Hey, Just a quick update. I updated the pull request and renamed `stack` into `block`. Have a look: https://github.com/numpy/numpy/pull/5057
I'm sticking with simple initial implementation because it's simple and does what you think it does. Cheers, Stefan On Fri, Oct 31, 2014 at 2:13 PM Stefan Otte <stefan.o...@gmail.com> wrote: > To make the last point more concrete the implementation could look > something like this (note that I didn't test it and that it still > takes some work): > > > def bmat(obj, ldict=None, gdict=None): > return matrix(stack(obj, ldict, gdict)) > > > def stack(obj, ldict=None, gdict=None): > # the old bmat code minus the matrix calls > if isinstance(obj, str): > if gdict is None: > # get previous frame > frame = sys._getframe().f_back > glob_dict = frame.f_globals > loc_dict = frame.f_locals > else: > glob_dict = gdict > loc_dict = ldict > return _from_string(obj, glob_dict, loc_dict) > > if isinstance(obj, (tuple, list)): > # [[A,B],[C,D]] > arr_rows = [] > for row in obj: > if isinstance(row, N.ndarray): # not 2-d > return concatenate(obj, axis=-1) > else: > arr_rows.append(concatenate(row, axis=-1)) > return concatenate(arr_rows, axis=0) > > if isinstance(obj, N.ndarray): > return obj > > > I basically turned the old `bmat` into `stack` and removed the matrix > calls. > > > Best, > Stefan > > > > On Wed, Oct 29, 2014 at 3:59 PM, Stefan Otte <stefan.o...@gmail.com> > wrote: > > Hey, > > > > there are several ways how to proceed. > > > > - My proposed solution covers the 80% case quite well (at least I use > > it all the time). I'd convert the doctests into unittests and we're > > done. > > > > - We could slightly change the interface to leave out the surrounding > > square brackets, i.e. turning `stack([[a, b], [c, d]])` into > > `stack([a, b], [c, d])` > > > > - We could extend it even further allowing a "filler value" for non > > set values and a "shape" argument. This could be done later as well. > > > > - `bmat` is not really matrix specific. We could refactor `bmat` a bit > > to use the same logic in `stack`. Except the `matrix` calls `bmat` and > > `_from_string` are pretty agnostic to the input. > > > > I'm in favor of the first or last approach. The first: because it > > already works and is quite simple. The last: because the logic and > > tests of both `bmat` and `stack` would be the same and the feature to > > specify a string representation of the block matrix is nice. > > > > > > Best, > > Stefan > > > > > > > > On Tue, Oct 28, 2014 at 7:46 PM, Nathaniel Smith <n...@pobox.com> wrote: > >> On 28 Oct 2014 18:34, "Stefan Otte" <stefan.o...@gmail.com> wrote: > >>> > >>> Hey, > >>> > >>> In the last weeks I tested `np.asarray(np.bmat(....))` as `stack` > >>> function and it works quite well. So the question persits: If `bmat` > >>> already offers something like `stack` should we even bother > >>> implementing `stack`? More code leads to more > >>> bugs and maintenance work. (However, the current implementation is > >>> only 5 lines and by using `bmat` which would reduce that even more.) > >> > >> In the long run we're trying to reduce usage of np.matrix and ideally > >> deprecate it entirely. So yes, providing ndarray equivalents of matrix > >> functionality (like bmat) is valuable. > >> > >> -n > >> > >> > >> _______________________________________________ > >> NumPy-Discussion mailing list > >> NumPy-Discussion@scipy.org > >> http://mail.scipy.org/mailman/listinfo/numpy-discussion > >> >
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