如何用NumPy从列表中选择不同概率的元素

我们将看到如何使用numpy.random.choice()方法从列表中选择具有不同概率的元素。

语法: numpy.random.choice(a, size=None, replace=True, p=None)

输出:返回随机样本的numpy数组。

注意: 参数p是与a(1d-array)中每个条目相关的概率。如果没有给定，样本会假定对a中的所有条目进行均匀分布。

现在，让我们看看这些例子。

示例 1:

# import numpy library
import numpy as np
  
# create a list
num_list = [10, 20, 30, 40, 50]
  
# uniformly select any element
# from the list
number = np.random.choice(num_list)
  
print(number)

输出:

示例 2:

# import numpy library
import numpy as np
  
# create a list
num_list = [10, 20, 30, 40, 50]
  
# choose index number-3rd element
# with 100% probability and other
# elements probability set to 0
# using p parameter of the
# choice() method so only
# 3rd index element selected
# every time in the list size of 3.
number_list = np.random.choice(num_list, 3,
                          p = [0, 0, 0, 1, 0])
  
print(number_list)

输出:

[40 40 40]

在上面的例子中，我们每次只想从给定的列表中选择第三个索引元素。

示例 3:

# import numpy library
import numpy as np
  
# create a list
num_list = [10, 20, 30, 40, 50]
  
  
# choose index number 2nd & 3rd element
# with  50%-50% probability and other
# elements probability set to 0
# using p parameter of the
# choice() method so 2nd & 
# 3rd index elements selected
# every time in the list size of 3.
number_list = np.random.choice(num_list, 3,
                          p = [0, 0, 0.5, 0.5, 0])
  
print(number_list)