arbitrary precision linear algebra

[geremy condra]

On Wed, Mar 2, 2011 at 6:42 AM, Ben123 <ben.is.located at gmail.com> wrote:
> Hello. I have a written Python program which currently uses numpy to
> perform linear algebra operations. Specifically, I do matrix*matrix,
> matrix*vector, numpy.linalg.inv(matrix), and linalg.eig(matrix)
> operations. Now I am interested in allowing arbitrary precision. I
> have tried gmpy, bigfloat, mpmath, and decimal but I have been unable
> to easily implement any with my current program. I suspect I have to
> change some commands but I am unsure what.
>
> My question is which of the arbitrary precision implementations will
> most easily handle linear algebra? I don't care about speed, just ease
> of use. Online tutorials for arbitrary precision linear algebra
> operations would be useful.
>
> For example, it looks like mpmath can handle matrix operations
> http://fredrik-j.blogspot.com/search?q=matrix
> but I was unable to find a clear tutorial. The tutorials for most of
> the arbitrary precision implementations demonstrate simple scalar
> examples.
>
> Thanks in advance

Have you looked at Sage[0]? I don't know for a fact, but you should be
able to define a matrix over RealField(precision_in_bits) and then
take the eigenvalue of it. I don't know if it will actually produce
the precision you need though.

Geremy Condra