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// Scilab ( http://www.scilab.org/ ) - This file is part of Scilab
// Copyright (C) XXXX-2008 - INRIA
// Copyright (C) 2005 - IRISA - Sage Group
//
// This file must be used under the terms of the CeCILL.
// This source file is licensed as described in the file COPYING, which
// you should have received as part of this distribution. The terms
// are also available at
// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
// [x, flag, err, iter, res] = qmr( A, Ap, b, x, M1, M2, max_it, tol )
//
// QMR solves the linear system Ax=b using the
// Quasi Minimal Residual method with preconditioning.
//
// input A REAL matrix or function
// x REAL initial guess vector
// b REAL right hand side vector
// M1 REAL left preconditioner matrix
// M2 REAL right preconditioner matrix
// max_it INTEGER maximum number of iterations
// tol REAL error tolerance
//
// output x REAL solution vector
// flag INTEGER: 0: solution found to tolerance
// 1: no convergence given max_it
// breakdown:
// -1: rho
// -2: Beta
// -3: gam
// -4: delta
// -5: ep
// -6: xi
// err REAL final residual norm
// iter INTEGER number of iterations performed
// res REAL residual vector
// Details of this algorithm are described in
//
// "Templates for the Solution of Linear Systems: Building Blocks
// for Iterative Methods",
// Barrett, Berry, Chan, Demmel, Donato, Dongarra, Eijkhout,
// Pozo, Romine, and Van der Vorst, SIAM Publications, 1993
// (ftp netlib2.cs.utk.edu; cd linalg; get templates.ps).
//
// "Iterative Methods for Sparse Linear Systems, Second Edition"
// Saad, SIAM Publications, 2003
// (ftp ftp.cs.umn.edu; cd dept/users/saad/PS; get all_ps.zip).
// Sage Group (IRISA, 2005)
function [x, flag, err, iter, res] = qmr( A, varargin)
// -----------------------
// Parsing input arguments
// -----------------------
[lhs,rhs]=argn(0);
if ( rhs < 2 ),
error(msprintf(gettext("%s: Wrong number of input arguments: At least %d expected.\n"),"qmr",2));
end
// Parsing the matrix A
select type(A)
case 1 then
cpt=1;
case 5 then
cpt=1;
case 13 then
cpt=0;
else
error(msprintf(gettext("%s: Wrong type for input argument #%d.\n"),"qmr",1));
end
// If A is a matrix (dense or sparse)
if (cpt==1),
if (size(A,1) ~= size(A,2)),
error(msprintf(gettext("%s: Wrong type for input argument #%d: Square matrix expected.\n"),"qmr",1));
end
deff('y=matvec(x)','y=A*x');
deff('y=matvecp(x)','y=A''*x');
fct=0;
end
// If A is a function
if (cpt==0),
if (rhs == 1),
error(msprintf(gettext("%s: Wrong type for input argument #%d: Transpose of the function %s expected.\n"),"qmr",1,"A"));
end
matvec=A;
fct=1;
end
if (rhs >= 2 & fct==1 ),
matvecp=varargin(1);
if ( type(matvecp) ~= 13 ),
error(msprintf(gettext("%s: Wrong value for input argument #%d: Transpose of the function %s expected.\n"),"qmr",2,"A"));
end
end
// Parsing right hand side b
if ( rhs >= fct+2 ),
b=varargin(fct+1);
if ( size(b,2) ~= 1),
error(msprintf(gettext("%s: Wrong value for input argument #%d: Column vector expected.\n"),"qmr",3));
end
else
error(msprintf(gettext("%s: Wrong value for input argument #%d: Vector expected.\n"),"qmr",3));
end
// Parsing initial vector x
if ( rhs >= fct+3),
x=varargin(fct+2);
if (size(x,2) ~= 1),
error(msprintf(gettext("%s: Wrong type for input argument #%d: Column vector expected.\n"),"qmr",4));
end
if ( size(x,1) ~= size(b,1)),
error(msprintf(gettext("%s: Wrong type for input argument #%d: Same size as the input argument #%d expected.\n"),"qmr",4,3));
end
else
x=zeros(size(b,1),1);
end
//--------------------------------------------------------
// Parsing of the preconditioner matrix M1
//--------------------------------------------------------
if (rhs >=fct+4),
Prec_g=varargin(fct+3);
select type(Prec_g)
case 1 then
cpt=1;
case 5 then
cpt=1;
case 13 then
cpt=0;
end
if ( cpt==1 ),
if (size(Prec_g,1) ~= size(Prec_g,2)),
error(msprintf(gettext("%s: Wrong type for input argument #%d: Square matrix expected.\n"),"qmr",5));
end
if (size(Prec_g,1)~=size(b,1)),
error(msprintf(gettext("%s: Wrong size for input argument #%d: Must be same size as input argument #%d"),"qmr",5,3));
end
deff('y=precond_g(x)','y=Prec_g \ x');
deff('y=precondp_g(x)','y=Prec_g'' \ x');
end
if ( cpt==0 ),
if ( rhs >= fct+5 ),
Precp_g=varargin(fct+4);
select type(Precp_g)
case 1 then
cpt1=1;
case 5 then
cpt1=1;
case 13 then
cpt1=0;
end
if ( cpt1==0 ),
precond_g=Prec_g;
precondp_g=Precp_g;
fct=fct+1;
else
error(msprintf(gettext("%s: Wrong type for input argument #%d: Transpose of the function %s expected.\n"),"qmr",5,"M1"));
end
else
error(msprintf(gettext("%s: Wrong type for input argument #%d: Transpose of the function %s expected.\n"),"qmr",5,"M1"));
end
end
else
deff('y=precond_g(x)','y=x');
deff('y=precondp_g(x)','y=x');
end
//--------------------------------------------------------
// Parsing of the preconditioner matrix M1
//--------------------------------------------------------
if (rhs >=fct+5),
Prec_d=varargin(fct+4);
select type(Prec_d)
case 1 then
cpt=1;
case 5 then
cpt=1;
case 13 then
cpt=0;
end
if ( cpt==1 ),
if (size(Prec_d,1) ~= size(Prec_d,2)),
error(msprintf(gettext("%s: Wrong type for input argument #%d: Square matrix expected.\n"),"qmr",6));
end
if (size(Prec_d,1)~=size(b,1)),
error(msprintf(gettext("%s: Wrong size for input argument #%d: Must be same size as input argument #%d"),"qmr",6,3));
end
deff('y=precond_d(x)','y=Prec_d \ x');
deff('y=precondp_d(x)','y=Prec_d'' \ x');
end
if ( cpt==0 ),
if ( rhs >= fct+6 ),
Precp_d=varargin(fct+5);
select type(Precp_d)
case 1 then
cpt1=1;
case 5 then
cpt1=1;
case 13 then
cpt1=0;
end
if ( cpt1==0 ),
precond_d=Prec_d;
precondp_d=Precp_d;
fct=fct+1;
else
error(msprintf(gettext("%s: Wrong type for input argument #%d: Transpose of the function %s expected.\n"),"qmr",6,"M2"));
end
else
error(msprintf(gettext("%s: Wrong type for input argument #%d: Transpose of the function %s expected.\n"),"qmr",6,"M2"));
end
end
else
deff('y=precond_d(x)','y=x');
deff('y=precondp_d(x)','y=x');
end
//--------------------------------------------------------
// Parsing of the maximum number of iterations max_it
//--------------------------------------------------------
if (rhs >= fct+6),
max_it=varargin(fct+5);
if (size(max_it,1) ~= 1 | size(max_it,2) ~=1),
error(msprintf(gettext("%s: Wrong type for input argument #%d: Scalar expected.\n"),"qmr",7));
end
else
max_it=size(b,1);
end
//--------------------------------------------------------
// Parsing of the error tolerance tol
//--------------------------------------------------------
if (rhs == fct+7),
tol=varargin(fct+6);
if (size(tol,1) ~= 1 | size(tol,2) ~=1),
error(msprintf(gettext("%s: Wrong type for input argument #%d: Scalar expected.\n"),"qmr",8));
end
else
tol=1000*%eps;
end
//--------------------------------------------------------
// test about input arguments number
//--------------------------------------------------------
if (rhs > fct+8),
error(msprintf(gettext("%s: Wrong number of input arguments: %d to %d expected.\n"),"qmr",2,8));
end
// ------------
// Computations
// ------------
// initialization
i = 0;
flag = 0;
bnrm2 = norm( b );
if (bnrm2 == 0.0),
bnrm2 = 1.0;
end
// r = b - A*x;
r = b - matvec(x);
err = norm( r ) / bnrm2;
res = err;
if ( err < tol ), return; end
// [M1,M2] = lu( M );
v_tld = r;
// y = M1 \ v_tld;
y = precond_g(v_tld)
rho = norm( y );
w_tld = r;
// z = M2' \ w_tld;
z = precondp_d(w_tld);
xi = norm( z );
gam = 1.0;
eta = -1.0;
theta = 0.0;
for i = 1:max_it, // begin iteration
if ( rho == 0.0 | xi == 0.0 ), iter=i; break; end
v = v_tld / rho;
y = y / rho;
w = w_tld / xi;
z = z / xi;
delta = z'*y;
if ( delta == 0.0 ), iter=i; break; end
// y_tld = M2 \ y;
y_tld = precond_d(y);
// z_tld = M1'\ z;
z_tld = precondp_g(z);
if ( i > 1 ), // direction vector
p = y_tld - ( xi*delta / ep )*p;
q = z_tld - ( rho*delta / ep )*q;
else
p = y_tld;
q = z_tld;
end
// p_tld = A*p;
p_tld = matvec(p);
ep = q'*p_tld;
if ( ep == 0.0 ), iter=i; break; end
Beta = ep / delta;
if ( Beta == 0.0 ), iter=i; break; end
v_tld = p_tld - Beta*v;
// y = M1 \ v_tld;
y = precond_g(v_tld);
rho_1 = rho;
rho = norm( y );
// w_tld = ( A'*q ) - ( Beta*w );
w_tld = ( matvecp(q) ) - ( Beta*w );
// z = M2' \ w_tld;
z = precondp_d(w_tld);
xi = norm( z );
gamma_1 = gam;
theta_1 = theta;
theta = rho / ( gamma_1*Beta );
gam = 1.0 / sqrt( 1.0 + (theta^2) );
if ( gam == 0.0 ), iter=i; break; end
eta = -eta*rho_1*(gam^2) / ( Beta*(gamma_1^2) );
if ( i > 1 ), // compute adjustment
d = eta*p + (( theta_1*gam )^2)*d;
s = eta*p_tld + (( theta_1*gam )^2)*s;
else
d = eta*p;
s = eta*p_tld;
end
x = x + d; // update approximation
r = r - s; // update residual
err = norm( r ) / bnrm2; // check convergence
res = [res;err];
if ( err <= tol ), iter=i; break; end
if ( i == max_it ), iter=i; end
end
if ( err <= tol ), // converged
flag = 0;
elseif ( rho == 0.0 ), // breakdown
flag = -1;
elseif ( Beta == 0.0 ),
flag = -2;
elseif ( gam == 0.0 ),
flag = -3;
elseif ( delta == 0.0 ),
flag = -4;
elseif ( ep == 0.0 ),
flag = -5;
elseif ( xi == 0.0 ),
flag = -6;
else // no convergence
flag = 1;
end
endfunction
|
