setuptestpoint

 SETUPTESTPOINT sets a point from original Pennon for comparison
 prob ... initialized object with the same problem as it is stored in DCF
 filename ... name (path) to a DCF (Data Container File) generated from
   Pennon suit, so far PenSDP (for linear SDP stored in SDPA) or Pennon/Pennlp
   for Ampl problems
 type ... what's the type (origin) of the DCF? either 'pennlp' or 'pensdp'

0001 
0002 function [alx,aldx,alddx] = setuptestpoint(obj, filename, type)
0003 % SETUPTESTPOINT sets a point from original Pennon for comparison
0004 % prob ... initialized object with the same problem as it is stored in DCF
0005 % filename ... name (path) to a DCF (Data Container File) generated from
0006 %   Pennon suit, so far PenSDP (for linear SDP stored in SDPA) or Pennon/Pennlp
0007 %   for Ampl problems
0008 % type ... what's the type (origin) of the DCF? either 'pennlp' or 'pensdp'
0009 
0010 % This file is a part of PENLAB package distributed under GPLv3 license
0011 % Copyright (c) 2013 by  J. Fiala, M. Kocvara, M. Stingl
0012 % Last Modified: 27 Nov 2013
0013 
0014   % make datatransfer quiet?
0015   global DCF_SILENT
0016   DCF_SILENT=1;
0017 
0018   if (strcmpi(type,'pennlp') || strcmpi(type,'nlp'))
0019 
0020     % unfortunately, it is impossible to identify content of the dcf file
0021     % automatically ... so it is expected that all dcf files are in the same
0022     % format (for now, xUPgHAuf)
0023 
0024     % read the data and check their dimensions
0025     x=datatransfer(filename,0);     % dim Nx
0026     pen_u=datatransfer(filename,1); % dim Nxbox+Nineq+Neq
0027       % lagr. mlt. for all mixed together (box, NLN, LIN; NLN & LIN include eq)
0028       % order of transformed inequalities: lb<=g(x)<=ub should be the same
0029       % as here, i.e., lb-g(x)<=0 followed by g(x)-ub<=0
0030     pen_p=datatransfer(filename,2); % dtto as pen_u but for penalty parameters
0031     aldx=datatransfer(filename,3);  % gradient of augm. lagr.
0032     pen_H=datatransfer(filename,4); % either (1,1) block of KKT or the whole one
0033     pen_A=datatransfer(filename,5); % Jacobian of equalities if store separately
0034     ueq=datatransfer(filename,6);   % Lagr. mlt. for equalities
0035     alx=datatransfer(filename,7);   % value of augm. lagr. without penalization
0036       % of violation of equalitites (i.e. augm. lagr., not merit function)
0037 
0038     % check if the 'obj' looks compatible and copy all the data
0039     if (length(x)~=obj.Nx || obj.NYnnz~=0)
0040       error('DCF does not fit the number of variables.');
0041     end
0042     if (obj.NA~=0)
0043       error('Problem object is not a NLP (only) problem.');
0044     end
0045     if (length(pen_u)~=obj.Nxbox+obj.Nineq+obj.Neq)
0046       error('Problem object does not seem to be defined by the same NLP model');
0047     end
0048     if (length(pen_u)~=length(pen_p))
0049       error('Arrays U and P in DCF are of different size? Corrupted DCF?');
0050     end
0051     if (length(pen_u)~=length(obj.userdata.BEQUAL_M2))
0052       error('Mapping to separate ineq+eq is incompatible, different problem loaded?');
0053     end
0054     if (length(aldx)~=obj.Nx)
0055       error('DCF looks incompatible (because of aldx).');
0056     end
0057     if (length(ueq)~=obj.Neq)
0058       error('Different number of equalities.');
0059     end
0060     % check pen_H, pen_A ?
0061 
0062     % get only inequality multipliers and penalties
0063     u=pen_u(~obj.userdata.BEQUAL_M2);
0064     p=pen_p(~obj.userdata.BEQUAL_M2);
0065 
0066     % copy everything
0067     obj.xall=x;
0068     obj.uxbox=u(1:obj.Nxbox);
0069     obj.uineq=u(obj.Nxbox+1:end);
0070     obj.pxbox=p(1:obj.Nxbox);
0071     obj.pineq=p(obj.Nxbox+1:end);
0072     obj.ueq=ueq;
0073     
0074     % transform Hessian from eqltymode=3 (e.i., separate equality Jacobian)
0075     [pha,phb]=size(pen_H);
0076     if (obj.Neq~=0 && isempty(pen_A) && pha==obj.Nx+obj.Neq && phb==pha)
0077       disp('  ---Separating equalities from input data.---');
0078       disp(' ');
0079       pen_A = pen_H(1:obj.Nx,(obj.Nx+1):phb);
0080       pen_H = pen_H(1:obj.Nx,1:obj.Nx);
0081     %else
0082     %  warning('strange pen_H??');
0083     end
0084 
0085     % Do NOT trust to the dense hessian, only upper half is for sure complete
0086     if (~issparse(pen_H))
0087       disp('  ---pen_H is dense, symmetrizing it for sure---');
0088       disp(' ');
0089       pen_H_ut=triu(pen_H,1);
0090       %pen_H = pen_H.*triu(ones(obj.Nx,obj.Nx)) + pen_H_ut';
0091       pen_H = triu(pen_H) + pen_H_ut';
0092     end
0093 
0094     alddx=[pen_H, pen_A; pen_A', sparse(obj.Neq,obj.Neq)];
0095 
0096   elseif (strcmpi(type,'pensdp') || strcmpi(type,'sdp'))
0097     % reads/decodes the saved data structure from Pennon (linear) SDP
0098     % expect "xUPDfgHv" (default)
0099 
0100     % don't forget that the indices in datatransfer are 0-based!
0101     x=datatransfer(filename,0);  % dim Nx; x
0102     u=datatransfer(filename,1);  % dim Ng; lagr. multiplers for normal inequal.
0103     p=datatransfer(filename,2);  % dim Ng+Na; penalty params for ineq. & matr
0104       % really for both? Yes
0105     dense=datatransfer(filename,3); % density flag
0106     alx=datatransfer(filename,4); % merit function (AL + penalty for equal)
0107     aldx=datatransfer(filename,5);% dim Nx; gradient of AL
0108     alddx=datatransfer(filename,6);% dim Nx x Nx, might be sparse; hessian of AL
0109     % symetrize alddx if dense (perhaps even if sparse? ... Need to test)
0110     if (~issparse(alddx))
0111       % only upper triangle is stored
0112       alddx = alddx+triu(alddx,1)';
0113     end
0114     % matrix constraint lagrangian multipliers
0115     Na = datatransfer(filename,7); % N_MATRIX_CONSTR
0116     umat=cell(Na,1);
0117     for k=1:Na
0118       % either dense ... dim x dim or sparse (dim*(dim+1)/2) x 1
0119       % TODO careful, datatransfer expects double as the number of elements!
0120       % and iterating index is automatically int.
0121       umatk=datatransfer(filename,double(7+k));
0122       if (size(umatk,1)~=size(umatk,2))
0123         % Ak is sparse ==> unpack packed triangular format of umat
0124         % upper triangle, column order (1,2,3,...,dim nnz)
0125         % dim:  2*nnz=dim^2+dim -> 0=d^2+d-2nnz -> D=1+8nnz, d=(-1+-sqrt(D))/2
0126         nnz=size(umatk,1);
0127         dim=(-1+sqrt(1+8*nnz))/2;
0128 
0129         % get mapping for the packed format
0130         Mtmp=triu(ones(dim));
0131         [irow,icol]=find(Mtmp);
0132         utmp=sparse(irow,icol,umatk);
0133         umat{k}=full(utmp+triu(utmp,1)');
0134         %umat{k}(1:10,1:10)
0135         %umatk(1:20)
0136       else
0137         % dense, as it is
0138         umat{k}=umatk;
0139       end
0140     end
0141     
0142     % check if the 'obj' looks compatible and copy all the data
0143     if (length(x)~=obj.Nx || obj.NYnnz~=0)
0144       error('DCF does not fit the number of variables.');
0145     end
0146     if (Na~=obj.NA || obj.NANLN~=0)
0147       error('DCF has different number of matrix constraints.');
0148     end
0149     if (obj.Nxbox~=0 || obj.NgNLN~=0 || obj.Neq~=0)
0150       error('Problem object does not seem to be from SDPA');
0151     end
0152     if (length(u)~=obj.Nineq)
0153       error('DCF has a different number of linear inequalitites.');
0154     end
0155 
0156     obj.xall=x;
0157     obj.uineq=u;  % same order? should be ... only linear ineq.
0158     obj.pineq=p(1:obj.Nineq);
0159     for k=1:Na
0160       obj.UA{k}=umat{k};   % same order? ... should be
0161     end
0162     %obj.UA=umat;
0163     % in Pennon or my Matlab test there used to be 2*p in the computation
0164     % this version use only PA(k) ==> pass it here 2*
0165     obj.PA=2*p(obj.Nineq+1:end);
0166 
0167 
0168   else
0169     error('Unknown type of DCF file.');
0170   end
0171