use num::{One, Zero};
use std::cmp;
#[cfg(any(feature = "std", feature = "alloc"))]
use std::iter::ExactSizeIterator;
use std::ptr;
use crate::base::allocator::{Allocator, Reallocator};
use crate::base::constraint::{DimEq, SameNumberOfColumns, SameNumberOfRows, ShapeConstraint};
#[cfg(any(feature = "std", feature = "alloc"))]
use crate::base::dimension::Dyn;
use crate::base::dimension::{Const, Dim, DimAdd, DimDiff, DimMin, DimMinimum, DimSub, DimSum, U1};
use crate::base::storage::{RawStorage, RawStorageMut, ReshapableStorage};
use crate::base::{DefaultAllocator, Matrix, OMatrix, RowVector, Scalar, Vector};
use crate::{Storage, UninitMatrix};
use std::mem::MaybeUninit;
/// # Triangular matrix extraction
impl<T: Scalar + Zero, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
/// Extracts the upper triangular part of this matrix (including the diagonal).
#[inline]
#[must_use]
pub fn upper_triangle(&self) -> OMatrix<T, R, C>
where
DefaultAllocator: Allocator<T, R, C>,
{
let mut res = self.clone_owned();
res.fill_lower_triangle(T::zero(), 1);
res
}
/// Extracts the lower triangular part of this matrix (including the diagonal).
#[inline]
#[must_use]
pub fn lower_triangle(&self) -> OMatrix<T, R, C>
where
DefaultAllocator: Allocator<T, R, C>,
{
let mut res = self.clone_owned();
res.fill_upper_triangle(T::zero(), 1);
res
}
}
/// # Rows and columns extraction
impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
/// Creates a new matrix by extracting the given set of rows from `self`.
#[cfg(any(feature = "std", feature = "alloc"))]
#[must_use]
pub fn select_rows<'a, I>(&self, irows: I) -> OMatrix<T, Dyn, C>
where
I: IntoIterator<Item = &'a usize>,
I::IntoIter: ExactSizeIterator + Clone,
DefaultAllocator: Allocator<T, Dyn, C>,
{
let irows = irows.into_iter();
let ncols = self.shape_generic().1;
let mut res = Matrix::uninit(Dyn(irows.len()), ncols);
// First, check that all the indices from irows are valid.
// This will allow us to use unchecked access in the inner loop.
for i in irows.clone() {
assert!(*i < self.nrows(), "Row index out of bounds.")
}
for j in 0..ncols.value() {
// TODO: use unchecked column indexing
let mut res = res.column_mut(j);
let src = self.column(j);
for (destination, source) in irows.clone().enumerate() {
// Safety: all indices are in range.
unsafe {
*res.vget_unchecked_mut(destination) =
MaybeUninit::new(src.vget_unchecked(*source).clone());
}
}
}
// Safety: res is now fully initialized.
unsafe { res.assume_init() }
}
/// Creates a new matrix by extracting the given set of columns from `self`.
#[cfg(any(feature = "std", feature = "alloc"))]
#[must_use]
pub fn select_columns<'a, I>(&self, icols: I) -> OMatrix<T, R, Dyn>
where
I: IntoIterator<Item = &'a usize>,
I::IntoIter: ExactSizeIterator,
DefaultAllocator: Allocator<T, R, Dyn>,
{
let icols = icols.into_iter();
let nrows = self.shape_generic().0;
let mut res = Matrix::uninit(nrows, Dyn(icols.len()));
for (destination, source) in icols.enumerate() {
// NOTE: this is basically a copy_frow but wrapping the values insnide of MaybeUninit.
res.column_mut(destination)
.zip_apply(&self.column(*source), |out, e| *out = MaybeUninit::new(e));
}
// Safety: res is now fully initialized.
unsafe { res.assume_init() }
}
}
/// # Set rows, columns, and diagonal
impl<T: Scalar, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> Matrix<T, R, C, S> {
/// Fills the diagonal of this matrix with the content of the given vector.
#[inline]
pub fn set_diagonal<R2: Dim, S2>(&mut self, diag: &Vector<T, R2, S2>)
where
R: DimMin<C>,
S2: RawStorage<T, R2>,
ShapeConstraint: DimEq<DimMinimum<R, C>, R2>,
{
let (nrows, ncols) = self.shape();
let min_nrows_ncols = cmp::min(nrows, ncols);
assert_eq!(diag.len(), min_nrows_ncols, "Mismatched dimensions.");
for i in 0..min_nrows_ncols {
unsafe { *self.get_unchecked_mut((i, i)) = diag.vget_unchecked(i).clone() }
}
}
/// Fills the diagonal of this matrix with the content of the given iterator.
///
/// This will fill as many diagonal elements as the iterator yields, up to the
/// minimum of the number of rows and columns of `self`, and starting with the
/// diagonal element at index (0, 0).
#[inline]
pub fn set_partial_diagonal(&mut self, diag: impl Iterator<Item = T>) {
let (nrows, ncols) = self.shape();
let min_nrows_ncols = cmp::min(nrows, ncols);
for (i, val) in diag.enumerate().take(min_nrows_ncols) {
unsafe { *self.get_unchecked_mut((i, i)) = val }
}
}
/// Fills the selected row of this matrix with the content of the given vector.
#[inline]
pub fn set_row<C2: Dim, S2>(&mut self, i: usize, row: &RowVector<T, C2, S2>)
where
S2: RawStorage<T, U1, C2>,
ShapeConstraint: SameNumberOfColumns<C, C2>,
{
self.row_mut(i).copy_from(row);
}
/// Fills the selected column of this matrix with the content of the given vector.
#[inline]
pub fn set_column<R2: Dim, S2>(&mut self, i: usize, column: &Vector<T, R2, S2>)
where
S2: RawStorage<T, R2, U1>,
ShapeConstraint: SameNumberOfRows<R, R2>,
{
self.column_mut(i).copy_from(column);
}
}
/// # In-place filling
impl<T, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> Matrix<T, R, C, S> {
/// Sets all the elements of this matrix to the value returned by the closure.
#[inline]
pub fn fill_with(&mut self, val: impl Fn() -> T) {
for e in self.iter_mut() {
*e = val()
}
}
/// Sets all the elements of this matrix to `val`.
#[inline]
pub fn fill(&mut self, val: T)
where
T: Scalar,
{
for e in self.iter_mut() {
*e = val.clone()
}
}
/// Fills `self` with the identity matrix.
#[inline]
pub fn fill_with_identity(&mut self)
where
T: Scalar + Zero + One,
{
self.fill(T::zero());
self.fill_diagonal(T::one());
}
/// Sets all the diagonal elements of this matrix to `val`.
#[inline]
pub fn fill_diagonal(&mut self, val: T)
where
T: Scalar,
{
let (nrows, ncols) = self.shape();
let n = cmp::min(nrows, ncols);
for i in 0..n {
unsafe { *self.get_unchecked_mut((i, i)) = val.clone() }
}
}
/// Sets all the elements of the selected row to `val`.
#[inline]
pub fn fill_row(&mut self, i: usize, val: T)
where
T: Scalar,
{
assert!(i < self.nrows(), "Row index out of bounds.");
for j in 0..self.ncols() {
unsafe { *self.get_unchecked_mut((i, j)) = val.clone() }
}
}
/// Sets all the elements of the selected column to `val`.
#[inline]
pub fn fill_column(&mut self, j: usize, val: T)
where
T: Scalar,
{
assert!(j < self.ncols(), "Row index out of bounds.");
for i in 0..self.nrows() {
unsafe { *self.get_unchecked_mut((i, j)) = val.clone() }
}
}
/// Sets all the elements of the lower-triangular part of this matrix to `val`.
///
/// The parameter `shift` allows some subdiagonals to be left untouched:
/// * If `shift = 0` then the diagonal is overwritten as well.
/// * If `shift = 1` then the diagonal is left untouched.
/// * If `shift > 1`, then the diagonal and the first `shift - 1` subdiagonals are left
/// untouched.
#[inline]
pub fn fill_lower_triangle(&mut self, val: T, shift: usize)
where
T: Scalar,
{
for j in 0..self.ncols() {
for i in (j + shift)..self.nrows() {
unsafe { *self.get_unchecked_mut((i, j)) = val.clone() }
}
}
}
/// Sets all the elements of the lower-triangular part of this matrix to `val`.
///
/// The parameter `shift` allows some superdiagonals to be left untouched:
/// * If `shift = 0` then the diagonal is overwritten as well.
/// * If `shift = 1` then the diagonal is left untouched.
/// * If `shift > 1`, then the diagonal and the first `shift - 1` superdiagonals are left
/// untouched.
#[inline]
pub fn fill_upper_triangle(&mut self, val: T, shift: usize)
where
T: Scalar,
{
for j in shift..self.ncols() {
// TODO: is there a more efficient way to avoid the min ?
// (necessary for rectangular matrices)
for i in 0..cmp::min(j + 1 - shift, self.nrows()) {
unsafe { *self.get_unchecked_mut((i, j)) = val.clone() }
}
}
}
}
impl<T: Scalar, D: Dim, S: RawStorageMut<T, D, D>> Matrix<T, D, D, S> {
/// 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();
for j in 0..dim {
for i in j + 1..dim {
unsafe {
*self.get_unchecked_mut((i, j)) = self.get_unchecked((j, i)).clone();
}
}
}
}
/// 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.");
for j in 1..self.ncols() {
for i in 0..j {
unsafe {
*self.get_unchecked_mut((i, j)) = self.get_unchecked((j, i)).clone();
}
}
}
}
}
/// # In-place swapping
impl<T: Scalar, R: Dim, C: Dim, S: RawStorageMut<T, R, C>> Matrix<T, R, C, S> {
/// Swaps two rows in-place.
#[inline]
pub fn swap_rows(&mut self, irow1: usize, irow2: usize) {
assert!(irow1 < self.nrows() && irow2 < self.nrows());
if irow1 != irow2 {
// TODO: optimize that.
for i in 0..self.ncols() {
unsafe { self.swap_unchecked((irow1, i), (irow2, i)) }
}
}
// Otherwise do nothing.
}
/// Swaps two columns in-place.
#[inline]
pub fn swap_columns(&mut self, icol1: usize, icol2: usize) {
assert!(icol1 < self.ncols() && icol2 < self.ncols());
if icol1 != icol2 {
// TODO: optimize that.
for i in 0..self.nrows() {
unsafe { self.swap_unchecked((i, icol1), (i, icol2)) }
}
}
// Otherwise do nothing.
}
}
/*
*
* TODO: specialize all the following for slices.
*
*/
/// # Rows and columns removal
impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
/*
*
* Column removal.
*
*/
/// Removes the `i`-th column from this matrix.
#[inline]
pub fn remove_column(self, i: usize) -> OMatrix<T, R, DimDiff<C, U1>>
where
C: DimSub<U1>,
DefaultAllocator: Reallocator<T, R, C, R, DimDiff<C, U1>>,
{
self.remove_fixed_columns::<1>(i)
}
/// Removes all columns in `indices`
#[cfg(any(feature = "std", feature = "alloc"))]
pub fn remove_columns_at(self, indices: &[usize]) -> OMatrix<T, R, Dyn>
where
C: DimSub<Dyn, Output = Dyn>,
DefaultAllocator: Reallocator<T, R, C, R, Dyn>,
{
let mut m = self.into_owned();
let (nrows, ncols) = m.shape_generic();
let mut offset: usize = 0;
let mut target: usize = 0;
while offset + target < ncols.value() {
if indices.contains(&(target + offset)) {
// Safety: the resulting pointer is within range.
let col_ptr = unsafe { m.data.ptr_mut().add((target + offset) * nrows.value()) };
// Drop every element in the column we are about to overwrite.
// We use the a similar technique as in `Vec::truncate`.
let s = ptr::slice_from_raw_parts_mut(col_ptr, nrows.value());
// Safety: we drop the column in-place, which is OK because we will overwrite these
// entries later in the loop, or discard them with the `reallocate_copy`
// afterwards.
unsafe { ptr::drop_in_place(s) };
offset += 1;
} else {
unsafe {
let ptr_source = m.data.ptr().add((target + offset) * nrows.value());
let ptr_target = m.data.ptr_mut().add(target * nrows.value());
// Copy the data, overwriting what we dropped.
ptr::copy(ptr_source, ptr_target, nrows.value());
target += 1;
}
}
}
// Safety: The new size is smaller than the old size, so
// DefaultAllocator::reallocate_copy will initialize
// every element of the new matrix which can then
// be assumed to be initialized.
unsafe {
let new_data = DefaultAllocator::reallocate_copy(
nrows,
ncols.sub(Dyn::from_usize(offset)),
m.data,
);
Matrix::from_data(new_data).assume_init()
}
}
/// Removes all rows in `indices`
#[cfg(any(feature = "std", feature = "alloc"))]
pub fn remove_rows_at(self, indices: &[usize]) -> OMatrix<T, Dyn, C>
where
R: DimSub<Dyn, Output = Dyn>,
DefaultAllocator: Reallocator<T, R, C, Dyn, C>,
{
let mut m = self.into_owned();
let (nrows, ncols) = m.shape_generic();
let mut offset: usize = 0;
let mut target: usize = 0;
while offset + target < nrows.value() * ncols.value() {
if indices.contains(&((target + offset) % nrows.value())) {
// Safety: the resulting pointer is within range.
unsafe {
let elt_ptr = m.data.ptr_mut().add(target + offset);
// Safety: we drop the component in-place, which is OK because we will overwrite these
// entries later in the loop, or discard them with the `reallocate_copy`
// afterwards.
ptr::drop_in_place(elt_ptr)
};
offset += 1;
} else {
unsafe {
let ptr_source = m.data.ptr().add(target + offset);
let ptr_target = m.data.ptr_mut().add(target);
// Copy the data, overwriting what we dropped in the previous iterations.
ptr::copy(ptr_source, ptr_target, 1);
target += 1;
}
}
}
// Safety: The new size is smaller than the old size, so
// DefaultAllocator::reallocate_copy will initialize
// every element of the new matrix which can then
// be assumed to be initialized.
unsafe {
let new_data = DefaultAllocator::reallocate_copy(
nrows.sub(Dyn::from_usize(offset / ncols.value())),
ncols,
m.data,
);
Matrix::from_data(new_data).assume_init()
}
}
/// Removes `D::dim()` consecutive columns from this matrix, starting with the `i`-th
/// (included).
#[inline]
pub fn remove_fixed_columns<const D: usize>(
self,
i: usize,
) -> OMatrix<T, R, DimDiff<C, Const<D>>>
where
C: DimSub<Const<D>>,
DefaultAllocator: Reallocator<T, R, C, R, DimDiff<C, Const<D>>>,
{
self.remove_columns_generic(i, Const::<D>)
}
/// Removes `n` consecutive columns from this matrix, starting with the `i`-th (included).
#[inline]
#[cfg(any(feature = "std", feature = "alloc"))]
pub fn remove_columns(self, i: usize, n: usize) -> OMatrix<T, R, Dyn>
where
C: DimSub<Dyn, Output = Dyn>,
DefaultAllocator: Reallocator<T, R, C, R, Dyn>,
{
self.remove_columns_generic(i, Dyn(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) -> OMatrix<T, R, DimDiff<C, D>>
where
D: Dim,
C: DimSub<D>,
DefaultAllocator: Reallocator<T, R, C, R, DimDiff<C, D>>,
{
let mut m = self.into_owned();
let (nrows, ncols) = m.shape_generic();
assert!(
i + nremove.value() <= ncols.value(),
"Column index out of range."
);
let need_column_shifts = nremove.value() != 0 && i + nremove.value() < ncols.value();
if need_column_shifts {
// The first `deleted_i * nrows` are left untouched.
let copied_value_start = i + nremove.value();
unsafe {
let ptr_in = m.data.ptr().add(copied_value_start * nrows.value());
let ptr_out = m.data.ptr_mut().add(i * nrows.value());
// Drop all the elements of the columns we are about to overwrite.
// We use the a similar technique as in `Vec::truncate`.
let s = ptr::slice_from_raw_parts_mut(ptr_out, nremove.value() * nrows.value());
// Safety: we drop the column in-place, which is OK because we will overwrite these
// entries with `ptr::copy` afterward.
ptr::drop_in_place(s);
ptr::copy(
ptr_in,
ptr_out,
(ncols.value() - copied_value_start) * nrows.value(),
);
}
} else {
// All the columns to remove are at the end of the buffer. Drop them.
unsafe {
let ptr = m.data.ptr_mut().add(i * nrows.value());
let s = ptr::slice_from_raw_parts_mut(ptr, nremove.value() * nrows.value());
ptr::drop_in_place(s)
};
}
// Safety: The new size is smaller than the old size, so
// DefaultAllocator::reallocate_copy will initialize
// every element of the new matrix which can then
// be assumed to be initialized.
unsafe {
let new_data = DefaultAllocator::reallocate_copy(nrows, ncols.sub(nremove), m.data);
Matrix::from_data(new_data).assume_init()
}
}
/*
*
* Row removal.
*
*/
/// Removes the `i`-th row from this matrix.
#[inline]
pub fn remove_row(self, i: usize) -> OMatrix<T, DimDiff<R, U1>, C>
where
R: DimSub<U1>,
DefaultAllocator: Reallocator<T, R, C, DimDiff<R, U1>, C>,
{
self.remove_fixed_rows::<1>(i)
}
/// Removes `D::dim()` consecutive rows from this matrix, starting with the `i`-th (included).
#[inline]
pub fn remove_fixed_rows<const D: usize>(self, i: usize) -> OMatrix<T, DimDiff<R, Const<D>>, C>
where
R: DimSub<Const<D>>,
DefaultAllocator: Reallocator<T, R, C, DimDiff<R, Const<D>>, C>,
{
self.remove_rows_generic(i, Const::<D>)
}
/// 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) -> OMatrix<T, Dyn, C>
where
R: DimSub<Dyn, Output = Dyn>,
DefaultAllocator: Reallocator<T, R, C, Dyn, C>,
{
self.remove_rows_generic(i, Dyn(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) -> OMatrix<T, DimDiff<R, D>, C>
where
D: Dim,
R: DimSub<D>,
DefaultAllocator: Reallocator<T, R, C, DimDiff<R, D>, C>,
{
let mut m = self.into_owned();
let (nrows, ncols) = m.shape_generic();
assert!(
i + nremove.value() <= nrows.value(),
"Row index out of range."
);
if nremove.value() != 0 {
unsafe {
compress_rows(
&mut m.as_mut_slice(),
nrows.value(),
ncols.value(),
i,
nremove.value(),
);
}
}
// Safety: The new size is smaller than the old size, so
// DefaultAllocator::reallocate_copy will initialize
// every element of the new matrix which can then
// be assumed to be initialized.
unsafe {
let new_data = DefaultAllocator::reallocate_copy(nrows.sub(nremove), ncols, m.data);
Matrix::from_data(new_data).assume_init()
}
}
}
/// # Rows and columns insertion
impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
/*
*
* Columns insertion.
*
*/
/// Inserts a column filled with `val` at the `i-th` position.
#[inline]
pub fn insert_column(self, i: usize, val: T) -> OMatrix<T, R, DimSum<C, U1>>
where
C: DimAdd<U1>,
DefaultAllocator: Reallocator<T, R, C, R, DimSum<C, U1>>,
{
self.insert_fixed_columns::<1>(i, val)
}
/// Inserts `D` columns filled with `val` starting at the `i-th` position.
#[inline]
pub fn insert_fixed_columns<const D: usize>(
self,
i: usize,
val: T,
) -> OMatrix<T, R, DimSum<C, Const<D>>>
where
C: DimAdd<Const<D>>,
DefaultAllocator: Reallocator<T, R, C, R, DimSum<C, Const<D>>>,
{
let mut res = unsafe { self.insert_columns_generic_uninitialized(i, Const::<D>) };
res.fixed_columns_mut::<D>(i)
.fill_with(|| MaybeUninit::new(val.clone()));
// Safety: the result is now fully initialized. The added columns have
// been initialized by the `fill_with` above, and the rest have
// been initialized by `insert_columns_generic_uninitialized`.
unsafe { res.assume_init() }
}
/// 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: T) -> OMatrix<T, R, Dyn>
where
C: DimAdd<Dyn, Output = Dyn>,
DefaultAllocator: Reallocator<T, R, C, R, Dyn>,
{
let mut res = unsafe { self.insert_columns_generic_uninitialized(i, Dyn(n)) };
res.columns_mut(i, n)
.fill_with(|| MaybeUninit::new(val.clone()));
// Safety: the result is now fully initialized. The added columns have
// been initialized by the `fill_with` above, and the rest have
// been initialized by `insert_columns_generic_uninitialized`.
unsafe { res.assume_init() }
}
/// Inserts `ninsert.value()` columns starting at the `i-th` place of this matrix.
///
/// # Safety
/// The output matrix has all its elements initialized except for the the components of the
/// added columns.
#[inline]
pub unsafe fn insert_columns_generic_uninitialized<D>(
self,
i: usize,
ninsert: D,
) -> UninitMatrix<T, R, DimSum<C, D>>
where
D: Dim,
C: DimAdd<D>,
DefaultAllocator: Reallocator<T, R, C, R, DimSum<C, D>>,
{
let m = self.into_owned();
let (nrows, ncols) = m.shape_generic();
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().add(i * nrows.value());
let ptr_out = res
.data
.ptr_mut()
.add((i + ninsert.value()) * nrows.value());
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: T) -> OMatrix<T, DimSum<R, U1>, C>
where
R: DimAdd<U1>,
DefaultAllocator: Reallocator<T, R, C, DimSum<R, U1>, C>,
{
self.insert_fixed_rows::<1>(i, val)
}
/// Inserts `D::dim()` rows filled with `val` starting at the `i-th` position.
#[inline]
pub fn insert_fixed_rows<const D: usize>(
self,
i: usize,
val: T,
) -> OMatrix<T, DimSum<R, Const<D>>, C>
where
R: DimAdd<Const<D>>,
DefaultAllocator: Reallocator<T, R, C, DimSum<R, Const<D>>, C>,
{
let mut res = unsafe { self.insert_rows_generic_uninitialized(i, Const::<D>) };
res.fixed_rows_mut::<D>(i)
.fill_with(|| MaybeUninit::new(val.clone()));
// Safety: the result is now fully initialized. The added rows have
// been initialized by the `fill_with` above, and the rest have
// been initialized by `insert_rows_generic_uninitialized`.
unsafe { res.assume_init() }
}
/// 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: T) -> OMatrix<T, Dyn, C>
where
R: DimAdd<Dyn, Output = Dyn>,
DefaultAllocator: Reallocator<T, R, C, Dyn, C>,
{
let mut res = unsafe { self.insert_rows_generic_uninitialized(i, Dyn(n)) };
res.rows_mut(i, n)
.fill_with(|| MaybeUninit::new(val.clone()));
// Safety: the result is now fully initialized. The added rows have
// been initialized by the `fill_with` above, and the rest have
// been initialized by `insert_rows_generic_uninitialized`.
unsafe { res.assume_init() }
}
/// Inserts `ninsert.value()` rows at the `i-th` place of this matrix.
///
/// # Safety
/// 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,
) -> UninitMatrix<T, DimSum<R, D>, C>
where
D: Dim,
R: DimAdd<D>,
DefaultAllocator: Reallocator<T, R, C, DimSum<R, D>, C>,
{
let m = self.into_owned();
let (nrows, ncols) = m.shape_generic();
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.as_mut_slice(),
nrows.value(),
ncols.value(),
i,
ninsert.value(),
);
}
res
}
}
/// # Resizing and reshaping
impl<T: Scalar, R: Dim, C: Dim, S: Storage<T, R, C>> Matrix<T, R, C, S> {
/// 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: T) -> OMatrix<T, Dyn, Dyn>
where
DefaultAllocator: Reallocator<T, R, C, Dyn, Dyn>,
{
self.resize_generic(Dyn(new_nrows), Dyn(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: T) -> OMatrix<T, Dyn, C>
where
DefaultAllocator: Reallocator<T, R, C, Dyn, C>,
{
let ncols = self.shape_generic().1;
self.resize_generic(Dyn(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: T) -> OMatrix<T, R, Dyn>
where
DefaultAllocator: Reallocator<T, R, C, R, Dyn>,
{
let nrows = self.shape_generic().0;
self.resize_generic(nrows, Dyn(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<const R2: usize, const C2: usize>(
self,
val: T,
) -> OMatrix<T, Const<R2>, Const<C2>>
where
DefaultAllocator: Reallocator<T, R, C, Const<R2>, Const<C2>>,
{
self.resize_generic(Const::<R2>, Const::<C2>, 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: T,
) -> OMatrix<T, R2, C2>
where
DefaultAllocator: Reallocator<T, R, C, R2, C2>,
{
let (nrows, ncols) = self.shape();
let mut data = self.into_owned();
if new_nrows.value() == nrows {
if new_ncols.value() < ncols {
unsafe {
let num_cols_to_delete = ncols - new_ncols.value();
let col_ptr = data.data.ptr_mut().add(new_ncols.value() * nrows);
let s = ptr::slice_from_raw_parts_mut(col_ptr, num_cols_to_delete * nrows);
// Safety: drop the elements of the deleted columns.
// these are the elements that will be truncated
// by the `reallocate_copy` afterward.
ptr::drop_in_place(s)
};
}
let res = unsafe { DefaultAllocator::reallocate_copy(new_nrows, new_ncols, data.data) };
let mut res = Matrix::from_data(res);
if new_ncols.value() > ncols {
res.columns_range_mut(ncols..)
.fill_with(|| MaybeUninit::new(val.clone()));
}
// Safety: the result is now fully initialized by `reallocate_copy` and
// `fill_with` (if the output has more columns than the input).
unsafe { res.assume_init() }
} 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.data,
));
} else {
res = Matrix::from_data(DefaultAllocator::reallocate_copy(
new_nrows, new_ncols, data.data,
));
extend_rows(
&mut res.as_mut_slice(),
nrows,
new_ncols.value(),
nrows,
new_nrows.value() - nrows,
);
}
}
if new_ncols.value() > ncols {
res.columns_range_mut(ncols..)
.fill_with(|| MaybeUninit::new(val.clone()));
}
if new_nrows.value() > nrows {
res.view_range_mut(nrows.., ..cmp::min(ncols, new_ncols.value()))
.fill_with(|| MaybeUninit::new(val.clone()));
}
// Safety: the result is now fully initialized by `reallocate_copy` and
// `fill_with` (whenever applicable).
unsafe { res.assume_init() }
}
}
/// Reshapes `self` such that it has dimensions `new_nrows × new_ncols`.
///
/// This will reinterpret `self` as if it is a matrix with `new_nrows` rows and `new_ncols`
/// columns. The arrangements of the component in the output matrix are the same as what
/// would be obtained by `Matrix::from_slice_generic(self.as_slice(), new_nrows, new_ncols)`.
///
/// If `self` is a dynamically-sized matrix, then its components are neither copied nor moved.
/// If `self` is staticyll-sized, then a copy may happen in some situations.
/// This function will panic if the given dimensions are such that the number of elements of
/// the input matrix are not equal to the number of elements of the output matrix.
///
/// # Examples
///
/// ```
/// # use nalgebra::{Matrix3x2, Matrix2x3, DMatrix, Const, Dyn};
///
/// let m1 = Matrix2x3::new(
/// 1.1, 1.2, 1.3,
/// 2.1, 2.2, 2.3
/// );
/// let m2 = Matrix3x2::new(
/// 1.1, 2.2,
/// 2.1, 1.3,
/// 1.2, 2.3
/// );
/// let reshaped = m1.reshape_generic(Const::<3>, Const::<2>);
/// assert_eq!(reshaped, m2);
///
/// let dm1 = DMatrix::from_row_slice(
/// 4,
/// 3,
/// &[
/// 1.0, 0.0, 0.0,
/// 0.0, 0.0, 1.0,
/// 0.0, 0.0, 0.0,
/// 0.0, 1.0, 0.0
/// ],
/// );
/// let dm2 = DMatrix::from_row_slice(
/// 6,
/// 2,
/// &[
/// 1.0, 0.0,
/// 0.0, 1.0,
/// 0.0, 0.0,
/// 0.0, 1.0,
/// 0.0, 0.0,
/// 0.0, 0.0,
/// ],
/// );
/// let reshaped = dm1.reshape_generic(Dyn(6), Dyn(2));
/// assert_eq!(reshaped, dm2);
/// ```
pub fn reshape_generic<R2, C2>(
self,
new_nrows: R2,
new_ncols: C2,
) -> Matrix<T, R2, C2, S::Output>
where
R2: Dim,
C2: Dim,
S: ReshapableStorage<T, R, C, R2, C2>,
{
let data = self.data.reshape_generic(new_nrows, new_ncols);
Matrix::from_data(data)
}
}
/// # In-place resizing
#[cfg(any(feature = "std", feature = "alloc"))]
impl<T: Scalar> OMatrix<T, Dyn, Dyn> {
/// 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: T)
where
DefaultAllocator: Reallocator<T, Dyn, Dyn, Dyn, Dyn>,
{
// TODO: avoid the clone.
*self = self.clone().resize(new_nrows, new_ncols, val);
}
}
#[cfg(any(feature = "std", feature = "alloc"))]
impl<T: Scalar, C: Dim> OMatrix<T, Dyn, C>
where
DefaultAllocator: Allocator<T, Dyn, 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: T)
where
DefaultAllocator: Reallocator<T, Dyn, C, Dyn, C>,
{
// TODO: avoid the clone.
*self = self.clone().resize_vertically(new_nrows, val);
}
}
#[cfg(any(feature = "std", feature = "alloc"))]
impl<T: Scalar, R: Dim> OMatrix<T, R, Dyn>
where
DefaultAllocator: Allocator<T, R, Dyn>,
{
/// 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: T)
where
DefaultAllocator: Reallocator<T, R, Dyn, R, Dyn>,
{
// TODO: avoid the clone.
*self = self.clone().resize_horizontally(new_ncols, val);
}
}
// Move the elements of `data` in such a way that the matrix with
// the rows `[i, i + nremove[` deleted is represented in a contigous
// way in `data` after this method completes.
// Every deleted element are manually dropped by this method.
unsafe fn compress_rows<T: Scalar>(
data: &mut [T],
nrows: usize,
ncols: usize,
i: usize,
nremove: usize,
) {
let new_nrows = nrows - nremove;
if nremove == 0 {
return; // Nothing to remove or drop.
}
if new_nrows == 0 || ncols == 0 {
// The output matrix is empty, drop everything.
ptr::drop_in_place(data);
return;
}
// Safety: because `nremove != 0`, the pointers given to `ptr::copy`
// won’t alias.
let ptr_in = data.as_ptr();
let ptr_out = data.as_mut_ptr();
let mut curr_i = i;
for k in 0..ncols - 1 {
// Safety: we drop the row elements in-place because we will overwrite these
// entries later with the `ptr::copy`.
let s = ptr::slice_from_raw_parts_mut(ptr_out.add(curr_i), nremove);
ptr::drop_in_place(s);
ptr::copy(
ptr_in.add(curr_i + (k + 1) * nremove),
ptr_out.add(curr_i),
new_nrows,
);
curr_i += new_nrows;
}
/*
* Deal with the last column from which less values have to be copied.
*/
// Safety: we drop the row elements in-place because we will overwrite these
// entries later with the `ptr::copy`.
let s = ptr::slice_from_raw_parts_mut(ptr_out.add(curr_i), nremove);
ptr::drop_in_place(s);
let remaining_len = nrows - i - nremove;
ptr::copy(
ptr_in.add(nrows * ncols - remaining_len),
ptr_out.add(curr_i),
remaining_len,
);
}
// Moves entries of a matrix buffer to make place for `ninsert` empty 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<T>(data: &mut [T], 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.add(nrows * ncols - remaining_len),
ptr_out.add(curr_i),
remaining_len,
);
for k in (0..ncols - 1).rev() {
curr_i -= new_nrows;
ptr::copy(ptr_in.add(k * nrows + i), ptr_out.add(curr_i), nrows);
}
}
/// Extend the number of columns of the `Matrix` with elements from
/// a given iterator.
#[cfg(any(feature = "std", feature = "alloc"))]
impl<T, R, S> Extend<T> for Matrix<T, R, Dyn, S>
where
T: Scalar,
R: Dim,
S: Extend<T>,
{
/// Extend the number of columns of the `Matrix` with elements
/// from the given iterator.
///
/// # Example
/// ```
/// # use nalgebra::{DMatrix, Dyn, Matrix, OMatrix, 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, Dyn, OMatrix};
/// 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 = T>>(&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<T, S> Extend<T> for Matrix<T, Dyn, U1, S>
where
T: Scalar,
S: Extend<T>,
{
/// 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 = T>>(&mut self, iter: I) {
self.data.extend(iter);
}
}
#[cfg(any(feature = "std", feature = "alloc"))]
impl<T, R, S, RV, SV> Extend<Vector<T, RV, SV>> for Matrix<T, R, Dyn, S>
where
T: Scalar,
R: Dim,
S: Extend<Vector<T, RV, SV>>,
RV: Dim,
SV: RawStorage<T, 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<T, RV, SV>>>(&mut self, iter: I) {
self.data.extend(iter);
}
}