%global _empty_manifest_terminate_build 0 Name: python-mne Version: 1.3.1 Release: 1 Summary: MNE-Python project for MEG and EEG data analysis. License: BSD-3-Clause URL: https://mne.tools/dev/ Source0: https://mirrors.nju.edu.cn/pypi/web/packages/d6/ee/2dbb0a27d7431bec54c9300ae571f227fe5b21015c73a77dd641af684d21/mne-1.3.1.tar.gz BuildArch: noarch Requires: python3-numpy Requires: python3-scipy Requires: python3-matplotlib Requires: python3-tqdm Requires: python3-pooch Requires: python3-decorator Requires: python3-packaging Requires: python3-jinja2 Requires: python3-h5io Requires: python3-pymatreader Requires: python3-pytest Requires: python3-pytest-cov Requires: python3-pytest-timeout Requires: python3-pytest-harvest Requires: python3-flake8 Requires: python3-flake8-array-spacing Requires: python3-numpydoc Requires: python3-codespell Requires: python3-pydocstyle Requires: python3-check-manifest Requires: python3-twine Requires: python3-wheel Requires: python3-nitime Requires: python3-nbclient Requires: python3-sphinx-gallery Requires: python3-eeglabio Requires: python3-EDFlib-Python Requires: python3-pybv Requires: python3-imageio-ffmpeg %description `MNE-Python software`_ is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, and statistics. Documentation ^^^^^^^^^^^^^ `MNE documentation`_ for MNE-Python is available online. Installing MNE-Python ^^^^^^^^^^^^^^^^^^^^^ To install the latest stable version of MNE-Python, you can use pip_ in a terminal: $ pip install -U mne - MNE-Python 0.17 was the last release to support Python 2.7 - MNE-Python 0.18 requires Python 3.5 or higher - MNE-Python 0.21 requires Python 3.6 or higher - MNE-Python 0.24 requires Python 3.7 or higher For more complete instructions and more advanced installation methods (e.g. for the latest development version), see the `installation guide`_. Get the latest code ^^^^^^^^^^^^^^^^^^^ To install the latest version of the code using pip_ open a terminal and type: $ pip install -U https://github.com/mne-tools/mne-python/archive/main.zip To get the latest code using `git `__, open a terminal and type: $ git clone https://github.com/mne-tools/mne-python.git Alternatively, you can also download a `zip file of the latest development version `__. Dependencies ^^^^^^^^^^^^ The minimum required dependencies to run MNE-Python are: - Python >= 3.7 - NumPy >= 1.18.1 - SciPy >= 1.4.1 - Matplotlib >= 3.1.0 - pooch >= 1.5 - tqdm - Jinja2 - decorator For full functionality, some functions require: - Scikit-learn >= 0.22.0 - joblib >= 0.15 (for parallelization control) - Numba >= 0.48.0 - NiBabel >= 2.5.0 - OpenMEEG >= 2.5.5 - Pandas >= 1.0.0 - Picard >= 0.3 - CuPy >= 7.1.1 (for NVIDIA CUDA acceleration) - DIPY >= 1.1.0 - Imageio >= 2.6.1 - PyVista >= 0.32 - pyvistaqt >= 0.4 - mffpy >= 0.5.7 - h5py - h5io - pymatreader Contributing to MNE-Python ^^^^^^^^^^^^^^^^^^^^^^^^^^ Please see the documentation on the MNE-Python homepage: https://mne.tools/dev/install/contributing.html Forum ^^^^^^ https://mne.discourse.group Licensing ^^^^^^^^^ MNE-Python is **BSD-licenced** (BSD-3-Clause): This software is OSI Certified Open Source Software. OSI Certified is a certification mark of the Open Source Initiative. Copyright (c) 2011-2022, authors of MNE-Python. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the names of MNE-Python authors nor the names of any contributors may be used to endorse or promote products derived from this software without specific prior written permission. **This software is provided by the copyright holders and contributors "as is" and any express or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed. In no event shall the copyright owner or contributors be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in contract, strict liability, or tort (including negligence or otherwise) arising in any way out of the use of this software, even if advised of the possibility of such damage.** %package -n python3-mne Summary: MNE-Python project for MEG and EEG data analysis. Provides: python-mne BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-mne `MNE-Python software`_ is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, and statistics. Documentation ^^^^^^^^^^^^^ `MNE documentation`_ for MNE-Python is available online. Installing MNE-Python ^^^^^^^^^^^^^^^^^^^^^ To install the latest stable version of MNE-Python, you can use pip_ in a terminal: $ pip install -U mne - MNE-Python 0.17 was the last release to support Python 2.7 - MNE-Python 0.18 requires Python 3.5 or higher - MNE-Python 0.21 requires Python 3.6 or higher - MNE-Python 0.24 requires Python 3.7 or higher For more complete instructions and more advanced installation methods (e.g. for the latest development version), see the `installation guide`_. Get the latest code ^^^^^^^^^^^^^^^^^^^ To install the latest version of the code using pip_ open a terminal and type: $ pip install -U https://github.com/mne-tools/mne-python/archive/main.zip To get the latest code using `git `__, open a terminal and type: $ git clone https://github.com/mne-tools/mne-python.git Alternatively, you can also download a `zip file of the latest development version `__. Dependencies ^^^^^^^^^^^^ The minimum required dependencies to run MNE-Python are: - Python >= 3.7 - NumPy >= 1.18.1 - SciPy >= 1.4.1 - Matplotlib >= 3.1.0 - pooch >= 1.5 - tqdm - Jinja2 - decorator For full functionality, some functions require: - Scikit-learn >= 0.22.0 - joblib >= 0.15 (for parallelization control) - Numba >= 0.48.0 - NiBabel >= 2.5.0 - OpenMEEG >= 2.5.5 - Pandas >= 1.0.0 - Picard >= 0.3 - CuPy >= 7.1.1 (for NVIDIA CUDA acceleration) - DIPY >= 1.1.0 - Imageio >= 2.6.1 - PyVista >= 0.32 - pyvistaqt >= 0.4 - mffpy >= 0.5.7 - h5py - h5io - pymatreader Contributing to MNE-Python ^^^^^^^^^^^^^^^^^^^^^^^^^^ Please see the documentation on the MNE-Python homepage: https://mne.tools/dev/install/contributing.html Forum ^^^^^^ https://mne.discourse.group Licensing ^^^^^^^^^ MNE-Python is **BSD-licenced** (BSD-3-Clause): This software is OSI Certified Open Source Software. OSI Certified is a certification mark of the Open Source Initiative. Copyright (c) 2011-2022, authors of MNE-Python. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the names of MNE-Python authors nor the names of any contributors may be used to endorse or promote products derived from this software without specific prior written permission. **This software is provided by the copyright holders and contributors "as is" and any express or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed. In no event shall the copyright owner or contributors be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in contract, strict liability, or tort (including negligence or otherwise) arising in any way out of the use of this software, even if advised of the possibility of such damage.** %package help Summary: Development documents and examples for mne Provides: python3-mne-doc %description help `MNE-Python software`_ is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, and statistics. Documentation ^^^^^^^^^^^^^ `MNE documentation`_ for MNE-Python is available online. Installing MNE-Python ^^^^^^^^^^^^^^^^^^^^^ To install the latest stable version of MNE-Python, you can use pip_ in a terminal: $ pip install -U mne - MNE-Python 0.17 was the last release to support Python 2.7 - MNE-Python 0.18 requires Python 3.5 or higher - MNE-Python 0.21 requires Python 3.6 or higher - MNE-Python 0.24 requires Python 3.7 or higher For more complete instructions and more advanced installation methods (e.g. for the latest development version), see the `installation guide`_. Get the latest code ^^^^^^^^^^^^^^^^^^^ To install the latest version of the code using pip_ open a terminal and type: $ pip install -U https://github.com/mne-tools/mne-python/archive/main.zip To get the latest code using `git `__, open a terminal and type: $ git clone https://github.com/mne-tools/mne-python.git Alternatively, you can also download a `zip file of the latest development version `__. Dependencies ^^^^^^^^^^^^ The minimum required dependencies to run MNE-Python are: - Python >= 3.7 - NumPy >= 1.18.1 - SciPy >= 1.4.1 - Matplotlib >= 3.1.0 - pooch >= 1.5 - tqdm - Jinja2 - decorator For full functionality, some functions require: - Scikit-learn >= 0.22.0 - joblib >= 0.15 (for parallelization control) - Numba >= 0.48.0 - NiBabel >= 2.5.0 - OpenMEEG >= 2.5.5 - Pandas >= 1.0.0 - Picard >= 0.3 - CuPy >= 7.1.1 (for NVIDIA CUDA acceleration) - DIPY >= 1.1.0 - Imageio >= 2.6.1 - PyVista >= 0.32 - pyvistaqt >= 0.4 - mffpy >= 0.5.7 - h5py - h5io - pymatreader Contributing to MNE-Python ^^^^^^^^^^^^^^^^^^^^^^^^^^ Please see the documentation on the MNE-Python homepage: https://mne.tools/dev/install/contributing.html Forum ^^^^^^ https://mne.discourse.group Licensing ^^^^^^^^^ MNE-Python is **BSD-licenced** (BSD-3-Clause): This software is OSI Certified Open Source Software. OSI Certified is a certification mark of the Open Source Initiative. Copyright (c) 2011-2022, authors of MNE-Python. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the names of MNE-Python authors nor the names of any contributors may be used to endorse or promote products derived from this software without specific prior written permission. **This software is provided by the copyright holders and contributors "as is" and any express or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed. In no event shall the copyright owner or contributors be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in contract, strict liability, or tort (including negligence or otherwise) arising in any way out of the use of this software, even if advised of the possibility of such damage.** %prep %autosetup -n mne-1.3.1 %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-mne -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri Apr 21 2023 Python_Bot - 1.3.1-1 - Package Spec generated