Vectorizations, distances and kernels that work on persistence diagrams, compatible with scikit-learn and tensorflow. This module aims at bridging the gap between persistence diagrams and machine learning, by providing implementations of most of the vector representations for persistence diagrams in the literature, in a scikit-learn format.

A persistence image is a 2D function computed from a persistence diagram by convolving the diagram points with a weighted Gaussian kernel. The plane is then discretized into an image with pixels, which is flattened and returned as a vector. See …

Persistence landscapes are represented as a vector of vectors of real numbers. Assume that i-th vector consist of \(n_i\) numbers sorted from larger to smaller. They represent the values of the functions \(\lambda_1,\ldots,\lambda_{n_i}\) , \(\lambda_{n_i+1}\) and the functions with larger indices are then zero functions) on the i-th point of a ...

The GUDHI library is a generic open source C++ library, with a Python interface, for Topological Data Analysis (TDA) and Higher Dimensional Geometry Understanding. This web app is a reimplementation of the paper [TDA of financial time series: Landscapes of crashes] (https://arxiv.org/abs/1703.04385) using [gudhi] (https://gudhi.inria.fr).

2025年2月21日 · The Gudhi library is an open source library for Computational Topology and Topological Data Analysis (TDA). It offers state-of-the-art algorithms to construct various types of simplicial complexes, data structures to represent them, and algorithms to compute geometric approximations of shapes and persistent homology.

The GUDHI library is a generic open source C++ library, with a Python interface, for Topological Data Analysis (TDA) and Higher Dimensional Geometry Understanding. - GUDHI/gudhi-devel

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The GUDHI library is a generic open source C++ library, with a Python interface, for Topological Data Analysis and Higher Dimensional Geometry Understanding. The library offers state-of-the-art data structures and algorithms to construct simplicial complexes and …

Gudhi also contains implementations of less common vectorization methods, such as the [Betti curve] (https://www.researchgate.net/publication/316604237_Time_Series_Classification_via_Topological_Data_Analysis), the [complex polynomial] ( https://link.springer.com/chapter/10.1007%2F978-3-319-23231-7_27), or the [topological vector] (https://digli...

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