sdpastats

 SDPASTATS gets some statistics (& vision) how the given SDPA problem looks
 for example:
    sdpastats('datafiles/arch0.dat-s');

0001 function []=sdpastats(filename)
0002 % SDPASTATS gets some statistics (& vision) how the given SDPA problem looks
0003 % for example:
0004 %    sdpastats('datafiles/arch0.dat-s');
0005 
0006 % This file is a part of PENLAB package distributed under GPLv3 license
0007 % Copyright (c) 2013 by  J. Fiala, M. Kocvara, M. Stingl
0008 % Last Modified: 27 Nov 2013
0009 
0010   % read the file in
0011   disp(['Reading the input file: ',filename]);
0012   tic;
0013   sdpdata=readsdpa(filename);
0014   toc
0015   Nx=sdpdata.Nx;
0016   Na=sdpdata.Na;
0017 
0018   % create nonzero pattern of all matrices in A
0019   A=cell(Na,1);
0020   Ader=cell(Na,1);
0021   Adim=zeros(Na,1);
0022   Adep=zeros(Na,1);
0023   dim=0;
0024   rowall=[];
0025   colall=[];
0026   for k=1:Na
0027     Akx=spones(sdpdata.A{k,1});
0028     Ader{k}=zeros(5,1);
0029     for i=sdpdata.Adep{k}
0030       Akx = Akx + spones(sdpdata.A{k,i+1});
0031       Ader{k}=sparsetype(Ader{k},sdpdata.A{k,i+1});
0032     end
0033     %figure;spy(Akx);
0034     n=size(Akx,1);
0035     A{k}=Akx;
0036     Adep(k)=length(sdpdata.Adep{k});
0037     Adim(k)=n;
0038     [row,col]=find(Akx);
0039     rowall=[rowall;row+dim];
0040     colall=[colall;col+dim];
0041     dim=dim+n;
0042   end
0043 
0044   Aall=sparse(rowall,colall,ones(size(rowall)),dim,dim);
0045   %figure;
0046   spy(Aall);
0047 
0048   fprintf('Nx = %5i,  NA = %5i\n',Nx,Na);
0049   fprintf('  k:   dim sparsity  #dep    %%dep  |  <5%% <10%% <25%% <50%% >50%%\n');
0050   for k=1:Na
0051     sparsity=nnz(A{k})/Adim(k)/Adim(k)*100;
0052     pct=Adep(k)/Nx*100;
0053     fprintf('%3i: %5i  %5.1f%%  %5i  %5.1f%%  | %4i %4i %4i %4i %4i\n',k,Adim(k),sparsity,Adep(k),pct,Ader{k});
0054   end
0055 
0056 end
0057 
0058 %%%%%
0059 % count which 'category' the given matrix falls into w.r.t. its density
0060 % categoriesL: 5%, 10%, 25%, 50%, >50%
0061 function [der]=sparsetype(der,A)
0062   nz=nnz(A);
0063   n=size(A,1);
0064   nnzmax=n*n;
0065   if (nz<0.05*nnzmax)
0066     der(1)=der(1)+1;
0067   elseif (nz<0.1*nnzmax)
0068     der(2)=der(2)+1;
0069   elseif (nz<0.25*nnzmax)
0070     der(3)=der(3)+1;
0071   elseif (nz<0.5*nnzmax)
0072     der(4)=der(4)+1;
0073   else
0074     der(5)=der(5)+1;
0075   end
0076 end
0077