nested_iters(op, axes, flags=None, op_flags=None, op_dtypes=None, order="K", casting="safe", buffersize=0)
Create a tuple of nditer
objects which iterate in nested loops over different axes of the op argument. The first iterator is used in the outermost loop, the last in the innermost loop. Advancing one will change the subsequent iterators to point at its new element.
The array(s) to iterate over.
Each item is used as an "op_axes" argument to an nditer
See nditer
parameters of the same name
An nditer for each item in :None:None:`axes`, outermost first
Create nditers for use in nested loops
Basic usage. Note how y is the "flattened" version of [a[:, 0, :], a[:, 1, 0], a[:, 2, :]] since we specified the first iter's axes as [1]
>>> a = np.arange(12).reshape(2, 3, 2)See :
... i, j = np.nested_iters(a, [[1], [0, 2]], flags=["multi_index"])
... for x in i:
... print(i.multi_index)
... for y in j:
... print('', j.multi_index, y) (0,) (0, 0) 0 (0, 1) 1 (1, 0) 6 (1, 1) 7 (1,) (0, 0) 2 (0, 1) 3 (1, 0) 8 (1, 1) 9 (2,) (0, 0) 4 (0, 1) 5 (1, 0) 10 (1, 1) 11
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