[Numpy-discussion] vectorized function inside a class
Wed Aug 8 10:54:18 CDT 2007
On 8/8/07, mark <email@example.com> wrote:
> I am trying to figure out a way to define a vectorized function inside
> a class.
> This is what I tried:
> class test:
> def __init__(self):
> self.x = 3.0
> def func(self,y):
> rv = self.x
> if y > self.x: rv = y
> return rv
> f = vectorize(func)
> >>> m = test()
> >>> m.f( m, [-20,4,6] )
> array([ 3., 4., 6.])
> But as you can see, I can only call the m.f function when I also pass
> it the instance m again.
> I really want to call it as
> m.f( [-20,4,6] )
> But then I get an error
> ValueError: mismatch between python function inputs and received
> Any ideas how to do this better?
Don't use vectorize? Something like:
return np.where(y > self.x, y, self.x)
You could also use vectorize by wrapping the result in a real method like
_f = vectorize(func)
def f(self, y):
return self._f(self, y)
That seems kind of silly in this instance though.
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