% Welcome to SuiteSparse : a Suite of Sparse matrix packages, containing a % collection of sparse matrix packages authored or co-authored by Tim Davis. % Only the primary MATLAB functions are listed below. % % Example: % SuiteSparse_install - compiles and installs all of SuiteSparse, and runs % several demos and tests. % %------------------- % Ordering methods: %------------------- % % amd - approximate minimum degree ordering. % colamd - column approximate minimum degree ordering. % symamd - symmetrix approximate min degree ordering based on colamd. % camd - constrained amd. % ccolamd - constrained colamd. % csymamd - constrained symamd. % %--------------------------------------------------------------- % CHOLMOD: a sparse supernodal Cholesky update/downdate package: %--------------------------------------------------------------- % % cholmod - computes x=A\b when A is symmetric and positive definite. % chol2 - same as MATLAB chol(sparse(A)), just faster. % lchol - computes an LL' factorization. % ldlchol - computes an LDL' factorization. % ldlupdate - updates an LDL' factorization. % resymbol - recomputes symbolic LL or LDL' factorization. % ldlsolve - solves Ax=b using an LDL' factorization. % ldlsplit - splits LD into L and D. % metis - interface to METIS node-nested-dissection. % nesdis - interface to CHOLMOD's nested-dissection (based on METIS). % septree - prune a separator tree. % bisect - interface to METIS' node bisector. % analyze - order and analyze using CHOLMOD. % etree2 - same as MATLAB "etree", just faster and more reliable. % sparse2 - same as MATLAB "sparse", just faster. % symbfact2 - same as MATLAB "symbfact", just faster and more reliable. % sdmult - same as MATLAB S*F or S'*F (S sparse, F full), just faster. % ldl_normest - compute error in LDL' factorization. % lu_normest - compute error in LU factorization. % mread - read a sparse matrix in Matrix Market format % mwrite - write a sparse matrix in Matrix Market format % spsym - determine the symmetry of a sparse matrix % %------------------------------------------ % CSPARSE: a Concise Sparse matrix package: %------------------------------------------ % % Matrices used in CSparse must in general be either sparse and real, % or dense vectors. Ordering methods can accept any sparse matrix. % % cs_add - sparse matrix addition. % cs_amd - approximate minimum degree ordering. % cs_chol - sparse Cholesky factorization. % cs_cholsol - solve A*x=b using a sparse Cholesky factorization. % cs_counts - column counts for sparse Cholesky factor L. % cs_dmperm - maximum matching or Dulmage-Mendelsohn permutation. % cs_dmsol - x=A\b using the coarse Dulmage-Mendelsohn decomposition. % cs_dmspy - plot the Dulmage-Mendelsohn decomposition of a matrix. % cs_droptol - remove small entries from a sparse matrix. % cs_esep - find an edge separator of a symmetric matrix A % cs_etree - elimination tree of A or A'*A. % cs_gaxpy - sparse matrix times vector. % cs_lsolve - solve a sparse lower triangular system L*x=b. % cs_ltsolve - solve a sparse upper triangular system L'*x=b. % cs_lu - sparse LU factorization, with fill-reducing ordering. % cs_lusol - solve Ax=b using LU factorization. % cs_make - compiles CSparse for use in MATLAB. % cs_multiply - sparse matrix multiply. % cs_nd - generalized nested dissection ordering. % cs_nsep - find a node separator of a symmetric matrix A. % cs_permute - permute a sparse matrix. % cs_print - print the contents of a sparse matrix. % cs_qr - sparse QR factorization. % cs_qleft - apply Householder vectors on the left. % cs_qright - apply Householder vectors on the right. % cs_qrsol - solve a sparse least-squares problem. % cs_randperm - random permutation. % cs_sep - convert an edge separator into a node separator. % cs_scc - strongly-connected components of a square sparse matrix. % cs_scc2 - cs_scc, or connected components of a bipartite graph. % cs_sparse - convert a triplet form into a sparse matrix. % cs_sqr - symbolic sparse QR factorization. % cs_symperm - symmetric permutation of a symmetric matrix. % cs_transpose - transpose a real sparse matrix. % cs_updown - rank-1 update/downdate of a sparse Cholesky factorization. % cs_usolve - solve a sparse upper triangular system U*x=b. % cs_utsolve - solve a sparse lower triangular system U'*x=b. % cspy - plot a sparse matrix in color. % ccspy - plot the connected components of a matrix. % %------------------------------- % LDL: Sparse LDL factorization: %------------------------------- % % ldlsparse - LDL' factorization of a real, sparse, symmetric matrix. % ldlrow - an m-file description of the algorithm used by LDL. % %----------------------------------------------- % UMFPACK: the Unsymmetric MultiFrontal Package: %----------------------------------------------- % % umfpack - computes x=A\b, x=A/b, or lu (A) for a sparse matrix A % umfpack_details - details on all the options for using umfpack in MATLAB % umfpack_report - prints optional control settings and statistics % umfpack_btf - factorize A using a block triangular form % umfpack_solve - x = A\b or x = b/A % lu_normest - estimates norm (L*U-A,1) without forming L*U-A % (duplicate of CHOLMOD/lu_normest, for completeness) % luflop - given L and U, computes # of flops required % %------------------------------------------------------ % RBio: read/write matrices in Rutherford/Boeing format %------------------------------------------------------ % % RBread - read a sparse matrix from a Rutherford/Boeing file % RBreade - read a symmetric finite-element matrix from a R/B file % RBtype - determine the Rutherford/Boeing type of a sparse matrix % RBwrite - write a sparse matrix to a Rutherford/Boeing file % %------------------------------------------------------------------------------- % % For help on compiling SuiteSparse or the demos, testing functions, etc., % please see the help for each individual package. % % NOTE: None of the packages above have yet been ported to 64-bit MATLAB. % Do not attempt to use these in 64-bit MATLAB. % % Copyright 2006, Timothy A. Davis % http://www.cise.ufl.edu/research/sparse help SuiteSparse