[NumPy-Tickets] [NumPy] #2122: numpy.take gives corrupted result with inplace operation

NumPy Trac numpy-tickets@scipy....
Sun Apr 29 18:20:46 CDT 2012

#2122: numpy.take gives corrupted result with inplace operation
 Reporter:  rainwoodman  |       Owner:  somebody   
     Type:  defect       |      Status:  new        
 Priority:  high         |   Milestone:  Unscheduled
Component:  numpy.core   |     Version:  1.6.1      
 Keywords:               |  
 Take doesn't work as expected when the output is inplace.

 When mode='clip' or mode='wrap', the operation is truly in-place,
 and the simple take algorithm currently implemented will overwrite the
 array elements before they are memmoved to the correct reindexed

 A simple test case is listed below,

 In [37]: a = array([0, 1, 2])
 In [38]: ind = array([2, 1, 0])
 In [39]: b = a.copy()
 In [40]: a.take(ind, out=a)
 Out[40]: array([2, 1, 0])
 In [41]: a = b.copy()
 In [42]: a.take(ind, out=a, mode='clip')
 Out[42]: array([2, 1, 2])

 Out[40] is correct, for mode='raise' secretly creates a copy of the output
 before copying. But Out[42] is in-correct. No error or warning is given.

 A fix is either to create a copy for the other two modes, or to actually
 use a permuting algorithm. The latter calls for a full rewrite of
 PyArray_Take but will save memory usage significantly.
 A proper implementation is used in GSL: gsl_permute.

Ticket URL: <http://projects.scipy.org/numpy/ticket/2122>
NumPy <http://projects.scipy.org/numpy>
My example project

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