[gentoo-commits] proj/sci:master commit in: dev-python/hdbscan/

[Horea Christian]

commit:     207a85724b6526e0f3be017a8a953412fcdcf597
Author:     Horea Christian <chr <AT> chymera <DOT> eu>
AuthorDate: Tue Jan 31 03:23:22 2023 +0000
Commit:     Horea Christian <horea.christ <AT> gmail <DOT> com>
CommitDate: Tue Jan 31 03:23:22 2023 +0000
URL:        https://gitweb.gentoo.org/proj/sci.git/commit/?id=207a8572

dev-python/hdbscan: new package, add 0.8.26, 0.8.29

Signed-off-by: Horea Christian <chr <AT> chymera.eu>

 dev-python/hdbscan/hdbscan-0.8.26.ebuild | 33 ++++++++++++++++++++++++++++++++
 dev-python/hdbscan/hdbscan-0.8.29.ebuild | 33 ++++++++++++++++++++++++++++++++
 dev-python/hdbscan/metadata.xml          | 28 +++++++++++++++++++++++++++
 3 files changed, 94 insertions(+)

diff --git a/dev-python/hdbscan/hdbscan-0.8.26.ebuild b/dev-python/hdbscan/hdbscan-0.8.26.ebuild
new file mode 100644
index 000000000..91e83eb87
--- /dev/null
+++ b/dev-python/hdbscan/hdbscan-0.8.26.ebuild
@@ -0,0 +1,33 @@
+# Copyright 2021-2023 Gentoo Authors
+# Distributed under the terms of the GNU General Public License v2
+
+EAPI=8
+
+PYTHON_COMPAT=( python3_{10..11} )
+DISTUTILS_USE_PEP517=setuptools
+inherit distutils-r1
+
+DESCRIPTION="A high performance implementation of HDBSCAN clustering."
+HOMEPAGE="https://github.com/scikit-learn-contrib/hdbscan"
+SRC_URI="mirror://pypi/${PN:0:1}/${PN}/${P}.tar.gz"
+
+LICENSE="BSD"
+SLOT="0"
+KEYWORDS="~amd64 ~x86"
+IUSE="test"
+RESTRICT="test"
+# Tests fail, reported to upstream
+# https://github.com/scikit-learn-contrib/hdbscan/issues/501
+
+DEPEND=""
+RDEPEND="
+	dev-python/cython[${PYTHON_USEDEP}]
+	dev-python/joblib[${PYTHON_USEDEP}]
+	dev-python/numpy[${PYTHON_USEDEP}]
+	dev-python/scipy[${PYTHON_USEDEP}]
+	dev-python/six[${PYTHON_USEDEP}]
+	sci-libs/scikit-learn[${PYTHON_USEDEP}]
+"
+BDEPEND=""
+
+distutils_enable_tests pytest

diff --git a/dev-python/hdbscan/hdbscan-0.8.29.ebuild b/dev-python/hdbscan/hdbscan-0.8.29.ebuild
new file mode 100644
index 000000000..85d049d4c
--- /dev/null
+++ b/dev-python/hdbscan/hdbscan-0.8.29.ebuild
@@ -0,0 +1,33 @@
+# Copyright 2021-2023 Gentoo Authors
+# Distributed under the terms of the GNU General Public License v2
+
+EAPI=8
+
+PYTHON_COMPAT=( python3_{8..10} )
+DISTUTILS_USE_PEP517=setuptools
+inherit distutils-r1
+
+DESCRIPTION="A high performance implementation of HDBSCAN clustering."
+HOMEPAGE="https://github.com/scikit-learn-contrib/hdbscan"
+SRC_URI="mirror://pypi/${PN:0:1}/${PN}/${P}.tar.gz"
+
+LICENSE="BSD"
+SLOT="0"
+KEYWORDS="~amd64 ~x86"
+IUSE="test"
+# Reported upstream:
+# https://github.com/scikit-learn-contrib/hdbscan/issues/501
+RESTRICT="test"
+
+DEPEND=""
+RDEPEND="
+	dev-python/cython[${PYTHON_USEDEP}]
+	dev-python/joblib[${PYTHON_USEDEP}]
+	dev-python/numpy[${PYTHON_USEDEP}]
+	dev-python/scipy[${PYTHON_USEDEP}]
+	dev-python/six[${PYTHON_USEDEP}]
+	sci-libs/scikit-learn[${PYTHON_USEDEP}]
+"
+BDEPEND=""
+
+distutils_enable_tests pytest

diff --git a/dev-python/hdbscan/metadata.xml b/dev-python/hdbscan/metadata.xml
new file mode 100644
index 000000000..b43e627e0
--- /dev/null
+++ b/dev-python/hdbscan/metadata.xml
@@ -0,0 +1,28 @@
+<?xml version='1.0' encoding='UTF-8'?>
+<!DOCTYPE pkgmetadata SYSTEM "http://www.gentoo.org/dtd/metadata.dtd">
+<pkgmetadata>
+	<maintainer type="person">
+		<email>gentoo@×××××××.eu</email>
+		<name>Horea Christian</name>
+	</maintainer>
+	<maintainer type="project">
+		<email>sci@g.o</email>
+		<name>Gentoo Science Project</name>
+	</maintainer>
+	<longdescription lang="en">
+		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.
+
+		In practice this means that HDBSCAN returns a good clustering straight away
+		with little or no parameter tuning -- and the primary parameter, minimum
+		cluster size, is intuitive and easy to select. 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).
+	</longdescription>
+	<upstream>
+		<remote-id type="github">scikit-learn-contrib/hdbscan</remote-id>
+	</upstream>
+</pkgmetadata>