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.


On Fri, Oct 31, 2014 at 2:13 PM Stefan Otte <stefan.otte@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
            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)
                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.


On Wed, Oct 29, 2014 at 3:59 PM, Stefan Otte <stefan.otte@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 <njs@pobox.com> wrote:
>> On 28 Oct 2014 18:34, "Stefan Otte" <stefan.otte@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
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