https://github.com/jss95/curvesimilarities
Python package for curve similarity measures.
https://github.com/jss95/curvesimilarities
frechet-distance geometry mathematics python
Last synced: 5 months ago
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Python package for curve similarity measures.
- Host: GitHub
- URL: https://github.com/jss95/curvesimilarities
- Owner: JSS95
- License: bsd-3-clause
- Created: 2024-05-17T08:13:22.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2024-08-30T00:45:04.000Z (almost 2 years ago)
- Last Synced: 2026-01-07T16:40:47.873Z (6 months ago)
- Topics: frechet-distance, geometry, mathematics, python
- Language: Python
- Homepage: https://pypi.org/project/curvesimilarities
- Size: 266 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
# CurveSimilarities
[](https://github.com/JSS95/curvesimilarities/blob/master/LICENSE)
[](https://github.com/JSS95/curvesimilarities/actions/workflows/ci.yml)
[](https://github.com/JSS95/curvesimilarities/actions/workflows/cd.yml)
[](https://curvesimilarities.readthedocs.io/en/latest/?badge=latest)
[](https://pypi.python.org/pypi/curvesimilarities/)
[](https://pypi.python.org/pypi/curvesimilarities/)

A Numpy-friendly package for curve similarity measures.
List of supported measures:
- Dynamic time warping distance (`dtw()`)
- (Continuous) Fréchet distance (`fd()`)
- Discrete Fréchet distance (`dfd()`)
- Integral Fréchet distance (`ifd()`)
## Usage
```python
>>> import numpy as np
>>> from curvesimilarities import fd # (Continuous) Fréchet distance
>>> fd(np.array([[0, 0], [1, 3], [2, 0]]), np.array([[0, 1], [2, 1]]))
2.0
```
## Installation
CurveSimilarities can be installed using `pip`.
```
$ pip install curvesimilarities
```
## Documentation
CurveSimilarities is documented with [Sphinx](https://pypi.org/project/Sphinx/).
The manual can be found on Read the Docs:
> https://curvesimilarities.readthedocs.io/
If you want to build the document yourself, get the source code and install with `[doc]` dependency.
Then, go to `doc` directory and build the document:
```
$ pip install .[doc]
$ cd doc
$ make html
```
Document will be generated in `build/html` directory. Open `index.html` to see the central page.