Python numpy.random.randn()用法及代码示例

关于：
numpy.random.randn(d0，d1，…，dn)：创建一个指定形状的数组，并按照标准正态分布用随机值填充它。

如果提供了正参数，则randn会生成一个形状为(d0，d1，…，dn)的数组，其中填充了从均值0和方差1的单变量“normal”(Gaussian)分布采样的随机浮点数(如果d_i中的任何一个为浮点数，它们首先通过截断转换为整数)。如果未提供任何参数，则返回从分布中随机采样的单个浮点数。

参数：

d0, d1, ..., dn : [int, optional]Dimension of the returned array we require, 
     If no argument is given a single Python float is returned.

返回：

Array of defined shape, filled with random floating-point samples from 
the standard normal distribution.

代码1：随机构造一维数组

# Python Program illustrating 
# numpy.random.randn() method 
   
import numpy as geek 
   
# 1D Array 
array = geek.random.randn(5) 
print("1D Array filled with random values : \n", array);

输出：

1D Array filled with randnom values : 
 [-0.51733692  0.48813676 -0.88147002  1.12901958  0.68026197]

代码2：随机构造2D数组

# Python Program illustrating 
# numpy.random.randn() method 
   
import numpy as geek 
   
# 2D Array    
array = geek.random.randn(3, 4) 
print("2D Array filled with random values : \n", array);

输出：

2D Array filled with random values : 
 [[ 1.33262386 -0.88922967 -0.07056098  0.27340112]
 [ 1.00664965 -0.68443807  0.43801295 -0.35874714]
 [-0.19289416 -0.42746963 -1.80435223  0.02751727]]

代码3：随机构造3D数组

# Python Program illustrating 
# numpy.random.randn() method 
   
import numpy as geek 
   
# 3D Array      
array = geek.random.randn(2, 2 ,2) 
print("3D Array filled with random values : \n", array);

输出：

3D Array filled with random values : 
 [[[-0.00416587 -0.66211158]
  [-0.97254293 -0.68981333]]

 [[-0.18304476 -0.8371425 ]
  [ 2.18985366 -0.9740637 ]]]

代码4：使用随机创建的数组进行操作

# Python Program illustrating 
# numpy.random.randn() method 
   
import numpy as geek 
   
# 3D Array      
array = geek.random.randn(2, 2 ,2) 
print("3D Array filled with random values : \n", array); 
       
# Multiplying values with 3 
print("\nArray * 3 : \n", array *3) 
  
# Or we cab directly do so by  
array = geek.random.randn(2, 2 ,2) * 3 + 2
print("\nArray * 3 + 2 : \n", array);

输出：

3D Array filled with random values : 
 [[[ 1.9609643  -1.89882763]
  [ 0.52252173  0.08159455]]

 [[-0.6060213  -0.86759247]
  [ 0.53870235 -0.77388125]]]

Array * 3 : 
 [[[ 5.88289289 -5.69648288]
  [ 1.56756519  0.24478366]]

 [[-1.81806391 -2.6027774 ]
  [ 1.61610704 -2.32164376]]]

Array * 3 + 2 : 
 [[[-2.73766306  6.80761741]
  [-1.57909191 -1.64195796]]

 [[ 0.51019498  1.30017345]
  [ 3.8107863  -4.07438963]]]

参考文献：
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.random.randn.html