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zgscal.m
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1999-03-05
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# Copyright (C) 1996,1998 A. Scottedward Hodel
#
# This file is part of Octave.
#
# Octave is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the
# Free Software Foundation; either version 2, or (at your option) any
# later version.
#
# Octave is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
# FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
# for more details.
#
# You should have received a copy of the GNU General Public License
# along with Octave; see the file COPYING. If not, write to the Free
# Software Foundation, 675 Mass Ave, Cambridge, MA 02139, USA.
function x = zgscal(a,b,c,d,z,n,m,p)
# x = zgscal(f,z,n,m,p) generalized conjugate gradient iteration to
# solve zero-computation generalized eigenvalue problem balancing equation
# fx=z
# called by zgepbal
#
# References:
# ZGEP: Hodel, "Computation of Zeros with Balancing," 1992, submitted to LAA
# Generalized CG: Golub and Van Loan, "Matrix Computations, 2nd ed" 1989
# A. S. Hodel July 24 1992
# Conversion to Octave R. Bruce Tenison July 3, 1994
#**************************************************************************
#initialize parameters:
# Givens rotations, diagonalized 2x2 block of F, gcg vector initialization
#**************************************************************************
nmp = n+m+p;
#x_0 = x_{-1} = 0, r_0 = z
x = zeros(nmp,1);
xk1 = x;
xk2 = x;
rk1 = z;
k = 0;
# construct balancing least squares problem
F = eye(nmp);
for kk=1:nmp
F(1:nmp,kk) = zgfmul(a,b,c,d,F(:,kk));
endfor
[U,H,k1] = krylov(F,z,nmp,1e-12);
if(!is_square(H))
if(columns(H) != k1)
error("zgscal(tzero): k1=%d, columns(H)=%d",k1,columns(H));
elseif(rows(H) != k1+1)
error("zgscal: k1=%d, rows(H) = %d",k1,rows(H));
elseif ( norm(H(k1+1,:)) > 1e-12*norm(H,"inf") )
zgscal_last_row_of_H = H(k1+1,:)
error("zgscal: last row of H nonzero (norm(H)=%e)",norm(H,"inf"))
endif
H = H(1:k1,1:k1);
U = U(:,1:k1);
endif
# tridiagonal H can still be rank deficient, so do permuted qr
# factorization
[qq,rr,pp] = qr(H); # H = qq*rr*pp'
nn = rank(rr);
qq = qq(:,1:nn);
rr = rr(1:nn,:); # rr may not be square, but "\" does least
xx = U*pp*(rr\qq'*(U'*z)); # squares solution, so this works
#xx1 = pinv(F)*z;
#zgscal_x_xx1_err = [xx,xx1,xx-xx1]
return;
# the rest of this is left from the original zgscal;
# I've had some numerical problems with the GCG algorithm,
# so for now I'm solving it with the krylov routine.
#initialize residual error norm
rnorm = norm(rk1,1);
xnorm = 0;
fnorm = 1e-12 * norm([a,b;c,d],1);
# dummy defines for MATHTOOLS compiler
gamk2 = 0; omega1 = 0; ztmz2 = 0;
#do until small changes to x
len_x = length(x);
while ((k < 2*len_x) & (xnorm> 0.5) & (rnorm>fnorm))|(k == 0)
k = k+1;
# solve F_d z_{k-1} = r_{k-1}
zk1= zgfslv(n,m,p,rk1);
# Generalized CG iteration
# gamk1 = (zk1'*F_d*zk1)/(zk1'*F*zk1);
ztMz1 = zk1'*rk1;
gamk1 = ztMz1/(zk1'*zgfmul(a,b,c,d,zk1));
if(rem(k,len_x) == 1) omega = 1;
else omega = 1/(1-gamk1*ztMz1/(gamk2*omega1*ztmz2));
endif
# store x in xk2 to save space
xk2 = xk2 + omega*(gamk1*zk1 + xk1 - xk2);
# compute new residual error: rk = z - F xk, check end conditions
rk1 = z - zgfmul(a,b,c,d,xk2);
rnorm = norm(rk1);
xnorm = max(abs(xk1 - xk2));
#printf("zgscal: k=%d, gamk1=%e, gamk2=%e, \nztMz1=%e ztmz2=%e\n", ...
# k,gamk1, gamk2, ztMz1, ztmz2);
# xk2_1_zk1 = [xk2 xk1 zk1]
# ABCD = [a,b;c,d]
# prompt
# get ready for next iteration
gamk2 = gamk1;
omega1 = omega;
ztmz2 = ztMz1;
[xk1,xk2] = swap(xk1,xk2);
endwhile
x = xk2;
# check convergence
if (xnorm> 0.5 & rnorm>fnorm)
warning("zgscal(tzero): GCG iteration failed; solving with pinv");
# perform brute force least squares; construct F
Am = eye(nmp);
for ii=1:nmp
Am(:,ii) = zgfmul(a,b,c,d,Am(:,ii));
endfor
# now solve with qr factorization
x = pinv(Am)*z;
endif
endfunction