[EMAIL PROTECTED] wrote:
>
>
> Hi users,
>
> i have some problem in Numpy with indexing speed for array to tensor
> matrix transport.
> With 200000 cycles it's 9sec ! (without sort(eigvals() - functions)
>
> Many thanks
> f.
>
The big problem you have here is that you are operating on your matrices
one element at a time. Overhead is going to kill you doing this. The key
thing is to operate on your data in chunks -- I'll show one way below
that speeds thing up by a factor of 40 or so *neglecting
sort(eigvals())*. Unfortunately, sort(eigvals()) is still likely to kill
you since there's not really a good way to chunk that up. (I'll have
more to say about that in a more general
sense in another email). Here's the two versions I compared, perhaps
this will help you out:
from numpy import *
import timeit
out = zeros((200000,11),float)
def f0(out):
for j in arange(0,200000):
pass
def f1(out):
# stress values/matrix in array form for 200000 points
#
#.....out = filling matrix ...etc...
#
# stress tensor matrix
eig = zeros((3,3),float)
#
#output for eigvalues
eigwert = array([0,0,0])
#
for j in arange(0,200000):
eig[0,0] = out[j,1]
eig[1,1] = out[j,2]
eig[2,2] = out[j,3]
#
eig[0,1] = out[j,4]
eig[0,2] = out[j,6]
eig[1,0] = out[j,4]
eig[1,2] = out[j,5]
eig[2,0] = out[j,6]
eig[2,1] = out[j,5]
#
#~ eigwert = sort(eigvals(eig))
out[j,7] = eigwert[2]
out[j,8] = eigwert[1]
out[j,9] = eigwert[0]
out[j,10] = abs(eigwert[0]-eigwert[2])
#
def f2(out):
# stress values/matrix in array form for 200000 points
#
#.....out = filling matrix ...etc...
#
# stress tensor matrix
eig = zeros((100,3,3),float)
#
#output for eigvalues
eigwert = zeros([100,3], dtype=float)
#
local_abs = abs
rangen = range(0,200000,100)
for j in rangen:
eig[:,0,0] = out[j:j+100,1]
eig[:,1,1] = out[j:j+100,2]
eig[:,2,2] = out[j:j+100,3]
#
eig[:,1,0] = eig[:,0,1] = out[j:j+100,4]
eig[:,2,0] = eig[:,0,2] = out[j:j+100,6]
eig[:,2,1] = eig[:,1,2] = out[j:j+100,5]
#
#~ eigwert = sort(eigvals(eig))
for j in rangen:
out[j:j+100,7:10] = eigwert # Changed order of out here
out[j:j+100,10] = abs(eigwert[:,0]-eigwert[:,2])
if __name__ == '__main__':
print timeit.Timer("f0(out)", "from scratch import f0,
out").timeit(1)
print timeit.Timer("f1(out)", "from scratch import f1,
out").timeit(1)
print timeit.Timer("f2(out)", "from scratch import f2,
out").timeit(1)
>
> # stress values/matrix in array form for 200000 points
> out = zeros((200000,11),Float32)
> #
> #.....out = filling matrix ...etc...
> #
> # stress tensor matrix
> eig = zeros((3,3),Float32)
> #
> #output for eigvalues
> eigwert = array([0,0,0])
> #
> for j in arange(0,200000):
> eig[0,0] = out[j,1]
> eig[1,1] = out[j,2]
> eig[2,2] = out[j,3]
> #
> eig[0,1] = out[j,4]
> eig[0,2] = out[j,6]
> eig[1,0] = out[j,4]
> eig[1,2] = out[j,5]
> eig[2,0] = out[j,6]
> eig[2,1] = out[j,5]
> #
> eigwert = sort(eigvals(eig))
> out[j,7] = eigwert[2]
> out[j,8] = eigwert[1]
> out[j,9] = eigwert[0]
> out[j,10] = abs(eigwert[0]-eigwert[2])
> #
>
>
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