A Lean Persistent Homology Library for Python
Project description
[](https://badge.fury.io/py/ripser)
[](https://travis-ci.org/ctralie/ripser)
[](https://codecov.io/gh/ctralie/ripser)
[](https://www.gnu.org/licenses/lgpl-3.0)
# Ripser
Ripser is now a Python class implemented in the Scikit-learn style. 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 Rips
r = Rips()
data = np.random.random((100,2))
diagram = r.fit_transform(data)
r.plot(diagram)
```
[](https://travis-ci.org/ctralie/ripser)
[](https://codecov.io/gh/ctralie/ripser)
[](https://www.gnu.org/licenses/lgpl-3.0)
# Ripser
Ripser is now a Python class implemented in the Scikit-learn style. 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 Rips
r = Rips()
data = np.random.random((100,2))
diagram = r.fit_transform(data)
r.plot(diagram)
```
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