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Parallel package: Difference between revisions
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add "diagonalize NxN matrices contained in an array"
(category is Octave-Forge) |
(add "diagonalize NxN matrices contained in an array") |
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[[Category:Octave-Forge]] | [[Category:Octave-Forge]] | ||
=== Output in cell arrays === | |||
The following sample code was an answer to [http://stackoverflow.com/questions/27422219/for-every-row-reshape-and-calculate-eigenvectors-in-a-vectorized-way this question]. The goal was to diagonalize 2x2 matrices contained as rows of a 2d array (each row of the array being a flattened 2x2 matrix). | |||
{{code|diagonalize NxN matrices contained in an array| | |||
<pre> | |||
A = [0.6060168 0.8340029 0.0064574 0.7133187; | |||
0.6325375 0.0919912 0.5692567 0.7432627; | |||
0.8292699 0.5136958 0.4171895 0.2530783; | |||
0.7966113 0.1975865 0.6687064 0.3226548; | |||
0.0163615 0.2123476 0.9868179 0.1478827]; | |||
N = 2; | |||
[eigenvectors, eigenvalues] = pararrayfun(nproc, | |||
@(row_idx) eig(reshape(A(row_idx, :), N, N)), | |||
1:rows(A), "UniformOutput", false) | |||
</pre> | |||
}} | |||
With {{codeline|"UniformOutput", false}}, the outputs are contained in cell arrays (one cell per slice). In the sample above, both {{codeline|eigenvectors}} and {{codeline|eigenvalues}} are {{codeline|1x5}} cell arrays. | |||