vectorize pitfall

[A. M. Archibald]

Hi,

Vectorize is a very handy function, but it has at least one pitfall:

def f(x):
    if 1.3<x<2.5:
        return sqrt(x)
    else:
        return 0

Now vectorize(f)(2)=1.41421356237 but vectorize(f)(array([1,2]))=array([0,1]).

The problem is that, when given an array as input, vectorize feeds in
the first element, looks at the return type, and returns an array of
that type - and I didn't put a "." after the zero.

This should perhaps be in the docstring of vectorize, since I can't
see any way to work around it, but it can easily lead to
difficult-to-find bugs. It may seem like an artificial example, but it
came up with a function I was working on. But it's confusing
behaviour.

vectorize appears to support an "otypes" argument, but it doesn't take
standard numpy type objects, and it doesn't do anything obvious.

Perhaps I should file a ticket, but first I'd like to understand the
correct behaviour...

A. M. Archibald

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