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%global _empty_manifest_terminate_build 0
Name: python-COCOPLOTS
Version: 1.0.8
Release: 1
Summary: COlor COllapsed PLOTting quick-look and context image software
License: BSD License
URL: https://github.com/mdruett/COCOPLOT/tree/master/Python
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/b6/26/12b0ddf837f66cfb51987505ce69306d92361792fdf9b68746c6ea7e5535/COCOPLOTS-1.0.8.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-astropy
Requires: python3-matplotlib
Requires: python3-Pillow
%description
# COCOPLOT
COlor COllapsed PLOTting software (COCOPLOT) generates quick-look and context images. The aim is to convey spectral profile information from all of the spatial pixels in a 3D datacube via a single 2D image, using color. Filters for red, green, and blue channels are convolved with the datacube to produce an RGB a color image. This process avoids the user needing to scan through many different wavelengths when searching for regions in the datacube that satisfy multiple criteria.
Although applicable to any 3D datacube, this software was inspired by a single thought: what would the Sun look like if we could only see light from one spectral line? In an absorption line, with low emission in the central wavelengths, and high wings on either side, the blue and red cone receptors of our thought experiment would be triggered, making the Sun appear purple. For a strong, narrow emission line the converse is true, and so the line would appear green. A red or blue Doppler-shifted emission would appear in those colours respectively.
## Citing this method
These routines were developed as part of a publication by
[M. Druett et al. (2022)](https://ui.adsabs.harvard.edu/abs/2021arXiv211110786D/abstract).
Please if you use them in your project we would appreciate
it if you cite our publication.
## Acknowledgements
This work was supported by The Swedish Research Council, grant number 2017-04099
%package -n python3-COCOPLOTS
Summary: COlor COllapsed PLOTting quick-look and context image software
Provides: python-COCOPLOTS
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-COCOPLOTS
# COCOPLOT
COlor COllapsed PLOTting software (COCOPLOT) generates quick-look and context images. The aim is to convey spectral profile information from all of the spatial pixels in a 3D datacube via a single 2D image, using color. Filters for red, green, and blue channels are convolved with the datacube to produce an RGB a color image. This process avoids the user needing to scan through many different wavelengths when searching for regions in the datacube that satisfy multiple criteria.
Although applicable to any 3D datacube, this software was inspired by a single thought: what would the Sun look like if we could only see light from one spectral line? In an absorption line, with low emission in the central wavelengths, and high wings on either side, the blue and red cone receptors of our thought experiment would be triggered, making the Sun appear purple. For a strong, narrow emission line the converse is true, and so the line would appear green. A red or blue Doppler-shifted emission would appear in those colours respectively.
## Citing this method
These routines were developed as part of a publication by
[M. Druett et al. (2022)](https://ui.adsabs.harvard.edu/abs/2021arXiv211110786D/abstract).
Please if you use them in your project we would appreciate
it if you cite our publication.
## Acknowledgements
This work was supported by The Swedish Research Council, grant number 2017-04099
%package help
Summary: Development documents and examples for COCOPLOTS
Provides: python3-COCOPLOTS-doc
%description help
# COCOPLOT
COlor COllapsed PLOTting software (COCOPLOT) generates quick-look and context images. The aim is to convey spectral profile information from all of the spatial pixels in a 3D datacube via a single 2D image, using color. Filters for red, green, and blue channels are convolved with the datacube to produce an RGB a color image. This process avoids the user needing to scan through many different wavelengths when searching for regions in the datacube that satisfy multiple criteria.
Although applicable to any 3D datacube, this software was inspired by a single thought: what would the Sun look like if we could only see light from one spectral line? In an absorption line, with low emission in the central wavelengths, and high wings on either side, the blue and red cone receptors of our thought experiment would be triggered, making the Sun appear purple. For a strong, narrow emission line the converse is true, and so the line would appear green. A red or blue Doppler-shifted emission would appear in those colours respectively.
## Citing this method
These routines were developed as part of a publication by
[M. Druett et al. (2022)](https://ui.adsabs.harvard.edu/abs/2021arXiv211110786D/abstract).
Please if you use them in your project we would appreciate
it if you cite our publication.
## Acknowledgements
This work was supported by The Swedish Research Council, grant number 2017-04099
%prep
%autosetup -n COCOPLOTS-1.0.8
%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-COCOPLOTS -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue May 30 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.8-1
- Package Spec generated
|
