randomisation() Function to generate Random Vector | Linear Algebra using Python

Linear Algebra using Python | randomisation_matrix() Function to generate Random Matrix: Here, we are going to learn about the randomisation_matrix() Function in Python?
Submitted by Anuj Singh, on May 22, 2020

Prerequisite: numpy.random.random( ) function with no input parameter

Numpy is the library of function that helps to construct or manipulate matrices and vectors. The function numpy.random.random() is a function used for generating a random value between 0 and 1. Now we are going to use this function to create a vector of elements having random value between 0 and 1. In this article, we are defining a function called randomisation() which returns a vector.

Syntax:

    random_vector = randomisation(length_n)

Input parameter(s):

  • length_n – represent the length of the vector.

Return value:

It returns a vector of length length_n with random values (between 0 and 1) at each entry.

Applications:

  1. Machine Learning
  2. Neural Network
  3. Probability - (PMF specifically)
  4. Statistics and Inference

Python code to demonstrate example of randomisation() function

# Linear Algebra Learning Sequence
# Randomisation Function which return a vector

import numpy as np

def randomization(n):
   x = np.random.random([n,1])
   return x

n = int(input('Length of vector: '))
print(randomization(n))

Output:

RUN 1:
Length of vector: 4
[[0.05183679]
 [0.31612445]
 [0.09396175]
 [0.5120439 ]]

RUN 2:
Length of vector: 15
[[0.82281558]
 [0.69170917]
 [0.97428563]
 [0.95208111]
 [0.67069261]
 [0.1387415 ]
 [0.42731091]
 [0.5170017 ]
 [0.4783402 ]
 [0.14740506]
 [0.59898893]
 [0.17684872]
 [0.53167923]
 [0.4925715 ]
 [0.59492722]]





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