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 <sh...@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 <mangab...@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 <sh...@keba.be> wrote:
>>
>>> I'm probably missing something, but... Why would you want non-normalized
>>> eigenvectors?
>>>
>>> -=- Olivier
>>>
>>>
>>> 2011/12/20 Fahreddın Basegmez <mangab...@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
>>>>
>>>
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