### 22.6 Function Reference

#### 22.6.1 Functions by Category

##### 22.6.1.1 Generate sparse matrix

spdiags
  A generalization of the function `spdiag'.
speye
  Returns a sparse identity matrix.
sprand
  Generate a random sparse matrix.
sprandn
  Generate a random sparse matrix.
sprandsym
  Generate a symmetric random sparse matrix.

##### 22.6.1.2 Sparse matrix conversion

full
  returns a full storage matrix from a sparse one See also: sparse
sparse
  SPARSE: create a sparse matrix
spconvert
  This function converts for a simple sparse matrix format easily produced by other programs into Octave's internal sparse format.
spfind
  SPFIND: a sparse version of the find operator 1.

##### 22.6.1.3 Manipulate sparse matrices

issparse
  Return 1 if the value of the expression EXPR is a sparse matrix.
nnz
  returns number of non zero elements in SM See also: sparse
nonzeros
  Returns a vector of the non-zero values of the sparse matrix S
nzmax
  Returns the amount of storage allocated to the sparse matrix SM.
spalloc
  Returns an empty sparse matrix of size R-by-C.
spfun
  Compute `f(X)' for the non-zero values of X This results in a sparse matrix with the same structure as X.
spones
  Replace the non-zero entries of X with ones.
spy
  Plot the sparsity pattern of the sparse matrix X

##### 22.6.1.4 Graph Theory

etree
  Returns the elimination tree for the matrix S.
etreeplot
  Plots the elimination tree of the matrix s or s`+`s`'` if s in non-symmetric.
gplot
  Plots a graph defined by A and xy in the graph theory sense.
treelayout
  Not implemented
treeplot
  Produces a graph of a tree or forest.

##### 22.6.1.5 Sparse matrix reordering

ccolamd
  Constrained column approximate minimum degree permutation.
colamd
  Column approximate minimum degree permutation.
colperm
  Returns the column permutations such that the columns of `S (:, P)' are ordered in terms of increase number of non-zero elements.
csymamd
  For a symmetric positive definite matrix S, returns the permutation vector p such that `S (P, P)' tends to have a sparser Cholesky factor than S.
dmperm
  Perform a Deulmage-Mendelsohn permutation on the sparse matrix S.
symamd
  For a symmetric positive definite matrix S, returns the permutation vector p such that `S (P, P)' tends to have a sparser Cholesky factor than S.
symrcm
  Not implemented

##### 22.6.1.6 Linear algebra

cholinc
  Not implemented
condest
  Not implemented
eigs
  Not implemented
matrix_type
  Identify the matrix type or mark a matrix as a particular type.
normest
  Not implemented
spchol
  Compute the Cholesky factor, R, of the symmetric positive definite.
spcholinv
  Use the Cholesky factorization to compute the inverse of the sparse symmetric positive definite matrix A.
spchol2inv
  Invert a sparse symmetric, positive definite square matrix from its Cholesky decomposition, U.
spdet
  Compute the determinant of sparse matrix A using UMFPACK.
spinv
  Compute the inverse of the square matrix A.
spkron
  Form the kronecker product of two sparse matrices.
splchol
  Compute the Cholesky factor, L, of the symmetric positive definite.
splu
  Compute the LU decomposition of the sparse matrix A, using subroutines from UMFPACK.
spqr
  Compute the sparse QR factorization of a, using CSPARSE.
sprank
  Not implemented
svds
  Not implemented

##### 22.6.1.7 Iterative techniques

bicg
  Not implemented
bicgstab
  Not implemented
cgs
  Not implemented
gmres
  Not implemented
luinc
  Produce the incomplete LU factorization of the sparse matrix A.
lsqr
  Not implemented
minres
  Not implemented
pcg
  Solves the linear system of equations A`*` x`=` b by means of the Preconditioned Conjugate Gradient iterative method.
pcr
  Solves the linear system of equations A`*` x`=` b by means of the Preconditioned Conjugate Residual iterative method.
qmr
  Not implemented
symmlq
  Not implemented

##### 22.6.1.8 Miscellaneous

spaugment
  Not implemented
spparms
  Sets or displays the parameters used by the sparse solvers and factorization functions.
symbfact
  Performs a symbolic factorization analysis on the sparse matrix S.
spstats
  Return the stats for the non-zero elements of the sparse matrix S COUNT is the number of non-zeros in each column, MEAN is the mean of the non-zeros in each column, and VAR is the variance of the non-zeros in each column
spprod
  Product of elements along dimension DIM.
spcumprod
  Cumulative product of elements along dimension DIM.
spcumsum
  Cumulative sum of elements along dimension DIM.
spsum
  Sum of elements along dimension DIM.
spsumsq
  Sum of squares of elements along dimension DIM.
spmin
  For a vector argument, return the minimum value.
spmax
  For a vector argument, return the maximum value.
spatan2
  Compute atan (Y / X) for corresponding sparse matrix elements of Y and X.
spdiag
  Return a diagonal matrix with the sparse vector V on diagonal K.

#### 22.6.2 Functions Alphabetically