# [Numpy-discussion] Vectorizing a function

Charles R Harris charlesr.harris@gmail....
Wed Jan 30 11:10:29 CST 2008

```On Jan 30, 2008 2:22 AM, Gael Varoquaux <gael.varoquaux@normalesup.org>
wrote:

> On Wed, Jan 30, 2008 at 12:49:44AM -0800, LB wrote:
> > My problem is that the complexe calculations made in calc_0d use some
> > parameters, which are currently defined at the head of my python file.
> > This is not very nice and I can't define a module containing theses
> > two functions and call them with different parameters.
>
> > I would like to make this cleaner and pass theses parameter as
> > keyword  argument, but this don't seems to be possible with vectorize.
> > Indeed, some of theses parameters are array parameters and only the x
> > and y arguments should be interpreted with the broadcasting rules....
>
> > What is the "good way" for doing this ?
>
> I don't know what the "good way" is, but you can always use functional
> programming style (Oh, no, CaML is getting on me !):
>
> def calc_0d_params(param1, param2, param3):
>    def calc_0d(x, y):
>        # Here your code making use of param1, param2, param3)
>        ...
>
>    return calc_0d(x, y)
>
> you call the function like this:
>
> calc_0d_params(param1, param2, param3)(x, y)
>
> To vectorize it you can do:
>
> calc_0d_vect = lambda *params: vectorize(calc_0d_params(*params))
>
> This is untested code, but I hope you get the idea. It all about partial
> evaluation of arguments. By the way, the parameters can now be keyword
> arguments.
>

IIRC, the way to do closures in Python is something like

In [5]: def factory(x) :
...:     def f() :
...:         print x
...:     f.x = x
...:     return f
...:

In [6]: f = factory("Hello world.")

In [7]: f()
Hello world.

There is a reason to do it that way, but I don't recall what it is. Nor do I
know if the result can be vectorized, I've never used vectorize.

Chuck
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