Type Alias SparseRowMatMut 

pub type SparseRowMatMut<'a, I, T, Rows = usize, Cols = usize> = SparseRowMat<Mut<'a, I, T, Rows, Cols>>;

view over sparse row major matrix

see SymbolicSparseRowMatRef

Aliased Type

#[repr(transparent)]
pub struct SparseRowMatMut<'a, I, T, Rows = usize, Cols = usize>(pub Mut<'a, I, T, Rows, Cols>);

Tuple Fields

0: Mut<'a, I, T, Rows, Cols>

Implementations

impl<'a, Rows: Shape, Cols: Shape, I: Index, T> SparseRowMatMut<'a, I, T, Rows, Cols>

pub fn new( symbolic: SymbolicSparseRowMatRef<'a, I, Rows, Cols>, val: &'a mut [T], ) -> Self

see SparseRowMatRef::new

pub fn parts(self) -> (SymbolicSparseRowMatRef<'a, I, Rows, Cols>, &'a [T])

see SparseRowMatRef::parts

pub fn parts_mut( self, ) -> (SymbolicSparseRowMatRef<'a, I, Rows, Cols>, &'a mut [T])

see SparseRowMatRef::parts

pub fn symbolic(&self) -> SymbolicSparseRowMatRef<'a, I, Rows, Cols>

see SparseRowMatRef::symbolic

pub fn val(self) -> &'a [T]

see SparseRowMatRef::val

pub fn val_mut(self) -> &'a mut [T]

see SparseRowMatRef::val

pub fn val_of_row(self, i: Idx<Rows>) -> &'a [T]

see SparseRowMatRef::val_of_row

pub fn val_of_row_mut(self, j: Idx<Rows>) -> &'a mut [T]

see SparseRowMatRef::val_of_row

pub fn as_shape<V: Shape, H: Shape>( self, nrows: V, ncols: H, ) -> SparseRowMatRef<'a, I, T, V, H>

see SparseRowMatRef::as_shape

pub fn as_shape_mut<V: Shape, H: Shape>( self, nrows: V, ncols: H, ) -> SparseRowMatMut<'a, I, T, V, H>

see SparseRowMatRef::as_shape

pub fn get(self, row: Idx<Rows>, col: Idx<Cols>) -> Option<&'a T>

see SparseRowMatRef::get

pub fn get_mut(self, row: Idx<Rows>, col: Idx<Cols>) -> Option<&'a mut T>

returns a reference to the value at the given index, or None if the symbolic structure doesn’t contain it, or contains multiple indices with the given index

panics

• panics if row >= self.nrows()
• panics if col >= self.ncols() see SparseRowMatRef::get

pub fn as_dyn(self) -> SparseRowMatRef<'a, I, T>

see SparseRowMatRef::as_dyn

pub fn as_dyn_mut(self) -> SparseRowMatMut<'a, I, T>

see SparseRowMatRef::as_dyn

pub fn transpose(self) -> SparseColMatRef<'a, I, T, Cols, Rows>

see SparseRowMatRef::transpose

pub fn transpose_mut(self) -> SparseColMatMut<'a, I, T, Cols, Rows>

see SparseRowMatRef::transpose

pub fn conjugate(self) -> SparseRowMatRef<'a, I, T::Conj, Rows, Cols>

where T: Conjugate,

see SparseRowMatRef::conjugate

pub fn conjugate_mut(self) -> SparseRowMatMut<'a, I, T::Conj, Rows, Cols>

where T: Conjugate,

see SparseRowMatRef::conjugate

pub fn adjoint(self) -> SparseColMatRef<'a, I, T::Conj, Cols, Rows>

where T: Conjugate,

see SparseRowMatRef::adjoint

pub fn adjoint_mut(self) -> SparseColMatMut<'a, I, T::Conj, Cols, Rows>

where T: Conjugate,

see SparseRowMatRef::adjoint

pub fn canonical(self) -> SparseRowMatRef<'a, I, T::Canonical, Rows, Cols>

where T: Conjugate,

see SparseRowMatRef::canonical

pub fn canonical_mut(self) -> SparseRowMatMut<'a, I, T::Canonical, Rows, Cols>

where T: Conjugate,

see SparseRowMatRef::canonical

pub fn to_col_major( &self, ) -> Result<SparseColMat<I, T::Canonical, Rows, Cols>, FaerError>

where T: Conjugate,

see SparseRowMatRef::to_col_major

pub fn to_dense(&self) -> Mat<T::Canonical, Rows, Cols>

where T: Conjugate,

see SparseRowMatRef::to_dense

pub fn triplet_iter( self, ) -> impl 'a + Iterator<Item = Triplet<Idx<Rows>, Idx<Cols>, &'a T>>

where Rows: 'a, Cols: 'a,

see SparseRowMatRef::triplet_iter

Methods from Deref<Target = SymbolicSparseRowMatRef<'a, I, Rows, Cols>>

pub fn nrows(&self) -> Rows

returns the number of rows of the matrix

pub fn ncols(&self) -> Cols

returns the number of columns of the matrix

pub fn shape(&self) -> (Rows, Cols)

returns the number of rows and columns of the matrix

pub fn to_owned(&self) -> Result<SymbolicSparseRowMat<I, Rows, Cols>, FaerError>

returns a newly allocated matrix holding the values of self

pub fn to_col_major( &self, ) -> Result<SymbolicSparseColMat<I, Rows, Cols>, FaerError>

returns a newly allocated matrix holding the values of self in column major format

pub fn compute_nnz(&self) -> usize

returns the number of non-zero elements in the matrix

pub fn row_ptr(&self) -> &'a [I]

returns the row pointers

pub fn row_nnz(&self) -> Option<&'a [I]>

returns the row non-zero counts

pub fn col_idx(&self) -> &'a [I]

returns the column indices

pub fn row_range(&self, i: Idx<Rows>) -> Range<usize>

returns the range specifying the indices of row i

pub unsafe fn row_range_unchecked(&self, i: Idx<Rows>) -> Range<usize>

returns the range specifying the indices of row i, without bound checks

pub fn col_idx_of_row_raw(&self, i: Idx<Rows>) -> &'a [Idx<Cols, I>]

returns the column indices of row i

pub fn col_idx_of_row( &self, i: Idx<Rows>, ) -> impl 'a + Clone + ExactSizeIterator + DoubleEndedIterator<Item = Idx<Cols>>

where Rows: 'a, Cols: 'a,

returns the column indices of row i

pub fn parts(&self) -> (Rows, Cols, &[I], Option<&[I]>, &[I])

see SymbolicSparseRowMatRef::parts

pub fn nrows(&self) -> Rows

see SymbolicSparseRowMatRef::nrows

pub fn ncols(&self) -> Cols

see SymbolicSparseRowMatRef::ncols

pub fn shape(&self) -> (Rows, Cols)

see SymbolicSparseRowMatRef::as_shape

pub fn transpose(&self) -> SymbolicSparseColMatRef<'_, I, Cols, Rows>

see SymbolicSparseRowMatRef::transpose

pub fn to_owned(&self) -> Result<SymbolicSparseRowMat<I, Rows, Cols>, FaerError>

see SymbolicSparseRowMatRef::to_owned

pub fn to_col_major( &self, ) -> Result<SymbolicSparseColMat<I, Rows, Cols>, FaerError>

see SymbolicSparseRowMatRef::to_col_major

pub fn compute_nnz(&self) -> usize

see SymbolicSparseRowMatRef::compute_nnz

pub fn row_ptr(&self) -> &[I]

see SymbolicSparseRowMatRef::row_ptr

pub fn row_nnz(&self) -> Option<&[I]>

see SymbolicSparseRowMatRef::row_nnz

pub fn col_idx(&self) -> &[I]

see SymbolicSparseRowMatRef::col_idx

pub fn row_range(&self, i: Idx<Rows>) -> Range<usize>

see SymbolicSparseRowMatRef::row_range

pub unsafe fn row_range_unchecked(&self, i: Idx<Rows>) -> Range<usize>

see SymbolicSparseRowMatRef::row_range_unchecked

pub fn col_idx_of_row_raw(&self, i: Idx<Rows>) -> &[Idx<Cols, I>]

see SymbolicSparseRowMatRef::col_idx_of_row_raw

pub fn col_idx_of_row( &self, i: Idx<Rows>, ) -> impl '_ + Clone + ExactSizeIterator + DoubleEndedIterator<Item = Idx<Cols>>

see SymbolicSparseRowMatRef::col_idx_of_row

pub fn as_shape<V: Shape, H: Shape>( &self, nrows: V, ncols: H, ) -> SymbolicSparseRowMatRef<'_, I, V, H>

see SymbolicSparseRowMatRef::as_shape

pub fn as_dyn(&self) -> SymbolicSparseRowMatRef<'_, I>

see SymbolicSparseRowMatRef::as_dyn

pub fn as_ref(&self) -> SymbolicSparseRowMatRef<'_, I, Rows, Cols>

Returns a view over the symbolic structure of self.

Trait Implementations

impl<I: Index, T: ComplexField, ViewT: Conjugate<Canonical = T>> BiLinOp<T> for SparseRowMatMut<'_, I, ViewT>

fn transpose_apply_scratch(&self, rhs_ncols: usize, par: Par) -> StackReq

computes the workspace size and alignment required to apply the transpose or adjoint o self to a matrix with rhs_ncols columns

fn transpose_apply( &self, out: MatMut<'_, T>, rhs: MatRef<'_, T>, par: Par, stack: &mut MemStack, )

applies the transpose of self to rhs, and stores the result in out

fn adjoint_apply( &self, out: MatMut<'_, T>, rhs: MatRef<'_, T>, par: Par, stack: &mut MemStack, )

applies the adjoint of self to rhs, and stores the result in out

impl<I: Index, T: ComplexField, ViewT: Conjugate<Canonical = T>> BiPrecond<T> for SparseRowMatMut<'_, I, ViewT>

fn transpose_apply_in_place_scratch( &self, rhs_ncols: usize, par: Par, ) -> StackReq

computes the workspace size and alignment required to apply the transpose or adjoint of self to a matrix with rhs_ncols columns in place

fn transpose_apply_in_place( &self, rhs: MatMut<'_, T>, par: Par, stack: &mut MemStack, )

applies the transpose of self to rhs, and stores the result in rhs

fn adjoint_apply_in_place( &self, rhs: MatMut<'_, T>, par: Par, stack: &mut MemStack, )

applies the adjoint of self to rhs, and stores the result in rhs

impl<Rows: Shape, Cols: Shape, I: Index, T: Debug> Debug for SparseRowMatMut<'_, I, T, Rows, Cols>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'a, Rows: Shape, Cols: Shape, I: Index, T> Deref for SparseRowMatMut<'a, I, T, Rows, Cols>

type Target = SymbolicSparseRowMat<Ref<'a, I, Rows, Cols>>

The resulting type after dereferencing.

fn deref(&self) -> &Self::Target

Dereferences the value.

impl<I: Index, T> Index<(usize, usize)> for SparseRowMatMut<'_, I, T>

type Output = T

The returned type after indexing.

fn index(&self, (row, col): (usize, usize)) -> &Self::Output

Performs the indexing (container[index]) operation.

impl<I: Index, T> IndexMut<(usize, usize)> for SparseRowMatMut<'_, I, T>

fn index_mut(&mut self, (row, col): (usize, usize)) -> &mut Self::Output

Performs the mutable indexing (container[index]) operation.

impl<I: Index, T: ComplexField, ViewT: Conjugate<Canonical = T>> LinOp<T> for SparseRowMatMut<'_, I, ViewT>

fn nrows(&self) -> usize

output dimension of the operator

fn ncols(&self) -> usize

input dimension of the operator

fn apply_scratch(&self, rhs_ncols: usize, par: Par) -> StackReq

computes the workspace size and alignment required to apply self or the conjugate o self to a matrix with rhs_ncols columns

fn apply( &self, out: MatMut<'_, T>, rhs: MatRef<'_, T>, par: Par, stack: &mut MemStack, )

applies self to rhs, and stores the result in out

fn conj_apply( &self, out: MatMut<'_, T>, rhs: MatRef<'_, T>, par: Par, stack: &mut MemStack, )

applies the conjugate of self to rhs, and stores the result in out

impl<I: Index, T: ComplexField, ViewT: Conjugate<Canonical = T>> Precond<T> for SparseRowMatMut<'_, I, ViewT>

fn apply_in_place_scratch(&self, rhs_ncols: usize, par: Par) -> StackReq

computes the workspace size and alignment required to apply self or the conjugate of self to a matrix with rhs_ncols columns in place

fn apply_in_place(&self, rhs: MatMut<'_, T>, par: Par, stack: &mut MemStack)

applies self to rhs, and stores the result in rhs

fn conj_apply_in_place( &self, rhs: MatMut<'_, T>, par: Par, stack: &mut MemStack, )

applies the conjugate of self to rhs, and stores the result in rhs