numpy API:

 

flip:

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.

>>> A = np.arange(8).reshape((2,2,2))>>> Aarray([[[0, 1],        [2, 3]],       [[4, 5],        [6, 7]]])>>> flip(A, 0)array([[[4, 5],        [6, 7]],       [[0, 1],        [2, 3]]])>>> 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]]])>>> A = np.random.randn(3,4,5)>>> np.all(flip(A,2) == A[:,:,::-1,...])True

flipud: (==flip(m, 1) )

Flip array in the up/down direction.

Flip the entries in each column in the up/down direction. Rows are preserved, but appear in a different order than before.

Equivalent to m[::-1,...]. Does not require the array to be two-dimensional.

>>> A = np.diag([1.0, 2, 3])>>> Aarray([[ 1.,  0.,  0.],       [ 0.,  2.,  0.],       [ 0.,  0.,  3.]])>>> np.flipud(A)array([[ 0.,  0.,  3.],       [ 0.,  2.,  0.],       [ 1.,  0.,  0.]])>>>>>> A = np.random.randn(2,3,5)>>> np.all(np.flipud(A) == A[::-1,...])True>>>>>> np.flipud([1,2])array([2, 1])

 

fliplr: (==flip(m, 0))

　　Equivalent to m[:,::-1]. Requires the array to be at least 2-D.

        Flip array in the left/right direction.

    rot90

        Rotate array counterclockwise.

>>> A = np.diag([1.,2.,3.])>>> Aarray([[ 1.,  0.,  0.],       [ 0.,  2.,  0.],       [ 0.,  0.,  3.]])>>> np.fliplr(A)array([[ 0.,  0.,  1.],       [ 0.,  2.,  0.],       [ 3.,  0.,  0.]])>>>>>> A = np.random.randn(2,3,5)>>> np.all(np.fliplr(A) == A[:,::-1,...])True