[Numpy-discussion] Getting non-normalized eigenvectors from generalized eigenvalue solution?

[Fahreddın Basegmez]

I should include the scipy response too I guess.


scipy.linalg.eig(STIFM, MASSM)
(array([ 3937.15984097+0.j,  3937.15984097+0.j,  3937.15984097+0.j,
        3923.07692308+0.j,  3923.07692308+0.j,  7846.15384615+0.j]),
array([[ 1.,  0.,  0.,  0.,  0.,  0.],
       [ 0.,  1.,  0.,  0.,  0.,  0.],
       [ 0.,  0.,  1.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  1.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  1.,  0.],
       [ 0.,  0.,  0.,  0.,  0.,  1.]]))

On Tue, Dec 20, 2011 at 9:14 PM, Fahreddın Basegmez <mangabasi at gmail.com>wrote:

> If I can get the same response as Matlab I would be all set.
>
>
> Octave results
>
> >> STIFM
> STIFM =
>
> Diagonal Matrix
>
>      1020        0        0        0        0        0
>         0     1020        0        0        0        0
>         0        0     1020        0        0        0
>         0        0        0   102000        0        0
>         0        0        0        0   102000        0
>         0        0        0        0        0   204000
>
> >> MASSM
> MASSM =
>
> Diagonal Matrix
>
>     0.25907          0          0          0          0          0
>           0    0.25907          0          0          0          0
>           0          0    0.25907          0          0          0
>           0          0          0   26.00000          0          0
>           0          0          0          0   26.00000          0
>           0          0          0          0          0   26.00000
>
> >> [a, b] = eig(STIFM, MASSM)
> a =
>
>    0.00000   0.00000   0.00000   1.96468   0.00000   0.00000
>    0.00000   0.00000   0.00000   0.00000   1.96468   0.00000
>    0.00000   0.00000   1.96468   0.00000   0.00000   0.00000
>    0.19612   0.00000   0.00000   0.00000   0.00000   0.00000
>    0.00000   0.19612   0.00000   0.00000   0.00000   0.00000
>    0.00000   0.00000   0.00000   0.00000   0.00000   0.19612
>
> b =
>
> Diagonal Matrix
>
>    3923.1        0        0        0        0        0
>         0   3923.1        0        0        0        0
>         0        0   3937.2        0        0        0
>         0        0        0   3937.2        0        0
>         0        0        0        0   3937.2        0
>         0        0        0        0        0   7846.2
>
>
> Numpy Results
>
> >>> STIFM
> array([[   1020.,       0.,       0.,       0.,       0.,       0.],
>        [      0.,    1020.,       0.,       0.,       0.,       0.],
>        [      0.,       0.,    1020.,       0.,       0.,       0.],
>        [      0.,       0.,       0.,  102000.,       0.,       0.],
>        [      0.,       0.,       0.,       0.,  102000.,       0.],
>        [      0.,       0.,       0.,       0.,       0.,  204000.]])
>
> >>> MASSM
>
> array([[  0.25907,   0.     ,   0.     ,   0.     ,   0.     ,   0.     ],
>        [  0.     ,   0.25907,   0.     ,   0.     ,   0.     ,   0.     ],
>        [  0.     ,   0.     ,   0.25907,   0.     ,   0.     ,   0.     ],
>        [  0.     ,   0.     ,   0.     ,  26.     ,   0.     ,   0.     ],
>        [  0.     ,   0.     ,   0.     ,   0.     ,  26.     ,   0.     ],
>        [  0.     ,   0.     ,   0.     ,   0.     ,   0.     ,  26.     ]])
>
> >>> a, b = linalg.eig(dot( linalg.pinv(MASSM), STIFM))
>
> >>> a
>
> array([ 3937.15984097,  3937.15984097,  3937.15984097,  3923.07692308,
>         3923.07692308,  7846.15384615])
>
> >>> b
>
> array([[ 1.,  0.,  0.,  0.,  0.,  0.],
>        [ 0.,  1.,  0.,  0.,  0.,  0.],
>        [ 0.,  0.,  1.,  0.,  0.,  0.],
>        [ 0.,  0.,  0.,  1.,  0.,  0.],
>        [ 0.,  0.,  0.,  0.,  1.,  0.],
>        [ 0.,  0.,  0.,  0.,  0.,  1.]])
>
> On Tue, Dec 20, 2011 at 8:40 PM, Olivier Delalleau <shish at keba.be> wrote:
>
>> Hmm... ok ;) (sorry, I can't follow you there)
>>
>> Anyway, what kind of non-normalization are you after? I looked at the doc
>> for Matlab and it just says eigenvectors are not normalized, without
>> additional details... so it looks like it could be anything.
>>
>>
>> -=- Olivier
>>
>> 2011/12/20 Fahreddın Basegmez <mangabasi at gmail.com>
>>
>>> I am computing normal-mode frequency response of a mass-spring system.
>>>  The algorithm I am using requires it.
>>>
>>> On Tue, Dec 20, 2011 at 8:10 PM, Olivier Delalleau <shish at keba.be>wrote:
>>>
>>>> I'm probably missing something, but... Why would you want
>>>> non-normalized eigenvectors?
>>>>
>>>> -=- Olivier
>>>>
>>>>
>>>> 2011/12/20 Fahreddın Basegmez <mangabasi at gmail.com>
>>>>
>>>>> Howdy,
>>>>>
>>>>> Is it possible to get non-normalized eigenvectors from
>>>>> scipy.linalg.eig(a, b)?  Preferably just by using  numpy.
>>>>>
>>>>> BTW, Matlab/Octave provides this with its eig(a, b) function but I
>>>>> would like to use numpy for obvious reasons.
>>>>>
>>>>> Regards,
>>>>>
>>>>> Fahri
>>>>>
>>>>
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion at scipy.org
>> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>>
>>
>
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