Skip to main content

A Lean Persistent Homology Library for Python

Project description

[![PyPI version](https://badge.fury.io/py/ripser.svg)](https://badge.fury.io/py/ripser)
[![Build Status](https://travis-ci.org/ctralie/ripser.svg?branch=master)](https://travis-ci.org/ctralie/ripser)
[![codecov](https://codecov.io/gh/ctralie/ripser/branch/master/graph/badge.svg)](https://codecov.io/gh/ctralie/ripser)
[![License: LGPL v3](https://img.shields.io/badge/License-LGPL%20v3-blue.svg)](https://www.gnu.org/licenses/lgpl-3.0)

# Ripser


Ripser is now a Python class. It is easy to install, only requires that you have Cython installed first. It is even easier to use.

For the C++ library, see [Ripser/ripser](https://github.com/Ripser/ripser/releases/latest).

Details from the old readme can be found [here](docs/README.md).

## Setup

Installation requires Cython, and currently must be installed from source. An example of how to install is
```
pip install Cython
pip install Ripser
```

We use matplotlib for generating persistence diagrams


## Usage

```
import numpy as np
from ripser import ripser, plot_dgms

data = np.random.random((100,2))
diagrams = ripser(data)['dgms']
plot_dgms(diagrams, show=True)
```


Note that there is also a <i>Rips</i> object with the same functionality, which conforms to the Scikit-learn style

```
import numpy as np
from ripser import Rips
r = Rips()

data = np.random.random((100,2))
diagram = r.fit_transform(data)
r.plot(diagram, show=True)
```

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

ripser-0.2.3.tar.gz (65.0 kB view details)

Uploaded Source

File details

Details for the file ripser-0.2.3.tar.gz.

File metadata

  • Download URL: ripser-0.2.3.tar.gz
  • Upload date:
  • Size: 65.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for ripser-0.2.3.tar.gz
Algorithm Hash digest
SHA256 49bf43ac8a6a79c73c367ba33aad28f6aa00033f68621b2b8a3631f3c8d69c43
MD5 e2d9fbeeb34fdc9e251f1784ffa98fe9
BLAKE2b-256 501cf04b3172a4525fc1d29c6ffbfc61c638ca889a39dec052969228b1c6c829

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