%global _empty_manifest_terminate_build 0 Name: python-eslearn Version: 1.1.8 Release: 1 Summary: This project is designed for machine learning in resting-state fMRI field License: MIT License URL: https://github.com/easylearn-fmri/ Source0: https://mirrors.aliyun.com/pypi/web/packages/da/4d/89928a9a4f6b425cbedbe4a58ec8634bc4ce8f990e98f9dba72d8c1a5185/eslearn-1.1.8.tar.gz BuildArch: noarch Requires: python3-imbalanced-learn Requires: python3-joblib Requires: python3-requests Requires: python3-matplotlib Requires: python3-nibabel Requires: python3-openpyxl Requires: python3-xlrd Requires: python3-pandas Requires: python3-PyQt5 Requires: python3-PyQt5-sip Requires: python3-dateutil Requires: python3-scikit-learn Requires: python3-numpy Requires: python3-scipy Requires: python3-seaborn Requires: python3-progressbar Requires: python3-netron %description Easylearn is designed for machine learning mainly in resting-state fMRI, radiomics and other fields (such as EEG). Easylearn is built on top of scikit-learn, pytorch and other packages. Easylearn can assist doctors and researchers who have limited coding experience to easily realize machine learning, e.g., (MR/CT/PET/EEG)imaging-marker- or other biomarker-based disease diagnosis and prediction, treatment response prediction, disease subtyping, dimensional decoding for transdiagnostic psychiatric diseases or other diseases, disease mechanism exploration and etc. We focus on machine learning rather than data preprocessing. Many software, such as SPM, GRETNA, DPABI, REST, RESTPlus, CCS, FSL, Freesufer, nipy, nipype, nibabel, fmriprep and etc, can be used for data preprocessing. # Citing information: If you think this software (or some function) is useful, citing the easylearn software in your paper or code would be greatly appreciated! Citing link: https://github.com/lichao312214129/easylearn # Install ``` pip install -U eslearn ``` # Usage ``` import eslearn as el el.run() ``` # Development We hope you can join us! > Email: lichao19870617@gmail.com > Wechat: 13591648206 # Supervisors/Consultants ##### Ke Xu kexu@vip.sina.com Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. Department of Radiology, The First Affiliated Hospital of China Medical University. ##### Yanqing Tang yanqingtang@163.com 1 Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. 2 Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. ##### Yong He yong.he@bnu.edu.cn 1 National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China 2 Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China 3 IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China # Maintainers ##### Chao Li lichao19870617@gmail.com Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. ##### Mengshi Dong dongmengshi1990@163.com Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. %package -n python3-eslearn Summary: This project is designed for machine learning in resting-state fMRI field Provides: python-eslearn BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-eslearn Easylearn is designed for machine learning mainly in resting-state fMRI, radiomics and other fields (such as EEG). Easylearn is built on top of scikit-learn, pytorch and other packages. Easylearn can assist doctors and researchers who have limited coding experience to easily realize machine learning, e.g., (MR/CT/PET/EEG)imaging-marker- or other biomarker-based disease diagnosis and prediction, treatment response prediction, disease subtyping, dimensional decoding for transdiagnostic psychiatric diseases or other diseases, disease mechanism exploration and etc. We focus on machine learning rather than data preprocessing. Many software, such as SPM, GRETNA, DPABI, REST, RESTPlus, CCS, FSL, Freesufer, nipy, nipype, nibabel, fmriprep and etc, can be used for data preprocessing. # Citing information: If you think this software (or some function) is useful, citing the easylearn software in your paper or code would be greatly appreciated! Citing link: https://github.com/lichao312214129/easylearn # Install ``` pip install -U eslearn ``` # Usage ``` import eslearn as el el.run() ``` # Development We hope you can join us! > Email: lichao19870617@gmail.com > Wechat: 13591648206 # Supervisors/Consultants ##### Ke Xu kexu@vip.sina.com Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. Department of Radiology, The First Affiliated Hospital of China Medical University. ##### Yanqing Tang yanqingtang@163.com 1 Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. 2 Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. ##### Yong He yong.he@bnu.edu.cn 1 National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China 2 Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China 3 IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China # Maintainers ##### Chao Li lichao19870617@gmail.com Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. ##### Mengshi Dong dongmengshi1990@163.com Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. %package help Summary: Development documents and examples for eslearn Provides: python3-eslearn-doc %description help Easylearn is designed for machine learning mainly in resting-state fMRI, radiomics and other fields (such as EEG). Easylearn is built on top of scikit-learn, pytorch and other packages. Easylearn can assist doctors and researchers who have limited coding experience to easily realize machine learning, e.g., (MR/CT/PET/EEG)imaging-marker- or other biomarker-based disease diagnosis and prediction, treatment response prediction, disease subtyping, dimensional decoding for transdiagnostic psychiatric diseases or other diseases, disease mechanism exploration and etc. We focus on machine learning rather than data preprocessing. Many software, such as SPM, GRETNA, DPABI, REST, RESTPlus, CCS, FSL, Freesufer, nipy, nipype, nibabel, fmriprep and etc, can be used for data preprocessing. # Citing information: If you think this software (or some function) is useful, citing the easylearn software in your paper or code would be greatly appreciated! Citing link: https://github.com/lichao312214129/easylearn # Install ``` pip install -U eslearn ``` # Usage ``` import eslearn as el el.run() ``` # Development We hope you can join us! > Email: lichao19870617@gmail.com > Wechat: 13591648206 # Supervisors/Consultants ##### Ke Xu kexu@vip.sina.com Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. Department of Radiology, The First Affiliated Hospital of China Medical University. ##### Yanqing Tang yanqingtang@163.com 1 Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. 2 Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. ##### Yong He yong.he@bnu.edu.cn 1 National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China 2 Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China 3 IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China # Maintainers ##### Chao Li lichao19870617@gmail.com Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. ##### Mengshi Dong dongmengshi1990@163.com Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China. %prep %autosetup -n eslearn-1.1.8 %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-eslearn -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri Jun 09 2023 Python_Bot - 1.1.8-1 - Package Spec generated