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Answered

SVD behavior in mp different from Matlab when applied to negative scalar

Denis Tkachenko 2 years ago • updated 2 years ago 2

I have the following question:


In one of my examples I need to compute the Singular Value Decomposition (SVD) of a negative scalar, specifically -0.7276.


In double precision, Matlab returns:

>> [U S V]=svd(-0.7276)

U = -1
S = 0.7276
V =1


In MP, I obtain:


s=mp('-0,7276');


>> [U,S,V]=svd(s)


U = 1
S = -0.7276
V = 1


The definition of SVD states that the matrix S should have nonnegative diagonal entries. In the above example, the first two elements seem to be multiplied by -1 compared to Matlab output. While the product doesn't change, the unexpected negative sign of the singular value causes problems in subsequent code.


Is this a bug or is there an option to make it return the same output as Matlab's svd?


The 4.2.3.11967 release of the toolbox was used.

Thank you,

Denis

Answer

Answer
Answered

Dear Denis,

Thank you very much for the report!


Indeed, this is bug and it has been fixed in latest build.

Please download updated version: http://goo.gl/pMXV3


Thank you,

Pavel.

Answer
Answered

Dear Denis,

Thank you very much for the report!


Indeed, this is bug and it has been fixed in latest build.

Please download updated version: http://goo.gl/pMXV3


Thank you,

Pavel.

Dear Pavel,


Thank you very much for your very prompt reply! The problem is fixed with the new build.


Best,

Denis