swarmauri_distance_minkowski 0.6.1.dev6

Minkowski Distance for Swarmauri.

---

Minkowski Distance Package

A Python package implementing Minkowski distance metric for vector comparison. This distance metric is a generalization that includes both Euclidean and Manhattan distances.

Installation

pip install swarmauri_distance_minkowski

Usage

from swarmauri.distances.MinkowskiDistance import MinkowskiDistance
from swarmauri.vectors.Vector import Vector

# Create vectors for comparison
vector_a = Vector(value=[1, 2])
vector_b = Vector(value=[1, 2])

# Initialize Minkowski distance calculator (default p=2 for Euclidean distance)
distance_calculator = MinkowskiDistance()

# Calculate distance between vectors
distance = distance_calculator.distance(vector_a, vector_b)
print(f"Distance: {distance}")  # Output: Distance: 0.0

# Calculate similarity between vectors
similarity = distance_calculator.similarity(vector_a, vector_b)
print(f"Similarity: {similarity}")  # Output: Similarity: 1.0

Want to help?

If you want to contribute to swarmauri-sdk, read up on our guidelines for contributing that will help you get started.