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Awesome TDA Awesome

A curated list of Topological Data Analysis (TDA) tools and resources.

If you know of any other tools or resources, read Contribution Guidelines and feel free to fork/PR or open a new issue.

Contents

Theory

Algorithms

Books

Articles

Courses

Tools

  • Ctl - (C++11 library) A set of generic tools for Building Neighborhood Graphs and Cellular Complexes, Computing (persistent) homology over finite fields, Parallel algorithms for homology. an be used with c++, Python, MATLAB and R.

  • Knotter - Implementation of Mapper algorithm for TDA.

  • RIVET - For the visualization and analysis of two-parameter persistent homology with Python API.

  • TdaToolbox - Some tools that may be applied to data science in general.

  • TTk - Topological data analysis in scientific visualization. Can be used with C++, python.

Frameworks and Libs

C++

  • Dionysus - Computing persistent (co)homology, Implementation of the Persistent (co)homology computation, Vineyards, Zigzag persistent homology algorithms.

  • PHAT - Persistent Homology Algorithm Toolbox.

  • Topology ToolKit (TTK) - Efficient, generic and easy and Topological data analysis and visualization

Go

  • TDA - Some methods are provided for gridded data (images).

Haskell

Java

  • JavaPlex - The JavaPlex library implements persistent homology and related techniques. It designed for ease of use from Matlab and java-based systems.

Julia

  • Eirene.jl - For homological persistence.
  • TDA.jl - This package provides Persistence Diagram & Barcode, Nerve, Mapper tools for topological data analysis.

Matlab

  • Clique Top - Doing topological analysis of symmetric matrices.

Python

  • GDA Public - Several fundamental tools by Geometric Data Analytics Inc. geomdata

  • Giotto TDA(GTDA) - A high-performance topological machine learning toolbox

  • GUDHI - Geometry Understanding in Higher Dimensional with a Python interface.

  • KeplerMapper - TDA Mapper algorithm for visualization of high-dimensional data. it can make use of Scikit-Learn API compatible cluster and scaling algorithms.

  • Kohonen - Kohonen-style vector quantizers: Self-Organizing Map (SOM), Neural Gas, and Growing Neural Gas.

  • Mapper Implementation - Topological Data Analysis for high dimensional dataset exploration.

  • MoguTDA - Numerical calculation of algebraic topology in an application to topological data analysis: implicial complex, and the estimation of homology and Betti numbers.

  • OpenTDA

  • Persim - package for many tools used in analyzing Persistence Diagrams

  • Python Mapper - Mapper algorithm implementation + graphical user interface.

  • Qsv - Data structure visualizer.

  • Ripser - lean persistent homology package.

  • Scikit-TDA - For non-topologists.

  • Giotto-TDA - A scikit-learn - compatible library for end-to-end topological machine learning including Mapper, persistent homology, vectorization methods for persistence diagrams, and preprocessing components for time series, graphs, images, and point clouds (paper).

  • ScTDA - It includes tools for the preprocessing, analysis, and exploration of single-cell RNA-seq data based on topological representations.

  • Topology ToolKit (TTK) - Efficient, generic and easy and Topological data analysis and visualization

  • TMAP - Population-scale microbiome data analysis.

R

  • TDA - Tools for the statistical analysis of persistent homology and for density clustering.

  • TDAmapper - An R package for using discrete Morse theory to analyze a data set using the Mapper algorithm described in G. Singh, F. Memoli, G. Carlsson (2007).

  • TDAstats - Computing persistent homology.

Spark

  • Spark Mapper - Estimating a lower dimensional simplicial complex from a dataset.

  • Spark TDA - Scalable topological data analysis package.

Useful Links

Bioinformatics

Brain Network Analysis

Computing Homology

Computer Vision

Data Professionals

Deep Learning

Machine Learning

Persistent Homology

Use Python

Use R

Theory and applications of TDA

Event

2024

2025