if new_nrows.value() > nrows {
|
||
res.slice_range_mut(nrows.., ..cmp::min(ncols, new_ncols.value()))
|
||
.fill(val);
|
||
}
|
||
|
||
res
|
||
}
|
||
}
|
||
}
|
||
|
||
impl<N, R, C, S> Matrix<N, R, C, S>
|
||
where
|
||
N: Scalar,
|
||
R: Dim,
|
||
C: Dim,
|
||
{
|
||
/// Reshapes `self` in-place such that it has dimensions `new_nrows × new_ncols`.
|
||
///
|
||
/// The values are not copied or moved. This function will panic if dynamic sizes are provided
|
||
/// and not compatible.
|
||
pub fn reshape_generic<R2, C2>(
|
||
self,
|
||
new_nrows: R2,
|
||
new_ncols: C2,
|
||
) -> Matrix<N, R2, C2, S::Output>
|
||
where
|
||
R2: Dim,
|
||
C2: Dim,
|
||
S: ReshapableStorage<N, R, C, R2, C2>,
|
||
{
|
||
let data = self.data.reshape_generic(new_nrows, new_ncols);
|
||
Matrix::from_data(data)
|
||
}
|
||
}
|
||
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
impl<N: Scalar> DMatrix<N> {
|
||
/// Resizes this matrix in-place.
|
||
///
|
||
/// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
|
||
/// rows and/or columns than `self`, then the extra rows or columns are filled with `val`.
|
||
///
|
||
/// Defined only for owned fully-dynamic matrices, i.e., `DMatrix`.
|
||
pub fn resize_mut(&mut self, new_nrows: usize, new_ncols: usize, val: N)
|
||
where
|
||
DefaultAllocator: Reallocator<N, Dynamic, Dynamic, Dynamic, Dynamic>,
|
||
{
|
||
let placeholder = unsafe { Self::new_uninitialized(0, 0) };
|
||
let old = mem::replace(self, placeholder);
|
||
let new = old.resize(new_nrows, new_ncols, val);
|
||
let _ = mem::replace(self, new);
|
||
}
|
||
}
|
||
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
impl<N: Scalar, C: Dim> MatrixMN<N, Dynamic, C>
|
||
where
|
||
DefaultAllocator: Allocator<N, Dynamic, C>,
|
||
{
|
||
/// Changes the number of rows of this matrix in-place.
|
||
///
|
||
/// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
|
||
/// rows than `self`, then the extra rows are filled with `val`.
|
||
///
|
||
/// Defined only for owned matrices with a dynamic number of rows (for example, `DVector`).
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
pub fn resize_vertically_mut(&mut self, new_nrows: usize, val: N)
|
||
where
|
||
DefaultAllocator: Reallocator<N, Dynamic, C, Dynamic, C>,
|
||
{
|
||
let placeholder =
|
||
unsafe { Self::new_uninitialized_generic(Dynamic::new(0), self.data.shape().1) };
|
||
let old = mem::replace(self, placeholder);
|
||
let new = old.resize_vertically(new_nrows, val);
|
||
let _ = mem::replace(self, new);
|
||
}
|
||
}
|
||
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
impl<N: Scalar, R: Dim> MatrixMN<N, R, Dynamic>
|
||
where
|
||
DefaultAllocator: Allocator<N, R, Dynamic>,
|
||
{
|
||
/// Changes the number of column of this matrix in-place.
|
||
///
|
||
/// The values are copied such that `self[(i, j)] == result[(i, j)]`. If the result has more
|
||
/// columns than `self`, then the extra columns are filled with `val`.
|
||
///
|
||
/// Defined only for owned matrices with a dynamic number of columns (for example, `DVector`).
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
pub fn resize_horizontally_mut(&mut self, new_ncols: usize, val: N)
|
||
where
|
||
DefaultAllocator: Reallocator<N, R, Dynamic, R, Dynamic>,
|
||
{
|
||
let placeholder =
|
||
unsafe { Self::new_uninitialized_generic(self.data.shape().0, Dynamic::new(0)) };
|
||
let old = mem::replace(self, placeholder);
|
||
let new = old.resize_horizontally(new_ncols, val);
|
||
let _ = mem::replace(self, new);
|
||
}
|
||
}
|
||
|
||
unsafe fn compress_rows<N: Scalar>(
|
||
data: &mut [N],
|
||
nrows: usize,
|
||
ncols: usize,
|
||
i: usize,
|
||
nremove: usize,
|
||
) {
|
||
let new_nrows = nrows - nremove;
|
||
|
||
if new_nrows == 0 || ncols == 0 {
|
||
return; // Nothing to do as the output matrix is empty.
|
||
}
|
||
|
||
let ptr_in = data.as_ptr();
|
||
let ptr_out = data.as_mut_ptr();
|
||
|
||
let mut curr_i = i;
|
||
|
||
for k in 0..ncols - 1 {
|
||
ptr::copy(
|
||
ptr_in.offset((curr_i + (k + 1) * nremove) as isize),
|
||
ptr_out.offset(curr_i as isize),
|
||
new_nrows,
|
||
);
|
||
|
||
curr_i += new_nrows;
|
||
}
|
||
|
||
// Deal with the last column from which less values have to be copied.
|
||
let remaining_len = nrows - i - nremove;
|
||
ptr::copy(
|
||
ptr_in.offset((nrows * ncols - remaining_len) as isize),
|
||
ptr_out.offset(curr_i as isize),
|
||
remaining_len,
|
||
);
|
||
}
|
||
|
||
// Moves entries of a matrix buffer to make place for `ninsert` emty rows starting at the `i-th` row index.
|
||
// The `data` buffer is assumed to contained at least `(nrows + ninsert) * ncols` elements.
|
||
unsafe fn extend_rows<N: Scalar>(
|
||
data: &mut [N],
|
||
nrows: usize,
|
||
ncols: usize,
|
||
i: usize,
|
||
ninsert: usize,
|
||
) {
|
||
let new_nrows = nrows + ninsert;
|
||
|
||
if new_nrows == 0 || ncols == 0 {
|
||
return; // Nothing to do as the output matrix is empty.
|
||
}
|
||
|
||
let ptr_in = data.as_ptr();
|
||
let ptr_out = data.as_mut_ptr();
|
||
|
||
let remaining_len = nrows - i;
|
||
let mut curr_i = new_nrows * ncols - remaining_len;
|
||
|
||
// Deal with the last column from which less values have to be copied.
|
||
ptr::copy(
|
||
ptr_in.offset((nrows * ncols - remaining_len) as isize),
|
||
ptr_out.offset(curr_i as isize),
|
||
remaining_len,
|
||
);
|
||
|
||
for k in (0..ncols - 1).rev() {
|
||
curr_i -= new_nrows;
|
||
|
||
ptr::copy(
|
||
ptr_in.offset((k * nrows + i) as isize),
|
||
ptr_out.offset(curr_i as isize),
|
||
nrows,
|
||
);
|
||
}
|
||
}
|
||
|
||
/// Extend the number of columns of the `Matrix` with elements from
|
||
/// a given iterator.
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
impl<N, R, S> Extend<N> for Matrix<N, R, Dynamic, S>
|
||
where
|
||
N: Scalar,
|
||
R: Dim,
|
||
S: Extend<N>,
|
||
{
|
||
/// Extend the number of columns of the `Matrix` with elements
|
||
/// from the given iterator.
|
||
///
|
||
/// # Example
|
||
/// ```
|
||
/// # use nalgebra::{DMatrix, Dynamic, Matrix, MatrixMN, Matrix3};
|
||
///
|
||
/// let data = vec![0, 1, 2, // column 1
|
||
/// 3, 4, 5]; // column 2
|
||
///
|
||
/// let mut matrix = DMatrix::from_vec(3, 2, data);
|
||
///
|
||
/// matrix.extend(vec![6, 7, 8]); // column 3
|
||
///
|
||
/// assert!(matrix.eq(&Matrix3::new(0, 3, 6,
|
||
/// 1, 4, 7,
|
||
/// 2, 5, 8)));
|
||
/// ```
|
||
///
|
||
/// # Panics
|
||
/// This function panics if the number of elements yielded by the
|
||
/// given iterator is not a multiple of the number of rows of the
|
||
/// `Matrix`.
|
||
///
|
||
/// ```should_panic
|
||
/// # use nalgebra::{DMatrix, Dynamic, MatrixMN};
|
||
/// let data = vec![0, 1, 2, // column 1
|
||
/// 3, 4, 5]; // column 2
|
||
///
|
||
/// let mut matrix = DMatrix::from_vec(3, 2, data);
|
||
///
|
||
/// // The following panics because the vec length is not a multiple of 3.
|
||
/// matrix.extend(vec![6, 7, 8, 9]);
|
||
/// ```
|
||
fn extend<I: IntoIterator<Item = N>>(&mut self, iter: I) {
|
||
self.data.extend(iter);
|
||
}
|
||
}
|
||
|
||
/// Extend the number of rows of the `Vector` with elements from
|
||
/// a given iterator.
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
impl<N, S> Extend<N> for Matrix<N, Dynamic, U1, S>
|
||
where
|
||
N: Scalar,
|
||
S: Extend<N>,
|
||
{
|
||
/// Extend the number of rows of a `Vector` with elements
|
||
/// from the given iterator.
|
||
///
|
||
/// # Example
|
||
/// ```
|
||
/// # use nalgebra::DVector;
|
||
/// let mut vector = DVector::from_vec(vec![0, 1, 2]);
|
||
/// vector.extend(vec![3, 4, 5]);
|
||
/// assert!(vector.eq(&DVector::from_vec(vec![0, 1, 2, 3, 4, 5])));
|
||
/// ```
|
||
fn extend<I: IntoIterator<Item = N>>(&mut self, iter: I) {
|
||
self.data.extend(iter);
|
||
}
|
||
}
|
||
|
||
#[cfg(any(feature = "std", feature = "alloc"))]
|
||
impl<N, R, S, RV, SV> Extend<Vector<N, RV, SV>> for Matrix<N, R, Dynamic, S>
|
||
where
|
||
N: Scalar,
|
||
R: Dim,
|
||
S: Extend<Vector<N, RV, SV>>,
|
||
RV: Dim,
|
||
SV: Storage<N, RV>,
|
||
ShapeConstraint: SameNumberOfRows<R, RV>,
|
||
{
|
||
/// Extends the number of columns of a `Matrix` with `Vector`s
|
||
/// from a given iterator.
|
||
///
|
||
/// # Example
|
||
/// ```
|
||
/// # use nalgebra::{DMatrix, Vector3, Matrix3x4};
|
||
///
|
||
/// let data = vec![0, 1, 2, // column 1
|
||
/// 3, 4, 5]; // column 2
|
||
///
|
||
/// let mut matrix = DMatrix::from_vec(3, 2, data);
|
||
///
|
||
/// matrix.extend(
|
||
/// vec![Vector3::new(6, 7, 8), // column 3
|
||
/// Vector3::new(9, 10, 11)]); // column 4
|
||
///
|
||
/// assert!(matrix.eq(&Matrix3x4::new(0, 3, 6, 9,
|
||
/// 1, 4, 7, 10,
|
||
/// 2, 5, 8, 11)));
|
||
/// ```
|
||
///
|
||
/// # Panics
|
||
/// This function panics if the dimension of each `Vector` yielded
|
||
/// by the given iterator is not equal to the number of rows of
|
||
/// this `Matrix`.
|
||
///
|
||
/// ```should_panic
|
||
/// # use nalgebra::{DMatrix, Vector2, Matrix3x4};
|
||
/// let mut matrix =
|
||
/// DMatrix::from_vec(3, 2,
|
||
/// vec![0, 1, 2, // column 1
|
||
/// 3, 4, 5]); // column 2
|
||
///
|
||
/// // The following panics because this matrix can only be extended with 3-dimensional vectors.
|
||
/// matrix.extend(
|
||
/// vec![Vector2::new(6, 7)]); // too few dimensions!
|
||
/// ```
|
||
///
|
||
/// ```should_panic
|
||
/// # use nalgebra::{DMatrix, Vector4, Matrix3x4};
|
||
/// let mut matrix =
|
||
/// DMatrix::from_vec(3, 2,
|
||
/// vec![0, 1, 2, // column 1
|
||
/// 3, 4, 5]); // column 2
|
||
///
|
||
/// // The following panics because this matrix can only be extended with 3-dimensional vectors.
|
||
/// matrix.extend(
|
||
/// vec![Vector4::new(6, 7, 8, 9)]); // too few dimensions!
|
||
/// ```
|
||
fn extend<I: IntoIterator<Item = Vector<N, RV, SV>>>(&mut self, iter: I) {
|
||
self.data.extend(iter);
|
||
}
|
||
}
|