On 05/14/2012 06:03 PM, Travis Oliphant wrote: > What happens, though when you have > > a[:, in1 :, in2]? > > in1 and in2 are broadcasted together to create a two-dimensional > "sub-space" that must fit somewhere. Where should it go? Should > it replace in1 or in2? I.e. should the output be > > (10,3,4,8) or (10,8,3,4). > > To "resolve" this ambiguity, the code sends the (3,4) sub-space to > the front of the "dimensions" and returns (3,4,10,8). In > retro-spect, the code should raise an error as I doubt anyone > actually relies on this behavior, and then we could have "done the > right" thing for situations like in1 being an integer which actually > makes some sense and should not have been confused with the "general > case" > > In this particular case you might also think that we could say the > result should be (10,3,8,4) but there is no guarantee that the number > of dimensions that should be appended by the "fancy-indexing" objects > will be the same as the number of dimensions replaced. Again, this > is how fancy-indexing combines with other fancy-indexing objects. > > So, the behavior is actually quite predictable, it's just that in > some common cases it doesn't do what you would expect --- especially > if you think that [0,1] is "the same" as :2. When I wrote this code > to begin with I should have raised an error and then worked in the > cases that make sense. This is a good example of making the > mistake of thinking that it's better to provide something very > general rather than just raise an error when an obvious and clear > solution is not available. > > There is the possibility that we could now raise an error in NumPy > when this situation is encountered because I strongly doubt anyone is > actually relying on the current behavior. I would like to do this, > actually, as soon as possible. Comments?
Travis, Good idea, especially if you can then make the integer case work as one might reasonably expect. Keeping the present too-fancy capabilities can only cause continuing confusion. Eric > > -Travis _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
