Detailed explanation of the difference between numpy.random.randn() and rand()

The following is a detailed explanation of the difference between numpy.random.randn() and rand(). It has a good reference value and I hope it will be helpful to everyone. Let’s take a look together

numpy There are some commonly used functions used to generate random numbers, randn() and rand() belong to them.

numpy.random.randn(d0, d1, …, dn) returns one or more sample values ​​from the standard normal distribution.

numpy.random.rand(d0, d1, …, dn) ’s random sample is located in [0, 1).

import numpy as np 
arr1 = np.random.randn(2,4)
print(arr1)
print('******************************************************************')
arr2 = np.random.rand(2,4)
print(arr2)

Result:

[[-1.03021018 0.5197033 0.52117459 -0.70102661]
 [ 0.98268569 1.21940697 -1.095241 -0.38161758]]
******************************************************************
[[ 0.19947349 0.05282713 0.56704222 0.45479972]
 [ 0.28827103 0.1643551 0.30486786 0.56386943]]

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