automatic import of python-py-casperopeneuler20.03

1 files changed, 299 insertions, 0 deletions

diff --git a/python-py-casper.spec b/python-py-casper.spec
new file mode 100644
index 0000000..44efd7d
--- /dev/null
+++ b/python-py-casper.spec
@@ -0,0 +1,299 @@
+%global _empty_manifest_terminate_build 0
+Name:		python-py-casper
+Version:	1.1.0
+Release:	1
+Summary:	A python package to predict halo concentration and shape parameter.
+License:	MIT License
+URL:		https://github.com/Shaun-T-Brown/CASPER
+Source0:	https://mirrors.aliyun.com/pypi/web/packages/59/71/6672dea1706cf357a0a10114050324d9f7619226b8af59802c48cc46b65f/py-casper-1.1.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-scipy
+
+%description
+# CASPER (Concentration And Shape Parameter Estimation Routine)
+
+Casper is a python package aimed at predicting the concentration and shape parameter of dark matter haloes as a function of mass and redshift for a specified cosmology.
+
+### Requirements
+
+The module requires the following:
+
+- python3.6 or higher
+
+### Installation
+
+The easiest way to install Casper is using pip:
+
+```
+pip install py-casper [--user]
+```
+
+The --user flag may be required if you do not have root privileges. Alternatively for a more involved 'installation' that is also editable you can simply  clone the github repository:
+
+```
+git clone https://github.com/Shaun-T-Brown/CASPER.git
+```
+
+and add the folder (specifically src) to your python path. This method will also require scipy and numpy to be installed. Using pip will automatically install all dependencies.
+
+To use the main functionality of the package (i.e. to predict c and alpha) you will need to be able to generate the linear power spectra for a given cosmology. In principle this can be done using any reliable method. However, we recommend installing and using [CAMB](https://camb.readthedocs.io/en/latest/).
+
+
+
+### Usage
+
+The best way to demonstrate how Casper can be used is with a few examples. An interactive jupyter notebook with all necessary modules available can be found on [Binder](https://mybinder.org/v2/gh/Shaun-T-Brown/CASPER-example.git/HEAD?filepath=.%2Fexample_script.ipynb). A static version of the same notebook can be found at the following github [repository](https://github.com/Shaun-T-Brown/CASPER-example.git), specifically in the file *example_script.ipynb*.
+
+The functionality of the package is relatively straightforward and is essentially a collection of useful functions centered around the density profiles of dark matter haloes. Basic documentation can be generated using *pydoc*.
+
+
+```
+import casper
+
+help(casper)
+```
+
+
+### Acknowledging the code
+
+If the results of this code, particularly the predictions for halo concentration and the shape parameter, are used in any published work then please acknowledge and cite the original [paper](https://arxiv.org/abs/2110.01632) appropriately.
+
+The following bibtex entry may be used:
+
+```
+@ARTICLE{2022MNRAS.509.5685B,
+       author = {{Brown}, Shaun T. and {McCarthy}, Ian G. and {Stafford}, Sam G. and {Font}, Andreea S.},
+        title = "{Towards a universal model for the density profiles of dark matter haloes}",
+      journal = {\mnras},
+     keywords = {methods: numerical, cosmology: theory, dark matter, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies},
+         year = 2022,
+        month = feb,
+       volume = {509},
+       number = {4},
+        pages = {5685-5701},
+          doi = {10.1093/mnras/stab3394},
+archivePrefix = {arXiv},
+       eprint = {2110.01632},
+ primaryClass = {astro-ph.CO},
+       adsurl = {https://ui.adsabs.harvard.edu/abs/2022MNRAS.509.5685B},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+```
+
+For any questions and enquires please contact me via email at *S.T.Brown@2018.ljmu.ac.uk*
+
+
+
+
+
+
+%package -n python3-py-casper
+Summary:	A python package to predict halo concentration and shape parameter.
+Provides:	python-py-casper
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-py-casper
+# CASPER (Concentration And Shape Parameter Estimation Routine)
+
+Casper is a python package aimed at predicting the concentration and shape parameter of dark matter haloes as a function of mass and redshift for a specified cosmology.
+
+### Requirements
+
+The module requires the following:
+
+- python3.6 or higher
+
+### Installation
+
+The easiest way to install Casper is using pip:
+
+```
+pip install py-casper [--user]
+```
+
+The --user flag may be required if you do not have root privileges. Alternatively for a more involved 'installation' that is also editable you can simply  clone the github repository:
+
+```
+git clone https://github.com/Shaun-T-Brown/CASPER.git
+```
+
+and add the folder (specifically src) to your python path. This method will also require scipy and numpy to be installed. Using pip will automatically install all dependencies.
+
+To use the main functionality of the package (i.e. to predict c and alpha) you will need to be able to generate the linear power spectra for a given cosmology. In principle this can be done using any reliable method. However, we recommend installing and using [CAMB](https://camb.readthedocs.io/en/latest/).
+
+
+
+### Usage
+
+The best way to demonstrate how Casper can be used is with a few examples. An interactive jupyter notebook with all necessary modules available can be found on [Binder](https://mybinder.org/v2/gh/Shaun-T-Brown/CASPER-example.git/HEAD?filepath=.%2Fexample_script.ipynb). A static version of the same notebook can be found at the following github [repository](https://github.com/Shaun-T-Brown/CASPER-example.git), specifically in the file *example_script.ipynb*.
+
+The functionality of the package is relatively straightforward and is essentially a collection of useful functions centered around the density profiles of dark matter haloes. Basic documentation can be generated using *pydoc*.
+
+
+```
+import casper
+
+help(casper)
+```
+
+
+### Acknowledging the code
+
+If the results of this code, particularly the predictions for halo concentration and the shape parameter, are used in any published work then please acknowledge and cite the original [paper](https://arxiv.org/abs/2110.01632) appropriately.
+
+The following bibtex entry may be used:
+
+```
+@ARTICLE{2022MNRAS.509.5685B,
+       author = {{Brown}, Shaun T. and {McCarthy}, Ian G. and {Stafford}, Sam G. and {Font}, Andreea S.},
+        title = "{Towards a universal model for the density profiles of dark matter haloes}",
+      journal = {\mnras},
+     keywords = {methods: numerical, cosmology: theory, dark matter, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies},
+         year = 2022,
+        month = feb,
+       volume = {509},
+       number = {4},
+        pages = {5685-5701},
+          doi = {10.1093/mnras/stab3394},
+archivePrefix = {arXiv},
+       eprint = {2110.01632},
+ primaryClass = {astro-ph.CO},
+       adsurl = {https://ui.adsabs.harvard.edu/abs/2022MNRAS.509.5685B},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+```
+
+For any questions and enquires please contact me via email at *S.T.Brown@2018.ljmu.ac.uk*
+
+
+
+
+
+
+%package help
+Summary:	Development documents and examples for py-casper
+Provides:	python3-py-casper-doc
+%description help
+# CASPER (Concentration And Shape Parameter Estimation Routine)
+
+Casper is a python package aimed at predicting the concentration and shape parameter of dark matter haloes as a function of mass and redshift for a specified cosmology.
+
+### Requirements
+
+The module requires the following:
+
+- python3.6 or higher
+
+### Installation
+
+The easiest way to install Casper is using pip:
+
+```
+pip install py-casper [--user]
+```
+
+The --user flag may be required if you do not have root privileges. Alternatively for a more involved 'installation' that is also editable you can simply  clone the github repository:
+
+```
+git clone https://github.com/Shaun-T-Brown/CASPER.git
+```
+
+and add the folder (specifically src) to your python path. This method will also require scipy and numpy to be installed. Using pip will automatically install all dependencies.
+
+To use the main functionality of the package (i.e. to predict c and alpha) you will need to be able to generate the linear power spectra for a given cosmology. In principle this can be done using any reliable method. However, we recommend installing and using [CAMB](https://camb.readthedocs.io/en/latest/).
+
+
+
+### Usage
+
+The best way to demonstrate how Casper can be used is with a few examples. An interactive jupyter notebook with all necessary modules available can be found on [Binder](https://mybinder.org/v2/gh/Shaun-T-Brown/CASPER-example.git/HEAD?filepath=.%2Fexample_script.ipynb). A static version of the same notebook can be found at the following github [repository](https://github.com/Shaun-T-Brown/CASPER-example.git), specifically in the file *example_script.ipynb*.
+
+The functionality of the package is relatively straightforward and is essentially a collection of useful functions centered around the density profiles of dark matter haloes. Basic documentation can be generated using *pydoc*.
+
+
+```
+import casper
+
+help(casper)
+```
+
+
+### Acknowledging the code
+
+If the results of this code, particularly the predictions for halo concentration and the shape parameter, are used in any published work then please acknowledge and cite the original [paper](https://arxiv.org/abs/2110.01632) appropriately.
+
+The following bibtex entry may be used:
+
+```
+@ARTICLE{2022MNRAS.509.5685B,
+       author = {{Brown}, Shaun T. and {McCarthy}, Ian G. and {Stafford}, Sam G. and {Font}, Andreea S.},
+        title = "{Towards a universal model for the density profiles of dark matter haloes}",
+      journal = {\mnras},
+     keywords = {methods: numerical, cosmology: theory, dark matter, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies},
+         year = 2022,
+        month = feb,
+       volume = {509},
+       number = {4},
+        pages = {5685-5701},
+          doi = {10.1093/mnras/stab3394},
+archivePrefix = {arXiv},
+       eprint = {2110.01632},
+ primaryClass = {astro-ph.CO},
+       adsurl = {https://ui.adsabs.harvard.edu/abs/2022MNRAS.509.5685B},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+```
+
+For any questions and enquires please contact me via email at *S.T.Brown@2018.ljmu.ac.uk*
+
+
+
+
+
+
+%prep
+%autosetup -n py-casper-1.1.0
+
+%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-py-casper -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.0-1
+- Package Spec generated