I had mentioned recently some interest in using fractions in the numpy
polynomial class. Suprisingly, it actually works for the most part out
of the box, which is great. However, there are some minor issues. For
example:
>>>> numpy.poly1d( [ fractions.Fraction(1,2) , fractions.Fraction(1,8) ] )/fractions.Fraction(3,4)
fails, so I have to move the division into the inner list, which leads
to a lot of duplicate typing and general messiness:
>>>> numpy.poly1d( [ fractions.Fraction(1,2)/fractions.Fraction(3,4) , fractions.Fraction(1,8)/fractions.Fraction(3,4) ] )
Another item of general interest for numpy is that there is no simple
way to allocate memory for fraction array.
>>>> def zeros( nsamples ):
>>>> list = []
>>>> for n in range( nsamples ):
>>>> list.append( fractions.Fraction( 0 ) )
>>>> return numpy.array( list )
is a solution, but it would be nice to have this built-in, e.g.:
>>>> numpy.zeros( n , dtype=numpy.fraction )
Perhaps developing a fraction dtype would solve the above poly1d issue
as well? Anyway, just some thoughts to ponder.
Best wishes,
Mike