Re: [Numpy-discussion] How to compare an array of arrays elementwise to None in

On Wed, 2017-07-19 at 08:31 +0000, Martin.Gfeller@swisscom.com wrote:

Thank you for your help!

Sebastian, I couldn't agree more with someone's bug being someone else's feature! A fast identity ufunc would be useful, though. 

An `object_identity` ufunc should be very easy to implement, the bigger work is likely to actually decide on it and the name. Also should probably check back with the PyPy guys to make sure it would also work on PyPy. - Sebastian

Actually, numpy.frompyfunc(operator.is_,2,1) is much faster than the numpy.vectorize approach - only about 35% slower on quick measurement  than the direct ==, as opposed to 62% slower with vectorize (with otypes hint). 

Robert, yes, that's what I already did provisionally. 

Eric, that is a nice puzzle - but I agree with Robert about understanding by code maintainers. 

Thanks again, and best regards, Martin

On Mon, 17 Jul 2017 11:41 Sebastian Berg write

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Yes, I guess ones bug is someone elses feature :(, if it is very bad, we could delay the deprecation probably. For a solutions, maybe  we could add a ufunc  for elementwise `is` on object arrays (dunno about the name, maybe `object_identity`. Just some quick thoughts. - Sebastian

On Mon, 17 Jul 2017 at 17:45 Robert Kern wrote:

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Wrap the clumsiness up in a documented, tested utility function with a descriptive name and use that function everywhere instead. Robert Kern

On Mon, Jul 17, 2017 at 10:52 AM, Eric Wieser wrote:

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Here's a hack that lets you keep using ==:

class IsCompare:     __array_priority__ = 999999  # needed to make it work on either side of `==`     def __init__(self, val): self._val = val     def __eq__(self, other): return other is self._val     def __neq__(self, other): return other is not self._val

a == IsCompare(None)  # a is None a == np.array(IsCompare(None)) # broadcasted a is None

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