[Numpy-discussion] Antwort: Re: vector to tensor matrix speed up

Ferenc.Pintye at eu.decoma.com Ferenc.Pintye at eu.decoma.com
Fri Jul 21 06:35:52 CDT 2006

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Hi Tim,

many thanks for the tipps, i used the same way
with vectorized (chunk)  method on the indexing operation.
..
....
......
............    # out = zeros((size_mcf[0],sizes_smatrix[2]+5),Float32)
#     size_mcf[0] ~ 240000
eig = zeros((size_mcf[0],3,3),dtype=Float32)
eigwert = zeros((size_mcf[0],3),dtype=Float64)
#
# here is speed up ~30
#for j in arange(0,size_mcf[0]):
#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]
#
eig[:,0,0] = out[:,1]
eig[:,1,1] = out[:,2]
eig[:,2,2] = out[:,3]
eig[:,1,0] = eig[:,0,1] = out[:,4]
eig[:,2,0] = eig[:,0,2] = out[:,6]
eig[:,2,1] = eig[:,1,2] = out[:,5]
#
for i in arange(size_mcf[0]):
eigwert[i] = eigvals(eig[i,:,:])
#
out[:,7:10] = sort(eigwert[:,:].astype(float32))
out[:,10] = abs(out[:,7]-out[:,9])

speedup factor ~30 !

f.

```