Interspace

Gives us different distance between two vectors which are given in as an input.

Installation

pip install interspace

Different Distance Functions

• Minkowski distance(p-Norm Distance)

minkowski(vector_1, vector_2, p=1)

• Euclidean distance (2-norm distance)

euclidean(vector_1, vector_2)

• Manhattan distance/Taxicab norm

manhattan(vector_1, vector_2)

• Cosine Similarity

cosine_similarity(vector_1, vector_2)

• Haversine formula

haversine(coord1, coord2, R = 6372800)

• Hamming distance

hamming(int, int); hamming(str, str) # where, length of both the strings should be same

• Mahalanobis distance

mahalanobis(vector_1, vector_2, inverse_of_the_covariance_matrix)

Usage

import interspace

# Calculate Euclidean Distace
interspace.euclidean([1,2,3],[4,5,6])
##Output: 5.196152422706632

# Compute the great-circle distance between two points on a sphere 
# given their longitudes and latitudes.
interspace.haversine((42.5170365,  15.2778599),(51.5073219,  -0.1276474))
##Output: 1532329.6237517272