On Sep 5, 10:29 pm, Bryan <alke...@gmail.com> wrote:
> Thats exactly what I am trying to do, solve symbolic matrices which
> have numeric coefficients along symbols, thus I would like the numeric
> coefficients to be treated as floats to speed things up a bit.
>
> The documentation says that it is generally the case that exact
> arithmetic
> is used, so I was wondering how to tap into the non-general case
> of having my numbers treated as floats.
>
> But it appears to me that this is just the case of misleading
> documentation
> then?
Please feel free to improve our documentation. :)
Actually it is quite easy to mix symbols and floating point
arithmetic, just use sympy.Float for your coefficients:
>>> from sympy import *
>>> var('a:d')
(a, b, c, d)
>>> m = Matrix([[Float('0.1')*a, Float('0.2')*b], [Float('0.3')*c,
>>> Float('0.4')*d]])
>>> m
[0.1*a, 0.2*b]
[0.3*c, 0.4*d]
I'm not sure that it will be much faster though.
Vinzent
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