Vectorization of functions with if tests; solutions

Simplest remedy: use NumPy's vectorize class to allow array arguments to a function: 
>>> somefuncv = vectorize(somefunc, otypes='d')

>>> # test:
>>> x = linspace(-1, 1, 3); print x
[-1.  0.  1.]
>>> somefuncv(x)
array([ 0.        ,  0.        ,  0.84147098])
Note: The data type must be specified as a character ('d' for double)
The speed of somefuncv is unfortunately quite slow
A better solution, using where: 
def somefuncv2(x):
    x2 = sin(x)
    return where(x < 0, 0, x2)

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