On 6/26/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
On 6/26/07, Charles R Harris <[EMAIL PROTECTED]> wrote: > > > > On 6/26/07, Tom Denniston < [EMAIL PROTECTED]> wrote: > > > > In [1]: intArr1 = numpy.array([ 0, 1, 2,-2,-1, 5,-5,-5]) > > In [2]: intArr2 = numpy.array([1,1,1,2,2,2,3,4]) > > In [3]: charArr = numpy.array(['a','a','a','b','b','b','c','d']) > > > > Here I sort two int arrays. As expected intArr2 dominates intArr1 but > > the items with the same intArr2 values are sorted forwards according > > to intArr1 > > In [6]: numpy.lexsort((intArr1, intArr2)) > > Out[6]: array([0, 1, 2, 3, 4, 5, 6, 7]) > > > > This, however, looks like a bug to me. Here I sort an int array and > > a str array. As expected charArray dominates intArr1 but the items > > with the same charArray values are sorted *backwards* according to > > intArr1 > > In [5]: numpy.lexsort((intArr1, charArr)) > > Out[5]: array([2, 1, 0, 5, 4, 3, 6, 7]) > > > > Is this a bug or am I missing something? > >
It was a bug. It is fixed in svn. Chuck Looks like a bug.
> > In [12]: numpy.argsort([charArr], kind='m') > Out[12]: array([[2, 1, 0, 5, 4, 3, 6, 7]]) > > In [13]: numpy.argsort([intArr2], kind='m') > Out[13]: array([[0, 1, 2, 3, 4, 5, 6, 7]]) > > Both of these are stable sorts, and since the elements are in order > should return [[0, 1, 2, 3, 4, 5, 6, 7]]. Actually, I think they should > return [0, 1, 2, 3, 4, 5, 6, 7], I'm not sure why the returned array is 2D > and I suspect that is a bug also. As to why the string array sorts > incorrectly, I am not sure. It could be that the sort isn't stable, there > could be a stride error, or the comparison is returning wrong values. My bet > is on the first being the case. > Nevermind the 2D thingee, that was pilot error in changing lexsort to argsort, charArr should not be in a list: In [25]: numpy.argsort(charArr, kind='m', axis=0) Out[25]: array([2, 1, 0, 5, 4, 3, 6, 7]) Works just fine. Chuck
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