numpy normalize code example

Example 1: how to normalize a 1d numpy array

# Foe 1d array
an_array = np.array([0.1,0.2,0.3,0.4,0.5])

norm = np.linalg.norm(an_array)
normal_array = an_array/norm
print(normal_array)

#[0.2,0.4,0.6,0.8,1] (Should be, I didin't run the code)

Example 2: numpy normal distribution

>>> mu, sigma = 0, 0.1 # mean and standard deviation
>>> s = np.random.normal(mu, sigma, 1000)

Example 3: numpy normalize

def normalize(v):
    norm = np.linalg.norm(v)
    if norm == 0: 
       return v
    return v / norm

Example 4: numpy normalize matrix

import numpy as np
x= np.random.random((3,3))
print("Original Array:")
print(x)
xmax, xmin = x.max(), x.min()
x = (x - xmin)/(xmax - xmin)
print("After normalization:")
print(x)