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|
%global _empty_manifest_terminate_build 0
Name: python-pingouin
Version: 0.5.5
Release: 1
Summary: Pingouin: statistical package for Python
License: GPL-3.0
URL: https://pingouin-stats.org/index.html
Source0: https://files.pythonhosted.org/packages/0e/3d/14a779790bac2d03a0d8f82c1857fc83c0ef8b1b77542b884808e55ee839/pingouin-0.5.5.tar.gz
BuildArch: noarch
Requires: (python3-matplotlib)
Requires: (python3-numpy)
Requires: (python3-pandas>=1.5)
Requires: (python3-pandas-flavor)
Requires: (python3-scikit-learn>=1.2)
Requires: (python3-scipy)
Requires: (python3-seaborn)
Requires: (python3-statsmodels)
Requires: (python3-tabulate)
Requires: (python3-sphinx>7.0.0)
Requires: (python3-pydata-sphinx-theme)
Requires: (python3-numpydoc)
Requires: (python3-sphinx-copybutton)
Requires: (python3-sphinx-design)
Requires: (python3-sphinx-notfound-page)
Requires: (python3-pytest>=6)
Requires: (python3-pytest-cov)
Requires: (python3-codecov)
Requires: (python3-openpyxl)
Requires: (python3-mpmath)
Requires: (python3-coverage[toml]>=5.3)
%description
**Pingouin** is an open-source statistical package written in Python 3 and based mostly on Pandas and NumPy. Some of its main features are listed below. For a full list of available functions, please refer to the `API documentation <https://pingouin-stats.org/build/html/api.html#>`_.
1. ANOVAs: N-ways, repeated measures, mixed, ancova
2. Pairwise post-hocs tests (parametric and non-parametric) and pairwise correlations
3. Robust, partial, distance and repeated measures correlations
4. Linear/logistic regression and mediation analysis
5. Bayes Factors
6. Multivariate tests
7. Reliability and consistency
8. Effect sizes and power analysis
9. Parametric/bootstrapped confidence intervals around an effect size or a correlation coefficient
10. Circular statistics
11. Chi-squared tests
12. Plotting: Bland-Altman plot, Q-Q plot, paired plot, robust correlation...
Pingouin is designed for users who want **simple yet exhaustive statistical functions**.
For example, the :code:`ttest_ind` function of SciPy returns only the T-value and the p-value. By contrast,
the :code:`ttest` function of Pingouin returns the T-value, the p-value, the degrees of freedom, the effect size (Cohen's d), the 95% confidence intervals of the difference in means, the statistical power and the Bayes Factor (BF10) of the test.
%package -n python3-pingouin
Summary: Pingouin: statistical package for Python
Provides: python-pingouin
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
BuildRequires: python3-wheel
%description -n python3-pingouin
**Pingouin** is an open-source statistical package written in Python 3 and based mostly on Pandas and NumPy. Some of its main features are listed below. For a full list of available functions, please refer to the `API documentation <https://pingouin-stats.org/build/html/api.html#>`_.
1. ANOVAs: N-ways, repeated measures, mixed, ancova
2. Pairwise post-hocs tests (parametric and non-parametric) and pairwise correlations
3. Robust, partial, distance and repeated measures correlations
4. Linear/logistic regression and mediation analysis
5. Bayes Factors
6. Multivariate tests
7. Reliability and consistency
8. Effect sizes and power analysis
9. Parametric/bootstrapped confidence intervals around an effect size or a correlation coefficient
10. Circular statistics
11. Chi-squared tests
12. Plotting: Bland-Altman plot, Q-Q plot, paired plot, robust correlation...
Pingouin is designed for users who want **simple yet exhaustive statistical functions**.
For example, the :code:`ttest_ind` function of SciPy returns only the T-value and the p-value. By contrast,
the :code:`ttest` function of Pingouin returns the T-value, the p-value, the degrees of freedom, the effect size (Cohen's d), the 95% confidence intervals of the difference in means, the statistical power and the Bayes Factor (BF10) of the test.
%package help
Summary: Development documents and examples for pingouin
Provides: python3-pingouin-doc
%description help
**Pingouin** is an open-source statistical package written in Python 3 and based mostly on Pandas and NumPy. Some of its main features are listed below. For a full list of available functions, please refer to the `API documentation <https://pingouin-stats.org/build/html/api.html#>`_.
1. ANOVAs: N-ways, repeated measures, mixed, ancova
2. Pairwise post-hocs tests (parametric and non-parametric) and pairwise correlations
3. Robust, partial, distance and repeated measures correlations
4. Linear/logistic regression and mediation analysis
5. Bayes Factors
6. Multivariate tests
7. Reliability and consistency
8. Effect sizes and power analysis
9. Parametric/bootstrapped confidence intervals around an effect size or a correlation coefficient
10. Circular statistics
11. Chi-squared tests
12. Plotting: Bland-Altman plot, Q-Q plot, paired plot, robust correlation...
Pingouin is designed for users who want **simple yet exhaustive statistical functions**.
For example, the :code:`ttest_ind` function of SciPy returns only the T-value and the p-value. By contrast,
the :code:`ttest` function of Pingouin returns the T-value, the p-value, the degrees of freedom, the effect size (Cohen's d), the 95% confidence intervals of the difference in means, the statistical power and the Bayes Factor (BF10) of the test.
%prep
%autosetup -n pingouin-0.5.5
%build
CFLAGS="${CFLAGS:-${RPM_OPT_FLAGS}}" LDFLAGS="${LDFLAGS:-${RPM_LD_FLAGS}}" \
%{__python3} -m pip wheel \
--verbose \
--progress-bar off \
--disable-pip-version-check \
--use-pep517 \
--no-build-isolation \
--no-deps \
--wheel-dir ./build \
.
%install
WHEEL_FILE=$(find ./build -name "*.whl" | head -n1)
if [ -z "$WHEEL_FILE" ]; then
echo "ERROR: No .whl file found in ./build!" >&2
exit 1
fi
CFLAGS="${CFLAGS:-${RPM_OPT_FLAGS}}" LDFLAGS="${LDFLAGS:-${RPM_LD_FLAGS}}" \
%{__python3} -m pip install \
--verbose \
--progress-bar off \
--disable-pip-version-check \
--root %{buildroot} \
--no-compile \
--ignore-installed \
--no-deps \
--no-index \
--find-links ./build \
"$WHEEL_FILE"
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}%{python3_sitelib}
if [ -d "UNKNOWN-0.0.0.dist-info" ]; then
mv "UNKNOWN-0.0.0.dist-info" "pingouin-%{version}.dist-info"
sed -i "s/^Name: UNKNOWN/Name: pingouin/" "pingouin-%{version}.dist-info/METADATA" 2>/dev/null || true
sed -i "s/^Version: 0.0.0/Version: %{version}/" "pingouin-%{version}.dist-info/METADATA" 2>/dev/null || true
fi
popd
pushd %{buildroot}
touch filelist.lst
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-pingouin -f filelist.lst
%{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Mon Nov 11 2024 Python_Bot <Python_Bot@openeuler.org> - 0.5.5-1
- Package Spec generated
|
