洗牌2D数组的行组-NumPy

假设我有一个（50，5）数组。我有没有办法根据数据点的行/序列分组来洗牌，即不是洗牌每一行，而是洗牌5行的块

感谢

方法#1:这是一种基于组大小重塑为

3D

数组的方法，使用从

np.random.permutation

获得的无序索引索引索引块索引，最后重塑为

2D

-

N = 5 # Blocks of N rows
M,n = a.shape[0]//N, a.shape[1]
out = a.reshape(M,-1,n)[np.random.permutation(M)].reshape(-1,n)

样本运行-

In [141]: a
Out[141]: 
array([[89, 26, 12],
       [97, 60, 96],
       [94, 38, 54],
       [41, 63, 29],
       [88, 62, 48],
       [95, 66, 32],
       [28, 58, 80],
       [26, 35, 89],
       [72, 91, 38],
       [26, 70, 93]])

In [142]: N = 2 # Blocks of N rows

In [143]: M,n = a.shape[0]//N, a.shape[1]

In [144]: a.reshape(M,-1,n)[np.random.permutation(M)].reshape(-1,n)
Out[144]: 
array([[94, 38, 54],
       [41, 63, 29],
       [28, 58, 80],
       [26, 35, 89],
       [89, 26, 12],
       [97, 60, 96],
       [72, 91, 38],
       [26, 70, 93],
       [88, 62, 48],
       [95, 66, 32]])

In [156]: a
Out[156]: 
array([[15, 12, 14],
       [55, 39, 35],
       [73, 78, 36],
       [54, 52, 32],
       [83, 34, 91],
       [42, 11, 98],
       [27, 65, 47],
       [78, 75, 82],
       [33, 52, 93],
       [87, 51, 80]])

In [157]: N = 2 # Blocks of N rows

In [158]: M,n = a.shape[0]//N, a.shape[1]

In [159]: np.random.shuffle(a.reshape(M,-1,n))

In [160]: a
Out[160]: 
array([[15, 12, 14],
       [55, 39, 35],
       [27, 65, 47],
       [78, 75, 82],
       [73, 78, 36],
       [54, 52, 32],
       [33, 52, 93],
       [87, 51, 80],
       [83, 34, 91],
       [42, 11, 98]])

---

方法#2:也可以简单地用于现场变更-

np.random.shuffle(a.reshape(M,-1,n))

样本运行-

In [141]: a
Out[141]: 
array([[89, 26, 12],
       [97, 60, 96],
       [94, 38, 54],
       [41, 63, 29],
       [88, 62, 48],
       [95, 66, 32],
       [28, 58, 80],
       [26, 35, 89],
       [72, 91, 38],
       [26, 70, 93]])

In [142]: N = 2 # Blocks of N rows

In [143]: M,n = a.shape[0]//N, a.shape[1]

In [144]: a.reshape(M,-1,n)[np.random.permutation(M)].reshape(-1,n)
Out[144]: 
array([[94, 38, 54],
       [41, 63, 29],
       [28, 58, 80],
       [26, 35, 89],
       [89, 26, 12],
       [97, 60, 96],
       [72, 91, 38],
       [26, 70, 93],
       [88, 62, 48],
       [95, 66, 32]])

In [156]: a
Out[156]: 
array([[15, 12, 14],
       [55, 39, 35],
       [73, 78, 36],
       [54, 52, 32],
       [83, 34, 91],
       [42, 11, 98],
       [27, 65, 47],
       [78, 75, 82],
       [33, 52, 93],
       [87, 51, 80]])

In [157]: N = 2 # Blocks of N rows

In [158]: M,n = a.shape[0]//N, a.shape[1]

In [159]: np.random.shuffle(a.reshape(M,-1,n))

In [160]: a
Out[160]: 
array([[15, 12, 14],
       [55, 39, 35],
       [27, 65, 47],
       [78, 75, 82],
       [73, 78, 36],
       [54, 52, 32],
       [33, 52, 93],
       [87, 51, 80],
       [83, 34, 91],
       [42, 11, 98]])