Hello all, The below seems to be a bug, but perhaps it's unavoidably part of the indexing mechanism?
It's easiest to show via example... note that using "[0,1]" to pull two columns out of the array gives the same shape as using ":2" in the simple case, but when there's additional slicing happening, the shapes get transposed or something. In [2]: numpy.version.version # latest git version Out[2]: '1.7.0.dev-3bbbbd4' In [3]: d = numpy.empty((10, 9, 8, 7)) In [4]: d[:,:,:,[0,1]].shape Out[4]: (10, 9, 8, 2) In [5]: d[:,:,:,:2].shape Out[5]: (10, 9, 8, 2) In [6]: d[:,0,:,[0,1]].shape Out[6]: (2, 10, 8) In [7]: d[:,0,:,:2].shape Out[7]: (10, 8, 2) In [8]: d[0,:,:,[0,1]].shape Out[8]: (2, 9, 8) In [9]: d[0,:,:,:2].shape Out[9]: (9, 8, 2) Oddly, this error can appear/disappear depending on the position of the other axis sliced: In [14]: d = numpy.empty((10, 9, 8)) In [15]: d[:,:,[0,1]].shape Out[15]: (10, 9, 2) In [16]: d[:,0,[0,1]].shape Out[16]: (10, 2) In [17]: d[0,:,[0,1]].shape Out[17]: (2, 9) This cannot be the expected behavior, right? Zach _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
