arbitrary precision linear algebra

[geremy condra]

On Wed, Mar 2, 2011 at 10:21 AM, geremy condra <debatem1 at gmail.com> wrote:
> 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
>

Apologies, forgot the links:

http://www.sagemath.org/doc/constructions/linear_algebra.html
http://www.sagemath.org/doc/reference/sage/rings/complex_field.html

Geremy Condra