Resurrected vineyard code:
* Switched StaticPersistence + (serializable) Filtration to Boost.MultiIndex
* Updated DynamicPersistenceTrails to work with the new MultiIndex way
* Created LSVineyard class, and fixed the grid examples
# LSQR solver from http://pages.cs.wisc.edu/~kline/cvxopt/
from cvxopt import matrix
from cvxopt.lapack import *
from cvxopt.blas import *
from math import sqrt
"""
a,b are scalars
On exit, returns scalars c,s,r
"""
def SymOrtho(a,b):
aa=abs(a)
ab=abs(b)
if b==0.:
s=0.
r=aa
if aa==0.:
c=1.
else:
c=a/aa
elif a==0.:
c=0.
s=b/ab
r=ab
elif ab>aa:
sb=1
if b<0: sb=-1
tau=a/b
s=sb*(1+tau**2)**-0.5
c=s*tau
r=b/s
elif aa>ab:
sa=1
if a<0: sa=-1
tau=b/a
c=sa*(1+tau**2)**-0.5
s=c*tau
r=a/c
return c,s,r
"""
It is usually recommended to use SYMMLQ for symmetric matrices
Requires the syntax
A(x,y) == y:=[A]*x
and
A(x,y,trans='T') == y:=[A.T]*x
comments with '###' are followed by the intent of the original matlab
code. This may be useful for debugging.
"""
def lsqr( A, b, damp=0.0, atol=1e-8, btol=1e-8, conlim=1e8, itnlim=None, show=False, wantvar=False):
"""
[ x, istop, itn, r1norm, r2norm, anorm, acond, arnorm, xnorm, var ]...
= lsqr( m, n, 'aprod', iw, rw, b, damp, atol, btol, conlim, itnlim, show );
LSQR solves Ax = b or min ||b - Ax||_2 if damp = 0,
or min || (b) - ( A )x || otherwise.
|| (0) (damp I) ||2
A is an m by n matrix defined by y = aprod( mode,m,n,x,iw,rw ),
where the parameter 'aprodname' refers to a function 'aprod' that
performs the matrix-vector operations.
If mode = 1, aprod must return y = Ax without altering x.
If mode = 2, aprod must return y = A'x without altering x.
WARNING: The file containing the function 'aprod'
must not be called aprodname.m !!!!
-----------------------------------------------------------------------
LSQR uses an iterative (conjugate-gradient-like) method.
For further information, see
1. C. C. Paige and M. A. Saunders (1982a).
LSQR: An algorithm for sparse linear equations and sparse least squares,
ACM TOMS 8(1), 43-71.
2. C. C. Paige and M. A. Saunders (1982b).
Algorithm 583. LSQR: Sparse linear equations and least squares problems,
ACM TOMS 8(2), 195-209.
3. M. A. Saunders (1995). Solution of sparse rectangular systems using
LSQR and CRAIG, BIT 35, 588-604.
Input parameters:
iw, rw are not used by lsqr, but are passed to aprod.
atol, btol are stopping tolerances. If both are 1.0e-9 (say),
the final residual norm should be accurate to about 9 digits.
(The final x will usually have fewer correct digits,
depending on cond(A) and the size of damp.)
conlim is also a stopping tolerance. lsqr terminates if an estimate
of cond(A) exceeds conlim. For compatible systems Ax = b,
conlim could be as large as 1.0e+12 (say). For least-squares
problems, conlim should be less than 1.0e+8.
Maximum precision can be obtained by setting
atol = btol = conlim = zero, but the number of iterations
may then be excessive.
itnlim is an explicit limit on iterations (for safety).
show = 1 gives an iteration log,
show = 0 suppresses output.
Output parameters:
x is the final solution.
istop gives the reason for termination.
istop = 1 means x is an approximate solution to Ax = b.
= 2 means x approximately solves the least-squares problem.
r1norm = norm(r), where r = b - Ax.
r2norm = sqrt( norm(r)^2 + damp^2 * norm(x)^2 )
= r1norm if damp = 0.
anorm = estimate of Frobenius norm of Abar = [ A ].
[damp*I]
acond = estimate of cond(Abar).
arnorm = estimate of norm(A'*r - damp^2*x).
xnorm = norm(x).
var (if present) estimates all diagonals of (A'A)^{-1} (if damp=0)
or more generally (A'A + damp^2*I)^{-1}.
This is well defined if A has full column rank or damp > 0.
(Not sure what var means if rank(A) < n and damp = 0.)
1990: Derived from Fortran 77 version of LSQR.
22 May 1992: bbnorm was used incorrectly. Replaced by anorm.
26 Oct 1992: More input and output parameters added.
01 Sep 1994: Matrix-vector routine is now a parameter 'aprodname'.
Print log reformatted.
14 Jun 1997: show added to allow printing or not.
30 Jun 1997: var added as an optional output parameter.
07 Aug 2002: Output parameter rnorm replaced by r1norm and r2norm.
Michael Saunders, Systems Optimization Laboratory,
Dept of MS&E, Stanford University.
-----------------------------------------------------------------------
"""
"""
Initialize.
"""
n=len(b)
m=n
if itnlim is None: itnlim=2*n
msg=('The exact solution is x = 0 ',
'Ax - b is small enough, given atol, btol ',
'The least-squares solution is good enough, given atol ',
'The estimate of cond(Abar) has exceeded conlim ',
'Ax - b is small enough for this machine ',
'The least-squares solution is good enough for this machine',
'Cond(Abar) seems to be too large for this machine ',
'The iteration limit has been reached ');
var = matrix(0.,(n,1));
if show:
print ' '
print 'LSQR Least-squares solution of Ax = b'
str1 = 'The matrix A has %8g rows and %8g cols' % (m, n)
str2 = 'damp = %20.14e wantvar = %8g' %( damp,wantvar)
str3 = 'atol = %8.2e conlim = %8.2e'%( atol, conlim)
str4 = 'btol = %8.2e itnlim = %8g' %( btol, itnlim)
print str1
print str2
print str3
print str4
itn = 0; istop = 0; nstop = 0;
ctol = 0;
if conlim > 0: ctol = 1/conlim
anorm = 0; acond = 0;
dampsq = damp**2; ddnorm = 0; res2 = 0;
xnorm = 0; xxnorm = 0; z = 0;
cs2 = -1; sn2 = 0;
"""
Set up the first vectors u and v for the bidiagonalization.
These satisfy beta*u = b, alfa*v = A'u.
"""
__x = matrix(0., (n,1)) # a matrix for temporary holding
v = matrix(0., (n,1))
u = +b;
x = matrix(0., (n,1))
alfa = 0;
beta = nrm2( u );
w = matrix(0., (n,1))
if beta > 0:
### u = (1/beta) * u;
### v = feval( aprodname, 2, m, n, u, iw, rw );
scal(1/beta,u)
A(u,v,trans='T'); #v = feval( aprodname, 2, m, n, u, iw, rw );
alfa = nrm2( v );
if alfa > 0:
### v = (1/alfa) * v;
scal(1/alfa,v)
copy(v,w)
rhobar = alfa; phibar = beta; bnorm = beta;
rnorm = beta;
r1norm = rnorm;
r2norm = rnorm;
# reverse the order here from the original matlab code because
# there was an error on return when arnorm==0
arnorm = alfa * beta;
if arnorm == 0:
print msg[0];
return x, istop, itn, r1norm, r2norm, anorm, acond, arnorm, xnorm, var
head1 = ' Itn x[0] r1norm r2norm ';
head2 = ' Compatible LS Norm A Cond A';
if show:
print ' '
print head1, head2
test1 = 1; test2 = alfa / beta;
str1 = '%6g %12.5e' %( itn, x[0] );
str2 = ' %10.3e %10.3e'%( r1norm, r2norm );
str3 = ' %8.1e %8.1e' %( test1, test2 );
print str1, str2, str3
"""
%------------------------------------------------------------------
% Main iteration loop.
%------------------------------------------------------------------
"""
while itn < itnlim:
itn = itn + 1;
"""
% Perform the next step of the bidiagonalization to obtain the
% next beta, u, alfa, v. These satisfy the relations
% beta*u = a*v - alfa*u,
% alfa*v = A'*u - beta*v.
"""
### u = feval( aprodname, 1, m, n, v, iw, rw ) - alfa*u;
copy(u, __x)
A(v,u)
axpy(__x,u,-alfa)
beta = nrm2( u );
if beta > 0:
### u = (1/beta) * u;
scal(1/beta,u)
anorm = sqrt(anorm**2 + alfa**2 + beta**2 + damp**2);
### v = feval( aprodname, 2, m, n, u, iw, rw ) - beta*v;
copy(v,__x)
A(u,v,trans='T')
axpy(__x,v,-beta)
alfa = nrm2( v );
if alfa > 0:
### v = (1/alfa) * v;
scal(1/alfa, v)
"""
% Use a plane rotation to eliminate the damping parameter.
% This alters the diagonal (rhobar) of the lower-bidiagonal matrix.
"""
rhobar1 = sqrt(rhobar**2 + damp**2);
cs1 = rhobar / rhobar1;
sn1 = damp / rhobar1;
psi = sn1 * phibar;
phibar = cs1 * phibar;
"""
% Use a plane rotation to eliminate the subdiagonal element (beta)
% of the lower-bidiagonal matrix, giving an upper-bidiagonal matrix.
"""
###cs = rhobar1/ rho;
###sn = beta / rho;
cs,sn,rho = SymOrtho(rhobar1,beta)
theta = sn * alfa;
rhobar = - cs * alfa;
phi = cs * phibar;
phibar = sn * phibar;
tau = sn * phi;
"""
% Update x and w.
"""
t1 = phi /rho;
t2 = - theta/rho;
dk = (1/rho)*w;
### x = x + t1*w;
axpy(w,x,t1)
### w = v + t2*w;
scal(t2,w)
axpy(v,w)
ddnorm = ddnorm + nrm2(dk)**2;
if wantvar:
### var = var + dk.*dk;
axpy(dk**2, var)
"""
% Use a plane rotation on the right to eliminate the
% super-diagonal element (theta) of the upper-bidiagonal matrix.
% Then use the result to estimate norm(x).
"""
delta = sn2 * rho;
gambar = - cs2 * rho;
rhs = phi - delta * z;
zbar = rhs / gambar;
xnorm = sqrt(xxnorm + zbar**2);
gamma = sqrt(gambar**2 +theta**2);
cs2 = gambar / gamma;
sn2 = theta / gamma;
z = rhs / gamma;
xxnorm = xxnorm + z**2;
"""
% Test for convergence.
% First, estimate the condition of the matrix Abar,
% and the norms of rbar and Abar'rbar.
"""
acond = anorm * sqrt(ddnorm);
res1 = phibar**2;
res2 = res2 + psi**2;
rnorm = sqrt( res1 + res2 );
arnorm = alfa * abs( tau );
"""
% 07 Aug 2002:
% Distinguish between
% r1norm = ||b - Ax|| and
% r2norm = rnorm in current code
% = sqrt(r1norm^2 + damp^2*||x||^2).
% Estimate r1norm from
% r1norm = sqrt(r2norm^2 - damp^2*||x||^2).
% Although there is cancellation, it might be accurate enough.
"""
r1sq = rnorm**2 - dampsq * xxnorm;
r1norm = sqrt( abs(r1sq) );
if r1sq < 0: r1norm = - r1norm;
r2norm = rnorm;
"""
% Now use these norms to estimate certain other quantities,
% some of which will be small near a solution.
"""
test1 = rnorm / bnorm;
test2 = arnorm/( anorm * rnorm );
test3 = 1 / acond;
t1 = test1 / (1 + anorm * xnorm / bnorm);
rtol = btol + atol * anorm * xnorm / bnorm;
"""
% The following tests guard against extremely small values of
% atol, btol or ctol. (The user may have set any or all of
% the parameters atol, btol, conlim to 0.)
% The effect is equivalent to the normal tests using
% atol = eps, btol = eps, conlim = 1/eps.
"""
if itn >= itnlim : istop = 7;
if 1 + test3 <= 1: istop = 6;
if 1 + test2 <= 1: istop = 5;
if 1 + t1 <= 1: istop = 4;
"""
% Allow for tolerances set by the user.
"""
if test3 <= ctol: istop = 3;
if test2 <= atol: istop = 2;
if test1 <= rtol: istop = 1;
"""
% See if it is time to print something.
"""
prnt = False;
if n <= 40 : prnt = True;
if itn <= 10 : prnt = True;
if itn >= itnlim-10: prnt = True;
# if itn%10 == 0 : prnt = True;
if test3 <= 2*ctol : prnt = True;
if test2 <= 10*atol : prnt = True;
if test1 <= 10*rtol : prnt = True;
if istop != 0 : prnt = True;
if prnt:
if show:
str1 = '%6g %12.5e'% (itn, x[0] );
str2 = ' %10.3e %10.3e'% (r1norm, r2norm );
str3 = ' %8.1e %8.1e'% ( test1, test2 );
str4 = ' %8.1e %8.1e'% ( anorm, acond );
print str1, str2, str3, str4
if istop != 0: break
"""
% End of iteration loop.
% Print the stopping condition.
"""
if show:
print ' '
print 'LSQR finished'
print msg[istop]
print ' '
str1 = 'istop =%8g r1norm =%8.1e'% ( istop, r1norm );
str2 = 'anorm =%8.1e arnorm =%8.1e'%( anorm, arnorm );
str3 = 'itn =%8g r2norm =%8.1e'% ( itn, r2norm );
str4 = 'acond =%8.1e xnorm =%8.1e'%( acond, xnorm );
print str1+ ' ' +str2
print str3+ ' ' +str4
print ' '
return x, istop, itn, r1norm, r2norm, anorm, acond, arnorm, xnorm, var
"""
%-----------------------------------------------------------------------
% End of lsqr.m
%-----------------------------------------------------------------------
"""