Struct CsrMatrix 

pub struct CsrMatrix<T> { /* private fields */ }

Compressed Sparse Row matrix.

Three-array representation: offsets (len = rows+1), col_indices (len = nnz), values (len = nnz). Row i has nonzeros at positions offsets[i]..offsets[i+1].

All invariants are validated at construction time (provable contract).

Implementations

impl<T: Clone + Default> CsrMatrix<T>

pub fn new( rows: usize, cols: usize, offsets: Vec<u32>, col_indices: Vec<u32>, values: Vec<T>, ) -> Result<Self, SparseError>

Create a CSR matrix with full validation.

Contract: sparse-spmv-v1.yaml / format_validation

Validates all CSR invariants before construction.

Errors

Returns error if any CSR invariant is violated.

pub fn from_coo(coo: &CooMatrix<T>) -> Self

where T: AddAssign + Copy,

Convert from COO format to CSR.

Sorts triplets by row, then by column within each row. Duplicate entries are summed (standard convention).

pub fn identity(n: usize) -> Self

where T: From<f32>,

Create an identity matrix of size n.

pub fn rows(&self) -> usize

Number of rows.

pub fn cols(&self) -> usize

Number of columns.

pub fn nnz(&self) -> usize

Number of stored nonzero entries.

pub fn offsets(&self) -> &[u32]

Row offsets array (len = rows + 1).

pub fn col_indices(&self) -> &[u32]

Column indices array (len = nnz).

pub fn values(&self) -> &[T]

Values array (len = nnz).

pub fn avg_nnz_per_row(&self) -> f64

Average number of nonzeros per row.

pub fn row_length_variance(&self) -> f64

Variance of row lengths (key metric for algorithm selection).

High variance → merge-based SpMV; low variance → row-split SpMV.

pub fn to_dense(&self) -> Vec<T>

where T: Copy + AddAssign,

Convert to dense matrix (row-major).

Trait Implementations

impl<T: Clone> Clone for CsrMatrix<T>

fn clone(&self) -> CsrMatrix<T>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<T: Debug> Debug for CsrMatrix<T>

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

Formats the value using the given formatter.

impl SparseOps for CsrMatrix<f32>

fn spmv( &self, alpha: f32, x: &[f32], beta: f32, y: &mut [f32], ) -> Result<(), SparseError>

Sparse matrix-vector multiply: y = α * A * x + β * y

fn spmm( &self, alpha: f32, b: &[f32], b_cols: usize, beta: f32, c: &mut [f32], ) -> Result<(), SparseError>

Sparse matrix-dense matrix multiply: C = α * A * B + β * C