Re: MATRIX LOGARITHM (and EXPONENTIAL) [message #74693] |
Thu, 27 January 2011 16:11  |
James[2]
Messages: 44 Registered: November 2009
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Member |
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On Jan 27, 4:10 pm, James <donje...@gmail.com> wrote:
>
> If the matrix A is diagonalizable, then:
>
> eigenvals = LA_EIGENPROBLEM(A, EIGENVECTORS=evecs)
> expA = evecs # diag_matrix(exp(eigenvals)) # invert(evecs)
> logA = evecs # diag_matrix(alog(eigenvals)) # invert(evecs)
sorry, replace INVERT with LA_INVERT to account for complex
eigenvectors.
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Re: MATRIX LOGARITHM (and EXPONENTIAL) [message #92161 is a reply to message #74693] |
Wed, 21 October 2015 16:04   |
zhaobw1993
Messages: 1 Registered: October 2015
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Junior Member |
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On Thursday, January 27, 2011 at 5:11:53 PM UTC-7, James wrote:
> On Jan 27, 4:10 pm, James <donje...@gmail.com> wrote:
>>
>> If the matrix A is diagonalizable, then:
>>
>> eigenvals = LA_EIGENPROBLEM(A, EIGENVECTORS=evecs)
>> expA = evecs # diag_matrix(exp(eigenvals)) # invert(evecs)
>> logA = evecs # diag_matrix(alog(eigenvals)) # invert(evecs)
>
> sorry, replace INVERT with LA_INVERT to account for complex
> eigenvectors.
Does logA need to be transposed?
My way was,
evens = transpose(evens)
logA = evecs ## diag_matrix(eigenvalues) ## invert(evecs)
result of this way seems to be transpose of result of your way.
Thanks
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Re: MATRIX LOGARITHM (and EXPONENTIAL) [message #92178 is a reply to message #92161] |
Fri, 23 October 2015 10:52  |
chris_torrence@NOSPAM
Messages: 528 Registered: March 2007
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Senior Member |
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On Wednesday, October 21, 2015 at 5:04:18 PM UTC-6, zhaob...@gmail.com wrote:
> On Thursday, January 27, 2011 at 5:11:53 PM UTC-7, James wrote:
>> On Jan 27, 4:10 pm, James <donje...@gmail.com> wrote:
>>>
>>> If the matrix A is diagonalizable, then:
>>>
>>> eigenvals = LA_EIGENPROBLEM(A, EIGENVECTORS=evecs)
>>> expA = evecs # diag_matrix(exp(eigenvals)) # invert(evecs)
>>> logA = evecs # diag_matrix(alog(eigenvals)) # invert(evecs)
>>
>> sorry, replace INVERT with LA_INVERT to account for complex
>> eigenvectors.
>
> Does logA need to be transposed?
> My way was,
> evens = transpose(evens)
> logA = evecs ## diag_matrix(eigenvalues) ## invert(evecs)
> result of this way seems to be transpose of result of your way.
>
> Thanks
Or, you could use the Python bridge:
la = Python.Import('scipy.linalg')
expm = la.expm(A)
logm = la.logm(A)
-Chris
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