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Copyright © 2022 Paul A. Patience ;;; Copyright © 2022 Wiktor Żelazny ;;; Copyright © 2022 Eric Bavier +;;; Copyright © 2022 Kiran Shila ;;; ;;; This file is part of GNU Guix. ;;; @@ -1478,3 +1479,43 @@ (define-public python-opt-einsum well as potentially any library which conforms to a standard API. See the documentation for more information.") (license license:expat))) + +(define-public python-hdbscan + (package + (name "python-hdbscan") + (version "0.8.28") + (source (origin + (method url-fetch) + (uri (pypi-uri "hdbscan" version)) + (sha256 + (base32 + "0nn0xm9ji74pkil1lbkrskmyak25jx4av8cdqg2dzgiv5wgzgnpf")))) + (build-system python-build-system) + (arguments + `(#:modules ((ice-9 ftw) + (srfi srfi-1) + (guix build utils) + (guix build python-build-system)) + #:phases (modify-phases + %standard-phases + (replace 'check + (lambda* (#:key tests? #:allow-other-keys) + (when tests? + (let ((outdir (string-append + (getcwd) "/build/" + (car (filter (lambda (s) (string-contains s "lib")) + (scandir "build")))))) + (invoke "pytest" "-vv" outdir)))))))) + (propagated-inputs (list python-cython python-joblib python-numpy + python-scikit-learn python-scipy)) + (native-inputs (list python-nose python-pytest python-pandas python-networkx)) + (home-page "http://github.com/scikit-learn-contrib/hdbscan") + (synopsis "Clustering based on density with variable density clusters") + (description "HDBSCAN - Hierarchical Density-Based Spatial Clustering of +Applications with Noise. Performs DBSCAN over varying epsilon values and +integrates the result to find a clustering that gives the best stability over +epsilon. This allows HDBSCAN to find clusters of varying densities (unlike +DBSCAN), and be more robust to parameter selection. HDBSCAN is ideal for +exploratory data analysis; it's a fast and robust algorithm that you can trust +to return meaningful clusters (if there are any).") + (license license:bsd-3))) -- 2.37.1