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| author | Ricardo Wurmus <rekado@elephly.net> | 2022-12-02 21:18:14 +0100 |
|---|---|---|
| committer | Ricardo Wurmus <rekado@elephly.net> | 2022-12-02 21:46:36 +0100 |
| commit | b2a9feab92fb78b441d693960962140d9467510a (patch) | |
| tree | 10f03837378bd8598f9d9c0e97616218c1a0c3e7 /gnu | |
| parent | 62da3f9837063b59c615accc86bb80ce03ae301d (diff) | |
| download | guix-b2a9feab92fb78b441d693960962140d9467510a.tar guix-b2a9feab92fb78b441d693960962140d9467510a.tar.gz | |
gnu: Add python-hdmedians.
* gnu/packages/statistics.scm (python-hdmedians): New variable.
Diffstat (limited to 'gnu')
| -rw-r--r-- | gnu/packages/statistics.scm | 31 |
1 files changed, 31 insertions, 0 deletions
diff --git a/gnu/packages/statistics.scm b/gnu/packages/statistics.scm index 616eded618..4c7609683b 100644 --- a/gnu/packages/statistics.scm +++ b/gnu/packages/statistics.scm @@ -45,6 +45,7 @@ #:use-module (guix build-system emacs) #:use-module (guix build-system gnu) #:use-module (guix build-system r) + #:use-module (guix build-system pyproject) #:use-module (guix build-system python) #:use-module (guix build-system trivial) #:use-module (gnu packages) @@ -2010,6 +2011,36 @@ and fast file reading.") "This package provides tools to export R data as LaTeX and HTML tables.") (license license:gpl2+))) +(define-public python-hdmedians + (package + (name "python-hdmedians") + (version "0.14.2") + (source (origin + (method url-fetch) + (uri (pypi-uri "hdmedians" version)) + (sha256 + (base32 + "1mn2k8srnmfy451l7zvb2l4hn9701bc5awjm6q3vmqbicyqyqyml")))) + (build-system pyproject-build-system) + (arguments + (list + #:phases + '(modify-phases %standard-phases + (add-before 'check 'build-extensions + (lambda _ + ;; Cython extensions have to be built before running the tests. + (invoke "python" "setup.py" "build_ext" "--inplace")))))) + (propagated-inputs (list python-cython python-numpy)) + (native-inputs (list python-nose)) + (home-page "http://github.com/daleroberts/hdmedians") + (synopsis "High-dimensional medians") + (description "Various definitions for a high-dimensional median exist and +this Python package provides a number of fast implementations of these +definitions. Medians are extremely useful due to their high breakdown +point (up to 50% contamination) and have a number of nice applications in +machine learning, computer vision, and high-dimensional statistics.") + (license license:asl2.0))) + (define-public python-patsy (package (name "python-patsy") |