[SciPy-User] maping a float to a function value

[Christopher Barker]

 > I need the (numerical) solution of the  integral
> equation
> 
> gamma(x) = c(x) + \int_0^\infty gamma(x-y) G(y) dy,
> 
> for given functions c(x) and G(x). (There are some technical
> conditions on G and c such that I can prove that the integral equation
> has a solution.)  Now I like to store the values gamma(x) as keys of
> x, as it feels natural. Moreover, I need gamma in a second integral
> equation. Sure I can store gamma as an array, but then I have to
> convert the index i to the key x, and I dislike this, as it is less
> elegant, and requires extra code.

However, I think it's a more correct solution -- as you've pointed out 
real numbers to not map directly to floats, and, indeed, you are never 
going to have gamma(x) pre-calculated for all x in your range. Indeed, 
it's a bit absurd to try to have gamma(x) for all floats in your range, 
either. So you are going to have to compute and store a subset. As they 
are ordered, it sure makes sense to simply store them, and it's easy to 
calculate an index -- you could put a different api on it if you really 
want:


class gamma:

     def__get_item(self, value):
         # compute index form value here
         return self._gamma[index]


but, as you are storing only a subset of your possible values, it seems 
that interpolation really is the best and most natural way to go anyway.

In fact, the above is simply a nearest neighbor interpolator already, as 
is your proposed dict with keys of rounded floats.

-Chris







-- 
Christopher Barker, Ph.D.
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