mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-12-05 02:40:16 +00:00
cecf43d648
* Pyupgrade to Python 3.9
* updating DIRECTORY.md
Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
65 lines
1.8 KiB
Python
65 lines
1.8 KiB
Python
from __future__ import annotations
|
|
|
|
from typing import Iterable, Union
|
|
|
|
import numpy as np
|
|
|
|
Vector = Union[Iterable[float], Iterable[int], np.ndarray]
|
|
VectorOut = Union[np.float64, int, float]
|
|
|
|
|
|
def euclidean_distance(vector_1: Vector, vector_2: Vector) -> VectorOut:
|
|
"""
|
|
Calculate the distance between the two endpoints of two vectors.
|
|
A vector is defined as a list, tuple, or numpy 1D array.
|
|
>>> euclidean_distance((0, 0), (2, 2))
|
|
2.8284271247461903
|
|
>>> euclidean_distance(np.array([0, 0, 0]), np.array([2, 2, 2]))
|
|
3.4641016151377544
|
|
>>> euclidean_distance(np.array([1, 2, 3, 4]), np.array([5, 6, 7, 8]))
|
|
8.0
|
|
>>> euclidean_distance([1, 2, 3, 4], [5, 6, 7, 8])
|
|
8.0
|
|
"""
|
|
return np.sqrt(np.sum((np.asarray(vector_1) - np.asarray(vector_2)) ** 2))
|
|
|
|
|
|
def euclidean_distance_no_np(vector_1: Vector, vector_2: Vector) -> VectorOut:
|
|
"""
|
|
Calculate the distance between the two endpoints of two vectors without numpy.
|
|
A vector is defined as a list, tuple, or numpy 1D array.
|
|
>>> euclidean_distance_no_np((0, 0), (2, 2))
|
|
2.8284271247461903
|
|
>>> euclidean_distance_no_np([1, 2, 3, 4], [5, 6, 7, 8])
|
|
8.0
|
|
"""
|
|
return sum((v1 - v2) ** 2 for v1, v2 in zip(vector_1, vector_2)) ** (1 / 2)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
|
|
def benchmark() -> None:
|
|
"""
|
|
Benchmarks
|
|
"""
|
|
from timeit import timeit
|
|
|
|
print("Without Numpy")
|
|
print(
|
|
timeit(
|
|
"euclidean_distance_no_np([1, 2, 3], [4, 5, 6])",
|
|
number=10000,
|
|
globals=globals(),
|
|
)
|
|
)
|
|
print("With Numpy")
|
|
print(
|
|
timeit(
|
|
"euclidean_distance([1, 2, 3], [4, 5, 6])",
|
|
number=10000,
|
|
globals=globals(),
|
|
)
|
|
)
|
|
|
|
benchmark()
|