Random sampling in numpy | random_sample() function

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 :

Output random float value :  0.9211987310893188

Code #2 :

# 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 :

Output 2D Array filled with random floats :  [[ 0.64325146  0.4699456   0.89895437]]

Code #3 :

# 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]]]