StefanCheers,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.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
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.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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