Crate sprs

sprs is a sparse linear algebra library for Rust.

It features a sparse matrix type, CsMat, and a sparse vector type, CsVec, both based on the compressed storage scheme.

Features

• sparse matrix/sparse matrix addition, multiplication.
• sparse vector/sparse vector addition, dot product.
• sparse matrix/dense matrix addition, multiplication.
• sparse triangular solves.
• powerful iteration over the sparse structure, enabling easy extension of the library.
• matrix construction using the triplet format, vertical and horizontal stacking, block construction.
• sparse cholesky solver in the separate crate sprs-ldl.
• fully generic integer type for the storage of indices, enabling compact representations.
• planned interoperability with existing sparse solvers such as SuiteSparse.

Quick Examples

Matrix construction:

use sprs::{CsMat, TriMat};

let mut a = TriMat::new((4, 4));
a.add_triplet(0, 0, 3.0_f64);
a.add_triplet(1, 2, 2.0);
a.add_triplet(3, 0, -2.0);

// This matrix type does not allow computations, and must to
// converted to a compatible sparse type, using for example
let b: CsMat<_> = a.to_csr();

Constructing matrix using the more efficient direct sparse constructor

use sprs::{CsMat, CsVec};
let eye : CsMat<f64> = CsMat::eye(3);
let a = CsMat::new_csc((3, 3),
                       vec![0, 2, 4, 5],
                       vec![0, 1, 0, 2, 2],
                       vec![1., 2., 3., 4., 5.]);

Matrix vector multiplication:

use sprs::{CsMat, CsVec};
let eye = CsMat::eye(5);
let x = CsVec::new(5, vec![0, 2, 4], vec![1., 2., 3.]);
let y = &eye * &x;
assert_eq!(x, y);

Matrix matrix multiplication, addition:

use sprs::{CsMat, CsVec};
let eye = CsMat::eye(3);
let a = CsMat::new_csc((3, 3),
                       vec![0, 2, 4, 5],
                       vec![0, 1, 0, 2, 2],
                       vec![1., 2., 3., 4., 5.]);
let b = &eye * &a;
assert_eq!(a, b.to_csc());

Re-exports

pub use crate::indexing::SpIndex;

pub use crate::sparse::CompressedStorage::CSC;

pub use crate::sparse::CompressedStorage::CSR;

pub use SymmetryCheck::*;

pub use PermutationCheck::*;

Modules

approx	Traits for comparing vectors and matrices using the approx traits
array_backend	Fixed size arrays usable for sparse matrices.
binop	Sparse matrix addition, subtraction
errors	Error type for sprs
indexing
io	Serialization and deserialization of sparse matrices
linalg
num_kinds	Trait to be able to know at runtime if a generic scalar is an integer, a float or a complex.
prod
smmp	Implementation of the paper Bank and Douglas, 2001, Sparse Matrix Multiplication Package (SMPP)
special_mats
stack
vec
visu

Structs

CsIter
CsMatBase	Compressed matrix in the CSR or CSC format, with sorted indices.
CsVecBase	A sparse vector, storing the indices of its non-zero data.
IndPtrBase
Permutation
TriMatBase	Sparse matrix in the triplet format.
TriMatIter	An iterator over elements of a sparse matrix, in the triplet format

Enums

CompressedStorage	Describe the storage of a CsMat
FillInReduction	The different kinds of fill-in-reduction algorithms supported by sprs
PermutationCheck	Configuration enum to ask for permutation checks in algorithms
SymmetryCheck	Configuration enum to ask for symmetry checks in algorithms

Traits

DenseVector	A trait for types representing dense vectors, useful for expressing algorithms such as sparse-dense dot product, or linear solves.
DenseVectorMut	Trait for dense vectors that can be modified, useful for expressing algorithms which compute a resulting dense vector, such as solvers.
MulAcc	Trait for types that have a multiply-accumulate operation, as required in dot products and matrix products.
SparseMat	A trait for common members of sparse matrices

Functions

assign_to_dense	Assign a sparse matrix into a dense matrix
bmat	Specify a sparse matrix by constructing it from blocks of other matrices
hstack	Construct a sparse matrix by horizontally stacking other matrices
is_symmetric
kronecker_product	Compute the Kronecker product between two matrices
perm_is_valid
transform_mat_papt	Compute the square matrix resulting from the product P * A * P^T
vstack	Construct a sparse matrix by vertically stacking other matrices

Type Definitions

CsMat
CsMatI
CsMatVecView
CsMatView
CsMatViewI
CsMatViewMut
CsMatViewMutI
CsStructure
CsStructureI
CsStructureView
CsStructureViewI
CsVec
CsVecI
CsVecView
CsVecViewI
CsVecViewMut
CsVecViewMutI
IndPtr
IndPtrView
Ix1
Ix2
PermOwned
PermOwnedI
PermView
PermViewI
Shape	The shape of a matrix. This a 2-tuple with the first element indicating the number of rows, and the second element indicating the number of columns.
TriMat
TriMatI
TriMatView
TriMatViewI
TriMatViewMut
TriMatViewMutI