Struct SparseSchurComplementSolver 

pub struct SparseSchurComplementSolver { /* private fields */ }

Sparse Schur Complement Solver for Bundle Adjustment

Implementations

impl SparseSchurComplementSolver

pub fn new() -> Self

pub fn with_ordering(self, ordering: SchurOrdering) -> Self

pub fn with_variant(self, variant: SchurVariant) -> Self

pub fn with_preconditioner(self, preconditioner: SchurPreconditioner) -> Self

pub fn with_cg_params(self, max_iter: usize, tol: f64) -> Self

pub fn block_structure(&self) -> Option<&SchurBlockStructure>

Trait Implementations

impl Clone for SparseSchurComplementSolver

fn clone(&self) -> SparseSchurComplementSolver

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for SparseSchurComplementSolver

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

Formats the value using the given formatter.

impl Default for SparseSchurComplementSolver

fn default() -> Self

Returns the “default value” for a type.

impl StructuredSparseLinearSolver for SparseSchurComplementSolver

fn initialize_structure( &mut self, variables: &HashMap<String, VariableEnum>, variable_index_map: &HashMap<String, usize>, ) -> LinAlgResult<()>

Initialize the solver’s block structure from problem variables.

fn solve_normal_equation( &mut self, residuals: &Mat<f64>, jacobians: &SparseColMat<usize, f64>, ) -> LinAlgResult<Mat<f64>>

Solve the normal equation: (J^T * J) * dx = -J^T * r

fn solve_augmented_equation( &mut self, residuals: &Mat<f64>, jacobians: &SparseColMat<usize, f64>, lambda: f64, ) -> LinAlgResult<Mat<f64>>

Solve the augmented equation: (J^T * J + λI) * dx = -J^T * r

fn get_hessian(&self) -> Option<&SparseColMat<usize, f64>>

Get the cached Hessian matrix

fn get_gradient(&self) -> Option<&Mat<f64>>

Get the cached gradient vector