It is common to want to pad an array along a *specific* axis. Examples: - https://stackoverflow.com/questions/72106542/how-to-pad-the-i-j-axes-of-a-3d-np-array-without-padding-its-k-axis - https://stackoverflow.com/questions/56076094/zero-pad-ndarray-along-axis - https://stackoverflow.com/questions/66225047/padding-a-3-dimensional-numpy-array-with-the-medians-alongside-specific-axis - https://stackoverflow.com/questions/19349410/how-to-pad-with-zeros-a-tensor-along-some-axis-python - https://stackoverflow.com/questions/74966041/how-to-pad-a-specific-dimension-of-a-numpy-array
Doing so with [`numpy.pad`](https://numpy.org/doc/stable/reference/generated/numpy.pad.html) requires constructing a list of pairs of length equal to the ndim of the array, with exactly one of those pairs at the right position containing the desired pad widths. This can be verbose and clumsy when there are several axes. I propose a new, more user-friendly way to pad along a specific axis (or axes): Let the `pad_width` argument accept a *dictionary* whose keys are axes and whose values are the `(before, after)` pair (or perhaps single number) for the corresponding axis. Example: ```python3 # before np.pad(array, [(0, 0), (0, 0), (1, 2), (0, 0), (0, 0)]) # after np.pad(array, {-3: (1, 2)}) ``` This should require only minor modification to the implementation of `numpy.pad`. If others like this idea, I can create a PR for it. _______________________________________________ NumPy-Discussion mailing list -- [email protected] To unsubscribe send an email to [email protected] https://mail.python.org/mailman3//lists/numpy-discussion.python.org Member address: [email protected]
