testmex

 TESTMEX tests that the behaviour of all the mex files is correct

0001 
0002 function []=testmex()
0003 % TESTMEX tests that the behaviour of all the mex files is correct
0004 
0005 % This file is a part of PENLAB package distributed under GPLv3 license
0006 % Copyright (c) 2013 by  J. Fiala, M. Kocvara, M. Stingl
0007 % Last Modified: 27 Nov 2013
0008 
0009   disp('Testing mextrdsdsmat()...');
0010   testmextrdsdsmat()
0011 
0012   disp('Testing mexsumsparse()...');
0013   testmexsumsparse()
0014 
0015 end
0016 
0017 % run all tests on mextrdsdsmat()
0018 function []=testmextrdsdsmat()
0019   
0020   onetestmextrdsds('n=0, all empty', [],[],[],[],0);
0021   onetestmextrdsds('n=1, all ones', 1,1,1,1,2);
0022   onetestmextrdsds('n=1, all nonzeros', 2,3,-4,5,-120*2);
0023   onetestmextrdsds('n=1, A=0', 0,3,-4,5,0);
0024   onetestmextrdsds('n=1, S1=0', 2,0,-4,5,0);
0025   onetestmextrdsds('n=1, B=0', 2,3,0,5,0);
0026   onetestmextrdsds('n=1, S2=0', 2,3,-4,0,0);
0027   %onetestmextrdsds('n=2, all numbers, A diag', diag([2 3]),[-2.1,3.2;3.2,4.4],magic(2)+3,-magic(2)^2); % magic is not symmetric!!!
0028   onetestmextrdsds('n=2, all numbers, A diag', diag([2 3]),[-2.1,3.2;3.2,4.4],[4,6;6,5],[-13,-9;-9,-16]);
0029   onetestmextrdsds('n=2, all numbers, A diag, B=[]', diag([2 3]),[-2.1,3.2;3.2,4.4],magic(2)+3,sparse(2,2),0);
0030   
0031   % build special examples with very sparse matrices
0032   n=5;
0033   A=diag(1:n);
0034   B=magic(n)+magic(n)';
0035   S1=sparse(n,n); S1(2,1)=2;
0036   S1=S1+S1';
0037   S2=sparse(n,n); S2(4,4)=9;
0038   onetestmextrdsds('n=5, very sparse', A,S1,B,S2);
0039 
0040   n=5;
0041   A=diag(1:n);
0042   B=magic(n)+magic(n)';
0043   S1=sparse(n,n); S1(2,1)=2;
0044   S1=S1+S1';
0045   S2=sparse(n,n); S2(2,2)=9;
0046   onetestmextrdsds('n=5, very sparse2', A,S1,B,S2);
0047 
0048   n=5;
0049   A=zeros(n,n);
0050   A(:)=[1:n^2]-10;
0051   A=A+A';
0052   B=magic(n)+magic(n)';
0053   S1=sparse(n,n); S1(2,1)=2;
0054   S1=S1+S1';
0055   S2=sparse(n,n); S2(2,2)=9;
0056   onetestmextrdsds('n=5, very sparse3', A,S1,B,S2);
0057 
0058   n=5;
0059   A=zeros(n,n);
0060   A(:)=[1:n^2]-10;
0061   A=A+A';
0062   B=magic(n)+magic(n)';
0063   S1=sparse(n,n); S1(2,1)=2;
0064   S1=S1+S1';
0065   S2=sparse(diag([5:9]));
0066   onetestmextrdsds('n=5, sparse, S2 spdiag', A,S1,B,S2);
0067 
0068 
0069   % random of different size
0070   for n=[5 5 5 10 10 10 100 100 999 1000]
0071   %for n=[2 5 5]
0072     A=rand(n,n);
0073     A=A+A';
0074     B=rand(n,n);
0075     B=B+B';
0076     S1=sprandsym(n,0.1);
0077     S2=sprandsym(n,0.05);
0078     testname=sprintf('n=%i all random',n);
0079     onetestmextrdsds(testname, A,S1,B,S2);
0080   end
0081 
0082 
0083 end
0084 
0085 % run one test with mextrdsdsmat()
0086 %   testname - string to print out
0087 %   A,B,S1,S2 - matrices for the test
0088 %   red [optional] - reference result, if not present, computed in Matlab
0089 function [ok]=onetestmextrdsds(testname,A,S1,B,S2,ref)
0090 
0091   ok=false;
0092 
0093   if (~issparse(S1))
0094     S1=sparse(S1);
0095   end
0096   if (~issparse(S2))
0097     S2=sparse(S2);
0098   end
0099 
0100   if (nargin==5)
0101     %ref = trace(A*S1*B*S2);
0102     ref = trace(A*S1*B*S2) + trace(A*S2*B*S1);
0103   end
0104   %result = mextrdsdsmat(A,S1,B,S2);
0105   result = mextrcolumn(A,S1,B,{S2});
0106 
0107   if (result==ref)
0108     fprintf(' test %-30s: ok %15.6e\n', testname,result);
0109     ok=true;
0110   elseif (abs(result-ref)<1e-10*(abs(result+ref)))
0111     fprintf(' test %-30s: ok (tol)  %15.6e %15.6e\n', testname,ref,result);
0112     ok=true;
0113   else
0114     fprintf(' test %-30s: FAILED  %15.6e %15.6e\n', testname,ref,result);
0115   end
0116 
0117 end
0118 
0119 % run all tests on mexsumsparse()
0120 function [] = testmexsumsparse()
0121 
0122   % some of Si will be empty...
0123   %onerandtestmexsumsparse('n=1, a few',1,20,0.8);
0124 
0125   onerandtestmexsumsparse('n=5, a few',5,20,0.8);
0126 
0127   onerandtestmexsumsparse('n=30 x1, a few',30,1,0.3);
0128   onerandtestmexsumsparse('n=30 x2, a few',30,2,0.3);
0129   onerandtestmexsumsparse('n=30 x50, a few',30,50,0.1);
0130 
0131   onerandtestmexsumsparse('n=401 x50, a few',401,50,0.1);
0132 
0133   %onerandtestmexsumsparse(testname,n,m,density);
0134 
0135 end
0136 
0137 % run one random test of mexsumsparse
0138 %   n - dimension of matrices
0139 %   m - number of matrices
0140 %   density (0..1) - density of the matrices
0141 function [ok] = onerandtestmexsumsparse(testname,n,m,density)
0142 
0143   ok = false;
0144 
0145   % generate the problem data
0146   S = cell(m,1);
0147   w = rand(m,1);
0148   for i=1:m
0149     S{i} = sprandsym(n,density);
0150   end
0151 
0152   % compute reference result (as dense)
0153   ref = zeros(n,n);
0154   for i=1:m
0155     ref = ref + w(i)*S{i};
0156   end
0157 
0158   % call mex to generate result as dense
0159   rd = mexsumsparse(w,S,-1);
0160 
0161   err = norm(ref-rd,inf);
0162   nrm = norm(ref,inf);
0163 
0164   if (err<1e-10*nrm)
0165     fprintf(' test (dense) %-30s: ok (tol)  %15.6e %15.6e\n', testname,err,nrm);
0166     ok=true;
0167   else
0168     fprintf(' test (dense) %-30s: FAILED  %15.6e %15.6e\n', testname,err,nrm);
0169   end
0170 
0171   % call mex to generate result as sparse (auto)
0172   rd = mexsumsparse(w,S);
0173 
0174   err = norm(ref-rd,inf);
0175 
0176   if (err<1e-10*nrm)
0177     fprintf(' test (auto)  %-30s: ok (tol)  %15.6e %15.6e\n', testname,err,nrm);
0178     ok=true;
0179   else
0180     fprintf(' test (auto)  %-30s: FAILED  %15.6e %15.6e\n', testname,err,nrm);
0181   end
0182 
0183 end