A general and simple implementation of the Hamming Neighbourhood Distance.

hn-distance.py

def hn_distance(x1:str, x2:str, j=0):
    """
    Hamming-Neighbourhood Distance
    See more here https://medium.com/p/73997d14706e/
        x1: The first comparision string
        x2: The second comparision string
        j: The ignorance threshold is the minimum difference between
           values required for them to be considered as a potential
           consideration. It is best to leave this alone unless you 
           know what you're doing.
    """
    
    # Convert each string to it's corresponding ASCII Vector
    a = [ord(c) for c in x1]
    b = [ord(c) for c in x2]
    
    # Delta Array
    z = []
    
    # Finding the longest array to ensure lengthy iteration
    ln = max(len(a), len(b))
    
    for x in range(ln):
        # if the observation point exceeds the length of string A, start pushing direct B ASCII codes to delta array
        if x > (len(a) - 1):
            z.append(b[x])
        # if the observation point exceeds the length of string B, start pushing direct A ASCII codes to delta array
        elif x > (len(b) - 1):
            z.append(a[x])
        else:
            # For now the observation point is within both strings, record difference in delta array
            z.append(b[x] - a[x])
    
    # In the case of Delta array, there are differences.
    # If the difference is equal to j (threshold of ignorance), remove it
    # otherwise record it.        
    
    # The length of the delta array is the difference between the two strings
    # The difference from HN-Distance is the number of characters that are different
    # from each other.
    
    return len([abs(n) for n in z if n > j])