City block distance is generally calculated between 2-coordinates of a paired object. It is the summation of absolute difference between 2-coordinates. The city block distance of 2-points a and b with k dimension is mathematically calculated using below formula:
In this article two solution are explained for this problem – one with the Python code and the other one with the use of a predefined method.
Examples:
Input:
array1 = [1, 2, 13, 5]
array2 = [1, 27, 3, 4]
Output:
The CityBlock distance between 2 array is: 36
Input:
a = [34, 44, 89, 81, 67, 49, 33, 59]
b = [98, 34, 23, 12, 233, 23, 44]
Output:
The CityBlock distance between 2 array is: 412
Code: Python scratch code to calculate the distance using the above formula.
import numpy as np def cityblock_distance(A, B): result = np.sum([abs(a - b) for (a, b) in zip(A, B)]) return result if __name__== "__main__": array1 = [1, 2, 13, 5] array2 = [1, 27, 3, 4] result = cityblock_distance(array1, array2) print("The CityBlock distance between 2 arrays is:", result) |
Output:
The CityBlock distance between 2 arrays is: 36
There is no restriction for the same size of arrays. So, it’s easy to calculate City Block distance between 2-coordinates using above formula but we can calculate the same using predefined method for arrays having 2-dimension or more.
Code: Python code using the predefined method to calculate the distance using the above formula.
# Import necessary package import scipy.spatial.distance as d def CityBlock_distance(A, B): result = d.cdist(A, B, 'cityblock') return result if __name__== "__main__": mat1 = [[1, 2, 13, 5], [2, 3, 4, 5]] mat2 = [[1, 27, 3, 4], [8, 6, 9, 3]] result = CityBlock_distance(mat1, mat2) print(result) |
Output:
[[ 36. 17.] [ 27. 16.]]
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