[Numpy-discussion] guvectorize, a helper for writing generalized ufuncs

[Stephan Hoyer]

NumPy has the handy np.vectorize for turning Python code that operates on
scalars into a function that vectorizes works like a ufunc, but no helper
function for creating generalized ufuncs (
http://docs.scipy.org/doc/numpy/reference/c-api.generalized-ufuncs.html).

np.apply_along_axis accomplishes some of this, but it only allows a single
core dimension on a single argument.

So I propose adding a new object, np.guvectorize(pyfunc, signature, otypes,
...), where pyfunc is defined over the core dimensions only of any inputs
and signature is any valid gufunc signature (a string). Calling this object
would apply the gufunc. This is inspired by the similar numba.guvectorize,
which is currently the easiest way to write a gufunc in Python.

In addition to be handy like vectorize, such functionality would be
especially useful for with working libraries that build upon NumPy to
extend the capabilities of generalized ufuncs (e.g., xarray after
https://github.com/pydata/xarray/pull/964).

Cheers,
Stephan
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