Ripser.py is a lean persistent homology package for Python. Building on the blazing fast C++ Ripser package as the core computational engine, Ripser.py provides an intuitive interface for
- computing persistence cohomology of sparse and dense data sets,
- visualizing persistence diagrams,
- computing lowerstar filtrations on images, and
- computing representative cochains.
Additionally, through extensive testing and continuous integration, Ripser.py is easy to install on Mac, Linux, and Windows platforms.
We supply a large set of interactive notebooks that demonstrate how to take advantage of all the features available.
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)