Struct BsrArray

pub struct BsrArray<T>
where
    T: Float + Add<Output = T> + Sub<Output = T> + Mul<Output = T> + Div<Output = T> + Debug + Copy + 'static + AddAssign,
{ /* private fields */ }

BSR Array format

The BSR (Block Sparse Row) format stores a sparse matrix as a sparse matrix of dense blocks. It’s particularly efficient for matrices with block-structured sparsity patterns, such as those arising in finite element methods.

Notes

• Very efficient for matrices with block structure
• Fast matrix-vector products for block-structured matrices
• Reduced indexing overhead compared to CSR for block-structured problems
• Not efficient for general sparse matrices
• Difficult to modify once constructed

Implementations

impl<T> BsrArray<T>

where T: Float + Add<Output = T> + Sub<Output = T> + Mul<Output = T> + Div<Output = T> + Debug + Copy + 'static + AddAssign,

pub fn new( data: Vec<Vec<Vec<T>>>, indices: Vec<Vec<usize>>, indptr: Vec<usize>, shape: (usize, usize), block_size: (usize, usize), ) -> SparseResult<Self>

Create a new BSR array from raw data

Arguments

• data - Block data (blocks stored row by row)
• indices - Column indices for each block
• indptr - Row pointers
• shape - Tuple containing the array dimensions (rows, cols)
• block_size - Tuple containing the block dimensions (r, c)

Returns

• A new BSR array

Examples

use scirs2_sparse::bsr_array::BsrArray;
use scirs2_sparse::sparray::SparseArray;

// Create a 4x4 sparse array with 2x2 blocks
// [1 2 0 0]
// [3 4 0 0]
// [0 0 5 6]
// [0 0 7 8]

let block1 = vec![vec![1.0, 2.0], vec![3.0, 4.0]];
let block2 = vec![vec![5.0, 6.0], vec![7.0, 8.0]];

let data = vec![block1, block2];
let indices = vec![vec![0], vec![1]];
let indptr = vec![0, 1, 2];

let array = BsrArray::new(data, indices, indptr, (4, 4), (2, 2)).unwrap();
assert_eq!(array.shape(), (4, 4));
assert_eq!(array.nnz(), 8); // All elements in the blocks are non-zero

pub fn empty( shape: (usize, usize), block_size: (usize, usize), ) -> SparseResult<Self>

Create a new empty BSR array

Arguments

• shape - Tuple containing the array dimensions (rows, cols)
• block_size - Tuple containing the block dimensions (r, c)

Returns

• A new empty BSR array

pub fn from_triplets( row: &[usize], col: &[usize], data: &[T], shape: (usize, usize), block_size: (usize, usize), ) -> SparseResult<Self>

Convert triplets to BSR format

Arguments

• row - Row indices
• col - Column indices
• data - Data values
• shape - Shape of the array
• block_size - Size of the blocks

Returns

• A new BSR array

Trait Implementations

impl<T> Clone for BsrArray<T>

where T: Float + Add<Output = T> + Sub<Output = T> + Mul<Output = T> + Div<Output = T> + Debug + Copy + 'static + AddAssign + Clone,

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

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<T> Display for BsrArray<T>

where T: Float + Add<Output = T> + Sub<Output = T> + Mul<Output = T> + Div<Output = T> + Debug + Copy + 'static + AddAssign,

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

Formats the value using the given formatter.

impl<T> SparseArray<T> for BsrArray<T>

where T: Float + Add<Output = T> + Sub<Output = T> + Mul<Output = T> + Div<Output = T> + Debug + Copy + 'static + AddAssign,

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

Returns the shape of the sparse array.

fn nnz(&self) -> usize

Returns the number of stored (non-zero) elements.

fn dtype(&self) -> &str

Returns the data type of the sparse array.

fn to_array(&self) -> Array2<T>

Returns a view of the sparse array as a dense ndarray.

fn toarray(&self) -> Array2<T>

Returns a dense copy of the sparse array.

fn to_coo(&self) -> SparseResult<Box<dyn SparseArray<T>>>

Returns a sparse array in COO format.

fn to_csr(&self) -> SparseResult<Box<dyn SparseArray<T>>>

Returns a sparse array in CSR format.

fn to_csc(&self) -> SparseResult<Box<dyn SparseArray<T>>>

Returns a sparse array in CSC format.

fn to_dok(&self) -> SparseResult<Box<dyn SparseArray<T>>>

Returns a sparse array in DOK format.

fn to_lil(&self) -> SparseResult<Box<dyn SparseArray<T>>>

Returns a sparse array in LIL format.

fn to_dia(&self) -> SparseResult<Box<dyn SparseArray<T>>>

Returns a sparse array in DIA format.

fn to_bsr(&self) -> SparseResult<Box<dyn SparseArray<T>>>

Returns a sparse array in BSR format.

fn add( &self, other: &dyn SparseArray<T>, ) -> SparseResult<Box<dyn SparseArray<T>>>

Element-wise addition.

fn sub( &self, other: &dyn SparseArray<T>, ) -> SparseResult<Box<dyn SparseArray<T>>>

Element-wise subtraction.

fn mul( &self, other: &dyn SparseArray<T>, ) -> SparseResult<Box<dyn SparseArray<T>>>

Element-wise multiplication.

fn div( &self, other: &dyn SparseArray<T>, ) -> SparseResult<Box<dyn SparseArray<T>>>

Element-wise division.

fn dot( &self, other: &dyn SparseArray<T>, ) -> SparseResult<Box<dyn SparseArray<T>>>

Matrix multiplication.

fn dot_vector(&self, other: &ArrayView1<'_, T>) -> SparseResult<Array1<T>>

Matrix-vector multiplication.

fn transpose(&self) -> SparseResult<Box<dyn SparseArray<T>>>

Transpose the sparse array.

fn copy(&self) -> Box<dyn SparseArray<T>>

Return a copy of the sparse array with the specified elements.

fn get(&self, i: usize, j: usize) -> T

Get a value at the specified position.

fn set(&mut self, i: usize, j: usize, value: T) -> SparseResult<()>

Set a value at the specified position.

fn eliminate_zeros(&mut self)

Eliminate zeros from the sparse array.

fn sort_indices(&mut self)

Sort indices of the sparse array.

fn sorted_indices(&self) -> Box<dyn SparseArray<T>>

Return a sorted copy of this sparse array.

fn has_sorted_indices(&self) -> bool

Check if indices are sorted.

fn sum(&self, axis: Option<usize>) -> SparseResult<SparseSum<T>>

Sum the sparse array elements.

fn max(&self) -> T

Compute the maximum value of the sparse array elements.

fn min(&self) -> T

Compute the minimum value of the sparse array elements.

fn find(&self) -> (Array1<usize>, Array1<usize>, Array1<T>)

Return the indices and values of the nonzero elements.

fn slice( &self, row_range: (usize, usize), col_range: (usize, usize), ) -> SparseResult<Box<dyn SparseArray<T>>>

Return a slice of the sparse array.

fn as_any(&self) -> &dyn Any

Returns the concrete type of the array for downcasting.