On Thu, May 5, 2011 at 9:18 PM, Benjamin Root <ben.r...@ou.edu> wrote:
> > > On Thu, May 5, 2011 at 1:08 PM, Paul Anton Letnes < > paul.anton.let...@gmail.com> wrote: > >> >> On 5. mai 2011, at 08.49, Benjamin Root wrote: >> >> > >> > >> > On Wed, May 4, 2011 at 11:08 PM, Paul Anton Letnes < >> paul.anton.let...@gmail.com> wrote: >> > >> > On 4. mai 2011, at 20.33, Benjamin Root wrote: >> > >> > > On Wed, May 4, 2011 at 7:54 PM, Derek Homeier < >> de...@astro.physik.uni-goettingen.de> wrote: >> > > On 05.05.2011, at 2:40AM, Paul Anton Letnes wrote: >> > > >> > > > But: Isn't the numpy.atleast_2d and numpy.atleast_1d functions >> written for this? Shouldn't we reuse them? Perhaps it's overkill, and >> perhaps it will reintroduce the 'transposed' problem? >> > > >> > > Yes, good point, one could replace the >> > > X.shape = (X.size, ) with X = np.atleast_1d(X), >> > > but for the ndmin=2 case, we'd need to replace >> > > X.shape = (X.size, 1) with X = np.atleast_2d(X).T - >> > > not sure which solution is more efficient in terms of memory access >> etc... >> > > >> > > Cheers, >> > > Derek >> > > >> > > >> > > I can confirm that the current behavior is not sufficient for all of >> the original corner cases that ndmin was supposed to address. Keep in mind >> that np.loadtxt takes a one-column data file and a one-row data file down to >> the same shape. I don't see how the current code is able to produce the >> correct array shape when ndmin=2. Do we have some sort of counter in >> loadtxt for counting the number of rows and columns read? Could we use >> those to help guide the ndmin=2 case? >> > > >> > > I think that using atleast_1d(X) might be a bit overkill, but it would >> be very clear as to the code's intent. I don't think we have to worry about >> memory usage if we limit its use to only situations where ndmin is greater >> than the number of dimensions of the array. In those cases, the array is >> either an empty result, a scalar value (in which memory access is trivial), >> or 1-d (in which a transpose is cheap). >> > >> > What if one does things the other way around - avoid calling squeeze >> until _after_ doing the atleast_Nd() magic? That way the row/column >> information should be conserved, right? Also, we avoid transposing, memory >> use, ... >> > >> > Oh, and someone could conceivably have a _looong_ 1D file, but would >> want it read as a 2D array. >> > >> > Paul >> > >> > >> > >> > @Derek, good catch with noticing the error in the tests. We do still >> need to handle the case I mentioned, however. I have attached an example >> script to demonstrate the issue. In this script, I would expect the >> second-to-last array to be a shape of (1, 5). I believe that the >> single-row, multi-column case would actually be the more common type of >> edge-case encountered by users than the others. Therefore, I believe that >> this ndmin fix is not adequate until this is addressed. >> > >> > @Paul, we can't call squeeze after doing the atleast_Nd() magic. That >> would just undo whatever we had just done. Also, wrt the transpose, a (1, >> 100000) array looks the same in memory as a (100000, 1) array, right? >> Agree. I thought more along the lines of (pseudocode-ish) >> if ndmin == 0: >> squeeze() >> if ndmin == 1: >> atleast_1D() >> elif ndmin == 2: >> atleast_2D() >> else: >> I don't rightly know what would go here, maybe raise ValueError? >> >> That would avoid the squeeze call before the atleast_Nd magic. But the >> code was changed, so I think my comment doesn't make sense anymore. It's >> probably fine the way it is! >> >> Paul >> >> > I have thought of that too, but the problem with that approach is that > after reading the file, X will have 2 or 3 dimensions, regardless of how > many singleton dims were in the file. A squeeze will always be needed. > Also, the purpose of squeeze is opposite that of the atleast_*d() > functions: squeeze reduces dimensions, while atleast_*d will add > dimensions. > > Therefore, I re-iterate... the patch by Derek gets the job done. I have > tested it for a wide variety of inputs for both regular arrays and record > arrays. Is there room for improvements? Yes, but I think that can wait for > later. Derek's patch however fixes an important bug in the ndmin > implementation and should be included for the release. > > Two questions: can you point me to the patch/ticket, and is this a regression? Thanks, Ralf
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