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|
%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
|
