Struct DiaArray

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

DIA Array format

The DIA (DIAgonal) format stores data as a collection of diagonals. It is efficient for matrices with values concentrated on a small number of diagonals, like tridiagonal or band matrices.

Notes

• Very efficient storage for band matrices
• Fast matrix-vector products for banded matrices
• Not efficient for general sparse matrices
• Difficult to modify once constructed

Implementations

impl<T> DiaArray<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<Array1<T>>, offsets: Vec<isize>, shape: (usize, usize), ) -> SparseResult<Self>

Create a new DIA array from raw data

Arguments

• data - Diagonals data (n_diags x max(rows, cols))
• offsets - Diagonal offsets from the main diagonal
• shape - Tuple containing the array dimensions (rows, cols)

Returns

• A new DIA array

Examples

use scirs2_sparse::dia_array::DiaArray;
use scirs2_sparse::sparray::SparseArray;
use ndarray::Array1;

// Create a 3x3 sparse array with main diagonal and upper diagonal
let data = vec![
    Array1::from_vec(vec![1.0, 2.0, 3.0]), // Main diagonal
    Array1::from_vec(vec![4.0, 5.0, 0.0]), // Upper diagonal (k=1)
];
let offsets = vec![0, 1]; // Main diagonal and k=1
let shape = (3, 3);

let array = DiaArray::new(data, offsets, shape).unwrap();
assert_eq!(array.shape(), (3, 3));
assert_eq!(array.nnz(), 5); // 3 on main diagonal, 2 on upper diagonal

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

Create a new empty DIA array

Arguments

• shape - Tuple containing the array dimensions (rows, cols)

Returns

• A new empty DIA array

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

Convert COO format to DIA format

Arguments

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

Returns

• A new DIA array

Trait Implementations

impl<T> Clone for DiaArray<T>

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

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

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<T> Display for DiaArray<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 DiaArray<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.