numpy.flip#
- numpy.flip(m, axis=None)[source]#
Reverse the order of elements in an array along the given axis.
The shape of the array is preserved, but the elements are reordered.
New in version 1.12.0.
- Parameters:
- marray_like
Input array.
- axisNone or int or tuple of ints, optional
Axis or axes along which to flip over. The default, axis=None, will flip over all of the axes of the input array. If axis is negative it counts from the last to the first axis.
If axis is a tuple of ints, flipping is performed on all of the axes specified in the tuple.
Changed in version 1.15.0: None and tuples of axes are supported
- Returns:
- outarray_like
A view of m with the entries of axis reversed. Since a view is returned, this operation is done in constant time.
Notes
flip(m, 0) is equivalent to flipud(m).
flip(m, 1) is equivalent to fliplr(m).
flip(m, n) corresponds to
m[...,::-1,...]
with::-1
at position n.flip(m) corresponds to
m[::-1,::-1,...,::-1]
with::-1
at all positions.flip(m, (0, 1)) corresponds to
m[::-1,::-1,...]
with::-1
at position 0 and position 1.Examples
>>> import numpy as np >>> A = np.arange(8).reshape((2,2,2)) >>> A array([[[0, 1], [2, 3]], [[4, 5], [6, 7]]]) >>> np.flip(A, 0) array([[[4, 5], [6, 7]], [[0, 1], [2, 3]]]) >>> np.flip(A, 1) array([[[2, 3], [0, 1]], [[6, 7], [4, 5]]]) >>> np.flip(A) array([[[7, 6], [5, 4]], [[3, 2], [1, 0]]]) >>> np.flip(A, (0, 2)) array([[[5, 4], [7, 6]], [[1, 0], [3, 2]]]) >>> rng = np.random.default_rng() >>> A = rng.normal(size=(3,4,5)) >>> np.all(np.flip(A,2) == A[:,:,::-1,...]) True