On Mon, Jul 17, 2017 at 2:13 AM, <martin.gfel...@swisscom.com> wrote: > > Dear all > > I have object array of arrays, which I compare element-wise to None in various places: > > >>> a = numpy.array([numpy.arange(5),None,numpy.nan,numpy.arange(6),None],dtype=numpy.object) > >>> a > array([array([0, 1, 2, 3, 4]), None, nan, array([0, 1, 2, 3, 4, 5]), None], dtype=object) > >>> numpy.equal(a,None) > FutureWarning: comparison to `None` will result in an elementwise object comparison in the future. > > > So far, I always ignored the warning, for lack of an idea how to resolve it. > > Now, with Numpy 1.13, I have to resolve the issue, because it fails with: > > ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() > > It seem that the numpy.equal is applied to each inner array, returning a Boolean array for each element, which cannot be coerced to a single Boolean. > > The expression > > >>> numpy.vectorize(operator.is_)(a,None) > > gives the desired result, but feels a bit clumsy.
Wrap the clumsiness up in a documented, tested utility function with a descriptive name and use that function everywhere instead. -- Robert Kern
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