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 >> _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion