Strange numpy.argmax behavior on object arrays in numpy 1.0.

[Tom Denniston]

Oh.  My mistake. I thought I had an array of 2 objects which were ints.  I
actually had an array of one list of 2 ints.  It works properly if I
construct the array properly.


In [14]: a = numpy.empty((2), dtype=object)

In [15]: a[0:]=[2,3]

In [16]: a
Out[16]: array([2, 3], dtype=object)

In [17]: a.shape
Out[17]: (2,)

In [18]: a[0]
Out[18]: 2

In [19]: a[1]
Out[19]: 3

In [20]: numpy.argmax(a)
Out[20]: 1






On 10/29/06, Charles R Harris <charlesr.harris at gmail.com> wrote:
>
>
>
>  On 10/29/06, Tom Denniston <tom.denniston at alum.dartmouth.org> wrote:
> >
> > I recently upgraded to numpy 1.0 from 1.0b5.   I noticed that
> > numpy.argmax behavior is very strange on object arrays.  See below:
> >
> > (Pdb) numpy.__version__
> > '1.0'
> > (Pdb) numpy.argmax(numpy.array([2, 3], dtype=object))
> > 0
> > (Pdb) numpy.argmax(numpy.array([2, 3], dtype=int))
> > 1
> > (Pdb) numpy.argmax(numpy.array([2, 3], dtype=object), axis=0)
> > 0
> >
> >
> > I would expect the argmax to behave the same on the dtype=int and
> > dtype=object examples but it doesn't.  Am I missing some subtelty or is this
> > just a bug?  1.0 is the most recent version, right?
> >
>
> Suppose
>
> In [22]: array([1,[2,3]], dtype=object)
> Out[22]: array([1, [2, 3]], dtype=object)
>
> How would you compare the elements?
>
> In [27]: 2 < [0,0]
> Out[27]: True
>
> In [28]: [0,0] > 2
> Out[28]: True
>
> Compares memory locations?
>
> In [28]: [2] < [0,0]
> Out[28]: False
>
> Lexical ordering?
>
>
> I don't know how python interprets these things. That said, I suspect your
> example should behave better, but it might give strange results sometimes
> anyway.
>
> Chuck
>
>
>
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