[Numpy-discussion] Vectorizing a function

[Gael Varoquaux]

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.

HTH,

Gaël