标签：... python flip flipud np array numpy 翻转
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))
>>> A
array([[[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])
>>> A
array([[ 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.])
>>> A
array([[ 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
标签：...,python,flip,flipud,np,array,numpy,翻转 来源： https://www.cnblogs.com/xiaoniu-666/p/11123560.html
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