2018-02-02 19:26:35 +08:00
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use num::{One, Zero};
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2017-08-03 01:37:44 +08:00
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use std::cmp;
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2019-02-03 22:16:50 +08:00
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#[cfg(any(feature = "std", feature = "alloc"))]
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2018-12-09 19:22:10 +08:00
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use std::iter::ExactSizeIterator;
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2019-02-03 22:16:50 +08:00
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#[cfg(any(feature = "std", feature = "alloc"))]
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2019-01-29 19:03:48 +08:00
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use std::mem;
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2019-04-08 23:29:32 +08:00
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use std::ptr;
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2017-08-03 01:37:44 +08:00
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2019-03-23 21:29:07 +08:00
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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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2019-04-08 23:29:32 +08:00
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#[cfg(any(feature = "std", feature = "alloc"))]
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use crate::base::dimension::Dynamic;
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2019-03-23 21:29:07 +08:00
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use crate::base::dimension::{
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2019-02-03 22:16:50 +08:00
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Dim, DimAdd, DimDiff, DimMin, DimMinimum, DimName, DimSub, DimSum, U1,
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2018-05-19 23:15:15 +08:00
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};
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2019-03-23 21:29:07 +08:00
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use crate::base::storage::{Storage, StorageMut};
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2018-05-19 23:15:15 +08:00
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#[cfg(any(feature = "std", feature = "alloc"))]
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2019-03-23 21:29:07 +08:00
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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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2017-08-03 01:37:44 +08:00
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2019-12-06 06:54:17 +08:00
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impl<N: Scalar + Clone + Zero, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
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2017-08-03 01:37:44 +08:00
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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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2018-11-07 01:32:20 +08:00
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where DefaultAllocator: Allocator<N, R, C> {
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2017-08-03 01:37:44 +08:00
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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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2019-01-30 15:42:28 +08:00
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/// Extracts the lower triangular part of this matrix (including the diagonal).
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2017-08-03 01:37:44 +08:00
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#[inline]
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pub fn lower_triangle(&self) -> MatrixMN<N, R, C>
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2018-11-07 01:32:20 +08:00
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where DefaultAllocator: Allocator<N, R, C> {
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2017-08-03 01:37:44 +08:00
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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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2018-12-09 19:22:10 +08:00
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/// Creates a new matrix by extracting the given set of rows from `self`.
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2019-02-03 22:16:50 +08:00
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#[cfg(any(feature = "std", feature = "alloc"))]
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2018-12-09 23:56:27 +08:00
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pub fn select_rows<'a, I>(&self, irows: I) -> MatrixMN<N, Dynamic, C>
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2019-04-08 23:29:32 +08:00
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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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2019-02-03 15:33:07 +08:00
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let irows = irows.into_iter();
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2018-12-09 19:22:10 +08:00
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let ncols = self.data.shape().1;
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2019-04-08 23:29:32 +08:00
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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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2018-12-09 19:22:10 +08:00
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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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2018-12-09 23:56:27 +08:00
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assert!(*i < self.nrows(), "Row index out of bounds.")
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2018-12-09 19:22:10 +08:00
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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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2019-03-31 19:32:26 +08:00
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let src = self.column(j);
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2018-12-09 19:22:10 +08:00
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for (destination, source) in irows.clone().enumerate() {
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2019-12-06 06:54:17 +08:00
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unsafe { *res.vget_unchecked_mut(destination) = src.vget_unchecked(*source).inlined_clone() }
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2018-12-09 19:22:10 +08:00
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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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2019-02-03 22:16:50 +08:00
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#[cfg(any(feature = "std", feature = "alloc"))]
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2018-12-09 23:56:27 +08:00
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pub fn select_columns<'a, I>(&self, icols: I) -> MatrixMN<N, R, Dynamic>
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2019-04-08 23:29:32 +08:00
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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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2019-02-03 15:33:07 +08:00
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let icols = icols.into_iter();
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2018-12-09 19:22:10 +08:00
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let nrows = self.data.shape().0;
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2019-04-08 23:29:32 +08:00
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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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2018-12-09 19:22:10 +08:00
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for (destination, source) in icols.enumerate() {
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2018-12-09 23:56:27 +08:00
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res.column_mut(destination).copy_from(&self.column(*source))
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2018-12-09 19:22:10 +08:00
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}
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res
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}
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2017-08-03 01:37:44 +08:00
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}
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2019-12-06 06:54:17 +08:00
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impl<N: Scalar + Clone, R: Dim, C: Dim, S: StorageMut<N, R, C>> Matrix<N, R, C, S> {
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2017-08-03 01:37:44 +08:00
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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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2019-12-06 06:54:17 +08:00
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*e = val.inlined_clone()
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2017-08-03 01:37:44 +08:00
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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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2018-11-07 01:32:20 +08:00
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where N: Zero + One {
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2017-08-03 01:37:44 +08:00
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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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2018-02-02 19:26:35 +08:00
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for i in 0..n {
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2019-12-06 06:54:17 +08:00
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unsafe { *self.get_unchecked_mut((i, i)) = val.inlined_clone() }
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2017-08-03 01:37:44 +08:00
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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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2018-02-02 19:26:35 +08:00
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for j in 0..self.ncols() {
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2019-12-06 06:54:17 +08:00
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unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
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2017-08-03 01:37:44 +08:00
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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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2018-02-02 19:26:35 +08:00
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for i in 0..self.nrows() {
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2019-12-06 06:54:17 +08:00
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unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
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2017-08-03 01:37:44 +08:00
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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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2019-04-08 23:29:32 +08:00
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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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2018-02-02 19:26:35 +08:00
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{
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let (nrows, ncols) = self.shape();
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2017-08-03 01:37:44 +08:00
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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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2018-02-02 19:26:35 +08:00
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for i in 0..min_nrows_ncols {
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2019-12-06 06:54:17 +08:00
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unsafe { *self.get_unchecked_mut((i, i)) = diag.vget_unchecked(i).inlined_clone() }
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2017-08-03 01:37:44 +08:00
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}
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}
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2019-03-23 21:13:00 +08:00
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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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2017-08-15 23:04:17 +08:00
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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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2018-02-02 19:26:35 +08:00
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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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2017-08-15 23:04:17 +08:00
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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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2018-02-02 19:26:35 +08:00
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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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2017-08-15 23:04:17 +08:00
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self.column_mut(i).copy_from(column);
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}
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2017-08-03 01:37:44 +08:00
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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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2018-02-02 19:26:35 +08:00
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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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2019-12-06 06:54:17 +08:00
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unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
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2017-08-03 01:37:44 +08:00
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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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2018-02-02 19:26:35 +08:00
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for j in shift..self.ncols() {
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2017-08-03 01:37:44 +08:00
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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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2018-02-02 19:26:35 +08:00
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for i in 0..cmp::min(j + 1 - shift, self.nrows()) {
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2019-12-06 06:54:17 +08:00
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unsafe { *self.get_unchecked_mut((i, j)) = val.inlined_clone() }
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2017-08-03 01:37:44 +08:00
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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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2018-02-02 19:26:35 +08:00
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for i in 0..self.ncols() {
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2017-08-03 01:37:44 +08:00
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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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2018-02-02 19:26:35 +08:00
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for i in 0..self.nrows() {
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2017-08-03 01:37:44 +08:00
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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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|
|
|
2019-12-06 06:54:17 +08:00
|
|
|
|
impl<N: Scalar + Clone, D: Dim, S: StorageMut<N, D, D>> Matrix<N, D, D, S> {
|
2017-08-03 01:37:44 +08:00
|
|
|
|
/// Copies the upper-triangle of this matrix to its lower-triangular part.
|
|
|
|
|
///
|
|
|
|
|
/// This makes the matrix symmetric. Panics if the matrix is not square.
|
|
|
|
|
pub fn fill_lower_triangle_with_upper_triangle(&mut self) {
|
|
|
|
|
assert!(self.is_square(), "The input matrix should be square.");
|
|
|
|
|
|
|
|
|
|
let dim = self.nrows();
|
2018-02-02 19:26:35 +08:00
|
|
|
|
for j in 0..dim {
|
|
|
|
|
for i in j + 1..dim {
|
2017-08-03 01:37:44 +08:00
|
|
|
|
unsafe {
|
2019-12-06 06:54:17 +08:00
|
|
|
|
*self.get_unchecked_mut((i, j)) = self.get_unchecked((j, i)).inlined_clone();
|
2017-08-03 01:37:44 +08:00
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
/// Copies the upper-triangle of this matrix to its upper-triangular part.
|
|
|
|
|
///
|
|
|
|
|
/// This makes the matrix symmetric. Panics if the matrix is not square.
|
|
|
|
|
pub fn fill_upper_triangle_with_lower_triangle(&mut self) {
|
|
|
|
|
assert!(self.is_square(), "The input matrix should be square.");
|
|
|
|
|
|
2018-02-02 19:26:35 +08:00
|
|
|
|
for j in 1..self.ncols() {
|
|
|
|
|
for i in 0..j {
|
2017-08-03 01:37:44 +08:00
|
|
|
|
unsafe {
|
2019-12-06 06:54:17 +08:00
|
|
|
|
*self.get_unchecked_mut((i, j)) = self.get_unchecked((j, i)).inlined_clone();
|
2017-08-03 01:37:44 +08:00
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
/*
|
|
|
|
|
*
|
|
|
|
|
* FIXME: specialize all the following for slices.
|
|
|
|
|
*
|
|
|
|
|
*/
|
2019-12-06 06:54:17 +08:00
|
|
|
|
impl<N: Scalar + Clone, R: Dim, C: Dim, S: Storage<N, R, C>> Matrix<N, R, C, S> {
|
2017-08-03 01:37:44 +08:00
|
|
|
|
/*
|
|
|
|
|
*
|
|
|
|
|
* Column removal.
|
|
|
|
|
*
|
|
|
|
|
*/
|
|
|
|
|
/// Removes the `i`-th column from this matrix.
|
|
|
|
|
#[inline]
|
|
|
|
|
pub fn remove_column(self, i: usize) -> MatrixMN<N, R, DimDiff<C, U1>>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
C: DimSub<U1>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, R, DimDiff<C, U1>>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
self.remove_fixed_columns::<U1>(i)
|
|
|
|
|
}
|
|
|
|
|
|
2019-04-08 23:29:32 +08:00
|
|
|
|
/// Removes all columns in `indices`
|
2019-04-09 04:32:26 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2019-04-08 23:29:32 +08:00
|
|
|
|
pub fn remove_columns_at(self, indices: &[usize]) -> MatrixMN<N, R, Dynamic>
|
|
|
|
|
where
|
|
|
|
|
C: DimSub<Dynamic, Output = Dynamic>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, R, Dynamic>,
|
|
|
|
|
{
|
|
|
|
|
let mut m = self.into_owned();
|
|
|
|
|
let (nrows, ncols) = m.data.shape();
|
|
|
|
|
let mut offset: usize = 0;
|
|
|
|
|
let mut target: usize = 0;
|
|
|
|
|
while offset + target < ncols.value() {
|
2019-04-09 05:10:27 +08:00
|
|
|
|
if indices.contains(&(target + offset)) {
|
2019-04-08 23:29:32 +08:00
|
|
|
|
offset += 1;
|
|
|
|
|
} else {
|
|
|
|
|
unsafe {
|
|
|
|
|
let ptr_source = m
|
|
|
|
|
.data
|
|
|
|
|
.ptr()
|
|
|
|
|
.offset(((target + offset) * nrows.value()) as isize);
|
|
|
|
|
let ptr_target = m.data.ptr_mut().offset((target * nrows.value()) as isize);
|
|
|
|
|
|
|
|
|
|
ptr::copy(ptr_source, ptr_target, nrows.value());
|
|
|
|
|
target += 1;
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
unsafe {
|
|
|
|
|
Matrix::from_data(DefaultAllocator::reallocate_copy(
|
|
|
|
|
nrows,
|
2019-04-09 05:10:27 +08:00
|
|
|
|
ncols.sub(Dynamic::from_usize(offset)),
|
2019-04-08 23:29:32 +08:00
|
|
|
|
m.data,
|
|
|
|
|
))
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
2019-04-09 05:10:27 +08:00
|
|
|
|
/// Removes all rows in `indices`
|
2019-04-09 04:32:26 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2019-04-08 23:29:32 +08:00
|
|
|
|
pub fn remove_rows_at(self, indices: &[usize]) -> MatrixMN<N, Dynamic, C>
|
|
|
|
|
where
|
|
|
|
|
R: DimSub<Dynamic, Output = Dynamic>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, Dynamic, C>,
|
2019-04-09 05:10:27 +08:00
|
|
|
|
{
|
2019-04-08 23:29:32 +08:00
|
|
|
|
let mut m = self.into_owned();
|
|
|
|
|
let (nrows, ncols) = m.data.shape();
|
|
|
|
|
let mut offset: usize = 0;
|
|
|
|
|
let mut target: usize = 0;
|
|
|
|
|
while offset + target < nrows.value() * ncols.value() {
|
2019-04-09 05:10:27 +08:00
|
|
|
|
if indices.contains(&((target + offset) % nrows.value())) {
|
2019-04-08 23:29:32 +08:00
|
|
|
|
offset += 1;
|
|
|
|
|
} else {
|
|
|
|
|
unsafe {
|
|
|
|
|
let ptr_source = m.data.ptr().offset((target + offset) as isize);
|
|
|
|
|
let ptr_target = m.data.ptr_mut().offset(target as isize);
|
|
|
|
|
|
|
|
|
|
ptr::copy(ptr_source, ptr_target, 1);
|
|
|
|
|
target += 1;
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
unsafe {
|
|
|
|
|
Matrix::from_data(DefaultAllocator::reallocate_copy(
|
2019-04-09 05:10:27 +08:00
|
|
|
|
nrows.sub(Dynamic::from_usize(offset / ncols.value ())),
|
2019-04-08 23:29:32 +08:00
|
|
|
|
ncols,
|
|
|
|
|
m.data,
|
|
|
|
|
))
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
2017-08-14 01:53:04 +08:00
|
|
|
|
/// Removes `D::dim()` consecutive columns from this matrix, starting with the `i`-th
|
|
|
|
|
/// (included).
|
2017-08-03 01:37:44 +08:00
|
|
|
|
#[inline]
|
|
|
|
|
pub fn remove_fixed_columns<D>(self, i: usize) -> MatrixMN<N, R, DimDiff<C, D>>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
D: DimName,
|
|
|
|
|
C: DimSub<D>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, R, DimDiff<C, D>>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
self.remove_columns_generic(i, D::name())
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
/// Removes `n` consecutive columns from this matrix, starting with the `i`-th (included).
|
|
|
|
|
#[inline]
|
2019-02-03 22:16:50 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2017-08-03 01:37:44 +08:00
|
|
|
|
pub fn remove_columns(self, i: usize, n: usize) -> MatrixMN<N, R, Dynamic>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
C: DimSub<Dynamic, Output = Dynamic>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, R, Dynamic>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
self.remove_columns_generic(i, Dynamic::new(n))
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
/// Removes `nremove.value()` columns from this matrix, starting with the `i`-th (included).
|
|
|
|
|
///
|
|
|
|
|
/// This is the generic implementation of `.remove_columns(...)` and
|
|
|
|
|
/// `.remove_fixed_columns(...)` which have nicer API interfaces.
|
|
|
|
|
#[inline]
|
|
|
|
|
pub fn remove_columns_generic<D>(self, i: usize, nremove: D) -> MatrixMN<N, R, DimDiff<C, D>>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
D: Dim,
|
|
|
|
|
C: DimSub<D>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, R, DimDiff<C, D>>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
let mut m = self.into_owned();
|
|
|
|
|
let (nrows, ncols) = m.data.shape();
|
2018-02-02 19:26:35 +08:00
|
|
|
|
assert!(
|
|
|
|
|
i + nremove.value() <= ncols.value(),
|
|
|
|
|
"Column index out of range."
|
|
|
|
|
);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
|
|
|
|
|
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 {
|
2018-10-21 04:26:44 +08:00
|
|
|
|
let ptr_in = m
|
|
|
|
|
.data
|
2018-02-02 19:26:35 +08:00
|
|
|
|
.ptr()
|
|
|
|
|
.offset((copied_value_start * nrows.value()) as isize);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
let ptr_out = m.data.ptr_mut().offset((i * nrows.value()) as isize);
|
|
|
|
|
|
2018-02-02 19:26:35 +08:00
|
|
|
|
ptr::copy(
|
|
|
|
|
ptr_in,
|
|
|
|
|
ptr_out,
|
|
|
|
|
(ncols.value() - copied_value_start) * nrows.value(),
|
|
|
|
|
);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
unsafe {
|
2018-02-02 19:26:35 +08:00
|
|
|
|
Matrix::from_data(DefaultAllocator::reallocate_copy(
|
|
|
|
|
nrows,
|
|
|
|
|
ncols.sub(nremove),
|
|
|
|
|
m.data,
|
|
|
|
|
))
|
2017-08-03 01:37:44 +08:00
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
/*
|
|
|
|
|
*
|
|
|
|
|
* Row removal.
|
|
|
|
|
*
|
|
|
|
|
*/
|
|
|
|
|
/// Removes the `i`-th row from this matrix.
|
|
|
|
|
#[inline]
|
|
|
|
|
pub fn remove_row(self, i: usize) -> MatrixMN<N, DimDiff<R, U1>, C>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
R: DimSub<U1>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, DimDiff<R, U1>, C>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
self.remove_fixed_rows::<U1>(i)
|
|
|
|
|
}
|
|
|
|
|
|
2017-08-14 01:53:04 +08:00
|
|
|
|
/// Removes `D::dim()` consecutive rows from this matrix, starting with the `i`-th (included).
|
2017-08-03 01:37:44 +08:00
|
|
|
|
#[inline]
|
|
|
|
|
pub fn remove_fixed_rows<D>(self, i: usize) -> MatrixMN<N, DimDiff<R, D>, C>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
D: DimName,
|
|
|
|
|
R: DimSub<D>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, DimDiff<R, D>, C>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
self.remove_rows_generic(i, D::name())
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
/// Removes `n` consecutive rows from this matrix, starting with the `i`-th (included).
|
|
|
|
|
#[inline]
|
2019-02-03 22:16:50 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2017-08-03 01:37:44 +08:00
|
|
|
|
pub fn remove_rows(self, i: usize, n: usize) -> MatrixMN<N, Dynamic, C>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
R: DimSub<Dynamic, Output = Dynamic>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, Dynamic, C>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
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>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
D: Dim,
|
|
|
|
|
R: DimSub<D>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, DimDiff<R, D>, C>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
let mut m = self.into_owned();
|
|
|
|
|
let (nrows, ncols) = m.data.shape();
|
2018-02-02 19:26:35 +08:00
|
|
|
|
assert!(
|
|
|
|
|
i + nremove.value() <= nrows.value(),
|
|
|
|
|
"Row index out of range."
|
|
|
|
|
);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
|
|
|
|
|
if nremove.value() != 0 {
|
|
|
|
|
unsafe {
|
2018-02-02 19:26:35 +08:00
|
|
|
|
compress_rows(
|
|
|
|
|
&mut m.data.as_mut_slice(),
|
|
|
|
|
nrows.value(),
|
|
|
|
|
ncols.value(),
|
|
|
|
|
i,
|
|
|
|
|
nremove.value(),
|
|
|
|
|
);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
unsafe {
|
2018-02-02 19:26:35 +08:00
|
|
|
|
Matrix::from_data(DefaultAllocator::reallocate_copy(
|
|
|
|
|
nrows.sub(nremove),
|
|
|
|
|
ncols,
|
|
|
|
|
m.data,
|
|
|
|
|
))
|
2017-08-03 01:37:44 +08:00
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
/*
|
|
|
|
|
*
|
|
|
|
|
* 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>>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
C: DimAdd<U1>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, R, DimSum<C, U1>>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
self.insert_fixed_columns::<U1>(i, val)
|
|
|
|
|
}
|
|
|
|
|
|
2017-08-14 01:53:04 +08:00
|
|
|
|
/// Inserts `D::dim()` columns filled with `val` starting at the `i-th` position.
|
2017-08-03 01:37:44 +08:00
|
|
|
|
#[inline]
|
|
|
|
|
pub fn insert_fixed_columns<D>(self, i: usize, val: N) -> MatrixMN<N, R, DimSum<C, D>>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
D: DimName,
|
|
|
|
|
C: DimAdd<D>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, R, DimSum<C, D>>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
let mut res = unsafe { self.insert_columns_generic_uninitialized(i, D::name()) };
|
|
|
|
|
res.fixed_columns_mut::<D>(i).fill(val);
|
|
|
|
|
res
|
|
|
|
|
}
|
|
|
|
|
|
2017-08-14 01:53:04 +08:00
|
|
|
|
/// Inserts `n` columns filled with `val` starting at the `i-th` position.
|
2017-08-03 01:37:44 +08:00
|
|
|
|
#[inline]
|
2019-02-03 22:16:50 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2017-08-03 01:37:44 +08:00
|
|
|
|
pub fn insert_columns(self, i: usize, n: usize, val: N) -> MatrixMN<N, R, Dynamic>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
C: DimAdd<Dynamic, Output = Dynamic>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, R, Dynamic>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
let mut res = unsafe { self.insert_columns_generic_uninitialized(i, Dynamic::new(n)) };
|
|
|
|
|
res.columns_mut(i, n).fill(val);
|
|
|
|
|
res
|
|
|
|
|
}
|
|
|
|
|
|
2017-08-14 01:53:04 +08:00
|
|
|
|
/// Inserts `ninsert.value()` columns starting at the `i-th` place of this matrix.
|
2017-08-03 01:37:44 +08:00
|
|
|
|
///
|
|
|
|
|
/// The added column values are not initialized.
|
|
|
|
|
#[inline]
|
2018-02-02 19:26:35 +08:00
|
|
|
|
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>>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
let m = self.into_owned();
|
|
|
|
|
let (nrows, ncols) = m.data.shape();
|
2018-02-02 19:26:35 +08:00
|
|
|
|
let mut res = Matrix::from_data(DefaultAllocator::reallocate_copy(
|
|
|
|
|
nrows,
|
|
|
|
|
ncols.add(ninsert),
|
|
|
|
|
m.data,
|
|
|
|
|
));
|
2017-08-03 01:37:44 +08:00
|
|
|
|
|
|
|
|
|
assert!(i <= ncols.value(), "Column insertion index out of range.");
|
|
|
|
|
|
|
|
|
|
if ninsert.value() != 0 && i != ncols.value() {
|
2018-02-02 19:26:35 +08:00
|
|
|
|
let ptr_in = res.data.ptr().offset((i * nrows.value()) as isize);
|
2018-10-21 04:26:44 +08:00
|
|
|
|
let ptr_out = res
|
|
|
|
|
.data
|
2018-02-02 19:26:35 +08:00
|
|
|
|
.ptr_mut()
|
|
|
|
|
.offset(((i + ninsert.value()) * nrows.value()) as isize);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
|
|
|
|
|
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>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
R: DimAdd<U1>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, DimSum<R, U1>, C>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
self.insert_fixed_rows::<U1>(i, val)
|
|
|
|
|
}
|
|
|
|
|
|
2017-08-14 01:53:04 +08:00
|
|
|
|
/// Inserts `D::dim()` rows filled with `val` starting at the `i-th` position.
|
2017-08-03 01:37:44 +08:00
|
|
|
|
#[inline]
|
|
|
|
|
pub fn insert_fixed_rows<D>(self, i: usize, val: N) -> MatrixMN<N, DimSum<R, D>, C>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
D: DimName,
|
|
|
|
|
R: DimAdd<D>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, DimSum<R, D>, C>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
let mut res = unsafe { self.insert_rows_generic_uninitialized(i, D::name()) };
|
|
|
|
|
res.fixed_rows_mut::<D>(i).fill(val);
|
|
|
|
|
res
|
|
|
|
|
}
|
|
|
|
|
|
2017-08-14 01:53:04 +08:00
|
|
|
|
/// Inserts `n` rows filled with `val` starting at the `i-th` position.
|
2017-08-03 01:37:44 +08:00
|
|
|
|
#[inline]
|
2019-02-03 22:16:50 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2017-08-03 01:37:44 +08:00
|
|
|
|
pub fn insert_rows(self, i: usize, n: usize, val: N) -> MatrixMN<N, Dynamic, C>
|
2018-02-02 19:26:35 +08:00
|
|
|
|
where
|
|
|
|
|
R: DimAdd<Dynamic, Output = Dynamic>,
|
|
|
|
|
DefaultAllocator: Reallocator<N, R, C, Dynamic, C>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
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.
|
2017-08-14 01:53:04 +08:00
|
|
|
|
/// This is the generic implementation of `.insert_rows(...)` and
|
|
|
|
|
/// `.insert_fixed_rows(...)` which have nicer API interfaces.
|
2017-08-03 01:37:44 +08:00
|
|
|
|
#[inline]
|
2018-02-02 19:26:35 +08:00
|
|
|
|
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>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
let m = self.into_owned();
|
|
|
|
|
let (nrows, ncols) = m.data.shape();
|
2018-02-02 19:26:35 +08:00
|
|
|
|
let mut res = Matrix::from_data(DefaultAllocator::reallocate_copy(
|
|
|
|
|
nrows.add(ninsert),
|
|
|
|
|
ncols,
|
|
|
|
|
m.data,
|
|
|
|
|
));
|
2017-08-03 01:37:44 +08:00
|
|
|
|
|
|
|
|
|
assert!(i <= nrows.value(), "Row insertion index out of range.");
|
|
|
|
|
|
|
|
|
|
if ninsert.value() != 0 {
|
2018-02-02 19:26:35 +08:00
|
|
|
|
extend_rows(
|
|
|
|
|
&mut res.data.as_mut_slice(),
|
|
|
|
|
nrows.value(),
|
|
|
|
|
ncols.value(),
|
|
|
|
|
i,
|
|
|
|
|
ninsert.value(),
|
|
|
|
|
);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
res
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
/*
|
|
|
|
|
*
|
|
|
|
|
* Resizing.
|
|
|
|
|
*
|
|
|
|
|
*/
|
|
|
|
|
|
2017-08-14 01:52:57 +08:00
|
|
|
|
/// 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`.
|
2018-05-19 23:15:15 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2017-08-03 01:37:44 +08:00
|
|
|
|
pub fn resize(self, new_nrows: usize, new_ncols: usize, val: N) -> DMatrix<N>
|
2018-11-07 01:32:20 +08:00
|
|
|
|
where DefaultAllocator: Reallocator<N, R, C, Dynamic, Dynamic> {
|
2017-08-03 01:37:44 +08:00
|
|
|
|
self.resize_generic(Dynamic::new(new_nrows), Dynamic::new(new_ncols), val)
|
|
|
|
|
}
|
|
|
|
|
|
2019-01-29 19:03:48 +08:00
|
|
|
|
/// 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>
|
2019-04-08 23:29:32 +08:00
|
|
|
|
where DefaultAllocator: Reallocator<N, R, C, Dynamic, C> {
|
2019-01-29 19:03:48 +08:00
|
|
|
|
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>
|
2019-04-08 23:29:32 +08:00
|
|
|
|
where DefaultAllocator: Reallocator<N, R, C, R, Dynamic> {
|
2019-01-29 19:03:48 +08:00
|
|
|
|
let nrows = self.data.shape().0;
|
|
|
|
|
self.resize_generic(nrows, Dynamic::new(new_ncols), val)
|
|
|
|
|
}
|
|
|
|
|
|
2017-08-14 01:52:57 +08:00
|
|
|
|
/// 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`.
|
2017-08-03 01:37:44 +08:00
|
|
|
|
pub fn fixed_resize<R2: DimName, C2: DimName>(self, val: N) -> MatrixMN<N, R2, C2>
|
2018-11-07 01:32:20 +08:00
|
|
|
|
where DefaultAllocator: Reallocator<N, R, C, R2, C2> {
|
2017-08-03 01:37:44 +08:00
|
|
|
|
self.resize_generic(R2::name(), C2::name(), val)
|
|
|
|
|
}
|
|
|
|
|
|
2017-08-14 01:52:57 +08:00
|
|
|
|
/// Resizes `self` such that it has dimensions `new_nrows × now_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`.
|
2017-08-03 01:37:44 +08:00
|
|
|
|
#[inline]
|
2018-02-02 19:26:35 +08:00
|
|
|
|
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>,
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
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) };
|
2018-05-19 23:15:15 +08:00
|
|
|
|
let mut res = Matrix::from_data(res);
|
2018-02-03 17:46:04 +08:00
|
|
|
|
if new_ncols.value() > ncols {
|
|
|
|
|
res.columns_range_mut(ncols..).fill(val);
|
|
|
|
|
}
|
2017-08-03 01:37:44 +08:00
|
|
|
|
|
2018-02-03 17:46:04 +08:00
|
|
|
|
res
|
2018-02-02 19:26:35 +08:00
|
|
|
|
} else {
|
2017-08-03 01:37:44 +08:00
|
|
|
|
let mut res;
|
|
|
|
|
|
|
|
|
|
unsafe {
|
|
|
|
|
if new_nrows.value() < nrows {
|
2018-02-02 19:26:35 +08:00
|
|
|
|
compress_rows(
|
|
|
|
|
&mut data.as_mut_slice(),
|
|
|
|
|
nrows,
|
|
|
|
|
ncols,
|
|
|
|
|
new_nrows.value(),
|
|
|
|
|
nrows - new_nrows.value(),
|
|
|
|
|
);
|
|
|
|
|
res = Matrix::from_data(DefaultAllocator::reallocate_copy(
|
2018-05-19 23:15:15 +08:00
|
|
|
|
new_nrows, new_ncols, data,
|
2018-02-02 19:26:35 +08:00
|
|
|
|
));
|
|
|
|
|
} else {
|
|
|
|
|
res = Matrix::from_data(DefaultAllocator::reallocate_copy(
|
2018-05-19 23:15:15 +08:00
|
|
|
|
new_nrows, new_ncols, data,
|
2018-02-02 19:26:35 +08:00
|
|
|
|
));
|
|
|
|
|
extend_rows(
|
|
|
|
|
&mut res.data.as_mut_slice(),
|
|
|
|
|
nrows,
|
2018-02-03 17:46:04 +08:00
|
|
|
|
new_ncols.value(),
|
2018-02-02 19:26:35 +08:00
|
|
|
|
nrows,
|
|
|
|
|
new_nrows.value() - nrows,
|
|
|
|
|
);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
if new_ncols.value() > ncols {
|
2019-12-06 06:54:17 +08:00
|
|
|
|
res.columns_range_mut(ncols..).fill(val.inlined_clone());
|
2017-08-03 01:37:44 +08:00
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
if new_nrows.value() > nrows {
|
2018-02-02 19:26:35 +08:00
|
|
|
|
res.slice_range_mut(nrows.., ..cmp::min(ncols, new_ncols.value()))
|
|
|
|
|
.fill(val);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
res
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
2019-02-03 22:16:50 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2019-12-06 06:54:17 +08:00
|
|
|
|
impl<N: Scalar + Clone> DMatrix<N> {
|
2019-01-29 19:03:48 +08:00
|
|
|
|
/// 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)
|
2019-04-08 23:29:32 +08:00
|
|
|
|
where DefaultAllocator: Reallocator<N, Dynamic, Dynamic, Dynamic, Dynamic> {
|
2019-01-29 19:03:48 +08:00
|
|
|
|
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);
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
2019-02-03 22:16:50 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2019-12-06 06:54:17 +08:00
|
|
|
|
impl<N: Scalar + Clone, C: Dim> MatrixMN<N, Dynamic, C>
|
2019-04-08 23:29:32 +08:00
|
|
|
|
where DefaultAllocator: Allocator<N, Dynamic, C>
|
|
|
|
|
{
|
2019-01-29 19:03:48 +08:00
|
|
|
|
/// 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)
|
2019-04-08 23:29:32 +08:00
|
|
|
|
where DefaultAllocator: Reallocator<N, Dynamic, C, Dynamic, C> {
|
|
|
|
|
let placeholder =
|
|
|
|
|
unsafe { Self::new_uninitialized_generic(Dynamic::new(0), self.data.shape().1) };
|
2019-01-29 19:03:48 +08:00
|
|
|
|
let old = mem::replace(self, placeholder);
|
|
|
|
|
let new = old.resize_vertically(new_nrows, val);
|
|
|
|
|
let _ = mem::replace(self, new);
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
2019-02-03 22:16:50 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2019-12-06 06:54:17 +08:00
|
|
|
|
impl<N: Scalar + Clone, R: Dim> MatrixMN<N, R, Dynamic>
|
2019-04-08 23:29:32 +08:00
|
|
|
|
where DefaultAllocator: Allocator<N, R, Dynamic>
|
|
|
|
|
{
|
2019-01-29 19:03:48 +08:00
|
|
|
|
/// 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)
|
2019-04-08 23:29:32 +08:00
|
|
|
|
where DefaultAllocator: Reallocator<N, R, Dynamic, R, Dynamic> {
|
|
|
|
|
let placeholder =
|
|
|
|
|
unsafe { Self::new_uninitialized_generic(self.data.shape().0, Dynamic::new(0)) };
|
2019-01-29 19:03:48 +08:00
|
|
|
|
let old = mem::replace(self, placeholder);
|
|
|
|
|
let new = old.resize_horizontally(new_ncols, val);
|
|
|
|
|
let _ = mem::replace(self, new);
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
2019-12-06 06:54:17 +08:00
|
|
|
|
unsafe fn compress_rows<N: Scalar + Clone>(
|
2018-02-02 19:26:35 +08:00
|
|
|
|
data: &mut [N],
|
|
|
|
|
nrows: usize,
|
|
|
|
|
ncols: usize,
|
|
|
|
|
i: usize,
|
|
|
|
|
nremove: usize,
|
2018-11-07 01:32:20 +08:00
|
|
|
|
)
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
let new_nrows = nrows - nremove;
|
2018-02-03 17:46:04 +08:00
|
|
|
|
|
|
|
|
|
if new_nrows == 0 || ncols == 0 {
|
|
|
|
|
return; // Nothing to do as the output matrix is empty.
|
|
|
|
|
}
|
|
|
|
|
|
2018-02-02 19:26:35 +08:00
|
|
|
|
let ptr_in = data.as_ptr();
|
|
|
|
|
let ptr_out = data.as_mut_ptr();
|
2017-08-03 01:37:44 +08:00
|
|
|
|
|
|
|
|
|
let mut curr_i = i;
|
|
|
|
|
|
2018-02-02 19:26:35 +08:00
|
|
|
|
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,
|
|
|
|
|
);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
|
|
|
|
|
curr_i += new_nrows;
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Deal with the last column from which less values have to be copied.
|
|
|
|
|
let remaining_len = nrows - i - nremove;
|
2018-02-02 19:26:35 +08:00
|
|
|
|
ptr::copy(
|
|
|
|
|
ptr_in.offset((nrows * ncols - remaining_len) as isize),
|
|
|
|
|
ptr_out.offset(curr_i as isize),
|
|
|
|
|
remaining_len,
|
|
|
|
|
);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
}
|
|
|
|
|
|
2018-02-03 17:54:51 +08:00
|
|
|
|
// 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.
|
2019-12-06 06:54:17 +08:00
|
|
|
|
unsafe fn extend_rows<N: Scalar + Clone>(
|
2018-02-02 19:26:35 +08:00
|
|
|
|
data: &mut [N],
|
|
|
|
|
nrows: usize,
|
|
|
|
|
ncols: usize,
|
|
|
|
|
i: usize,
|
|
|
|
|
ninsert: usize,
|
2018-11-07 01:32:20 +08:00
|
|
|
|
)
|
|
|
|
|
{
|
2017-08-03 01:37:44 +08:00
|
|
|
|
let new_nrows = nrows + ninsert;
|
2018-02-03 17:46:04 +08:00
|
|
|
|
|
|
|
|
|
if new_nrows == 0 || ncols == 0 {
|
|
|
|
|
return; // Nothing to do as the output matrix is empty.
|
|
|
|
|
}
|
|
|
|
|
|
2018-02-02 19:26:35 +08:00
|
|
|
|
let ptr_in = data.as_ptr();
|
|
|
|
|
let ptr_out = data.as_mut_ptr();
|
2017-08-03 01:37:44 +08:00
|
|
|
|
|
|
|
|
|
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.
|
2018-02-02 19:26:35 +08:00
|
|
|
|
ptr::copy(
|
|
|
|
|
ptr_in.offset((nrows * ncols - remaining_len) as isize),
|
|
|
|
|
ptr_out.offset(curr_i as isize),
|
|
|
|
|
remaining_len,
|
|
|
|
|
);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
|
2018-02-02 19:26:35 +08:00
|
|
|
|
for k in (0..ncols - 1).rev() {
|
2017-08-03 01:37:44 +08:00
|
|
|
|
curr_i -= new_nrows;
|
|
|
|
|
|
2018-02-02 19:26:35 +08:00
|
|
|
|
ptr::copy(
|
|
|
|
|
ptr_in.offset((k * nrows + i) as isize),
|
|
|
|
|
ptr_out.offset(curr_i as isize),
|
|
|
|
|
nrows,
|
|
|
|
|
);
|
2017-08-03 01:37:44 +08:00
|
|
|
|
}
|
|
|
|
|
}
|
2018-11-11 07:02:52 +08:00
|
|
|
|
|
|
|
|
|
/// Extend the number of columns of the `Matrix` with elements from
|
|
|
|
|
/// a given iterator.
|
2019-02-03 22:16:50 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2018-11-11 07:02:52 +08:00
|
|
|
|
impl<N, R, S> Extend<N> for Matrix<N, R, Dynamic, S>
|
|
|
|
|
where
|
2019-12-06 06:54:17 +08:00
|
|
|
|
N: Scalar + Clone,
|
2018-11-11 07:02:52 +08:00
|
|
|
|
R: Dim,
|
|
|
|
|
S: Extend<N>,
|
|
|
|
|
{
|
|
|
|
|
/// Extend the number of columns of the `Matrix` with elements
|
|
|
|
|
/// from the given iterator.
|
|
|
|
|
///
|
|
|
|
|
/// # Example
|
|
|
|
|
/// ```
|
2018-11-14 04:01:33 +08:00
|
|
|
|
/// # use nalgebra::{DMatrix, Dynamic, Matrix, MatrixMN, Matrix3};
|
2018-11-11 07:02:52 +08:00
|
|
|
|
///
|
|
|
|
|
/// let data = vec![0, 1, 2, // column 1
|
|
|
|
|
/// 3, 4, 5]; // column 2
|
|
|
|
|
///
|
2018-11-14 04:01:33 +08:00
|
|
|
|
/// let mut matrix = DMatrix::from_vec(3, 2, data);
|
2018-11-11 07:02:52 +08:00
|
|
|
|
///
|
|
|
|
|
/// 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
|
2018-11-14 04:01:33 +08:00
|
|
|
|
/// # use nalgebra::{DMatrix, Dynamic, MatrixMN};
|
2018-11-11 07:02:52 +08:00
|
|
|
|
/// let data = vec![0, 1, 2, // column 1
|
|
|
|
|
/// 3, 4, 5]; // column 2
|
|
|
|
|
///
|
2018-11-14 04:01:33 +08:00
|
|
|
|
/// let mut matrix = DMatrix::from_vec(3, 2, data);
|
2018-11-11 07:02:52 +08:00
|
|
|
|
///
|
2018-11-14 04:01:33 +08:00
|
|
|
|
/// // The following panics because the vec length is not a multiple of 3.
|
|
|
|
|
/// matrix.extend(vec![6, 7, 8, 9]);
|
2018-11-11 07:02:52 +08:00
|
|
|
|
/// ```
|
2019-04-08 23:29:32 +08:00
|
|
|
|
fn extend<I: IntoIterator<Item = N>>(&mut self, iter: I) {
|
2018-11-11 07:02:52 +08:00
|
|
|
|
self.data.extend(iter);
|
|
|
|
|
}
|
|
|
|
|
}
|
2018-11-13 02:53:30 +08:00
|
|
|
|
|
|
|
|
|
/// Extend the number of rows of the `Vector` with elements from
|
|
|
|
|
/// a given iterator.
|
2019-02-03 22:16:50 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2018-11-13 02:53:30 +08:00
|
|
|
|
impl<N, S> Extend<N> for Matrix<N, Dynamic, U1, S>
|
|
|
|
|
where
|
2019-12-06 06:54:17 +08:00
|
|
|
|
N: Scalar + Clone,
|
2018-11-13 02:53:30 +08:00
|
|
|
|
S: Extend<N>,
|
|
|
|
|
{
|
|
|
|
|
/// Extend the number of rows of a `Vector` with elements
|
|
|
|
|
/// from the given iterator.
|
|
|
|
|
///
|
|
|
|
|
/// # Example
|
|
|
|
|
/// ```
|
2018-11-14 04:01:33 +08:00
|
|
|
|
/// # use nalgebra::DVector;
|
2018-12-09 19:22:10 +08:00
|
|
|
|
/// let mut vector = DVector::from_vec(vec![0, 1, 2]);
|
2018-11-13 02:53:30 +08:00
|
|
|
|
/// vector.extend(vec![3, 4, 5]);
|
2018-12-09 19:22:10 +08:00
|
|
|
|
/// assert!(vector.eq(&DVector::from_vec(vec![0, 1, 2, 3, 4, 5])));
|
2018-11-13 02:53:30 +08:00
|
|
|
|
/// ```
|
2019-04-08 23:29:32 +08:00
|
|
|
|
fn extend<I: IntoIterator<Item = N>>(&mut self, iter: I) {
|
2018-11-13 02:53:30 +08:00
|
|
|
|
self.data.extend(iter);
|
|
|
|
|
}
|
|
|
|
|
}
|
2018-11-14 05:17:00 +08:00
|
|
|
|
|
2019-02-03 22:16:50 +08:00
|
|
|
|
#[cfg(any(feature = "std", feature = "alloc"))]
|
2018-11-14 05:17:00 +08:00
|
|
|
|
impl<N, R, S, RV, SV> Extend<Vector<N, RV, SV>> for Matrix<N, R, Dynamic, S>
|
|
|
|
|
where
|
2019-12-06 06:54:17 +08:00
|
|
|
|
N: Scalar + Clone,
|
2018-11-14 05:17:00 +08:00
|
|
|
|
R: Dim,
|
|
|
|
|
S: Extend<Vector<N, RV, SV>>,
|
|
|
|
|
RV: Dim,
|
2018-11-18 01:13:03 +08:00
|
|
|
|
SV: Storage<N, RV>,
|
|
|
|
|
ShapeConstraint: SameNumberOfRows<R, RV>,
|
2018-11-14 05:17:00 +08:00
|
|
|
|
{
|
|
|
|
|
/// 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!
|
|
|
|
|
/// ```
|
2019-04-08 23:29:32 +08:00
|
|
|
|
fn extend<I: IntoIterator<Item = Vector<N, RV, SV>>>(&mut self, iter: I) {
|
2018-11-14 05:17:00 +08:00
|
|
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self.data.extend(iter);
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|
|
|
|
}
|
|
|
|
|
}
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