forked from pool/python-cluster
Dirk Mueller
fb58af9bf0
- Do not build for Python 3.6, due to no NumPy. OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-cluster?expand=0&rev=7
65 lines
2.3 KiB
RPMSpec
65 lines
2.3 KiB
RPMSpec
#
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# spec file for package python-cluster
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#
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# Copyright (c) 2024 SUSE LLC
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#
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# All modifications and additions to the file contributed by third parties
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# remain the property of their copyright owners, unless otherwise agreed
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# upon. The license for this file, and modifications and additions to the
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# file, is the same license as for the pristine package itself (unless the
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# license for the pristine package is not an Open Source License, in which
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# case the license is the MIT License). An "Open Source License" is a
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# license that conforms to the Open Source Definition (Version 1.9)
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# published by the Open Source Initiative.
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# Please submit bugfixes or comments via https://bugs.opensuse.org/
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#
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%{?!python_module:%define python_module() python-%{**} python3-%{**}}
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%define skip_python36 1
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Name: python-cluster
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Version: 1.4.1.post2
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Release: 0
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Summary: Clustering library for python
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License: LGPL-2.0-or-later
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URL: https://github.com/exhuma/python-cluster
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Source: https://files.pythonhosted.org/packages/source/c/cluster/cluster-%{version}.tar.gz
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BuildRequires: %{python_module pip}
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BuildRequires: %{python_module setuptools}
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BuildRequires: fdupes
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BuildRequires: python-rpm-macros
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Requires: python-matplotlib >= 1.2
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Requires: python-numpy >= 1.2
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Requires: python-scipy >= 0.12
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BuildArch: noarch
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%python_subpackages
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%description
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The python-cluster package allows you to create several groups
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(clusters) of objects from a list. It’s meant to be flexible and able
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to cluster any object. To ensure this kind of flexibility, you need
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not only to supply the list of objects, but also a function that
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calculates the similarity between two of those objects. For simple
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datatypes, like integers, this can be as simple as a subtraction, but
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more complex calculations are possible. Right now, it is possible to
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generate the clusters using a hierarchical clustering and the popular
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K-Means algorithm. For the hierarchical algorithm there are different
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“linkage” (single, complete, average and uclus) methods available.
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%prep
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%setup -q -n cluster-%{version}
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%build
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%python_build
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%install
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%python_install
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%python_expand %fdupes %{buildroot}%{$python_sitelib}
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%files %{python_files}
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%license LICENSE
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%{python_sitelib}/*
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%changelog
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