Fix GridInterface multi-dimensional groupby #1130
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philippjfr
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holoviews/core/data/grid.py
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| # Iterate over the unique entries applying selection masks | ||
| grouped_data = [] | ||
| for unique_key in zip(*util.cartesian_product(keys)): | ||
| for unique_key in zip(*(arr.flat for arr in util.cartesian_product(keys))): |
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The definition of cartesian_product(arrays) is simply np.broadcast_arrays(*np.ix_(*arrays)). I'm wondering if it might be useful behavior to always output an iterator over flattened/flat arrays...
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I should mention that I am assuming that we are almost always doing cartesian products over keys which we want to iterate over. I haven't checked where else cartesian_product maybe used... e.g elsewhere in the data API...
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Right, they're actually always flattened, I'll make that fix.
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Ah, I remember now the issue is the difference between flat and flatten. Often flat is enough other times you need to flatten to make a copy. I'll give the function a copy kwarg.
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Hmm, actually there is one usage where it's not flat. Should I also have a flat kwarg?
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Yes, a flat kwarg would be good and a copy kwarg also makes sense (should probably default to False).
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As @basnijholt originally reported there was an issue for multi-dimensional groupbys in the GridInterface. This PR fixes the bug and adds a unit test.