662 lines
26 KiB
Scheme
662 lines
26 KiB
Scheme
;;; GNU Guix --- Functional package management for GNU
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;;; Copyright © 2017, 2018, 2019, 2020, 2022 Ricardo Wurmus <rekado@elephly.net>
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;;; Copyright © 2018 Joshua Sierles, Nextjournal <joshua@nextjournal.com>
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;;; Copyright © 2018, 2020, 2022 Tobias Geerinckx-Rice <me@tobias.gr>
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;;; Copyright © 2019, 2021, 2022 Efraim Flashner <efraim@flashner.co.il>
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;;; Copyright © 2019 Andreas Enge <andreas@enge.fr>
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;;; Copyright © 2020 Alexander Krotov <krotov@iitp.ru>
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;;; Copyright © 2020 Pierre Langlois <pierre.langlos@gmx.com>
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;;; Copyright © 2021 Vinicius Monego <monego@posteo.net>
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;;; Copyright © 2021 Alexandre Hannud Abdo <abdo@member.fsf.org>
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;;; Copyright © 2021, 2022 Maxim Cournoyer <maxim.cournoyer@gmail.com>
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;;; Copyright © 2022 Marius Bakke <marius@gnu.org>
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;;;
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;;; This file is part of GNU Guix.
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;;;
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;;; GNU Guix is free software; you can redistribute it and/or modify it
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;;; under the terms of the GNU General Public License as published by
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;;; the Free Software Foundation; either version 3 of the License, or (at
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;;; your option) any later version.
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;;;
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;;; GNU Guix is distributed in the hope that it will be useful, but
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;;; WITHOUT ANY WARRANTY; without even the implied warranty of
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;;; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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;;; GNU General Public License for more details.
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;;;
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;;; You should have received a copy of the GNU General Public License
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;;; along with GNU Guix. If not, see <http://www.gnu.org/licenses/>.
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(define-module (gnu packages graph)
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#:use-module (guix download)
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#:use-module (guix gexp)
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#:use-module (guix git-download)
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#:use-module (guix packages)
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#:use-module (guix utils)
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#:use-module (guix build-system cmake)
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#:use-module (guix build-system gnu)
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#:use-module (guix build-system python)
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#:use-module (guix build-system r)
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#:use-module ((guix licenses) #:prefix license:)
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#:use-module (gnu packages)
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#:use-module (gnu packages autotools)
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#:use-module (gnu packages bioconductor)
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#:use-module (gnu packages bioinformatics)
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#:use-module (gnu packages boost)
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#:use-module (gnu packages check)
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#:use-module (gnu packages compression)
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#:use-module (gnu packages cran)
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#:use-module (gnu packages datastructures)
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#:use-module (gnu packages gd)
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#:use-module (gnu packages graphics)
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#:use-module (gnu packages graphviz)
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#:use-module (gnu packages gtk)
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#:use-module (gnu packages maths)
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#:use-module (gnu packages multiprecision)
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#:use-module (gnu packages ncurses)
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#:use-module (gnu packages pkg-config)
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#:use-module (gnu packages python)
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#:use-module (gnu packages python-build)
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#:use-module (gnu packages python-science)
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#:use-module (gnu packages python-web)
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#:use-module (gnu packages python-xyz)
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#:use-module (gnu packages statistics)
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#:use-module (gnu packages swig)
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#:use-module (gnu packages time)
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#:use-module (gnu packages xml))
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(define-public plfit
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(package
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(name "plfit")
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(version "0.9.3")
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(source (origin
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(method git-fetch)
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(uri (git-reference
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(url "https://github.com/ntamas/plfit")
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(commit version)))
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(file-name (git-file-name name version))
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(sha256
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(base32
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"03x5jbvg8vwr92682swy58ljxrhqwmga1xzd0cpfbfmda41gm2fb"))))
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(build-system cmake-build-system)
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(arguments
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'(#:configure-flags (list "-DBUILD_SHARED_LIBS=ON")))
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(home-page "https://github.com/ntamas/plfit")
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(synopsis "Tool for fitting power-law distributions to empirical data")
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(description "The @command{plfit} command fits power-law distributions to
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empirical (discrete or continuous) data, according to the method of Clauset,
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Shalizi and Newman (@cite{Clauset A, Shalizi CR and Newman MEJ: Power-law
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distributions in empirical data. SIAM Review 51, 661-703 (2009)}).")
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(license license:gpl2+)))
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(define-public igraph
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(package
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(name "igraph")
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(version "0.9.8")
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(source
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(origin
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(method url-fetch)
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(uri (string-append "https://github.com/igraph/igraph/releases/"
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"download/" version "/igraph-" version ".tar.gz"))
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(modules '((guix build utils)))
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(snippet '(begin
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;; Fully unbundle igraph (see:
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;; https://github.com/igraph/igraph/issues/1897).
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(delete-file-recursively "vendor")
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(substitute* "CMakeLists.txt"
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(("add_subdirectory\\(vendor\\).*")
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""))
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;; Help CMake to find our plfit headers.
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(substitute* "etc/cmake/FindPLFIT.cmake"
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(("^ NAMES plfit.h.*" all)
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(string-append all
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" PATH_SUFFIXES plfit")))
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(substitute* '("src/CMakeLists.txt"
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"etc/cmake/benchmark_helpers.cmake")
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;; Remove bundling related variables.
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((".*_IS_VENDORED.*")
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""))))
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(sha256
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(base32 "15v3ydq95gahnas37cip637hvc2nwrmk76xp0nv3gq53rrrk9a7r"))))
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(build-system cmake-build-system)
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(arguments
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'(#:configure-flags (list "-DBUILD_SHARED_LIBS=ON")))
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(native-inputs (list pkg-config))
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(inputs
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(list arpack-ng
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gmp
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glpk
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libxml2
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lapack
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openblas
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plfit
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suitesparse))
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(home-page "https://igraph.org")
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(synopsis "Network analysis and visualization")
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(description
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"This package provides a library for the analysis of networks and graphs.
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It can handle large graphs very well and provides functions for generating
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random and regular graphs, graph visualization, centrality methods and much
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more.")
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(license license:gpl2+)))
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(define-public python-igraph
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(package
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(inherit igraph)
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(name "python-igraph")
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(version "0.9.11")
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(source (origin
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(method git-fetch)
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;; The PyPI archive lacks tests.
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(uri (git-reference
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(url "https://github.com/igraph/python-igraph")
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(commit version)))
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(file-name (git-file-name name version))
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(sha256
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(base32
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"1xlr0cnf3a1vs9n2psvgrmjhld4n1xr79kkjqzby4pxxyzk1bydn"))))
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(build-system python-build-system)
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(arguments
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(list
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#:phases
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#~(modify-phases %standard-phases
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(add-after 'unpack 'specify-libigraph-location
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(lambda _
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(let ((igraph #$(this-package-input "igraph")))
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(substitute* "setup.py"
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(("(LIBIGRAPH_FALLBACK_INCLUDE_DIRS = ).*" _ var)
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(string-append
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var (format #f "[~s]~%" (string-append igraph
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"/include/igraph"))))
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(("(LIBIGRAPH_FALLBACK_LIBRARY_DIRS = ).*" _ var)
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(string-append
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var (format #f "[~s]~%" (string-append igraph "/lib"))))))))
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(replace 'check
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(lambda* (#:key tests? #:allow-other-keys)
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(when tests?
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(invoke "pytest" "-v")))))))
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(inputs
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(list igraph))
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(propagated-inputs
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(list python-texttable))
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(native-inputs
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(list python-pytest))
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(home-page "https://igraph.org/python/")
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(synopsis "Python bindings for the igraph network analysis library")))
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(define-public r-rbiofabric
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(let ((commit "666c2ae8b0a537c006592d067fac6285f71890ac")
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(revision "1"))
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(package
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(name "r-rbiofabric")
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(version (string-append "0.3-" revision "." (string-take commit 7)))
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(source (origin
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(method git-fetch)
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(uri (git-reference
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(url "https://github.com/wjrl/RBioFabric")
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(commit commit)))
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(file-name (string-append name "-" version "-checkout"))
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(sha256
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(base32
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"1yahqrcrqpbcywv73y9rlmyz8apdnp08afialibrr93ch0p06f8z"))))
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(build-system r-build-system)
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(propagated-inputs
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(list r-igraph))
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(home-page "http://www.biofabric.org/")
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(synopsis "BioFabric network visualization")
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(description "This package provides an implementation of the function
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@code{bioFabric} for creating scalable network digrams where nodes are
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represented by horizontal lines, and edges are represented by vertical
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lines.")
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(license license:expat))))
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(define-public python-plotly
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(package
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(name "python-plotly")
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(version "5.6.0")
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(source (origin
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(method git-fetch)
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(uri (git-reference
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(url "https://github.com/plotly/plotly.py")
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(commit (string-append "v" version))))
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(file-name (git-file-name name version))
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(sha256
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(base32
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"0kc9v5ampq2paw6sls6zdchvqvis7b1z8xhdvlhz5xxdr1vj5xnn"))))
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(build-system python-build-system)
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(arguments
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`(#:phases
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(modify-phases %standard-phases
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(add-before 'build 'skip-npm
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;; npm is not packaged so build without it
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(lambda _
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(setenv "SKIP_NPM" "T")))
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(add-after 'unpack 'chdir
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(lambda _
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(chdir "packages/python/plotly")
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#t))
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(replace 'check
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(lambda* (#:key tests? #:allow-other-keys)
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(when tests?
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(invoke "pytest" "-x" "plotly/tests/test_core")
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(invoke "pytest" "-x" "plotly/tests/test_io")
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;; FIXME: Add optional dependencies and enable their tests.
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;; (invoke "pytest" "-x" "plotly/tests/test_optional")
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(invoke "pytest" "_plotly_utils/tests")))))))
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(native-inputs
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(list python-ipywidgets python-pytest python-xarray))
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(propagated-inputs
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(list python-ipython
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python-pandas
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python-pillow
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python-requests
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python-retrying
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python-six
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python-tenacity
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python-statsmodels))
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(home-page "https://plotly.com/python/")
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(synopsis "Interactive plotting library for Python")
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(description "Plotly's Python graphing library makes interactive,
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publication-quality graphs online. Examples of how to make line plots, scatter
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plots, area charts, bar charts, error bars, box plots, histograms, heatmaps,
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subplots, multiple-axes, polar charts, and bubble charts.")
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(license license:expat)))
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(define-public python-plotly-2.4.1
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(package (inherit python-plotly)
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(version "2.4.1")
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(source
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(origin
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(method url-fetch)
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(uri (pypi-uri "plotly" version))
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(sha256
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(base32
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"0s9gk2fl53x8wwncs3fwii1vzfngr0sskv15v3mpshqmrqfrk27m"))))
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(native-inputs '())
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(propagated-inputs
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(list python-decorator
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python-nbformat
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python-pandas
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python-pytz
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python-requests
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python-six))
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(arguments
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'(#:tests? #f)))) ; The tests are not distributed in the release
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(define-public python-louvain
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(package
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(name "python-louvain")
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(version "0.16")
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(source
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(origin
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(method url-fetch)
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(uri (pypi-uri "python-louvain" version))
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(sha256
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(base32 "0sx53l555rwq0z7if8agirjgw4ddp8r9b949wwz8vlig03sjvfmp"))))
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(build-system python-build-system)
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(native-inputs
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(list python-setuptools)) ;for use_2to3 support
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(propagated-inputs
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(list python-networkx python-numpy))
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(home-page "https://github.com/taynaud/python-louvain")
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(synopsis "Louvain algorithm for community detection")
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(description
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"This package provides a pure Python implementation of the Louvain
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algorithm for community detection in large networks.")
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(license license:bsd-3)))
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(define-public python-louvain-0.7
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(package
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(name "python-louvain")
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(version "0.7.1")
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;; The tarball on Pypi does not include the tests.
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(source (origin
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(method git-fetch)
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(uri (git-reference
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(url "https://github.com/vtraag/louvain-igraph")
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(commit version)))
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(file-name (git-file-name name version))
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(sha256
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(base32
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"1g6b5c2jgwagnhnqh859g61h7x6a81d8hm3g6mkin6kzwafww3g2"))))
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(build-system python-build-system)
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(arguments
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(list
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#:phases
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#~(modify-phases %standard-phases
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(add-before 'build 'pretend-version
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;; The version string is usually derived via setuptools-scm, but
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;; without the git metadata available this fails.
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(lambda _
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(setenv "SETUPTOOLS_SCM_PRETEND_VERSION" #$version)))
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(add-before 'build 'find-igraph
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(lambda* (#:key inputs #:allow-other-keys)
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(setenv "IGRAPH_EXTRA_INCLUDE_PATH"
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(string-append (assoc-ref inputs "igraph")
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"/include/igraph:"
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(getenv "C_INCLUDE_PATH")))
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(setenv "IGRAPH_EXTRA_LIBRARY_PATH"
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(getenv "LIBRARY_PATH")))))))
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(propagated-inputs
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(list python-ddt python-igraph))
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(inputs
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(list igraph))
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(native-inputs
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(list pkg-config
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python-pytest
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python-setuptools-scm
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python-wheel))
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(home-page "https://github.com/vtraag/louvain-igraph")
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(synopsis "Algorithm for methods of community detection in large networks")
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(description
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"This package provides an implementation of the Louvain algorithm for use
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with igraph. Louvain is a general algorithm for methods of community
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detection in large networks.
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This package has been superseded by the @code{leidenalg} package and should
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not be used for new projects.")
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(license license:gpl3+)))
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(define-public faiss
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(package
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(name "faiss")
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(version "1.5.0")
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(source (origin
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(method git-fetch)
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(uri (git-reference
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(url "https://github.com/facebookresearch/faiss")
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(commit (string-append "v" version))))
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(file-name (git-file-name name version))
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(sha256
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(base32
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"0pk15jfa775cy2pqmzq62nhd6zfjxmpvz5h731197c28aq3zw39w"))
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(modules '((guix build utils)))
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(snippet
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'(begin
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(substitute* "utils.cpp"
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(("#include <immintrin.h>")
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"#ifdef __SSE__\n#include <immintrin.h>\n#endif"))
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#t))))
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(build-system cmake-build-system)
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(arguments
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`(#:configure-flags
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(list "-DBUILD_WITH_GPU=OFF" ; thanks, but no thanks, CUDA.
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"-DBUILD_TUTORIAL=OFF") ; we don't need those
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#:phases
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(modify-phases %standard-phases
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(add-after 'unpack 'prepare-build
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(lambda _
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(let ((features (list ,@(let ((system (or (%current-target-system)
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(%current-system))))
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(cond
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((string-prefix? "x86_64" system)
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'("-mavx" "-msse2" "-mpopcnt"))
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((string-prefix? "i686" system)
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'("-msse2" "-mpopcnt"))
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(else
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'()))))))
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(substitute* "CMakeLists.txt"
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(("-m64") "")
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(("-mpopcnt") "") ; only some architectures
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(("-msse4")
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(string-append
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(string-join features)
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" -I" (getcwd)))
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;; Build also the shared library
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(("ARCHIVE DESTINATION lib")
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"LIBRARY DESTINATION lib")
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(("add_library.*" m)
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"\
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add_library(objlib OBJECT ${faiss_cpu_headers} ${faiss_cpu_cpp})
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set_property(TARGET objlib PROPERTY POSITION_INDEPENDENT_CODE 1)
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add_library(${faiss_lib}_static STATIC $<TARGET_OBJECTS:objlib>)
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add_library(${faiss_lib} SHARED $<TARGET_OBJECTS:objlib>)
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install(TARGETS ${faiss_lib}_static ARCHIVE DESTINATION lib)
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\n")))
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;; See https://github.com/facebookresearch/faiss/issues/520
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(substitute* "IndexScalarQuantizer.cpp"
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(("#define USE_AVX") ""))
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;; Make header files available for compiling tests.
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(mkdir-p "faiss")
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(for-each (lambda (file)
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(mkdir-p (string-append "faiss/" (dirname file)))
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(copy-file file (string-append "faiss/" file)))
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(find-files "." "\\.h$"))
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#t))
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(replace 'check
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(lambda _
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(invoke "make" "-C" "tests"
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(format #f "-j~a" (parallel-job-count)))))
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(add-after 'install 'remove-tests
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(lambda* (#:key outputs #:allow-other-keys)
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(delete-file-recursively
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(string-append (assoc-ref outputs "out")
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"/test"))
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#t)))))
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(inputs
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(list openblas))
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|
(native-inputs
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(list googletest))
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|
(home-page "https://github.com/facebookresearch/faiss")
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(synopsis "Efficient similarity search and clustering of dense vectors")
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(description "Faiss is a library for efficient similarity search and
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clustering of dense vectors. It contains algorithms that search in sets of
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vectors of any size, up to ones that possibly do not fit in RAM. It also
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contains supporting code for evaluation and parameter tuning.")
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(license license:bsd-3)))
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(define-public python-faiss
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(package (inherit faiss)
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(name "python-faiss")
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(build-system python-build-system)
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|
(arguments
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`(#:phases
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|
(modify-phases %standard-phases
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|
(add-after 'unpack 'chdir
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|
(lambda _ (chdir "python") #t))
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|
(add-after 'chdir 'build-swig
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(lambda* (#:key inputs #:allow-other-keys)
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|
(with-output-to-file "../makefile.inc"
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|
(lambda ()
|
|
(let ((python-version ,(version-major+minor (package-version python))))
|
|
(format #t "\
|
|
PYTHONCFLAGS =-I~a/include/python~a/ -I~a/lib/python~a/site-packages/numpy/core/include
|
|
LIBS = -lpython~a -lfaiss
|
|
SHAREDFLAGS = -shared -fopenmp
|
|
CXXFLAGS = -fpermissive -fopenmp -fPIC
|
|
CPUFLAGS = ~{~a ~}~%"
|
|
(assoc-ref inputs "python*") python-version
|
|
(assoc-ref inputs "python-numpy") python-version
|
|
python-version
|
|
(list ,@(let ((system (or (%current-target-system)
|
|
(%current-system))))
|
|
(cond
|
|
((string-prefix? "x86_64" system)
|
|
'("-mavx" "-msse2" "-mpopcnt"))
|
|
((string-prefix? "i686" system)
|
|
'("-msse2" "-mpopcnt"))
|
|
(else
|
|
'()))))))))
|
|
(substitute* "Makefile"
|
|
(("../libfaiss.a") ""))
|
|
(invoke "make" "cpu"))))))
|
|
(inputs
|
|
`(("faiss" ,faiss)
|
|
("openblas" ,openblas)
|
|
("python*" ,python)
|
|
("swig" ,swig)))
|
|
(propagated-inputs
|
|
(list python-matplotlib python-numpy))
|
|
(description "Faiss is a library for efficient similarity search and
|
|
clustering of dense vectors. This package provides Python bindings to the
|
|
Faiss library.")))
|
|
|
|
(define-public python-leidenalg
|
|
(package
|
|
(name "python-leidenalg")
|
|
(version "0.8.10")
|
|
(source
|
|
(origin
|
|
(method url-fetch)
|
|
(uri (pypi-uri "leidenalg" version))
|
|
(sha256
|
|
(base32
|
|
"1hbvagp1yyazvl7cid7mii5263qi48lpkq543n5w71qysgz1f0v7"))))
|
|
(build-system python-build-system)
|
|
(arguments
|
|
'(#:tests? #f ;tests are not included
|
|
#:phases (modify-phases %standard-phases
|
|
(add-after 'unpack 'fix-requirements
|
|
(lambda _
|
|
(substitute* "setup.py"
|
|
(("self.external = False")
|
|
"self.external = True")
|
|
(("self.use_pkgconfig = False")
|
|
"self.use_pkgconfig = True")
|
|
(("python-igraph >=")
|
|
"igraph >=")))))))
|
|
(native-inputs
|
|
(list pkg-config python-setuptools-scm))
|
|
(inputs
|
|
(list igraph))
|
|
(propagated-inputs
|
|
(list python-igraph))
|
|
(home-page "https://github.com/vtraag/leidenalg")
|
|
(synopsis "Community detection in large networks")
|
|
(description
|
|
"Leiden is a general algorithm for methods of community detection in
|
|
large networks. This package implements the Leiden algorithm in C++ and
|
|
exposes it to Python. Besides the relative flexibility of the implementation,
|
|
it also scales well, and can be run on graphs of millions of nodes (as long as
|
|
they can fit in memory). The core function is @code{find_partition} which
|
|
finds the optimal partition using the Leiden algorithm, which is an extension
|
|
of the Louvain algorithm, for a number of different methods.")
|
|
(license license:gpl3+)))
|
|
|
|
(define-public edge-addition-planarity-suite
|
|
(package
|
|
(name "edge-addition-planarity-suite")
|
|
(version "3.0.0.5")
|
|
(source
|
|
(origin
|
|
(method git-fetch)
|
|
(uri (git-reference
|
|
(url (string-append "https://github.com/graph-algorithms/"
|
|
name))
|
|
(commit (string-append "Version_" version))))
|
|
(file-name (git-file-name name version))
|
|
(sha256
|
|
(base32
|
|
"01cm7ay1njkfsdnmnvh5zwc7wg7x189hq1vbfhh9p3ihrbnmqzh8"))))
|
|
(build-system gnu-build-system)
|
|
(native-inputs
|
|
(list autoconf automake libtool))
|
|
(synopsis "Embedding of planar graphs")
|
|
(description "The package provides a reference implementation of the
|
|
linear time edge addition algorithm for embedding planar graphs and
|
|
isolating planarity obstructions.")
|
|
(license license:bsd-3)
|
|
(home-page
|
|
"https://github.com/graph-algorithms/edge-addition-planarity-suite")))
|
|
|
|
(define-public rw
|
|
(package
|
|
(name "rw")
|
|
;; There is a version 0.8, but the tarball is broken with symlinks
|
|
;; to /usr/share.
|
|
(version "0.7")
|
|
(source (origin
|
|
(method url-fetch)
|
|
(uri (string-append "mirror://sourceforge/rankwidth/"
|
|
"rw-" version ".tar.gz"))
|
|
(sha256
|
|
(base32
|
|
"1rv2v42x2506x7f10349m1wpmmfxrv9l032bkminni2gbip9cjg0"))))
|
|
(build-system gnu-build-system)
|
|
(native-inputs
|
|
(list pkg-config))
|
|
(inputs
|
|
(list igraph))
|
|
(home-page "https://sourceforge.net/projects/rankwidth/")
|
|
(synopsis "Rank-width and rank-decomposition of graphs")
|
|
(description "rw computes rank-width and rank-decompositions
|
|
of graphs.")
|
|
(license license:gpl2+)))
|
|
|
|
(define-public mscgen
|
|
(package
|
|
(name "mscgen")
|
|
(version "0.20")
|
|
(source
|
|
(origin
|
|
(method url-fetch)
|
|
(uri (string-append "http://www.mcternan.me.uk/mscgen/software/mscgen-src-"
|
|
version ".tar.gz"))
|
|
(sha256
|
|
(base32
|
|
"08yw3maxhn5fl1lff81gmcrpa4j9aas4mmby1g9w5qcr0np82d1w"))))
|
|
(build-system gnu-build-system)
|
|
(native-inputs
|
|
(list pkg-config))
|
|
(inputs
|
|
(list gd))
|
|
(home-page "http://www.mcternan.me.uk/mscgen/")
|
|
(synopsis "Message Sequence Chart Generator")
|
|
(description "Mscgen is a small program that parses Message Sequence Chart
|
|
descriptions and produces PNG, SVG, EPS or server side image maps (ismaps) as
|
|
the output. Message Sequence Charts (MSCs) are a way of representing entities
|
|
and interactions over some time period and are often used in combination with
|
|
SDL. MSCs are popular in Telecoms to specify how protocols operate although
|
|
MSCs need not be complicated to create or use. Mscgen aims to provide a simple
|
|
text language that is clear to create, edit and understand, which can also be
|
|
transformed into common image formats for display or printing.")
|
|
(license license:gpl2+)))
|
|
|
|
(define-public python-graph-tool
|
|
(package
|
|
(name "python-graph-tool")
|
|
(version "2.45")
|
|
(source (origin
|
|
(method url-fetch)
|
|
(uri (string-append
|
|
"https://downloads.skewed.de/graph-tool/graph-tool-"
|
|
version ".tar.bz2"))
|
|
(sha256
|
|
(base32
|
|
"0s46qqg454kwq2px7x1a4ckryclkxnrz1r7gj6bv40nsrynafbgr"))))
|
|
(build-system gnu-build-system)
|
|
(arguments
|
|
`(#:imported-modules (,@%gnu-build-system-modules
|
|
(guix build python-build-system))
|
|
#:modules (,@%gnu-build-system-modules
|
|
((guix build python-build-system) #:select (site-packages)))
|
|
#:configure-flags
|
|
(list (string-append "--with-boost="
|
|
(assoc-ref %build-inputs "boost"))
|
|
(string-append "--with-python-module-path="
|
|
(site-packages %build-inputs %outputs)))))
|
|
(native-inputs
|
|
(list ncurses pkg-config))
|
|
(inputs
|
|
(list boost
|
|
cairomm-1.14
|
|
cgal
|
|
expat
|
|
gmp
|
|
gtk+
|
|
python-wrapper
|
|
sparsehash))
|
|
(propagated-inputs
|
|
(list python-matplotlib python-numpy python-pycairo python-scipy))
|
|
(synopsis "Manipulate and analyze graphs with Python efficiently")
|
|
(description "Graph-tool is an efficient Python module for manipulation
|
|
and statistical analysis of graphs (a.k.a. networks). Contrary to most other
|
|
Python modules with similar functionality, the core data structures and
|
|
algorithms are implemented in C++, making extensive use of template
|
|
metaprogramming, based heavily on the Boost Graph Library. This confers it a
|
|
level of performance that is comparable (both in memory usage and computation
|
|
time) to that of a pure C/C++ library.")
|
|
(home-page "https://graph-tool.skewed.de/")
|
|
(license license:lgpl3+)))
|