Metadata-Version: 2.3
Name: swarmauri_distance_minkowski
Version: 0.6.1.dev6
Summary: Minkowski Distance for Swarmauri.
License: Apache-2.0
Author: Jacob Stewart
Author-email: jacob@swarmauri.com
Requires-Python: >=3.10,<3.13
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: scipy (>=1.7.0,<1.14.0)
Requires-Dist: swarmauri_base (>=0.6.1.dev6,<0.7.0)
Requires-Dist: swarmauri_core (>=0.6.1.dev6,<0.7.0)
Requires-Dist: swarmauri_standard (>=0.6.1.dev6,<0.7.0)
Project-URL: Repository, http://github.com/swarmauri/swarmauri-sdk
Description-Content-Type: text/markdown

![Swarmauri Logo](https://res.cloudinary.com/dbjmpekvl/image/upload/v1730099724/Swarmauri-logo-lockup-2048x757_hww01w.png)

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---

# 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

```bash
pip install swarmauri_distance_minkowski
```

## Usage

```python
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](https://github.com/swarmauri/swarmauri-sdk/blob/master/contributing.md) that will help you get started.


