Skip to main content

Minkowski Distance for Swarmauri.

Project description

Swamauri Logo

PyPI - Downloads GitHub Hits PyPI - Python Version PyPI - License PyPI - swarmauri_distance_minkowski


Swarmauri Distance Minkowski

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

swarmauri_distance_minkowski-0.7.3.dev2.tar.gz (7.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file swarmauri_distance_minkowski-0.7.3.dev2.tar.gz.

File metadata

File hashes

Hashes for swarmauri_distance_minkowski-0.7.3.dev2.tar.gz
Algorithm Hash digest
SHA256 7590c2873555631a7b6d6966f18c15a96ac9e15d8c4798a19ebd0dbd5a90390c
MD5 44b0182b3c92893fee722173b96283b6
BLAKE2b-256 d0528cd33acc86746f8b7134bfc87e81f869628d4e485a27be89ef71b171fbf4

See more details on using hashes here.

File details

Details for the file swarmauri_distance_minkowski-0.7.3.dev2-py3-none-any.whl.

File metadata

File hashes

Hashes for swarmauri_distance_minkowski-0.7.3.dev2-py3-none-any.whl
Algorithm Hash digest
SHA256 27df256cffe8123b6c2be08f9aefe3d56b3cd5a71ea14a206d4637f69f59bf6b
MD5 2be747ec63bd2220a73a019fb8741853
BLAKE2b-256 018dd98b22e255090c1c915df07c8c66f0de1837be7c66d6e7159d823fd4d181

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page