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|
%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 <Python_Bot@openeuler.org> - 1.1.8-1
- Package Spec generated
|
