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%global _empty_manifest_terminate_build 0
Name: python-pyimfit
Version: 0.12.0
Release: 1
Summary: Python wrapper for astronomical image-fitting program Imfit
License: GNU General Public License v3 (GPLv3)
URL: https://github.com/perwin/pyimfit
Source0: https://mirrors.aliyun.com/pypi/web/packages/2b/a8/054568ea68498fef20f9de6ae49a40a6f2cce8791dd9dff228d4387252fb/pyimfit-0.12.0.tar.gz
BuildArch: noarch
%description
# Pyimfit
This is a Python wrapper for the astronomical image-fitting program Imfit.
Online documentation: [https://pyimfit.readthedocs.io/en/latest/](https://pyimfit.readthedocs.io/en/latest/).
## Sample Usage
The following assumes an interactive Python session (such as an iPython session
or Jupyter notebook):
from astropy.io import fits
import pyimfit
imageFile = "<path-to-FITS-file-directory>/ic3478rss_256.fits"
imfitConfigFile = "<path-to-config-file-directory>/config_exponential_ic3478_256.dat"
# read in image data, convert to proper double-precisions, little-endian format
image_data = fits.getdata(imageFile)
# construct model from config file; construct new Imfit fitter based on model,;
model_desc = pyimfit.ModelDescription.load(configFile)
# create an Imfit object, using the previously loaded model configuration
imfit_fitter = pyimfit.Imfit(model_desc)
# load the image data and image characteristics and do a standard fit
# (using default chi^2 statistics and Levenberg-Marquardt solver)
result = imfit_fitter.fit(image_data, gain=4.725, read_noise=4.3, original_sky=130.14)
# check the fit and print the resulting best-fit parameter values
if result.fitConverged is True:
print("Fit converged: chi^2 = {0}, reduced chi^2 = {1}".format(imfit_fitter.fitStatistic,
result.reducedFitStat))
bestfit_params = result.params
print("Best-fit parameter values:", bestfit_params)
%package -n python3-pyimfit
Summary: Python wrapper for astronomical image-fitting program Imfit
Provides: python-pyimfit
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-pyimfit
# Pyimfit
This is a Python wrapper for the astronomical image-fitting program Imfit.
Online documentation: [https://pyimfit.readthedocs.io/en/latest/](https://pyimfit.readthedocs.io/en/latest/).
## Sample Usage
The following assumes an interactive Python session (such as an iPython session
or Jupyter notebook):
from astropy.io import fits
import pyimfit
imageFile = "<path-to-FITS-file-directory>/ic3478rss_256.fits"
imfitConfigFile = "<path-to-config-file-directory>/config_exponential_ic3478_256.dat"
# read in image data, convert to proper double-precisions, little-endian format
image_data = fits.getdata(imageFile)
# construct model from config file; construct new Imfit fitter based on model,;
model_desc = pyimfit.ModelDescription.load(configFile)
# create an Imfit object, using the previously loaded model configuration
imfit_fitter = pyimfit.Imfit(model_desc)
# load the image data and image characteristics and do a standard fit
# (using default chi^2 statistics and Levenberg-Marquardt solver)
result = imfit_fitter.fit(image_data, gain=4.725, read_noise=4.3, original_sky=130.14)
# check the fit and print the resulting best-fit parameter values
if result.fitConverged is True:
print("Fit converged: chi^2 = {0}, reduced chi^2 = {1}".format(imfit_fitter.fitStatistic,
result.reducedFitStat))
bestfit_params = result.params
print("Best-fit parameter values:", bestfit_params)
%package help
Summary: Development documents and examples for pyimfit
Provides: python3-pyimfit-doc
%description help
# Pyimfit
This is a Python wrapper for the astronomical image-fitting program Imfit.
Online documentation: [https://pyimfit.readthedocs.io/en/latest/](https://pyimfit.readthedocs.io/en/latest/).
## Sample Usage
The following assumes an interactive Python session (such as an iPython session
or Jupyter notebook):
from astropy.io import fits
import pyimfit
imageFile = "<path-to-FITS-file-directory>/ic3478rss_256.fits"
imfitConfigFile = "<path-to-config-file-directory>/config_exponential_ic3478_256.dat"
# read in image data, convert to proper double-precisions, little-endian format
image_data = fits.getdata(imageFile)
# construct model from config file; construct new Imfit fitter based on model,;
model_desc = pyimfit.ModelDescription.load(configFile)
# create an Imfit object, using the previously loaded model configuration
imfit_fitter = pyimfit.Imfit(model_desc)
# load the image data and image characteristics and do a standard fit
# (using default chi^2 statistics and Levenberg-Marquardt solver)
result = imfit_fitter.fit(image_data, gain=4.725, read_noise=4.3, original_sky=130.14)
# check the fit and print the resulting best-fit parameter values
if result.fitConverged is True:
print("Fit converged: chi^2 = {0}, reduced chi^2 = {1}".format(imfit_fitter.fitStatistic,
result.reducedFitStat))
bestfit_params = result.params
print("Best-fit parameter values:", bestfit_params)
%prep
%autosetup -n pyimfit-0.12.0
%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-pyimfit -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 0.12.0-1
- Package Spec generated
|
