Struct SparseJacobian 

pub struct SparseJacobian<F: IntegrateFloat> {
    pub pattern: SparsePattern,
    pub values: Vec<F>,
    pub index_map: HashMap<(usize, usize), usize>,
}

Sparse Jacobian representation

Fields

pattern: SparsePattern

The sparsity pattern

values: Vec<F>

Non-zero values in row-major order

index_map: HashMap<(usize, usize), usize>

Mapping from (row, col) to value index

Implementations

impl<F: IntegrateFloat> SparseJacobian<F>

pub fn new(pattern: SparsePattern) -> Self

Create a new sparse Jacobian

pub fn set(&mut self, row: usize, col: usize, value: F) -> IntegrateResult<()>

Set a value in the sparse Jacobian

pub fn get(&self, row: usize, col: usize) -> Option<F>

Get a value from the sparse Jacobian

pub fn to_dense(&self) -> Array2<F>

Convert to dense matrix

pub fn matvec(&self, x: ArrayView1<'_, F>) -> IntegrateResult<Array1<F>>

Multiply by a vector: y = J * x

pub fn matvec_transpose( &self, x: ArrayView1<'_, F>, ) -> IntegrateResult<Array1<F>>

Transpose multiply by a vector: y = J^T * x

impl<F: IntegrateFloat> SparseJacobian<F>

pub fn from_pattern(pattern: SparsePattern) -> Self

Create a new sparse Jacobian from pattern

pub fn set_unchecked(&mut self, row: usize, col: usize, value: F)

Set a value without error checking

pub fn get_or_zero(&self, row: usize, col: usize) -> F

Get a value with default zero

pub fn to_dense_alt(&self) -> Array2<F>

Convert to dense matrix (alternative implementation)

pub fn apply(&self, x: ArrayView1<'_, F>) -> IntegrateResult<Array1<F>>

Apply to vector (matrix-vector multiplication)

pub fn to_csr(&self) -> CSRJacobian<F>

Convert to CSR format for efficient row operations