Anne Archibald <peridot.faceted <at> gmail.com> writes:
> Vectorizing apply is what you're looking for, by the sound of it:
> In [13]: a = array([lambda x: x**2, lambda x: x**3])
>
> In [14]: b = arange(5)
>
> In [15]: va = vectorize(lambda f, x: f(x))
>
> In [16]: va(a[:,newaxis],b[newaxis,:])
> Out[16]:
> array([[ 0, 1, 4, 9, 16],
> [ 0, 1, 8, 27, 64]])
Thanks for pointing that out. Technically that works, but it doesn't really
express this operation as concisely and as naturally as I'd like to be able to.
What I really want is to be able to write:
>>> a = array([lambda x: x**2, lambda x: x**3])
>>> b = arange(5)
>>> a(b)
and get:
array([[ 0, 1, 4, 9, 16],
[ 0, 1, 8, 27, 64]])
instead of the present error message:
Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: 'numpy.ndarray' object is not callable
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