Metadata-Version: 2.1
Name: velour
Version: 2020.11.7
Summary: Topological inference from point clouds with persistent homology
Home-page: https://github.com/raphaeltinarrage/velour
Author: Raphaël Tinarrage
Author-email: raphael.tinarrage@gmail.com
License: UNKNOWN
Description: # `velour`
        
        Python package for topological inference from point clouds with persistent homology.
        Based on the [`gudhi`](https://gudhi.inria.fr/python/latest/)  library.
        
        ## Methods
        
        The package `velour` gathers implementations of our methods for topological inference. It allows the use of:
        - **DTM-filtrations:** a family of filtrations for persistent homology, that can be applied even when the input point cloud contains anomalous points. Notebook demo [here](https://github.com/raphaeltinarrage/DTM-Filtrations/blob/master/Demo.ipynb) and mathematical explanation [here](https://arxiv.org/abs/1811.04757).
        - **Lifted sets and lifted filtrations:** allows to estimate the homology of an abstract manifold from a finite sample of an immersion of it. Notebook demo [here](https://github.com/raphaeltinarrage/ImmersedManifolds/blob/master/Demo.ipynb) and mathematical explanation [here](https://arxiv.org/abs/1912.03033).
        - **Persistent Stiefel-Whitney classes:** allows to estimate the first Stiefel-Whitney class of a vector bundle from a finite sample of it. Notebook demo [here](https://github.com/raphaeltinarrage/PersistentCharacteristicClasses/blob/master/Demo.ipynb) and mathematical explanation [here](https://arxiv.org/abs/2005.12543).
        
        ## Structure
        
        The package is divided into three modules:
        - `persistent` gathers tools for handling filtrations of simplicial complexes (simplex trees).
        - `geometry` contains the implementation of various geometric quantities used by `persistent`.
        - `datasets` consists in various utilities for sampling datasets (from $\mathbb{R}^2$ to $\mathbb{R}^{12}$) and plotting them.
        
        ## Setup
        
        It can be installed from PyPI via
        ```
        pip install velour
        ```
        ## Documentation
        
        Not yet! But feel to contact me anytime :upside_down_face:
        
        Raphaël Tinarrage - https://raphaeltinarrage.github.io/
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
