Random sampling in numpy | random_sample() function
Last Updated :
26 Feb, 2019
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numpy.random.random_sample() 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_sample(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.sample() function
# importing numpy
import numpy as geek
# output random value
out_val = geek.random.random_sample()
print ("Output random float value : ", out_val)
Output :
Code #2 :
Output random float value : 0.9211987310893188
# Python program explaining
# numpy.random.random_sample() function
# importing numpy
import numpy as geek
# output array
out_arr = geek.random.random_sample(size =(1, 3))
print ("Output 2D Array filled with random floats : ", out_arr)
Output :
Code #3 :
Output 2D Array filled with random floats : [[ 0.64325146 0.4699456 0.89895437]]
# Python program explaining
# numpy.random.random_sample() function
# importing numpy
import numpy as geek
# output array
out_arr = geek.random.random_sample((3, 2, 1))
print ("Output 3D Array filled with random floats : ", out_arr)
Output :
Output 3D Array filled with random floats : [[[ 0.78245025] [ 0.77736746]] [[ 0.54389267] [ 0.18491758]] [[ 0.97428409] [ 0.73729256]]]
