To elaborate on what Julian wrote: it is indeed simply a convention; slices/ranges in python are from the start to one-past-the-end. The reason for the emergence of this convention is that C code using iterators looks most natural this way. This manifests in a simple for (i = 0; i < 5; i++), but also when specifying a slice of a linked list, for instance. We don't want to terminate the loop when we are just arriving at the last item; we want to terminate a loop when we have gone past the last item. Also, the length of a range is simply end-start under this convention; no breaking your head over -1 or +1. Such little nudges of elegance pop up all over C code; and that's where the convention comes from. Same as zero-based indexing; just a convention, and if you are going to pick a convention you might as well pick one that minimizes the number of required operations. Anything but zero-based indexing will require additional integer math to find an array element, given its base pointer.
On Wed, Feb 26, 2014 at 12:15 AM, Julian Taylor < jtaylor.deb...@googlemail.com> wrote: > On 26.02.2014 00:04, JB wrote: > > At the risk of igniting a flame war...can someone please help me > understand > > the indexing behavior of NumPy? I will readily I admit I come from a > Matlab > > background, but I appreciate the power of Python and am trying to learn > more. > > > >>From a Matlab user's perspective, the behavior of indexing in NumPy seems > > very bizarre. For example, if I define an array: > > > > x = np.array([1,2,3,4,5,6,7,8,9,10]) > > > > If I want the first 5 elements, what do I do? Well, I say to myself, > Python > > is zero-based, whereas Matlab is one-based, so if I want the values 1 - > 5, > > then I want to index 0 - 4. So I type: x[0:4] > > > > And get in return: array([1, 2, 3, 4]). So I got the first value of my > > array, but I did not get the 5th value of the array. So the "start" index > > needs to be zero-based, but the "end" index needs to be one-based. Or to > put > > it another way, if I type x[4] and x[0:4], the 4 means different things > > depending on which set of brackets you're looking at! > > > > It's hard for me to see this as anything by extremely confusing. Can > someone > > explain this more clearly. Feel free to post links if you'd like. I know > > this has been discussed ad nauseam online; I just haven't found any of > the > > explanations satisfactory (or sufficiently clear, at any rate). > > > > > > numpy indexing is like conventional C indexing beginning from inclusive > 0 to exclusive upper bound: [0, 5[. So the selection length is upper > bound - lower bound. > as a for loop: > for (i = 0; i < 5; i++) > select(i); > > This is the same way Python treats slices. > > in comparison one based indexing is usually inclusive 1 to inclusive > upper bound: [1, 4]. So the selection length is upper bound - lower > bound + 1. > for (i = 1; i <= 4; i++) > select(i); > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
