Python的numpy选择特定行列的方法

x = np.array([[ 0,  1,  2,  3],
               [ 4,  5,  6,  7],
               [ 8,  9, 10, 11],
               [12, 13, 14, 15]])
y = np.array([[ 0,  3],
              [ 4,  7]])

y
Out[22]: array([0, 7])

 x[[0,1]][:,[0,3]]
Out[31]: 
array([[0, 3],
       [4, 7]])

index = [[[0,0],[1,1]],[[0,3],[0,3]]]
x[index]
Out[33]: 
array([[0, 3],
       [4, 7]])

x[[0,1],[[0],[3]]]
Out[39]: 
array([[0, 4],
       [3, 7]])

ix_(*args)
    Construct an open mesh from multiple sequences.
    This function takes N 1-D sequences and returns N outputs with N
    dimensions each, such that the shape is 1 in all but one dimension
    and the dimension with the non-unit shape value cycles through all
    N dimensions.
    Using `ix_` one can quickly construct index arrays that will index
    the cross product. ``a[np.ix_([1,3],[2,5])]`` returns the array
    ``[[a[1,2] a[1,5]], [a[3,2] a[3,5]]]``.

i,j = np.ix_([0,1],[0,3]) 
x[i,j]
Out[44]: 
array([[0, 3],
       [4, 7]])