Random sampling in numpy | random() function
Last Updated :
26 Feb, 2019
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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 :
# 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)
Output :
Code #2 :
Output 1D Array filled with random floats : [ 0.21698734 0.01617363 0.70382199]
# 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)
Output :
Code #3 :
Output 2D Array filled with random floats : [[ 0.95423066 0.35595927 0.76048569 0.90163066] [ 0.41903408 0.85596254 0.21666156 0.05734769]]
# 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)
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]]]
