I'm not familiar with how the eigenvalue functions are written but I've
used them on complex matrices and gotten results similar to yours. If your
elements are numeric (as they appear to be in your example) then I would
suggest doing this computation in numpy if that's possible.

On Fri, Oct 12, 2012 at 12:34 PM, Bharath M R <[email protected]>wrote:

> Hi,
>    I was trying to implement rational chebychev series approximation to a
> function. This
> involves finding the eigen values of a symmetric matrix(for svd). I always
> get an empty set of
> eigen values.
>
> Here is an example. The matrix is an symmetric matrix and hence it should
> have real eigen values.
> ```
> from sympy import *
> a = [[               40,  59.0372649711174,  91.9159715266083,
> -18.3586972981465, -26.5974423018762],
> [ 59.0372649711174,  91.9159715266083,  149.966034521936,
> -26.5974423018762, -40.6785676729709],
> [ 91.9159715266083,  149.966034521936,   254.33769719335,
> -40.6785676729709, -65.3185292247321],
> [-18.3586972981465, -26.5974423018762, -40.6785676729709,
>  8.47893318890501,  12.0617341323178],
> [-26.5974423018762, -40.6785676729709, -65.3185292247321,
>  12.0617341323178,  18.1185091129712]]
> a = Matrix(a)
> print a.eigenvals()
> ```
> This return an empty eigen value set. Is this a bug? Is there any way
> around it?
>
> Thanks,
> Bharath M R
>
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