On Sat, Mar 30, 2013 at 11:43 PM, Matthew Brett <matthew.br...@gmail.com> wrote: > Hi, > > On Sat, Mar 30, 2013 at 7:02 PM, <josef.p...@gmail.com> wrote: >> On Sat, Mar 30, 2013 at 8:29 PM, Matthew Brett <matthew.br...@gmail.com> >> wrote: >>> Hi, >>> >>> On Sat, Mar 30, 2013 at 7:50 PM, <josef.p...@gmail.com> wrote: >>>> On Sat, Mar 30, 2013 at 7:31 PM, Bradley M. Froehle >>>> <brad.froe...@gmail.com> wrote: >>>>> On Sat, Mar 30, 2013 at 3:21 PM, Matthew Brett <matthew.br...@gmail.com> >>>>> wrote: >>>>>> >>>>>> On Sat, Mar 30, 2013 at 2:20 PM, <josef.p...@gmail.com> wrote: >>>>>> > On Sat, Mar 30, 2013 at 4:57 PM, <josef.p...@gmail.com> wrote: >>>>>> >> On Sat, Mar 30, 2013 at 3:51 PM, Matthew Brett >>>>>> >> <matthew.br...@gmail.com> wrote: >>>>>> >>> On Sat, Mar 30, 2013 at 4:14 AM, <josef.p...@gmail.com> wrote: >>>>>> >>>> On Fri, Mar 29, 2013 at 10:08 PM, Matthew Brett >>>>>> >>>> <matthew.br...@gmail.com> wrote: >>>>>> >>>>> >>>>>> >>>>> Ravel and reshape use the tems 'C' and 'F" in the sense of index >>>>>> >>>>> ordering. >>>>>> >>>>> >>>>>> >>>>> This is very confusing. We think the index ordering and memory >>>>>> >>>>> ordering ideas need to be separated, and specifically, we should >>>>>> >>>>> avoid >>>>>> >>>>> using "C" and "F" to refer to index ordering. >>>>>> >>>>> >>>>>> >>>>> Proposal >>>>>> >>>>> ------------- >>>>>> >>>>> >>>>>> >>>>> * Deprecate the use of "C" and "F" meaning backwards and forwards >>>>>> >>>>> index ordering for ravel, reshape >>>>>> >>>>> * Prefer "Z" and "N", being graphical representations of unraveling >>>>>> >>>>> in >>>>>> >>>>> 2 dimensions, axis1 first and axis0 first respectively (excellent >>>>>> >>>>> naming idea by Paul Ivanov) >>>>>> >>>>> >>>>>> >>>>> What do y'all think? >>>>>> >>>> >>>>>> >>>> I always thought "F" and "C" are easy to understand, I always >>>>>> >>>> thought >>>>>> >>>> about >>>>>> >>>> the content and never about the memory when using it. >>>>>> >> >>>>>> >> changing the names doesn't make it easier to understand. >>>>>> >> I think the confusion is because the new A and K refer to existing >>>>>> >> memory >>>>>> >> >>>>>> >>>>>> I disagree, I think it's confusing, but I have evidence, and that is >>>>>> that four out of four of us tested ourselves and got it wrong. >>>>>> >>>>>> Perhaps we are particularly dumb or poorly informed, but I think it's >>>>>> rash to assert there is no problem here. >>>> >>>> I think you are overcomplicating things or phrased it as a "trick question" >>> >>> I don't know what you mean by trick question - was there something >>> over-complicated in the example? I deliberately didn't include >>> various much more confusing examples in "reshape". >> >> I meant making the "candidates" think about memory instead of just >> column versus row stacking. >> I don't think I ever get confused about reshape "F" in 2d. >> But when I work with 3d or larger ndim nd-arrays, I always have to >> try an example to check my intuition (in general not just reshape). >> >>> >>>> ravel F and C have *nothing* to do with memory layout. >>> >>> We do agree on this of course - but you said in an earlier mail that >>> you thought of 'C" and 'F' as referring to target memory layout (which >>> they don't in this case) so I think we also agree that "C" and "F" do >>> often refer to memory layout elsewhere in numpy. >> >> I guess that wasn't so helpful. >> (emphasis on *target*, There are very few places where an order >> keyword refers to *existing* memory layout. > > It is helpful because it shows how easy it is to get confused between > memory order and index order. > >> What's reverse index order? > > I am not being clear, sorry about that: > > import numpy as np > > def ravel_iter_last_fastest(arr): > res = [] > for i in range(arr.shape[0]): > for j in range(arr.shape[1]): > for k in range(arr.shape[2]): > # Iterating over last dimension fastest > res.append(arr[i, j, k]) > return np.array(res) > > > def ravel_iter_first_fastest(arr): > res = [] > for k in range(arr.shape[2]): > for j in range(arr.shape[1]): > for i in range(arr.shape[0]): > # Iterating over first dimension fastest > res.append(arr[i, j, k]) > return np.array(res)
good example that's just C and F order in the terminology of numpy http://docs.scipy.org/doc/numpy/reference/arrays.nditer.html#controlling-iteration-order (independent of memory) http://docs.scipy.org/doc/numpy/reference/generated/numpy.flatiter.html#numpy.flatiter I don't think we want to rename a large part of the basic terminology of numpy Josef > > > a = np.arange(24).reshape((2, 3, 4)) > > print np.all(a.ravel('C') == ravel_iter_last_fastest(a)) > print np.all(a.ravel('F') == ravel_iter_first_fastest(a)) > > By 'reverse index ordering' I mean 'ravel_iter_last_fastest' above. I > guess one could argue that this was not 'reverse' but 'forward' index > ordering, but I am not arguing about which is better, or those names, > only that it's the order of indices that differs, not the memory > layout, and that these ideas need to be kept separate. > > Cheers, > > Matthew > _______________________________________________ > 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
