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@@ -0,0 +1 @@ +/neurora-1.1.6.9.tar.gz diff --git a/python-neurora.spec b/python-neurora.spec new file mode 100644 index 0000000..551da4e --- /dev/null +++ b/python-neurora.spec @@ -0,0 +1,311 @@ +%global _empty_manifest_terminate_build 0 +Name: python-neurora +Version: 1.1.6.9 +Release: 1 +Summary: A Python Toolbox for Multimodal Neural Data Representation Analysis +License: MIT License +URL: https://github.com/ZitongLu1996/NeuroRA +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/f0/2a/8e345b2b0e998a314e8e29f597624409d4df745e93b73ffe2c400a28be6e/neurora-1.1.6.9.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-scipy +Requires: python3-mne +Requires: python3-nibabel +Requires: python3-matplotlib +Requires: python3-nilearn +Requires: python3-scikit-learn +Requires: python3-scikit-image + +%description + + +#NeuroRA + +**A Python Toolbox of Representational Analysis from Multimodal Neural Data** + +## Overview +**Representational Similarity Analysis (RSA)** has become a popular and effective method to measure the representation of multivariable neural activity in different modes. + +**NeuroRA** is an easy-to-use toolbox based on **Python**, which can do some works about **RSA** among nearly all kinds of neural data, including **behavioral, EEG, MEG, fNIRS, sEEG, ECoG, fMRI and some other neuroelectrophysiological data**. +In addition, users can do **Neural Pattern Similarity (NPS)**, **Spatiotemporal Pattern Similarity (STPS)**, **Inter-Subject Correlation (ISC)**, **Classification-based EEG Decoding** and **a novel cross-temporal RSA (CTRSA)** on **NeuroRA**. + +## Installation +> pip install neurora + +## Paper + +Lu, Z., & Ku, Y. (2020). NeuroRA: A Python toolbox of representational analysis from multi-modal neural data. Frontiers in Neuroinformatics. 14:563669. doi: 10.3389/fninf.2020.563669 + +## Website & How to use +See more details at the [NeuroRA website](https://zitonglu1996.github.io/NeuroRA/). + +You can read the [Documentation here](https://neurora.github.io/documentation/index.html) or download the [Tutorial here](https://zitonglu1996.github.io/NeuroRA/neurora/Tutorial.pdf) to know how to use NeuroRA. + +## Required Dependencies: + +- **[Numpy](http://www.numpy.org)**: a fundamental package for scientific computing. +- **[SciPy](https://www.scipy.org/scipylib/index.html)**: a package that provides many user-friendly and efficient numerical routines. +- **[Scikit-learn](https://scikit-learn.org/stable/#)**: a Python module for machine learning. +- **[Matplotlib](https://matplotlib.org)**: a Python 2D plotting library. +- **[NiBabel](https://nipy.org/nibabel/)**: a package prividing read +/- write access to some common medical and neuroimaging file formats. +- **[Nilearn](https://nilearn.github.io/)**: a Python module for fast and easy statistical learning on NeuroImaging data. +- **[MNE-Python](https://mne.tools/)**: a Python software for exploring, visualizing, and analyzing human neurophysiological data. + +## Features + +- Calculate the Neural Pattern Similarity (NPS) + +- Calculate the Spatiotemporal Neural Pattern Similarity (STPS) + +- Calculate the Inter-Subject Correlation (ISC) + +- Calculate the Representational Dissimilarity Matrix (RDM) + +- Calculate the Cross-Temporal RDM (RDM) + +- Calculate the Representational Similarity based on RDMs + +- One-Step Realize Representational Similarity Analysis (RSA) + +- Conduct Cross-Temporal RSA (CTRSA) + +- Conduct Classification-based EEG decoding + +- Conduct Statistical Analysis + +- Save the RSA result as a NIfTI file for fMRI + +- Plot the results + +## Demos +There are several demos for NeuroRA, and you can see them in /demos/.. path (both .py files and .ipynb files are provided). + +| | Run the Demo | View the Demo | +| - | --- | ---- | +| Demo 1 | [](https://colab.research.google.com/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo1_colab.ipynb) | [](https://nbviewer.jupyter.org/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo1.ipynb) | +| Demo 2 | [](https://colab.research.google.com/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo2_colab.ipynb) | [](https://nbviewer.jupyter.org/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo2.ipynb) | +| Demo 3 | [](https://colab.research.google.com/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo3_colab.ipynb) | [](https://nbviewer.jupyter.org/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo3.ipynb) | + +## About NeuroRA +**Noteworthily**, this toolbox is currently only a **test version**. +If you have any question, find some bugs or have some useful suggestions while using, you can email me and I will be happy and thankful to know. +>My email address: +>zitonglu1996@gmail.com / zitonglu@outlook.com + +>My personal homepage: +>https://zitonglu1996.github.io + + +%package -n python3-neurora +Summary: A Python Toolbox for Multimodal Neural Data Representation Analysis +Provides: python-neurora +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-neurora + + +#NeuroRA + +**A Python Toolbox of Representational Analysis from Multimodal Neural Data** + +## Overview +**Representational Similarity Analysis (RSA)** has become a popular and effective method to measure the representation of multivariable neural activity in different modes. + +**NeuroRA** is an easy-to-use toolbox based on **Python**, which can do some works about **RSA** among nearly all kinds of neural data, including **behavioral, EEG, MEG, fNIRS, sEEG, ECoG, fMRI and some other neuroelectrophysiological data**. +In addition, users can do **Neural Pattern Similarity (NPS)**, **Spatiotemporal Pattern Similarity (STPS)**, **Inter-Subject Correlation (ISC)**, **Classification-based EEG Decoding** and **a novel cross-temporal RSA (CTRSA)** on **NeuroRA**. + +## Installation +> pip install neurora + +## Paper + +Lu, Z., & Ku, Y. (2020). NeuroRA: A Python toolbox of representational analysis from multi-modal neural data. Frontiers in Neuroinformatics. 14:563669. doi: 10.3389/fninf.2020.563669 + +## Website & How to use +See more details at the [NeuroRA website](https://zitonglu1996.github.io/NeuroRA/). + +You can read the [Documentation here](https://neurora.github.io/documentation/index.html) or download the [Tutorial here](https://zitonglu1996.github.io/NeuroRA/neurora/Tutorial.pdf) to know how to use NeuroRA. + +## Required Dependencies: + +- **[Numpy](http://www.numpy.org)**: a fundamental package for scientific computing. +- **[SciPy](https://www.scipy.org/scipylib/index.html)**: a package that provides many user-friendly and efficient numerical routines. +- **[Scikit-learn](https://scikit-learn.org/stable/#)**: a Python module for machine learning. +- **[Matplotlib](https://matplotlib.org)**: a Python 2D plotting library. +- **[NiBabel](https://nipy.org/nibabel/)**: a package prividing read +/- write access to some common medical and neuroimaging file formats. +- **[Nilearn](https://nilearn.github.io/)**: a Python module for fast and easy statistical learning on NeuroImaging data. +- **[MNE-Python](https://mne.tools/)**: a Python software for exploring, visualizing, and analyzing human neurophysiological data. + +## Features + +- Calculate the Neural Pattern Similarity (NPS) + +- Calculate the Spatiotemporal Neural Pattern Similarity (STPS) + +- Calculate the Inter-Subject Correlation (ISC) + +- Calculate the Representational Dissimilarity Matrix (RDM) + +- Calculate the Cross-Temporal RDM (RDM) + +- Calculate the Representational Similarity based on RDMs + +- One-Step Realize Representational Similarity Analysis (RSA) + +- Conduct Cross-Temporal RSA (CTRSA) + +- Conduct Classification-based EEG decoding + +- Conduct Statistical Analysis + +- Save the RSA result as a NIfTI file for fMRI + +- Plot the results + +## Demos +There are several demos for NeuroRA, and you can see them in /demos/.. path (both .py files and .ipynb files are provided). + +| | Run the Demo | View the Demo | +| - | --- | ---- | +| Demo 1 | [](https://colab.research.google.com/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo1_colab.ipynb) | [](https://nbviewer.jupyter.org/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo1.ipynb) | +| Demo 2 | [](https://colab.research.google.com/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo2_colab.ipynb) | [](https://nbviewer.jupyter.org/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo2.ipynb) | +| Demo 3 | [](https://colab.research.google.com/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo3_colab.ipynb) | [](https://nbviewer.jupyter.org/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo3.ipynb) | + +## About NeuroRA +**Noteworthily**, this toolbox is currently only a **test version**. +If you have any question, find some bugs or have some useful suggestions while using, you can email me and I will be happy and thankful to know. +>My email address: +>zitonglu1996@gmail.com / zitonglu@outlook.com + +>My personal homepage: +>https://zitonglu1996.github.io + + +%package help +Summary: Development documents and examples for neurora +Provides: python3-neurora-doc +%description help + + +#NeuroRA + +**A Python Toolbox of Representational Analysis from Multimodal Neural Data** + +## Overview +**Representational Similarity Analysis (RSA)** has become a popular and effective method to measure the representation of multivariable neural activity in different modes. + +**NeuroRA** is an easy-to-use toolbox based on **Python**, which can do some works about **RSA** among nearly all kinds of neural data, including **behavioral, EEG, MEG, fNIRS, sEEG, ECoG, fMRI and some other neuroelectrophysiological data**. +In addition, users can do **Neural Pattern Similarity (NPS)**, **Spatiotemporal Pattern Similarity (STPS)**, **Inter-Subject Correlation (ISC)**, **Classification-based EEG Decoding** and **a novel cross-temporal RSA (CTRSA)** on **NeuroRA**. + +## Installation +> pip install neurora + +## Paper + +Lu, Z., & Ku, Y. (2020). NeuroRA: A Python toolbox of representational analysis from multi-modal neural data. Frontiers in Neuroinformatics. 14:563669. doi: 10.3389/fninf.2020.563669 + +## Website & How to use +See more details at the [NeuroRA website](https://zitonglu1996.github.io/NeuroRA/). + +You can read the [Documentation here](https://neurora.github.io/documentation/index.html) or download the [Tutorial here](https://zitonglu1996.github.io/NeuroRA/neurora/Tutorial.pdf) to know how to use NeuroRA. + +## Required Dependencies: + +- **[Numpy](http://www.numpy.org)**: a fundamental package for scientific computing. +- **[SciPy](https://www.scipy.org/scipylib/index.html)**: a package that provides many user-friendly and efficient numerical routines. +- **[Scikit-learn](https://scikit-learn.org/stable/#)**: a Python module for machine learning. +- **[Matplotlib](https://matplotlib.org)**: a Python 2D plotting library. +- **[NiBabel](https://nipy.org/nibabel/)**: a package prividing read +/- write access to some common medical and neuroimaging file formats. +- **[Nilearn](https://nilearn.github.io/)**: a Python module for fast and easy statistical learning on NeuroImaging data. +- **[MNE-Python](https://mne.tools/)**: a Python software for exploring, visualizing, and analyzing human neurophysiological data. + +## Features + +- Calculate the Neural Pattern Similarity (NPS) + +- Calculate the Spatiotemporal Neural Pattern Similarity (STPS) + +- Calculate the Inter-Subject Correlation (ISC) + +- Calculate the Representational Dissimilarity Matrix (RDM) + +- Calculate the Cross-Temporal RDM (RDM) + +- Calculate the Representational Similarity based on RDMs + +- One-Step Realize Representational Similarity Analysis (RSA) + +- Conduct Cross-Temporal RSA (CTRSA) + +- Conduct Classification-based EEG decoding + +- Conduct Statistical Analysis + +- Save the RSA result as a NIfTI file for fMRI + +- Plot the results + +## Demos +There are several demos for NeuroRA, and you can see them in /demos/.. path (both .py files and .ipynb files are provided). + +| | Run the Demo | View the Demo | +| - | --- | ---- | +| Demo 1 | [](https://colab.research.google.com/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo1_colab.ipynb) | [](https://nbviewer.jupyter.org/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo1.ipynb) | +| Demo 2 | [](https://colab.research.google.com/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo2_colab.ipynb) | [](https://nbviewer.jupyter.org/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo2.ipynb) | +| Demo 3 | [](https://colab.research.google.com/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo3_colab.ipynb) | [](https://nbviewer.jupyter.org/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo3.ipynb) | + +## About NeuroRA +**Noteworthily**, this toolbox is currently only a **test version**. +If you have any question, find some bugs or have some useful suggestions while using, you can email me and I will be happy and thankful to know. +>My email address: +>zitonglu1996@gmail.com / zitonglu@outlook.com + +>My personal homepage: +>https://zitonglu1996.github.io + + +%prep +%autosetup -n neurora-1.1.6.9 + +%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-neurora -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.6.9-1 +- Package Spec generated @@ -0,0 +1 @@ +7cd7b4e96ed110783c545a7ab4638fdf neurora-1.1.6.9.tar.gz |