Robust Sparse data types 1.0

The main file in this package, rsparse.m, creates a sparse array object that is a subclass of MATLAB's native sparse data type, but which is robust against certain bugs and errors (present as of R2009b). S=rsparse(varargin) The I/O syntax and options for rsparse() are identical to that of sparse(). Where sparse() would return a double sparse matrix, rsparse() will return a matrix of class RobustSparseDouble, a class defined in this package. Similarly, wherever sparse() would return a logical sparse matrix, rsparse() will return a matrix of user-defined class RobustSparseLogical. %%%%%%%%% EXAMPLE 1: Indexing robustness - this utilizes the sparse-sub-access package by Bruno Luong. >> A=sparse(100000,100000,1), %native MATLAB sparse matrix A = (100000,100000) 1 >> B=rsparse(A), %convert to robust type B= (100000,100000) 1 >> whos A B Name Size Bytes Class Attributes A 100000x100000 400016 double sparse B 100000x100000 400072 RobustSparseDouble >> A(logical(A))=2, %Wrong result due to indexing bug A = (65408,14101) 2 (100000,100000) 1 >> B(logical(B))=2, %RIGHT!!! B= (100000,100000) 2 %%%%%%%%% EXAMPLE 2: Robustness to mixed data type operations. For some reason, MATLAB decides to issue an error when a mathematical operation involving sparse and non-double numeric data is attempted: A=speye(3); x=single([1;2;3]); >> y=A*x, %ANNOYING.... ??? Error using ==> mtimes Sparse single arrays are not supported. The RobustSparse types, however, will silently pre-convert the foreign data to doubles: B=rsparse(A); >>y=B*x, %BETTER!!! y = 1 2 3 %%%%%%%%%%%%%%%%%%%%%% I'm hoping that TMW will fix these problems soon, rendering this package obsolete. Once they do, simply replace the code in rsparse.m with the following, and rsparse() will become equivalent to sparse() function S=rsparse(varargin) S=sparse(varargin{:}); end The package also includes "robustified" versions of other common sparfun toolbox routines: rspeye, rsprand, rsprandn, rprandsym,... They too will revert to their native MATLAB versions when the above replacement is made.%%%%%%%% CAUTIONARY NOTES: (1) Because this package uses various M-coded wrappers for built-in sparse routines, there is obviously some compromise in speed. (2) I've overloaded all math operators (+ , - , .* , >=,

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Doubles,  Foreign,  Gtgty Dbx,  Hoping,  Preconvert,  Silently,  Simply,  Types
Users rating:	0/10