Module sparse 

sparse matrix data structures

most sparse matrix algorithms accept matrices in sparse column-oriented format. this format represents each column of the matrix by storing the row indices of its non-zero elements, as well as their values

the indices and the values are each stored in a contiguous slice (or group of slices for arbitrary values). in order to specify where each column starts and ends, a slice of size ncols + 1 stores the start of each column, with the last element being equal to the total number of non-zeros (or the capacity in uncompressed mode)

example

consider the 4-by-5 matrix:

[[10.0, 0.0, 12.0, -1.0, 13.0]
 [ 0.0, 0.0, 25.0, -2.0,  0.0]
 [ 1.0, 0.0,  0.0,  0.0,  0.0]
 [ 4.0, 0.0,  0.0,  0.0,  5.0]]

the matrix is stored as follows (with | marking column boundaries and , separating intra-column values):

column pointers: | 0                | 3 | 3           | 5           | 7           | 9

row indices    : |    0 ,   2 ,   3 |   |    0 ,    1 |    0 ,    1 |    0 ,    3 |
values         : | 10.0 , 1.0 , 4.0 |   | 12.0 , 25.0 | -1.0 , -2.0 | 13.0 ,  5.0 |

this is the standard compressed sparse column (csc) layout, see wikipedia.org/wiki/Sparse_matrix

Modules

csc_numeric

implementation of numeric representation

csc_symbolic

implementation of symbolic representation

csr_numeric

implementation of numeric representation

csr_symbolic

implementation of symbolic representation

linalg

sparse linear algebra module. contains low level routines and the implementation of their corresponding high level wrappers

ops

sparse matrix binary and ternary operation implementations

utils

algorithmic primitives for sparse matrices

Structs

Argsort

the order values should be read in, when constructing/filling from indices and values

Pair

pair of indices with C-compatible layout

Triplet

triplet of indices and value with C-compatible layout

Enums

CreationError

errors that can occur during the creation of sparse matrices from user input

FaerError

errors that can occur in sparse algorithms

Type Aliases

SparseColMat

owning sparse column major matrix

SparseColMatMut

view over sparse column major matrix

SparseColMatRef

view over sparse column major matrix

SparseRowMat

owning sparse row major matrix

SparseRowMatMut

view over sparse row major matrix

SparseRowMatRef

view over sparse row major matrix

SymbolicSparseColMat

owning symbolic structure of sparse matrix in column format, either compressed or uncompressed

SymbolicSparseColMatRef

symbolic view structure of sparse matrix in column format, either compressed or uncompressed

SymbolicSparseRowMat

owning symbolic structure of sparse matrix in row format, either compressed or uncompressed

SymbolicSparseRowMatRef

symbolic view structure of sparse matrix in row format, either compressed or uncompressed