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%global _empty_manifest_terminate_build 0
Name: python-neurokit2
Version: 0.2.4
Release: 1
Summary: The Python Toolbox for Neurophysiological Signal Processing.
License: MIT license
URL: https://github.com/neuropsychology/NeuroKit
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/94/ac/d63aa14e1b866878a1beca523766ce84e9496a560fccec4c34a2376eb1b9/neurokit2-0.2.4.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-pandas
Requires: python3-scipy
Requires: python3-scikit-learn
Requires: python3-matplotlib
Requires: python3-numpy
Requires: python3-pandas
Requires: python3-scipy
Requires: python3-scikit-learn
Requires: python3-matplotlib
Requires: python3-pytest
Requires: python3-coverage
Requires: python3-bioread
Requires: python3-mne[data]
Requires: python3-pyentrp
Requires: python3-antropy
Requires: python3-EntropyHub
Requires: python3-nolds
Requires: python3-biosppy
Requires: python3-cvxopt
Requires: python3-PyWavelets
Requires: python3-EMD-signal
Requires: python3-astropy
Requires: python3-plotly
Requires: python3-ts2vg
%description
import neurokit2 as nk
# Download example data
data = nk.data("bio_eventrelated_100hz")
# Preprocess the data (filter, find peaks, etc.)
processed_data, info = nk.bio_process(ecg=data["ECG"], rsp=data["RSP"], eda=data["EDA"], sampling_rate=100)
# Compute relevant features
results = nk.bio_analyze(processed_data, sampling_rate=100)
And **boom** 💥 your analysis is done 😎
%package -n python3-neurokit2
Summary: The Python Toolbox for Neurophysiological Signal Processing.
Provides: python-neurokit2
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-neurokit2
import neurokit2 as nk
# Download example data
data = nk.data("bio_eventrelated_100hz")
# Preprocess the data (filter, find peaks, etc.)
processed_data, info = nk.bio_process(ecg=data["ECG"], rsp=data["RSP"], eda=data["EDA"], sampling_rate=100)
# Compute relevant features
results = nk.bio_analyze(processed_data, sampling_rate=100)
And **boom** 💥 your analysis is done 😎
%package help
Summary: Development documents and examples for neurokit2
Provides: python3-neurokit2-doc
%description help
import neurokit2 as nk
# Download example data
data = nk.data("bio_eventrelated_100hz")
# Preprocess the data (filter, find peaks, etc.)
processed_data, info = nk.bio_process(ecg=data["ECG"], rsp=data["RSP"], eda=data["EDA"], sampling_rate=100)
# Compute relevant features
results = nk.bio_analyze(processed_data, sampling_rate=100)
And **boom** 💥 your analysis is done 😎
%prep
%autosetup -n neurokit2-0.2.4
%build
%py3_build
%install
%py3_install
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}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
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-neurokit2 -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.2.4-1
- Package Spec generated
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