numpy.nested_iters#
- numpy.nested_iters(op, axes, flags=None, op_flags=None, op_dtypes=None, order='K', casting='safe', buffersize=0)#
Create nditers for use in nested loops
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.- Parameters
- opndarray or sequence of array_like
The array(s) to iterate over.
- axeslist of list of int
Each item is used as an “op_axes” argument to an nditer
- flags, op_flags, op_dtypes, order, casting, buffersize (optional)
See
nditer
parameters of the same name
- Returns
- iterstuple of nditer
An nditer for each item in axes, outermost first
See also
Examples
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) >>> 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