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+/pyradiomics-3.0.1.tar.gz
diff --git a/python-pyradiomics.spec b/python-pyradiomics.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-pyradiomics
+Version:	3.0.1
+Release:	1
+Summary:	Radiomics features library for python
+License:	BSD License
+URL:		http://github.com/Radiomics/pyradiomics#readme
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/1b/35/c7f7fb7affd302fd8107dcee6b6e7aaf3708b75ad69d5f9a3dfcadb73eaa/pyradiomics-3.0.1.tar.gz
+
+Requires:	python3-numpy
+Requires:	python3-SimpleITK
+Requires:	python3-PyWavelets
+Requires:	python3-pykwalify
+Requires:	python3-six
+
+%description
+# pyradiomics v3.0.1
+
+## Build Status
+
+| Linux                          | macOS                         | Windows                       |
+|--------------------------------|-------------------------------|-------------------------------|
+| [![][circleci]][circleci-lnk]  | [![][travisci]][travisci-lnk] | [![][appveyor]][appveyor-lnk] |
+
+
+[appveyor]: https://ci.appveyor.com/api/projects/status/tw69xbbeyluk7fl7/branch/master?svg=true
+[appveyor-lnk]: https://ci.appveyor.com/project/Radiomics/pyradiomics/branch/master
+
+[circleci]: https://circleci.com/gh/Radiomics/pyradiomics.svg?style=svg&circle-token=a4748cf0de5fad2c12bc93a485282378551c3584
+[circleci-lnk]: https://circleci.com/gh/Radiomics/pyradiomics
+
+[travisci]: https://travis-ci.org/Radiomics/pyradiomics.svg?branch=master
+[travisci-lnk]: https://travis-ci.org/Radiomics/pyradiomics
+
+## Radiomics feature extraction in Python
+This is an open-source python package for the extraction of Radiomics features from medical imaging.
+
+With this package we aim to establish a reference standard for Radiomic Analysis, and provide a tested and maintained
+open-source platform for easy and reproducible Radiomic Feature extraction. By doing so, we hope to increase awareness
+of radiomic capabilities and expand the community.
+
+The platform supports both the feature extraction in 2D and 3D and can be used to calculate single values per feature
+for a region of interest ("segment-based") or to generate feature maps ("voxel-based"). 
+
+**Not intended for clinical use.**
+
+**If you publish any work which uses this package, please cite the following publication:**
+*van Griethuysen, J. J. M., Fedorov, A., Parmar, C., Hosny, A., Aucoin, N., Narayan, V., Beets-Tan, R. G. H.,
+Fillion-Robin, J. C., Pieper, S.,  Aerts, H. J. W. L. (2017). Computational Radiomics System to Decode the Radiographic
+Phenotype. Cancer Research, 77(21), e104–e107. https://doi.org/10.1158/0008-5472.CAN-17-0339*
+
+### Join the Community!
+Join the PyRadiomics community on google groups [here](https://groups.google.com/forum/#!forum/pyradiomics).
+
+### Feature Classes
+Currently supports the following feature classes:
+
+ - First Order Statistics
+ - Shape-based (2D and 3D)
+ - Gray Level Cooccurence Matrix (GLCM)
+ - Gray Level Run Length Matrix (GLRLM)
+ - Gray Level Size Zone Matrix (GLSZM)
+ - Gray Level Dependece Matrix (GLDM)
+ - Neighboring Gray Tone Difference Matrix (NGTDM)
+
+### Filter Classes
+Aside from the feature classes, there are also some built-in optional filters:
+
+- Laplacian of Gaussian (LoG, based on SimpleITK functionality)
+- Wavelet (using the PyWavelets package)
+- Square
+- Square Root
+- Logarithm
+- Exponential
+- Gradient (Magnitude)
+- Local Binary Pattern (LBP) 2D / 3D
+
+### Supporting reproducible extraction
+Aside from calculating features, the pyradiomics package includes provenance information in the
+output. This information contains information on used image and mask, as well as applied settings
+and filters, thereby enabling fully reproducible feature extraction.
+
+### Documentation
+For more information, see the sphinx generated documentation available [here](http://pyradiomics.readthedocs.io/).
+
+Alternatively, you can generate the documentation by checking out the master branch and running from the root directory:
+
+    python setup.py build_sphinx
+
+The documentation can then be viewed in a browser by opening `PACKAGE_ROOT\build\sphinx\html\index.html`. 
+
+Furthermore, an instruction video is available [here](http://radiomics.io/pyradiomics.html).
+
+### Installation
+PyRadiomics is OS independent and compatible with Python >= 3.5. Pre-built binaries are available on
+PyPi and Conda. To install PyRadiomics, ensure you have python
+installed and run:
+
+    `python -m pip install pyradiomics`
+
+Detailed installation instructions, as well as instructions for building PyRadiomics from source, are available in the 
+[documentation](http://pyradiomics.readthedocs.io/en/latest/installation.html).
+
+### Docker
+PyRadiomics also supports [Dockers](https://www.docker.com/).  Currently, 2 dockers are available:
+
+The first one is a [Jupyter notebook](http://jupyter.org/) with PyRadiomics pre-installed with example Notebooks. 
+
+To get the Docker:
+
+    docker pull radiomics/pyradiomics:latest
+
+The `radiomics/notebook` Docker has an exposed volume (`/data`) that can be mapped to the host system directory.  For example, to mount the current directory:
+
+    docker run --rm -it --publish 8888:8888 -v `pwd`:/data radiomics/notebook
+
+or for a less secure notebook, skip the randomly generated token
+
+    docker run --rm -it --publish 8888:8888 -v `pwd`:/data radiomics/notebook start-notebook.sh --NotebookApp.token=''
+
+and open the local webpage at http://localhost:8888/ with the current directory at http://localhost:8888/tree/data.
+
+The second is a docker which exposes the PyRadiomics CLI interface. To get the CLI-Docker:
+
+    docker pull radiomics/pyradiomics:CLI
+
+You can then use the PyRadiomics CLI as follows:
+
+    docker run radiomics/pyradiomics:CLI --help
+
+For more information on using docker, see
+[here](https://pyradiomics.readthedocs.io/en/latest/installation.html#use-pyradiomics-docker)
+
+### Usage
+PyRadiomics can be easily used in a Python script through the `featureextractor`
+module. Furthermore, PyRadiomics provides a commandline script, `pyradiomics`, for both single image extraction and 
+batchprocessing. Finally, a convenient front-end interface is provided as the 'Radiomics'
+extension for 3D Slicer, available [here](https://github.com/Radiomics/SlicerRadiomics).
+
+### 3rd-party packages used in pyradiomics:
+ - SimpleITK (Image loading and preprocessing)
+ - numpy (Feature calculation)
+ - PyWavelets (Wavelet filter)
+ - pykwalify (Enabling yaml parameters file checking)
+ - six (Python 3 Compatibility)
+ - scipy (Only for LBP filter, install separately to enable this filter)
+ - scikit-image (Only for LBP filter, install separately to enable this filter)
+ - trimesh (Only for LBP filter, install separately to enable this filter)
+
+See also the [requirements file](requirements.txt).
+
+### 3D Slicer
+PyRadiomics is also available as an [extension](https://github.com/Radiomics/SlicerRadiomics) to [3D Slicer](slicer.org). 
+Download and install the 3D slicer [nightly build](http://download.slicer.org/), the extension is then available in the
+extension manager under "SlicerRadiomics".
+
+### License
+This package is covered by the open source [3-clause BSD License](LICENSE.txt).
+
+### Developers
+ - [Joost van Griethuysen](https://github.com/JoostJM)<sup>1,3,4</sup>
+ - [Andriy Fedorov](https://github.com/fedorov)<sup>2</sup>
+ - [Nicole Aucoin](https://github.com/naucoin)<sup>2</sup>
+ - [Jean-Christophe Fillion-Robin](https://github.com/jcfr)<sup>5</sup>
+ - [Ahmed Hosny](https://github.com/ahmedhosny)<sup>1</sup>
+ - [Steve Pieper](https://github.com/pieper)<sup>6</sup>
+ - [Hugo Aerts (PI)](https://github.com/hugoaerts)<sup>1,2</sup>
+
+<sup>1</sup>Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA,
+<sup>2</sup>Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA,
+<sup>3</sup>Department of Radiology, Netherlands Cancer Institute, Amsterdam, The Netherlands, 
+<sup>4</sup>GROW-School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands,
+<sup>5</sup>Kitware,
+<sup>6</sup>Isomics
+
+### Contact
+We are happy to help you with any questions. Please contact us on the [Radiomics community section of the 3D Slicer Discourse](https://discourse.slicer.org/c/community/radiomics/23).
+
+We welcome contributions to PyRadiomics. Please read the [contributing guidelines](CONTRIBUTING.rst) on how to
+contribute to PyRadiomics.
+
+**This work was supported in part by the US National Cancer Institute grant 
+5U24CA194354, QUANTITATIVE RADIOMICS SYSTEM DECODING THE TUMOR PHENOTYPE.**
+
+
+
+
+%package -n python3-pyradiomics
+Summary:	Radiomics features library for python
+Provides:	python-pyradiomics
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+BuildRequires:	python3-cffi
+BuildRequires:	gcc
+BuildRequires:	gdb
+%description -n python3-pyradiomics
+# pyradiomics v3.0.1
+
+## Build Status
+
+| Linux                          | macOS                         | Windows                       |
+|--------------------------------|-------------------------------|-------------------------------|
+| [![][circleci]][circleci-lnk]  | [![][travisci]][travisci-lnk] | [![][appveyor]][appveyor-lnk] |
+
+
+[appveyor]: https://ci.appveyor.com/api/projects/status/tw69xbbeyluk7fl7/branch/master?svg=true
+[appveyor-lnk]: https://ci.appveyor.com/project/Radiomics/pyradiomics/branch/master
+
+[circleci]: https://circleci.com/gh/Radiomics/pyradiomics.svg?style=svg&circle-token=a4748cf0de5fad2c12bc93a485282378551c3584
+[circleci-lnk]: https://circleci.com/gh/Radiomics/pyradiomics
+
+[travisci]: https://travis-ci.org/Radiomics/pyradiomics.svg?branch=master
+[travisci-lnk]: https://travis-ci.org/Radiomics/pyradiomics
+
+## Radiomics feature extraction in Python
+This is an open-source python package for the extraction of Radiomics features from medical imaging.
+
+With this package we aim to establish a reference standard for Radiomic Analysis, and provide a tested and maintained
+open-source platform for easy and reproducible Radiomic Feature extraction. By doing so, we hope to increase awareness
+of radiomic capabilities and expand the community.
+
+The platform supports both the feature extraction in 2D and 3D and can be used to calculate single values per feature
+for a region of interest ("segment-based") or to generate feature maps ("voxel-based"). 
+
+**Not intended for clinical use.**
+
+**If you publish any work which uses this package, please cite the following publication:**
+*van Griethuysen, J. J. M., Fedorov, A., Parmar, C., Hosny, A., Aucoin, N., Narayan, V., Beets-Tan, R. G. H.,
+Fillion-Robin, J. C., Pieper, S.,  Aerts, H. J. W. L. (2017). Computational Radiomics System to Decode the Radiographic
+Phenotype. Cancer Research, 77(21), e104–e107. https://doi.org/10.1158/0008-5472.CAN-17-0339*
+
+### Join the Community!
+Join the PyRadiomics community on google groups [here](https://groups.google.com/forum/#!forum/pyradiomics).
+
+### Feature Classes
+Currently supports the following feature classes:
+
+ - First Order Statistics
+ - Shape-based (2D and 3D)
+ - Gray Level Cooccurence Matrix (GLCM)
+ - Gray Level Run Length Matrix (GLRLM)
+ - Gray Level Size Zone Matrix (GLSZM)
+ - Gray Level Dependece Matrix (GLDM)
+ - Neighboring Gray Tone Difference Matrix (NGTDM)
+
+### Filter Classes
+Aside from the feature classes, there are also some built-in optional filters:
+
+- Laplacian of Gaussian (LoG, based on SimpleITK functionality)
+- Wavelet (using the PyWavelets package)
+- Square
+- Square Root
+- Logarithm
+- Exponential
+- Gradient (Magnitude)
+- Local Binary Pattern (LBP) 2D / 3D
+
+### Supporting reproducible extraction
+Aside from calculating features, the pyradiomics package includes provenance information in the
+output. This information contains information on used image and mask, as well as applied settings
+and filters, thereby enabling fully reproducible feature extraction.
+
+### Documentation
+For more information, see the sphinx generated documentation available [here](http://pyradiomics.readthedocs.io/).
+
+Alternatively, you can generate the documentation by checking out the master branch and running from the root directory:
+
+    python setup.py build_sphinx
+
+The documentation can then be viewed in a browser by opening `PACKAGE_ROOT\build\sphinx\html\index.html`. 
+
+Furthermore, an instruction video is available [here](http://radiomics.io/pyradiomics.html).
+
+### Installation
+PyRadiomics is OS independent and compatible with Python >= 3.5. Pre-built binaries are available on
+PyPi and Conda. To install PyRadiomics, ensure you have python
+installed and run:
+
+    `python -m pip install pyradiomics`
+
+Detailed installation instructions, as well as instructions for building PyRadiomics from source, are available in the 
+[documentation](http://pyradiomics.readthedocs.io/en/latest/installation.html).
+
+### Docker
+PyRadiomics also supports [Dockers](https://www.docker.com/).  Currently, 2 dockers are available:
+
+The first one is a [Jupyter notebook](http://jupyter.org/) with PyRadiomics pre-installed with example Notebooks. 
+
+To get the Docker:
+
+    docker pull radiomics/pyradiomics:latest
+
+The `radiomics/notebook` Docker has an exposed volume (`/data`) that can be mapped to the host system directory.  For example, to mount the current directory:
+
+    docker run --rm -it --publish 8888:8888 -v `pwd`:/data radiomics/notebook
+
+or for a less secure notebook, skip the randomly generated token
+
+    docker run --rm -it --publish 8888:8888 -v `pwd`:/data radiomics/notebook start-notebook.sh --NotebookApp.token=''
+
+and open the local webpage at http://localhost:8888/ with the current directory at http://localhost:8888/tree/data.
+
+The second is a docker which exposes the PyRadiomics CLI interface. To get the CLI-Docker:
+
+    docker pull radiomics/pyradiomics:CLI
+
+You can then use the PyRadiomics CLI as follows:
+
+    docker run radiomics/pyradiomics:CLI --help
+
+For more information on using docker, see
+[here](https://pyradiomics.readthedocs.io/en/latest/installation.html#use-pyradiomics-docker)
+
+### Usage
+PyRadiomics can be easily used in a Python script through the `featureextractor`
+module. Furthermore, PyRadiomics provides a commandline script, `pyradiomics`, for both single image extraction and 
+batchprocessing. Finally, a convenient front-end interface is provided as the 'Radiomics'
+extension for 3D Slicer, available [here](https://github.com/Radiomics/SlicerRadiomics).
+
+### 3rd-party packages used in pyradiomics:
+ - SimpleITK (Image loading and preprocessing)
+ - numpy (Feature calculation)
+ - PyWavelets (Wavelet filter)
+ - pykwalify (Enabling yaml parameters file checking)
+ - six (Python 3 Compatibility)
+ - scipy (Only for LBP filter, install separately to enable this filter)
+ - scikit-image (Only for LBP filter, install separately to enable this filter)
+ - trimesh (Only for LBP filter, install separately to enable this filter)
+
+See also the [requirements file](requirements.txt).
+
+### 3D Slicer
+PyRadiomics is also available as an [extension](https://github.com/Radiomics/SlicerRadiomics) to [3D Slicer](slicer.org). 
+Download and install the 3D slicer [nightly build](http://download.slicer.org/), the extension is then available in the
+extension manager under "SlicerRadiomics".
+
+### License
+This package is covered by the open source [3-clause BSD License](LICENSE.txt).
+
+### Developers
+ - [Joost van Griethuysen](https://github.com/JoostJM)<sup>1,3,4</sup>
+ - [Andriy Fedorov](https://github.com/fedorov)<sup>2</sup>
+ - [Nicole Aucoin](https://github.com/naucoin)<sup>2</sup>
+ - [Jean-Christophe Fillion-Robin](https://github.com/jcfr)<sup>5</sup>
+ - [Ahmed Hosny](https://github.com/ahmedhosny)<sup>1</sup>
+ - [Steve Pieper](https://github.com/pieper)<sup>6</sup>
+ - [Hugo Aerts (PI)](https://github.com/hugoaerts)<sup>1,2</sup>
+
+<sup>1</sup>Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA,
+<sup>2</sup>Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA,
+<sup>3</sup>Department of Radiology, Netherlands Cancer Institute, Amsterdam, The Netherlands, 
+<sup>4</sup>GROW-School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands,
+<sup>5</sup>Kitware,
+<sup>6</sup>Isomics
+
+### Contact
+We are happy to help you with any questions. Please contact us on the [Radiomics community section of the 3D Slicer Discourse](https://discourse.slicer.org/c/community/radiomics/23).
+
+We welcome contributions to PyRadiomics. Please read the [contributing guidelines](CONTRIBUTING.rst) on how to
+contribute to PyRadiomics.
+
+**This work was supported in part by the US National Cancer Institute grant 
+5U24CA194354, QUANTITATIVE RADIOMICS SYSTEM DECODING THE TUMOR PHENOTYPE.**
+
+
+
+
+%package help
+Summary:	Development documents and examples for pyradiomics
+Provides:	python3-pyradiomics-doc
+%description help
+# pyradiomics v3.0.1
+
+## Build Status
+
+| Linux                          | macOS                         | Windows                       |
+|--------------------------------|-------------------------------|-------------------------------|
+| [![][circleci]][circleci-lnk]  | [![][travisci]][travisci-lnk] | [![][appveyor]][appveyor-lnk] |
+
+
+[appveyor]: https://ci.appveyor.com/api/projects/status/tw69xbbeyluk7fl7/branch/master?svg=true
+[appveyor-lnk]: https://ci.appveyor.com/project/Radiomics/pyradiomics/branch/master
+
+[circleci]: https://circleci.com/gh/Radiomics/pyradiomics.svg?style=svg&circle-token=a4748cf0de5fad2c12bc93a485282378551c3584
+[circleci-lnk]: https://circleci.com/gh/Radiomics/pyradiomics
+
+[travisci]: https://travis-ci.org/Radiomics/pyradiomics.svg?branch=master
+[travisci-lnk]: https://travis-ci.org/Radiomics/pyradiomics
+
+## Radiomics feature extraction in Python
+This is an open-source python package for the extraction of Radiomics features from medical imaging.
+
+With this package we aim to establish a reference standard for Radiomic Analysis, and provide a tested and maintained
+open-source platform for easy and reproducible Radiomic Feature extraction. By doing so, we hope to increase awareness
+of radiomic capabilities and expand the community.
+
+The platform supports both the feature extraction in 2D and 3D and can be used to calculate single values per feature
+for a region of interest ("segment-based") or to generate feature maps ("voxel-based"). 
+
+**Not intended for clinical use.**
+
+**If you publish any work which uses this package, please cite the following publication:**
+*van Griethuysen, J. J. M., Fedorov, A., Parmar, C., Hosny, A., Aucoin, N., Narayan, V., Beets-Tan, R. G. H.,
+Fillion-Robin, J. C., Pieper, S.,  Aerts, H. J. W. L. (2017). Computational Radiomics System to Decode the Radiographic
+Phenotype. Cancer Research, 77(21), e104–e107. https://doi.org/10.1158/0008-5472.CAN-17-0339*
+
+### Join the Community!
+Join the PyRadiomics community on google groups [here](https://groups.google.com/forum/#!forum/pyradiomics).
+
+### Feature Classes
+Currently supports the following feature classes:
+
+ - First Order Statistics
+ - Shape-based (2D and 3D)
+ - Gray Level Cooccurence Matrix (GLCM)
+ - Gray Level Run Length Matrix (GLRLM)
+ - Gray Level Size Zone Matrix (GLSZM)
+ - Gray Level Dependece Matrix (GLDM)
+ - Neighboring Gray Tone Difference Matrix (NGTDM)
+
+### Filter Classes
+Aside from the feature classes, there are also some built-in optional filters:
+
+- Laplacian of Gaussian (LoG, based on SimpleITK functionality)
+- Wavelet (using the PyWavelets package)
+- Square
+- Square Root
+- Logarithm
+- Exponential
+- Gradient (Magnitude)
+- Local Binary Pattern (LBP) 2D / 3D
+
+### Supporting reproducible extraction
+Aside from calculating features, the pyradiomics package includes provenance information in the
+output. This information contains information on used image and mask, as well as applied settings
+and filters, thereby enabling fully reproducible feature extraction.
+
+### Documentation
+For more information, see the sphinx generated documentation available [here](http://pyradiomics.readthedocs.io/).
+
+Alternatively, you can generate the documentation by checking out the master branch and running from the root directory:
+
+    python setup.py build_sphinx
+
+The documentation can then be viewed in a browser by opening `PACKAGE_ROOT\build\sphinx\html\index.html`. 
+
+Furthermore, an instruction video is available [here](http://radiomics.io/pyradiomics.html).
+
+### Installation
+PyRadiomics is OS independent and compatible with Python >= 3.5. Pre-built binaries are available on
+PyPi and Conda. To install PyRadiomics, ensure you have python
+installed and run:
+
+    `python -m pip install pyradiomics`
+
+Detailed installation instructions, as well as instructions for building PyRadiomics from source, are available in the 
+[documentation](http://pyradiomics.readthedocs.io/en/latest/installation.html).
+
+### Docker
+PyRadiomics also supports [Dockers](https://www.docker.com/).  Currently, 2 dockers are available:
+
+The first one is a [Jupyter notebook](http://jupyter.org/) with PyRadiomics pre-installed with example Notebooks. 
+
+To get the Docker:
+
+    docker pull radiomics/pyradiomics:latest
+
+The `radiomics/notebook` Docker has an exposed volume (`/data`) that can be mapped to the host system directory.  For example, to mount the current directory:
+
+    docker run --rm -it --publish 8888:8888 -v `pwd`:/data radiomics/notebook
+
+or for a less secure notebook, skip the randomly generated token
+
+    docker run --rm -it --publish 8888:8888 -v `pwd`:/data radiomics/notebook start-notebook.sh --NotebookApp.token=''
+
+and open the local webpage at http://localhost:8888/ with the current directory at http://localhost:8888/tree/data.
+
+The second is a docker which exposes the PyRadiomics CLI interface. To get the CLI-Docker:
+
+    docker pull radiomics/pyradiomics:CLI
+
+You can then use the PyRadiomics CLI as follows:
+
+    docker run radiomics/pyradiomics:CLI --help
+
+For more information on using docker, see
+[here](https://pyradiomics.readthedocs.io/en/latest/installation.html#use-pyradiomics-docker)
+
+### Usage
+PyRadiomics can be easily used in a Python script through the `featureextractor`
+module. Furthermore, PyRadiomics provides a commandline script, `pyradiomics`, for both single image extraction and 
+batchprocessing. Finally, a convenient front-end interface is provided as the 'Radiomics'
+extension for 3D Slicer, available [here](https://github.com/Radiomics/SlicerRadiomics).
+
+### 3rd-party packages used in pyradiomics:
+ - SimpleITK (Image loading and preprocessing)
+ - numpy (Feature calculation)
+ - PyWavelets (Wavelet filter)
+ - pykwalify (Enabling yaml parameters file checking)
+ - six (Python 3 Compatibility)
+ - scipy (Only for LBP filter, install separately to enable this filter)
+ - scikit-image (Only for LBP filter, install separately to enable this filter)
+ - trimesh (Only for LBP filter, install separately to enable this filter)
+
+See also the [requirements file](requirements.txt).
+
+### 3D Slicer
+PyRadiomics is also available as an [extension](https://github.com/Radiomics/SlicerRadiomics) to [3D Slicer](slicer.org). 
+Download and install the 3D slicer [nightly build](http://download.slicer.org/), the extension is then available in the
+extension manager under "SlicerRadiomics".
+
+### License
+This package is covered by the open source [3-clause BSD License](LICENSE.txt).
+
+### Developers
+ - [Joost van Griethuysen](https://github.com/JoostJM)<sup>1,3,4</sup>
+ - [Andriy Fedorov](https://github.com/fedorov)<sup>2</sup>
+ - [Nicole Aucoin](https://github.com/naucoin)<sup>2</sup>
+ - [Jean-Christophe Fillion-Robin](https://github.com/jcfr)<sup>5</sup>
+ - [Ahmed Hosny](https://github.com/ahmedhosny)<sup>1</sup>
+ - [Steve Pieper](https://github.com/pieper)<sup>6</sup>
+ - [Hugo Aerts (PI)](https://github.com/hugoaerts)<sup>1,2</sup>
+
+<sup>1</sup>Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA,
+<sup>2</sup>Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA,
+<sup>3</sup>Department of Radiology, Netherlands Cancer Institute, Amsterdam, The Netherlands, 
+<sup>4</sup>GROW-School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands,
+<sup>5</sup>Kitware,
+<sup>6</sup>Isomics
+
+### Contact
+We are happy to help you with any questions. Please contact us on the [Radiomics community section of the 3D Slicer Discourse](https://discourse.slicer.org/c/community/radiomics/23).
+
+We welcome contributions to PyRadiomics. Please read the [contributing guidelines](CONTRIBUTING.rst) on how to
+contribute to PyRadiomics.
+
+**This work was supported in part by the US National Cancer Institute grant 
+5U24CA194354, QUANTITATIVE RADIOMICS SYSTEM DECODING THE TUMOR PHENOTYPE.**
+
+
+
+
+%prep
+%autosetup -n pyradiomics-3.0.1
+
+%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-pyradiomics -f filelist.lst
+%dir %{python3_sitearch}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 3.0.1-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..a24e6fd
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+6c9ea1051be999265240fae5c9f4d088  pyradiomics-3.0.1.tar.gz