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 <[EMAIL PROTECTED]> wrote:
On 10/29/06, Tom Denniston < [EMAIL PROTECTED]> 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?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.
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?
Chuck
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