[Numpy-discussion] Vectorize and ufunc attribute

[T J]

Prior to 1.7, I had working compatibility code such as the following:


if has_good_functions:
    # http://projects.scipy.org/numpy/ticket/1096
    from numpy import logaddexp, logaddexp2
else:
    logaddexp = vectorize(_logaddexp, otypes=[numpy.float64])
    logaddexp2 = vectorize(_logaddexp2, otypes=[numpy.float64])

    # Run these at least once so that .ufunc.reduce exists
    logaddexp([1.,2.,3.],[1.,2.,3.])
    logaddexp2([1.,2.,3.],[1.,2.,3.])

    # And then make reduce available at the top level
    logaddexp.reduce = logaddexp.ufunc.reduce
    logaddexp2.reduce = logaddexp2.ufunc.reduce


The point was that I wanted to treat the output of vectorize as a hacky
drop-in replacement for a ufunc.  In 1.7, I discovered that vectorize had
changed (https://github.com/numpy/numpy/pull/290), and now there is no
longer a ufunc attribute at all.

Should this be added back in?  Besides hackish drop-in replacements, I see
value in to being able to call reduce, accumulate, etc (when possible) on
the output of vectorize().
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