Method
method/persistent-homology
Barcodes and persistence diagrams read off a filtration.
Method guide
Related notes
- dionysus Dionysus, a persistent-homology library with support for vineyards and circular coordinates alongside ordinary persistence. Environment
- giotto-ph The parallel Ripser-derived persistence backend, built from git because it vendors its C++ engine as submodules an sdist cannot carry. Recipe
- giotto-ph giotto-ph, a parallel Rips persistence backend, built from an in-repo recipe because it vendors its C++ engine as submodules. Environment
- giotto-tda giotto-tda, the scikit-learn-compatible TDA toolkit, and the corpus's deliberate out-of-profile L0 fixture. Environment
- gudhi GUDHI, the general-purpose computational topology library covering simplicial complexes, filtrations, and persistence. Environment
- Multiparameter Persistence Filter along two parameters at once — scale and density, say — when one axis cannot separate structure from noise. Method
- open-topoqa-featurizer The clean-room interface featurizer written from the TopoQA paper, packaged as the open replacement for an unlicensed upstream. Recipe
- open-topoqa-featurizer The MIT clean-room TopoQA interface featurizer, reproduced from the paper because the upstream code carries no license. Environment
- open-topoqa-featurizer The MIT clean-room TopoQA interface featurizer, written from the paper because the published implementation carries no license. Package
- persim persim, the scikit-tda component for comparing and vectorizing persistence diagrams once they have been computed. Environment
- Persistent Spectral Graph The founding persistent-Laplacian paper: harmonic spectra recover persistent homology exactly, and non-harmonic spectra carry the geometry it discards. Paper
- Persistent Topological Laplacians A Laplacian family built along a filtration; its zero eigenvalues are persistent homology, and the rest are the geometry persistence throws away. Method
- phat PHAT's C++ persistence matrix-reduction backend behind pybind11 bindings, built here because the channels carry no package for it. Recipe
- phat PHAT, the C++ persistent-homology matrix-reduction backend, exposed through pybind11 and built from an in-repo recipe. Environment
- pydowker The full two-parameter persistence stack: pyDowker over pyrivet over the RIVET console engine, built as a three-recipe chain. Environment
- pyflagser Persistent homology of directed flag complexes, built from git over a vendored C++ engine because no conda channel carries it. Recipe
- pyflagser pyflagser, for persistent homology of directed flag complexes, built from an in-repo recipe over a vendored C++ engine. Environment
- r-tda The established general-purpose R package for the field, packaged from CRAN with a compiled dependency set that is still a best guess. Recipe
- r-tda The R TDA package, covering persistent homology, density clustering, and statistical inference on diagrams from R. Environment
- r-tdastats The Ripser-backed R persistence package, built from CRAN because no conda channel carries the R side of the field at all. Recipe
- r-tdastats TDAstats, a lightweight R interface to Ripser with plotting and hypothesis testing on persistence diagrams. Environment
- ripser-cpp The Ripser C++ command-line tool for fast Vietoris-Rips persistent homology, installed as a single Bioconda package. Environment
- ripser-py The ripser.py Python bindings over the Ripser engine, for computing persistence diagrams inside a Python workflow. Environment
- scikit-tda The meta-package that pulls the Python TDA stack together behind one install, built here because the channels carry the parts but not the whole. Recipe
- scikit-tda The scikit-tda meta-package, pulling the Python TDA stack together behind one install. Environment
- score-docking-poses Rank candidate protein-complex structures by predicted DockQ-like interface quality. Mold
- TDA and TDL Beyond Persistent Homology Su and colleagues' map of the topological methods that extend past persistent homology, and what each one recovers. Paper
- TDA and TDL in Molecular Sciences Wee and Jiang's account of how molecular problems pushed topology from description to conditioned, learnable representations. Paper
- TopoDockQ A persistent-Laplacian scorer predicting DockQ interface quality to rank and filter peptide-protein docking poses. Package
- Topological Deep Learning Learn the readout instead of hand-picking it — topological structure as input to a model, or as the domain the model operates on. Method
- TopoMetry cell-cycle replication The pancreas result reproduces directionally, but TopoMetry's 2-D layouts ignore their seed — so no single-run layout number should be quoted. Replication experiment
- TopoQA A topological deep learning model ranking predicted protein-complex structures by the quality of their interface. Package
- TopoQA interface-quality replication The released TopoQA checkpoint does reproduce the paper's ranking losses — and part of the margin depends on a coordinate defect. Replication experiment