Struct SymbolicSparseRowMat

pub struct SymbolicSparseRowMat<I>
where
    I: Index,
{
    pub(crate) nrows: usize,
    pub(crate) ncols: usize,
    pub(crate) row_ptr: Vec<I>,
    pub(crate) row_nnz: Option<Vec<I>>,
    pub(crate) col_ind: Vec<I>,
}

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

Requires:

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

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

• row_ptrs has length nrows + 1 (always checked)

• row_ptrs is non-decreasing

• row_ptrs[0]..row_ptrs[nrows] is a valid range in row_indices (always checked, assuming non-decreasing)

• if nnz_per_row is None, elements of col_indices[row_ptrs[i]..row_ptrs[i + 1]] are less than ncols

• nnz_per_row[i] <= row_ptrs[i+1] - row_ptrs[i]

• if nnz_per_row is Some(_), elements of col_indices[row_ptrs[i]..][..nnz_per_row[i]] are less than ncols

• Within each row, column indices are sorted in non-decreasing 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.

Fields

nrows: usize

ncols: usize

row_ptr: Vec<I>

row_nnz: Option<Vec<I>>

col_ind: Vec<I>

Implementations

impl<I> SymbolicSparseRowMat<I>

where I: Index,

pub fn new_checked( nrows: usize, ncols: usize, row_ptrs: Vec<I>, nnz_per_row: Option<Vec<I>>, col_indices: Vec<I>, ) -> SymbolicSparseRowMat<I>

Creates a new symbolic matrix view after asserting its invariants.

Panics

See type level documentation.

pub fn new_unsorted_checked( nrows: usize, ncols: usize, row_ptrs: Vec<I>, nnz_per_row: Option<Vec<I>>, col_indices: Vec<I>, ) -> SymbolicSparseRowMat<I>

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

Panics

See type level documentation.

pub unsafe fn new_unchecked( nrows: usize, ncols: usize, row_ptrs: Vec<I>, nnz_per_row: Option<Vec<I>>, col_indices: Vec<I>, ) -> SymbolicSparseRowMat<I>

Creates a new symbolic matrix view without asserting its invariants.

Safety

See type level documentation.

pub fn into_parts(self) -> (usize, usize, Vec<I>, Option<Vec<I>>, Vec<I>)

Returns the components of the matrix in the order:

• row count,
• column count,
• row pointers,
• nonzeros per row,
• column indices.

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

Returns a view over the symbolic structure of self.

pub fn nrows(&self) -> usize

Returns the number of rows of the matrix.

pub fn ncols(&self) -> usize

Returns the number of columns of the matrix.

pub fn shape(&self) -> (usize, usize)

Returns the number of rows and columns of the matrix.

pub fn into_transpose(self) -> SymbolicSparseColMat<I>

Consumes the matrix, and returns its transpose in column-major format without reallocating.

Note

Allows unsorted matrices, producing an unsorted output.

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

Copies the current matrix into a newly allocated matrix.

Note

Allows unsorted matrices, producing an unsorted output.

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

Copies the current matrix into a newly allocated matrix, with column-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 row_ptrs(&self) -> &[I]

Returns the column pointers.

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

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

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

Returns the column indices.

pub fn col_indices_of_row_raw(&self, i: usize) -> &[I]

Returns the column indices of row i.

Panics

Panics if i >= self.nrows().

pub fn col_indices_of_row( &self, i: usize, ) -> impl ExactSizeIterator + DoubleEndedIterator

Returns the column indices of row i.

Panics

Panics if i >= self.ncols().

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

Returns the range that the row i occupies in self.col_indices().

Panics

Panics if i >= self.nrows().

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

Returns the range that the row i occupies in self.col_indices().

Safety

The behavior is undefined if i >= self.nrows().

impl<I> SymbolicSparseRowMat<I>

where I: Index,

pub fn try_new_from_indices( nrows: usize, ncols: usize, indices: &[(I, I)], ) -> Result<(SymbolicSparseRowMat<I>, ValuesOrder<I>), CreationError>

Create a new symbolic structure, and the corresponding order for the numerical values from pairs of indices (row, col).

pub fn try_new_from_nonnegative_indices( nrows: usize, ncols: usize, indices: &[(<I as Index>::Signed, <I as Index>::Signed)], ) -> Result<(SymbolicSparseRowMat<I>, ValuesOrder<I>), CreationError>

Create a new symbolic structure, and the corresponding order for the numerical values from pairs of indices (row, col).

Negative indices are ignored.

Trait Implementations

impl<I> Clone for SymbolicSparseRowMat<I>

where I: Clone + Index,

fn clone(&self) -> SymbolicSparseRowMat<I>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<I> Debug for SymbolicSparseRowMat<I>

where I: Index,

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

Formats the value using the given formatter.