Hi all,
I need eigen values and vectors for symmetric matrices (like VCV).
Solving with numarray and testing the results, I've got
strange results - input and output matrices of some sizes are
very different. That's an example of differencies:
Size MaxDif(E.Val) MaxDif(E.Vect)
2 0 1.110223e-016
3 1.776357e-015 2.053913e-015
10 1.221245e-015 7.255307e-014
11 3.552714e-015 0.8455322
12 1.526557e-016 1.345035e-013
13 8.881784e-016 0.7796273
14 2.775558e-016 0.7504375
15 2.331468e-015 2.045031e-013
This is for numarray 0.7 on W2K.
I hoped to have all the differencies below 1e-15 or so.
What's wrong ? Program text is below.
Thanks,
Eugene Druker
import numarray, numarray.linear _algebra
EigenVectors = numarray.linear _algebra.eigenv ectors
Multiply = numarray.matrix multiply
Zeros = numarray.zeros
Transpose = numarray.transp ose
def makeCovMat(size ):
covmat = Zeros((size,siz e),'f8')
d,t = 0.9,0.8
for i in xrange(size):
v = covmat[i,i] = d
for j in xrange(i+1,size ):
v *= t
covmat[i,j] = covmat[j,i] = v
return covmat
print 'Size MaxDif(E.Val) MaxDif(E.Vect)'
for size in [2,3]+range(10,24):
covmat = makeCovMat(size )
eval,evec = EigenVectors(co vmat)
# Test S = V L V'
mdiag = Zeros((size,siz e),'f8') # L
for j in xrange(size):
mdiag[j,j] = eval[j]
testmat = Multiply(Transp ose(evec),Multi ply(mdiag,evec) )
ival,ivec = EigenVectors(te stmat)
print ' %3d %-14.7g %-14.7g' % \
(size, (eval-ival).max(), (evec-ivec).max()) 1 2819 eu***********@y ahoo.com (Eugene Druker) writes: I need eigen values and vectors for symmetric matrices (like VCV). Solving with numarray and testing the results, I've got strange results - input and output matrices of some sizes are
[...]
You'll probably be much better off posting this to whichever mailing
list the numarray people use. Google for it. HTH
John This thread has been closed and replies have been disabled. Please start a new discussion. Similar topics |
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