Random sampling in NumPy | random_sample () function

numpy.random.random_sample() — one of the functions for random sampling in numpy. It returns an array of the given shape and fills it with random floating point numbers 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, eg, (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

 
# numpy import

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

 
# numpy import

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 no. 3:

# Python program explaining
# numpy.random. random_sample () function

 
# numpy import

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]]] 




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