Struct SymbolicSparseColMatRef

pub struct SymbolicSparseColMatRef<'a, I: Index, R: Shape = usize, C: Shape = usize> { /* private fields */ }

Symbolic view structure of sparse matrix in column format, either compressed or uncompressed.

Requires:

• nrows <= I::Signed::MAX (always checked)

• ncols <= I::Signed::MAX (always checked)

• col_ptrs has length ncols + 1 (always checked)

• col_ptrs is increasing

• col_ptrs[0]..col_ptrs[ncols] is a valid range in row_indices (always checked, assuming increasing)

• if nnz_per_col is None, elements of row_indices[col_ptrs[j]..col_ptrs[j + 1]] are less than nrows

• nnz_per_col[j] <= col_ptrs[j+1] - col_ptrs[j]

• if nnz_per_col is Some(_), elements of row_indices[col_ptrs[j]..][..nnz_per_col[j]] are less than nrows

• Within each column, row indices are sorted in increasing order.

Note

Some algorithms allow working with matrices containing unsorted row indices per column.

Passing such a matrix to an algorithm that does not explicitly permit this is unspecified (though not undefined) behavior.

Implementations

impl<'a, I: Index, R: Shape, C: Shape> SymbolicSparseColMatRef<'a, I, R, C>

pub fn new_checked( nrows: R, ncols: C, col_ptrs: &'a [I], nnz_per_col: Option<&'a [I]>, row_indices: &'a [I], ) -> Self

Creates a new symbolic matrix view after asserting its invariants.

Panics

See type level documentation.

pub fn new_unsorted_checked( nrows: R, ncols: C, col_ptrs: &'a [I], nnz_per_col: Option<&'a [I]>, row_indices: &'a [I], ) -> Self

Creates a new symbolic matrix view from data containing duplicate and/or unsorted row indices per column, after asserting its other invariants.

Panics

See type level documentation.

pub unsafe fn new_unchecked( nrows: R, ncols: C, col_ptrs: &'a [I], nnz_per_col: Option<&'a [I]>, row_indices: &'a [I], ) -> Self

Creates a new symbolic matrix view without asserting its invariants.

Safety

See type level documentation.

pub fn nrows(&self) -> R

Returns the number of rows of the matrix.

pub fn ncols(&self) -> C

Returns the number of columns of the matrix.

pub fn shape(&self) -> (R, C)

Returns the number of rows and columns of the matrix.

pub fn transpose(self) -> SymbolicSparseRowMatRef<'a, I, C, R>

Returns a view over the transpose of self in row-major format.

pub fn to_owned(&self) -> Result<SymbolicSparseColMat<I, R, C>, FaerError>

Copies the current matrix into a newly allocated matrix.

Note

Allows unsorted matrices, producing an unsorted output.

pub fn to_row_major(&self) -> Result<SymbolicSparseRowMat<I, R, C>, FaerError>

Copies the current matrix into a newly allocated matrix, with row-major order.

Note

Allows unsorted matrices, producing a sorted output. Duplicate entries are kept, however.

pub fn compute_nnz(&self) -> usize

Returns the number of symbolic non-zeros in the matrix.

The value is guaranteed to be less than I::Signed::MAX.

Note

Allows unsorted matrices, but the output is a count of all the entries, including the duplicate ones.

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

Returns the column pointers.

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

Returns the count of non-zeros per column of the matrix.

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

Returns the row indices.

pub fn row_indices_of_col_raw(self, j: Idx<C>) -> &'a [Idx<R, I>]

Returns the row indices of column j.

Panics

Panics if j >= self.ncols().

pub fn row_indices_of_col_raw_unbound(self, j: Idx<C>) -> &'a [I]

Returns the row indices of column j.

Panics

Panics if j >= self.ncols().

pub fn row_indices_of_col( self, j: Idx<C>, ) -> impl 'a + Clone + ExactSizeIterator + DoubleEndedIterator<Item = Idx<R>>

Returns the row indices of column j.

Panics

Panics if j >= self.ncols().

pub fn col_range(&self, j: Idx<C>) -> Range<usize>

Returns the range that the column j occupies in self.row_indices().

Panics

Panics if j >= self.ncols().

pub unsafe fn col_range_unchecked(&self, j: Idx<C>) -> Range<usize>

Returns the range that the column j occupies in self.row_indices().

Safety

The behavior is undefined if j >= self.ncols().

pub fn as_shape<V: Shape, H: Shape>( self, nrows: V, ncols: H, ) -> SymbolicSparseColMatRef<'a, I, V, H>

Returns the input matrix with the given shape after checking that it matches the current shape.

pub fn as_dyn(self) -> SymbolicSparseColMatRef<'a, I>

Returns the input matrix with dynamic shape.

Trait Implementations

impl<I: Index, R: Shape, C: Shape> Clone for SymbolicSparseColMatRef<'_, I, R, C>

fn clone(&self) -> Self

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<I: Index, R: Shape, C: Shape> Debug for SymbolicSparseColMatRef<'_, I, R, C>

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

Formats the value using the given formatter.

impl<'a, I: Index, R: Shape, C: Shape> IntoConst for SymbolicSparseColMatRef<'a, I, R, C>

type Target = SymbolicSparseColMatRef<'a, I, R, C>

fn into_const(self) -> Self::Target

impl<'short, I: Index, R: Shape, C: Shape> Reborrow<'short> for SymbolicSparseColMatRef<'_, I, R, C>

type Target = SymbolicSparseColMatRef<'short, I, R, C>

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

impl<'short, I: Index, R: Shape, C: Shape> ReborrowMut<'short> for SymbolicSparseColMatRef<'_, I, R, C>

type Target = SymbolicSparseColMatRef<'short, I, R, C>

fn rb_mut(&mut self) -> Self::Target

impl<I: Index, R: Shape, C: Shape> Copy for SymbolicSparseColMatRef<'_, I, R, C>