From: Tom D. <tom...@al...> - 2006-10-30 01:10:08
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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 <cha...@gm...> wrote: > > > > On 10/29/06, Tom Denniston <tom...@al...> 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 > > > > ------------------------------------------------------------------------- > Using Tomcat but need to do more? Need to support web services, security? > Get stuff done quickly with pre-integrated technology to make your job > easier > Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo > http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 > > _______________________________________________ > Numpy-discussion mailing list > Num...@li... > https://lists.sourceforge.net/lists/listinfo/numpy-discussion > > > |