%%*************************************************************** %% linsysolve: solve linear system to get dy, and direction %% corresponding to unrestricted variables. %% %% [xx,coeff,L,resnrm] = linsysolve(schur,UU,Afree,EE,rhs); %% %% child functions: symqmr.m, mybicgstable.m, linsysolvefun.m %% %% SDPT3: version 3.1 %% Copyright (c) 1997 by %% K.C. Toh, M.J. Todd, R.H. Tutuncu %% Last Modified: 16 Sep 2004 %%*************************************************************** function [xx,coeff,L,resnrm] = linsysolve(par,schur,UU,Afree,EE,rhs); global solve_ok exist_analytic_term global nnzmat nnzmatold matfct_options matfct_options_old use_LU global msg diagR diagRold numpertdiagschur spdensity = par.spdensity; printlevel = par.printlevel; iter = par.iter; if isfield(par,'relgap') & isfield(par,'pinfeas') & isfield(par,'dinfeas') err = max([par.relgap,par.pinfeas,par.dinfeas]); else err = inf; end %% m = length(schur); if (iter==1); use_LU = 0; matfct_options_old = ''; diagR = ones(m,1); numpertdiagschur = 0; end if isempty(nnzmatold); nnzmatold = 0; end diagRold = diagR; %% %% schur = schur + rho*diagschur + lam*AAt %% diagschur = abs(full(diag(schur))); if (par.ublksize) minrho(1) = 1e-15; else minrho(1) = 1e-17; end minrho(1) = max(minrho(1), 1e-6/3.0^iter); %% old: 1e-6/3.0^iter minrho(2) = max(1e-04, 0.7^iter); minlam = max(1e-10, 1e-4/2.0^iter); rho = min(minrho(1), minrho(2)*(1+norm(rhs))/(1+norm(diagschur.*par.y))); lam = min(minlam, 0.1*rho*norm(diagschur)/par.normAAt); if (exist_analytic_term); rho = 0; end; %% important ratio = max(diagR)/min(diagR); if (par.depconstr) | (ratio > 1e10) | (iter < 5) %% important: do not perturb beyond certain threshold %% since it will adversely affect prim_infeas of fp43 %% pertdiagschur = min(rho*diagschur,1e-4./max(1,abs(par.dy))); mexschurfun(schur,full(pertdiagschur)); %%if (printlevel>2); fprintf(' %2.1e',rho); end end if (par.depconstr) | (par.ZpATynorm > 1e10) | (par.ublksize) | (iter < 10) %% Note: do not add this perturbation even if ratio is large. %% It adversely affects hinf15. %% lam = min(lam,1e-4/max(1,norm(par.AAt*par.dy))); if (exist_analytic_term); lam = 0; end mexschurfun(schur,lam*par.AAt); %%if (printlevel>2); fprintf('*'); end end if (max(diagschur)/min(diagschur) > 1e14) & (par.blkdim(2) == 0) ... & (iter > 10) tol = 1e-8; idx = find(diagschur < tol); len = length(idx); pertdiagschur = zeros(m,1); if (len > 0 & len < 5) & (norm(rhs(idx)) < tol) pertdiagschur(idx) = 1*ones(length(idx),1); mexschurfun(schur,pertdiagschur); numpertdiagschur = numpertdiagschur + 1; if (printlevel>2); fprintf('#'); end end end %% %% assemble coefficient matrix %% len = size(Afree,2); if ~isempty(EE) EE(:,[1 2]) = len + EE(:,[1 2]); %% adjust for ublk end EE = [(1:len)' (1:len)' zeros(len,1); EE]; if isempty(EE) coeff.mat22 = []; else coeff.mat22 = spconvert(EE); end if (size(Afree,2) | size(UU,2)) coeff.mat12 = [Afree, UU]; else coeff.mat12 = []; end coeff.mat11 = schur; %% important to use perturbed schur matrix ncolU = size(coeff.mat12,2); %% %% pad rhs with zero vector %% decide which solution methods to use %% rhs = [rhs; zeros(m+ncolU-length(rhs),1)]; if (ncolU > 300); use_LU = 1; end %% %% Cholesky factorization %% L = []; resnrm = norm(rhs); xx = inf*ones(m,1); if (~use_LU) solve_ok = 1; solvesys = 1; nnzmat = mexnnz(coeff.mat11); nnzmatdiff = (nnzmat ~= nnzmatold); if (nnzmat > spdensity*m^2) | (m < 500) matfct_options = 'chol'; else matfct_options = 'spchol'; end if (printlevel>2); fprintf(' %s ',matfct_options); end if strcmp(matfct_options,'chol') if issparse(schur); schur = full(schur); end; if (iter<=5); %%--- to fix strange anonmaly in Matlab mexschurfun(schur,1e-20,2); end L.matfct_options = 'chol'; [L.R,indef] = chol(schur); L.perm = [1:m]; diagR = diag(L.R).^2; elseif strcmp(matfct_options,'spchol') if ~issparse(schur); schur = sparse(schur); end; L.matfct_options = 'spchol'; [L.R,indef,L.perm] = chol(schur,'vector'); L.Rt = L.R'; diagR = full(diag(L.R)).^2; end if (indef) diagR = diagRold; solve_ok = -2; solvesys = 0; msg = 'linsysolve: Schur complement matrix not positive definite'; if (printlevel); fprintf('\n %s',msg); end end if (solvesys) if (ncolU) tmp = coeff.mat12'*linsysolvefun(L,coeff.mat12)-coeff.mat22; if issparse(tmp); tmp = full(tmp); end tmp = 0.5*(tmp + tmp'); [L.Ml,L.Mu,L.Mp] = lu(tmp); tol = 1e-16; condest = max(abs(diag(L.Mu)))/min(abs(diag(L.Mu))); idx = find(abs(diag(L.Mu)) < tol); if ~isempty(idx) | (condest > 1e30); %%old: 1e18 solvesys = 0; solve_ok = -4; use_LU = 1; msg = 'SMW too ill-conditioned, switch to LU factor'; if (printlevel); fprintf('\n %s, %2.1e.',msg,condest); end end end [xx,resnrm,solve_ok] = symqmr(coeff,rhs,L,[],[],printlevel); if (solve_ok <= 0.3) & (printlevel) fprintf('\n warning: symqmr failed: %3.1f ',solve_ok); end end if (solve_ok <= 0.3) tol = 1e-10; if (m < 1e4 & strcmp(matfct_options,'chol') & (err > tol)) ... | (m < 2e5 & strcmp(matfct_options,'spchol') & (err > tol)) use_LU = 1; if (printlevel); fprintf('\n switch to LU factor.'); end end end end %% %% LU factorization %% if (use_LU) nnzmat = mexnnz(coeff.mat11)+mexnnz(coeff.mat12); nnzmatdiff = (nnzmat ~= nnzmatold); solve_ok = 1; solvesys = 1; if ~isempty(coeff.mat22) raugmat = [coeff.mat11, coeff.mat12; coeff.mat12', coeff.mat22]; else raugmat = coeff.mat11; end if (nnzmat > spdensity*m^2) | (m+ncolU < 500) matfct_options = 'lu'; %% lu is better than ldl else matfct_options = 'splu'; end if (printlevel>2); fprintf(' %s ',matfct_options); end if strcmp(matfct_options,'lu') if issparse(raugmat); raugmat = full(raugmat); end L.matfct_options = 'lu'; [L.l,L.u,L.p] = lu(raugmat); L.p = sparse(L.p); [ii,jj] = find(L.p); [dummy,idx] = sort(ii); L.perm = jj(idx); elseif strcmp(matfct_options,'splu') if ~issparse(raugmat); raugmat = sparse(raugmat); end L.matfct_options = 'splu'; L.symmatrix = 0; [L.l,L.u,L.p,L.q] = lu(raugmat); L.perm = [1:length(raugmat)]; elseif strcmp(matfct_options,'ldl') if issparse(raugmat); raugmat = full(raugmat); end L.matfct_options = 'ldl'; [L.L,L.D,L.p] = ldl(raugmat); L.D = sparse(L.D); L.p = sparse(L.p); [ii,jj] = find(L.p); [dummy,idx] = sort(jj); L.perm = ii(idx); elseif strcmp(matfct_options,'spldl') if ~issparse(raugmat); raugmat = sparse(raugmat); end L.matfct_options = 'spldl'; [L.L,L.D,L.perm] = ldl(raugmat,'vector'); L.Lt = L.L'; end if (solvesys) [xx,resnrm,solve_ok] = symqmr(coeff,rhs,L,[],[],printlevel); %%[xx,resnrm,solve_ok] = mybicgstab(coeff,rhs,L,[],[],printlevel); if (solve_ok<=0) & (printlevel) fprintf('\n warning: bicgstab fails: %3.1f,',solve_ok); end end end if (printlevel>2); fprintf('%2.0d ',length(resnrm)-1); end %% nnzmatold = nnzmat; matfct_options_old = matfct_options; %%***************************************************************