Re: [SciPy-user] csc, csr sparse complex matrix problems. Thanks.
by Mark Starnes other posts by this author
Dec 14 2006 3:30AM messages near this date
Re: [SciPy-user] csc, csr sparse complex matrix problems.
|
Re: [SciPy-user] csc, csr sparse complex matrix problems.
<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html>
<head>
<meta content="text/html;charset=ISO-8859-1" http-equiv="Content-Type">
<title> </title>
</head>
<body bgcolor="#ffffff" text="#000000">
Thanks to both Nils and Robert for such a speedy response! I'll be
trying your suggestions asap.<br>
<br>
Best regards,<br>
<br>
Mark.<br>
<br>
Robert Cimrman wrote:
<blockquote cite="mid458124BC.6080508@ntc.zcu.cz" type="cite">
<pre wrap=""> Mark Starnes wrote:
</pre>
<blockquote type="cite">
<pre wrap=""> Hi everyone,
I've been trying to get this simple example to work for a couple of days
now, to no avail. I noticed at
<a class="moz-txt-link-freetext" href="http://projects.scipy.org/scipy/scipy/ticket/329"> htt
p://projects.scipy.org/scipy/scipy/ticket/329</a> that there seem to be
come problems with csc and complex values but I'm hoping they're
unrelated and someone can help me sort this problem! I couldn't get the
csc matrix to work at all here - the csr matrix was having a go and
getting the right answer but now fails too! Anyway, here's the code.
I'm using Python2.4.3 on winxp with Scipy0.5.2, Numpy 1.0.1.
Any help will be appreciated.
Best regards,
Mark Starnes.
***
import numpy as n
import scipy as s
from scipy.linsolve import spsolve
from scipy import linalg as la
from numpy import zeros,complex64
# solve kx=f for x, where
#
#/ \ / \ / #| 1+1i 2+2i 3+3i | | 2 | | -5+3i |
#| | | | | |
#| 2 3 4+4i | | 3+2i | = | 1-6i |
#| | | | | |
#| 4+9i 5+10i 2+11i | | -3 | | -3+25i |
#\ / \ / \ /
#
k0=n.array([[1+1j,2+2j,3+3j],[2,3,4+4j],[4+9j,5+10j,2+11j]])
f0=[-5+3j,1-6j,-3+25j]
# Test numpy routine.
k=n.mat(k0)
f=n.mat(f0).T
fsol=s.dot(la.inv(k),f)
print fsol
print k*fsol
# result should = [2, 3+2j, -3]. Numpy passes.
# Test Scipy sparse routines.
k=s.sparse.csc_matrix((3,3),dtype='F')
k[0,0]=1+1j ; k[0,1]=2+2j ; k[0,2]=3+3j ;
k[1,0]=2 ; k[1,1]=3 ; k[1,2]=4+4j ;
k[2,0]=4+9j ; k[2,1]=5+10j ; k[2,2]=2+11j;
f=zeros((3),complex64)
f[0]=-5+3j
f[1]=1-6j
f[2]=-3+25j
#fsol2=spsolve(k,f) # this crashes python with typeD, AND with type F
#print fsol2
#print k.dot(fsol2)
k=s.sparse.csr_matrix((3,3),dtype='F')
k[0,0]=1+1j ; k[0,1]=2+2j ; k[0,2]=3+3j ;
k[1,0]=2 ; k[1,1]=3 ; k[1,2]=4+4j ;
k[2,0]=4+9j ; k[2,1]=5+10j ; k[2,2]=2+11j;
fsol3=spsolve(k,f) # this crashes python with typeD, originally ok
with type F
print fsol3
print k.dot(fsol3)
</pre>
</blockquote>
<pre wrap=""> <!---->
1. If you use umfpack, k.dtype.char should equal 'D', not 'F' (Look at
Nils response)
2. also, in case of umfpack usage, use
k=n.empty( (3,3), dtype = 'D' )
k[0,0]=1+1j ; k[0,1]=2+2j ; k[0,2]=3+3j ;
k[1,0]=2 ; k[1,1]=3 ; k[1,2]=4+4j ;
k[2,0]=4+9j ; k[2,1]=5+10j ; k[2,2]=2+11j;
k=s.sparse.csr_matrix(k,dtype='D')
because assigning to a CSR matrix via [] (__setitem__) is currently
buggy. You could use e.g. the following form of the CSR matrix constructor
csr_matrix((data, ij), [dims=(M, N), nzmax=nzmax])
for real data, then, see the doc.
There is now discussion on scipy-dev considering an overhaul of the
sparse module (speed-wise and functionality-wise and antibug-wise), so
hopefully bright future awaits us :).
r.
_______________________________________________
SciPy-user mailing list
<a class="moz-txt-link-abbreviated" href="mailto:SciPy-user@scipy.org"> SciPy-user@[...].org<
/a>
<a class="moz-txt-link-freetext" href="http://projects.scipy.org/mailman/listinfo/scipy-user
"> http://projects.scipy.org/mailman/listinfo/scipy-user</a>
</pre>
</blockquote>
<pre class="moz-signature" cols="72">
</pre>
</body>
</html>
Thread:
Mark Starnes
Robert Cimrman
Mark Starnes
Nils Wagner
|
