DistanceAlgorithms

euclidean_distance.py

#!/usr/bin/env python3

import math


def distance(xs, ys):
    return math.sqrt(sum([math.pow(q - p, 2) for (q,p) in zip(xs, ys)]))


a = [1,2,4,5,2]
b = [3,4,7,9,1]
print(distance(a, b))

a = [1,2,4,5,2]
b = [1,2,4,5,2]
print(distance(a, b))

levenshtien.py

def distance(a, b):
    m = [[0] * (len(b) + 1) for _ in range(len(a) + 1)]

    for i in range(len(a) + 1): m[i][0] = i
    for i in range(len(b) + 1): m[0][i] = i

    for i in range(1, len(a) + 1):
        for j in range(1, len(b) + 1):
            m[i][j] = min(
                m[i - 1][j    ] + 1,
                m[i    ][j - 1] + 1,
                m[i - 1][j - 1] + (0 if a[i - 1] == b[j - 1] else 1)
            )

    return m[-1][-1]
  

pythagoras.py

#!/usr/bin/env python

import math


class P(object):
    def __init__(self, x, y):
        self.x = x
        self.y = y

    def distance(a, b):
        return math.sqrt(math.pow(b.x-a.x, 2) + math.pow(b.y-a.y, 2))


if __name__ == '__main__':
    a = P(1, 1)
    b = P(4, 5)

    print a.distance(b)

pythagorass.hs

main = do
  let x = (1, 1)
  let y = (4, 5)
  print $ distance x y

distance (a, b) (c, d) = sqrt $ x + y
  where x = (c - a) ^ 2
        y = (d - b) ^ 2