[Tutor] Functional Derivatives

[Chris Fuller]

You should look up "numerical methods" or similar.  There are ways of 
rearranging your calculations to minimize the loss of precision.  You could 
also try a numerical/scientific library like GMP (for integers or rational 
numbers).  I don't know of any (Python) library for extended precision 
floats, but there ought to be.

Cheers

On Monday 20 April 2009 18:53, Matt wrote:
> I'm trying to calculate the derivative of a function in Python like so:
>
> def D5(func,h=1e-5):
>     ""' Return derivative of function func'''
>     def df(x):    return (func(x+h)-func(x))/h
>     df.__name__ = func.__name__ + '_dx'
>     return df
>
> However, I run into the problem of limited float precision. This is
> evident for this:
> import math
> print D5(D5(D5(D5(math.sin))))(0.3)
>  => -5551.11512313
> print math.sin(0.3)
>  => 0.295520206661
> Is there any way that any of you can think of to avoid this for
> general-purpose functions? Thanks.
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