TSSS Python

tsss.py

import numpy as np
import numba


@numba.njit()
def tsss(vec1, vec2):
    euclidean_distance = np.linalg.norm(vec1 - vec2)
    cosine_distance = np.dot(vec1, vec2.T) / (
        np.linalg.norm(vec1) * np.linalg.norm(vec2)
    )
    magnitude_difference = abs(np.linalg.norm(vec1) - np.linalg.norm(vec2))
    theta = np.arccos(cosine_distance) + np.radians(10.0)
    triangle = (np.linalg.norm(vec1) * np.linalg.norm(vec2) * np.sin(theta)) / 2
    sector = (
        np.pi
        * ((euclidean_distance + magnitude_difference) ** 2)
        * (np.degrees(theta) / 360)
    )
    return triangle * sector

# Equation 7 From Paper
@numba.njit()
def tsss_eq7(vec1, vec2):
    euclidean_distance = np.linalg.norm(vec1 - vec2)
    cosine_distance = np.dot(vec1, vec2.T) / (
        np.linalg.norm(vec1) * np.linalg.norm(vec2)
    )
    magnitude_difference = abs(np.linalg.norm(vec1) - np.linalg.norm(vec2))
    theta = np.arccos(cosine_distance) + np.radians(10.0)
    result = (
        np.linalg.norm(vec1)
        * np.linalg.norm(vec2)
        * np.sin(theta)
        * np.degrees(theta)
        * np.pi
        * ((euclidean_distance + magnitude_difference) ** 2)
    ) / 720
    return result


for i in range(200):
    vec1 = np.random.random(200)
    vec2 = np.random.random(200)
    sim1 = tsss(vec1, vec2)
    sim2 = tsss_eq7(vec1, vec2)
    assert sim1 >= 0, f"{sim1}"
    assert sim2 >= 0, f"{sim2}"
    assert np.isclose(sim1, sim2)