On Jan 30, 2008 10:10 AM, Charles R Harris <[EMAIL PROTECTED]> wrote:
> > > On Jan 30, 2008 2:22 AM, Gael Varoquaux <[EMAIL PROTECTED]> > 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 > ...: > Oops, looks like that needs to be: In [5]: def factory(x) : ...: def f() : ...: print f.x ...: f.x = x ...: return f ...: You can also do something simpler: In [51]: def f() : print f.x ....: In [52]: f.x = "Hello World!" In [53]: f() Hello World! Chuck
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