Random sampling in numpy | random() function

numpy.random.random() is one of the function for doing random sampling in numpy. It returns an array of specified shape and fills it with random floats in the half-open interval [0.0, 1.0).

Syntax : numpy.random.random(size=None)

Parameters :
size : [int or tuple of ints, optional] Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned.



Return : Array of random floats in the interval [0.0, 1.0). or a single such random float if size not provided.

Code #1 :

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# Python program explaining
# numpy.random.random() function
  
# importing numpy
import numpy as geek
  
  
# output array
out_arr = geek.random.random(size = 3)
print ("Output 1D Array filled with random floats : ", out_arr) 

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Output :

Output 1D Array filled with random floats :  [ 0.21698734  0.01617363  0.70382199]

 

Code #2 :

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# Python program explaining
# numpy.random.random() function
  
# importing numpy
import numpy as geek
  
  
# output array
out_arr = geek.random.random(size =(2, 4))
print ("Output 2D Array filled with random floats : ", out_arr) 

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Output :

Output 2D Array filled with random floats :  [[ 0.95423066  0.35595927  0.76048569  0.90163066]
 [ 0.41903408  0.85596254  0.21666156  0.05734769]]

 
Code #3 :

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# Python program explaining
# numpy.random.random() function
  
# importing numpy
import numpy as geek
  
# output array
out_arr = geek.random.random((2, 3, 2))
print ("Output 3D Array filled with random floats : ", out_arr) 

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Output :

Output 3D Array filled with random floats :  [[[ 0.07861816  0.79132387]
  [ 0.9112629   0.98162851]
  [ 0.0727613   0.03480279]]

 [[ 0.11267727  0.07631742]
  [ 0.47554553  0.83625053]
  [ 0.67781339  0.37856642]]]


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