Bugfix for Issue 218: NDCube slicing with numpy.int64 #223
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Thanks for the pull request @DanRyanIrish! Everything looks great! |
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Cadair
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ndcube/utils/wcs.py
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| @@ -207,7 +207,7 @@ def _wcs_slicer(wcs, missing_axes, item): | |||
| item_ = _slice_list(item_checked) | |||
| new_wcs = wcs.slice(item_) | |||
| for i, it in enumerate(item_checked): | |||
| if isinstance(it, int): | |||
| if isinstance(it, (int, np.int64, np.int32)): | |||
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I think this will work
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| if isinstance(it, (int, np.int64, np.int32)): | |
| if isinstance(it, numbers.Integral): |
having done a import numbers
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Looks like it does! Thanks!
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Hi @Cadair. Is there a better way to capture all int-types rather than just listing them out as is done in this PR? |
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If an axis after the first axis was sliced with a non-native int type, e.g. numpy.int64, the slixing would crash due to missing_axes not being altered. This commit adds support for nupy.int64 and numpy.int32 types.
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Description
If an NDCube axis after the first axis was sliced with a non-native int type,
e.g. numpy.int64, the slicing would crash due to missing_axes not being
altered. This commit adds support for numpy.int64 and numpy.int32 types.
Fixes #218