Often, I've wanted to concatenate arrays with different ndims along a particular axis, broadcasting the other axes as needed. Others have sought this functionality as well:
- https://stackoverflow.com/questions/56357047 - https://github.com/numpy/numpy/issues/2115 - https://stackoverflow.com/questions/52733240/concatenate-1d-array-to-a-3d-array - https://stackoverflow.com/questions/46700081/concat-two-arrays-of-different-dimensions-numpy - https://stackoverflow.com/questions/55879664/how-to-concatenate-a-2d-array-into-every-3d-array - https://stackoverflow.com/questions/63453495/combining-two-numpy-arrays However, [`numpy.concatenate`](https://numpy.org/doc/stable/reference/generated/numpy.concatenate.html) raises an error if the ndims don't match. For example: ```python3 import numpy as np a = np.full([2], 0.1) b = np.full([3, 2], 0.2) c = np.full([5, 3, 2], 0.3) arrays = [a, b, c] axis = -1 try: np.concatenate(arrays, axis) except ValueError as e: print(repr(e)) ``` ``` ValueError('all the input arrays must have same number of dimensions, but the array at index 0 has 1 dimension(s) and the array at index 1 has 2 dimension(s)') ``` It would be convenient to add to `numpy.concatenate` an optional boolean argument called `broadcast` that broadcasts the input arrays along the axes that are *not* the concatenation axis, before concatenating them. Its default value can be `False`, which is the current behavior. Below is an example implementation: ```python3 def tuple_replace(tupl, index, item): return tupl[:index] + (item,) + tupl[index:][1:] def broadcast_concat(arrays, axis): shape = np.broadcast_shapes(*(tuple_replace(a.shape, axis, 0) for a in arrays)) bcast_arrays = [ np.broadcast_to(a, tuple_replace(shape, axis, a.shape[axis])) for a in arrays ] return np.concatenate(bcast_arrays, axis) output = broadcast_concat(arrays, axis) assert output.shape[axis] == sum(a.shape[axis] for a in arrays) ``` If desired, I can submit a PR for this. _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
