如何在Python使用 NumPy 随机选择数组的元素？

先决条件： Numpy

随机值在机器学习、统计和概率等数据相关领域很有用。这 numpy.random.choice() 函数用于从 NumPy 数组中获取随机元素。它是Python的 NumPy 包中的内置函数。

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

Parameters:

• a: a one-dimensional array/list (random sample will be generated from its elements) or an integer (random samples will be generated in the range of this integer)
• size: int or tuple of ints (default is None where a single random value is returned). If the given shape is (m,n), then m x n  random samples are drawn.
• replace: (optional); the Boolean value that specifies whether the sample is drawn with or without replacement. When sample is larger than the population of the list, replace cannot be False.
• p: (optional); a 1-D array containing probabilities associated with each entry in a. If not given then sample assumes uniform distribution over all entries in a.

方法

• 导入模块
• 创建样本数组
• 从创建的数组中随机选择值
• 打印如此生成的数组。

下面给出的是一维和二维数组的实现。

生成一维随机样本列表

示例 1：

Python3

import numpy as np
  
prog_langs = ['python', 'c++', 'java', 'ruby']
  
# generating random samples
print(np.random.choice(prog_langs, size=8))
  
# generating random samples without replacement
print(np.random.choice(prog_langs, size=3, replace=False))
  
# generating random samples with probabilities
print(np.random.choice(prog_langs, size=10,
                       replace=True, p=[0.3, 0.5, 0.0, 0.2]))

输出 ：

示例 2：

蟒蛇3

import numpy as np
  
samples = 5
# generating random samples
print(np.random.choice(samples, size=10))
  
# generating random samples without replacement
print(np.random.choice(samples, size=5, replace=False))
  
# generating random samples with probablities
print(np.random.choice(samples, size=5, replace=True))
  
# generating with probabilities
print(np.random.choice(samples, size=15,
                       replace=True, p=[0.2, 0.1, 0.1, 0.3, 0.3]))

输出：

生成随机样本的二维列表

例子：

蟒蛇3

import numpy as np
  
prog_langs = ['python', 'c++', 'java', 'ruby']
  
# generating random samples
print(np.random.choice(prog_langs, size=(4, 5)))
  
# generating random samples with probabilities
print('\n')
print(np.random.choice(prog_langs, size=(10, 2),
                       replace=True, p=[0.3, 0.5, 0.0, 0.2]))

输出：

示例 2：

蟒蛇3

import numpy as np
  
samples = 5
  
# generating random samples
print(np.random.choice(samples, size=(5, 5)))
  
# generating with probabilities
print('\n')
print(np.random.choice(samples, size=(8, 3),
                       replace=True,
                       p=[0.2, 0.1, 0.1, 0.3, 0.3]))

输出：