python – Numpy：将每行的最大值更改为1,将所有其他数字更改为0

>>> a = np.array([[0, 1],
...               [2, 3],
...               [4, 5],
...               [6, 7],
...               [9, 8]])
>>> b = some_function(a)
>>> b
[[0. 1.]
 [0. 1.]
 [0. 1.]
 [0. 1.]
 [1. 0.]]

到目前为止我尝试过的

def some_function(x):
    a = np.zeros(x.shape)
    a[:,np.argmax(x, axis=1)] = 1
    return a

>>> b = some_function(a)
>>> b
[[1. 1.]
 [1. 1.]
 [1. 1.]
 [1. 1.]
 [1. 1.]]

>>> a = np.array([[0, 1], [2, 3], [4, 5], [6, 7], [9, 8]])
>>> b = np.zeros_like(a)
>>> b[np.arange(len(a)), a.argmax(1)] = 1
>>> b
array([[0, 1],
       [0, 1],
       [0, 1],
       [0, 1],
       [1, 0]])

[实际上,范围会很好;我出于习惯写了一个范围.

方法#2,使用max而不是argmax来处理多个元素达到最大值的情况：

>>> a = np.array([[0, 1], [2, 2], [4, 3]])
>>> (a == a.max(axis=1)[:,None]).astype(int)
array([[0, 1],
       [1, 1],
       [1, 0]])