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singular value decomposition

asked 2013-11-07 11:13:41 +0100

gundamlh gravatar image

updated 2013-11-07 11:14:05 +0100

I want to use SVD directly in Sage, is it possible?

from http://wiki.sagemath.org/interact/lin..., I know that, we can...

sage: from scipy import linalg

sage: U,s,Vh = linalg.svd(A) # A is a fixed matrix, e.g., A = [1, 2; 3, 4]

Thanks in advance!

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Can you explain what you mean by use SVD directly? The commands you mentioned is the way to use SVD. Is there any other way you wish to do it?

Shashank gravatar imageShashank ( 2013-11-07 12:55:13 +0100 )edit

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answered 2013-11-07 14:20:56 +0100

tmonteil gravatar image

updated 2013-11-07 14:24:54 +0100

It depends on the ring of the matrix. For example, it works for matrices over CDF:

sage: M = matrix(CDF, [[1,2,3],[1,4,6]])
sage: M.SVD()
(
[-0.455252372951 -0.890362441325]
[-0.890362441325  0.455252372951],

[ 8.17345734477            0.0            0.0]
[           0.0 0.441129270439            0.0],

[   -0.164632267291    -0.986355015482 -2.81388521797e-16]
[   -0.547131320636    0.0913215509714    -0.832050294338]
[   -0.820696980953     0.136982326457     0.554700196225]
)

but not for matrices over QQ:

sage: M = matrix(QQ, [[1,2,3],[1,4,6]])
sage: M.SVD()
AttributeError: 'sage.matrix.matrix_rational_dense.Matrix_rational_dense' object has no attribute 'SVD'

So, the method .SVD() is not implemented for every kind of matrices.

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.SVD() works for CDF and RDF. Thanks!

gundamlh gravatar imagegundamlh ( 2013-11-08 08:19:42 +0100 )edit

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Asked: 2013-11-07 11:13:41 +0100

Seen: 5,011 times

Last updated: Nov 07 '13