From 624587771ba48ac6e258c6e1f71601c41e2e2bb1 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Tue, 20 Jun 2023 04:39:19 +0000 Subject: automatic import of python-rampy --- .gitignore | 1 + python-rampy.spec | 223 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ sources | 1 + 3 files changed, 225 insertions(+) create mode 100644 python-rampy.spec create mode 100644 sources diff --git a/.gitignore b/.gitignore index e69de29..f23b55f 100644 --- a/.gitignore +++ b/.gitignore @@ -0,0 +1 @@ +/rampy-0.4.9.tar.gz diff --git a/python-rampy.spec b/python-rampy.spec new file mode 100644 index 0000000..f23e093 --- /dev/null +++ b/python-rampy.spec @@ -0,0 +1,223 @@ +%global _empty_manifest_terminate_build 0 +Name: python-rampy +Version: 0.4.9 +Release: 1 +Summary: A Python module containing functions to treat spectroscopic (XANES, Raman, IR...) data +License: GNU-GPLv2 +URL: https://github.com/charlesll/rampy +Source0: https://mirrors.aliyun.com/pypi/web/packages/a0/2c/61dd47122b4e024d523c02c01297a7425b71dde91ba09925fd23fb44afa0/rampy-0.4.9.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-scipy +Requires: python3-scikit-learn +Requires: python3-pandas +Requires: python3-xlrd +Requires: python3-gcvspline +Requires: python3-cvxpy + +%description +Copyright (2015-2021) C. Le Losq and co. +lelosq@ipgp.fr +[![Build Status](https://travis-ci.org/charlesll/rampy.svg?branch=master)](https://travis-ci.org/charlesll/rampy) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1168729.svg)](https://doi.org/10.5281/zenodo.1168729) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/charlesll/rampy.git/master) +Rampy is a Python library that aims at helping processing spectroscopic data, such as Raman, Infrared or XAS spectra. It offers, for instance, functions to subtract baselines as well as to stack, resample or smooth spectra. It aims at facilitating the use of Python in processing spectroscopic data. It integrates within a workflow that uses Numpy/Scipy as well as optimisation libraries such as lmfit or emcee, for instance. +The /examples/ folder contain various examples. +# REQUIREMENTS +Rampy is tested on Python 3.8 (see Travis badge; no garantee that it works on other Python versions) +The following libraries are required and indicated in setup.cfg: +- Scipy +- Numpy >= 1.12 +- sklearn +- pandas & xlrd +Optional dependencies: +- gcvspline (you need a working FORTRAN compiler for its installation. To avoid this problem under Windows, wheels for Python 2.7, 3.4 and 3.6 are provided for 64 bit Windows, and a wheel for Python 3.6 is provided for Windows 32 bits. If installation fails, please check if is due to a fortran compiler issue.) +- xlrd and matplotlib +*Installation of gcvspline as well as matplotlib and xlrd are necessary for use of the `rampy.rameau()` class.* +- cvxpy v 1.1 or higher. As for gcvspline, the installation of cvxpy can cause problems for Windows users due to missing compiler. See instructions from cvxpy in this case. +*Installation of cvxpy is necessary for use of the `rampy.mixing()` class.* +Additional libraries for model fitting may be wanted: +- lmfit & aeval (http://cars9.uchicago.edu/software/python/lmfit/) +- emcee +# INSTALLATION +Install with pip: + `pip install rampy` +If you want to use gcvspline and cvxpy, also install it: + `pip install gcvspline` + `pip install cvxpy` +# EXAMPLES +Given a signal [x y] containing a peak, and recorded in a text file myspectrum.txt. +You can import it, remove a automatic background, plot the result, and print the centroid of the peak as: +``` +import matplotlib.pyplot as plt +import numpy as np +import rampy as rp +spectrum = np.genfromtxt("myspectrum.txt") +bir = np.array([[0,100., 200., 1000]]) # the frequency regions devoid of signal, used by rp.baseline() +y_corrected, background = rp.baseline(spectrum[:,0],spectrum[:,1],bir,"arPLS",lam=10**10) +plt.figure() +plt.plot(spectrum[:,0],spectrum[:,1],"k",label="raw data") +plt.plot(spectrum[:,0],background,"k",label="background") +plt.plot(spectrum[:,0],y_corrected,"k",label="corrected signal") +plt.show() +print("Signal centroid is %.2f" % rp.centroid(spectrum[:,0],y_corrected)) +``` +See the /example folder for further examples. +# Other packages +rampy can be used also to analyse the output of the [RADIS](https://radis.readthedocs.io/en/latest/) package. +See for instance https://github.com/charlesll/rampy/issues/13 +Updated September 2021 + +%package -n python3-rampy +Summary: A Python module containing functions to treat spectroscopic (XANES, Raman, IR...) data +Provides: python-rampy +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-rampy +Copyright (2015-2021) C. Le Losq and co. +lelosq@ipgp.fr +[![Build Status](https://travis-ci.org/charlesll/rampy.svg?branch=master)](https://travis-ci.org/charlesll/rampy) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1168729.svg)](https://doi.org/10.5281/zenodo.1168729) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/charlesll/rampy.git/master) +Rampy is a Python library that aims at helping processing spectroscopic data, such as Raman, Infrared or XAS spectra. It offers, for instance, functions to subtract baselines as well as to stack, resample or smooth spectra. It aims at facilitating the use of Python in processing spectroscopic data. It integrates within a workflow that uses Numpy/Scipy as well as optimisation libraries such as lmfit or emcee, for instance. +The /examples/ folder contain various examples. +# REQUIREMENTS +Rampy is tested on Python 3.8 (see Travis badge; no garantee that it works on other Python versions) +The following libraries are required and indicated in setup.cfg: +- Scipy +- Numpy >= 1.12 +- sklearn +- pandas & xlrd +Optional dependencies: +- gcvspline (you need a working FORTRAN compiler for its installation. To avoid this problem under Windows, wheels for Python 2.7, 3.4 and 3.6 are provided for 64 bit Windows, and a wheel for Python 3.6 is provided for Windows 32 bits. If installation fails, please check if is due to a fortran compiler issue.) +- xlrd and matplotlib +*Installation of gcvspline as well as matplotlib and xlrd are necessary for use of the `rampy.rameau()` class.* +- cvxpy v 1.1 or higher. As for gcvspline, the installation of cvxpy can cause problems for Windows users due to missing compiler. See instructions from cvxpy in this case. +*Installation of cvxpy is necessary for use of the `rampy.mixing()` class.* +Additional libraries for model fitting may be wanted: +- lmfit & aeval (http://cars9.uchicago.edu/software/python/lmfit/) +- emcee +# INSTALLATION +Install with pip: + `pip install rampy` +If you want to use gcvspline and cvxpy, also install it: + `pip install gcvspline` + `pip install cvxpy` +# EXAMPLES +Given a signal [x y] containing a peak, and recorded in a text file myspectrum.txt. +You can import it, remove a automatic background, plot the result, and print the centroid of the peak as: +``` +import matplotlib.pyplot as plt +import numpy as np +import rampy as rp +spectrum = np.genfromtxt("myspectrum.txt") +bir = np.array([[0,100., 200., 1000]]) # the frequency regions devoid of signal, used by rp.baseline() +y_corrected, background = rp.baseline(spectrum[:,0],spectrum[:,1],bir,"arPLS",lam=10**10) +plt.figure() +plt.plot(spectrum[:,0],spectrum[:,1],"k",label="raw data") +plt.plot(spectrum[:,0],background,"k",label="background") +plt.plot(spectrum[:,0],y_corrected,"k",label="corrected signal") +plt.show() +print("Signal centroid is %.2f" % rp.centroid(spectrum[:,0],y_corrected)) +``` +See the /example folder for further examples. +# Other packages +rampy can be used also to analyse the output of the [RADIS](https://radis.readthedocs.io/en/latest/) package. +See for instance https://github.com/charlesll/rampy/issues/13 +Updated September 2021 + +%package help +Summary: Development documents and examples for rampy +Provides: python3-rampy-doc +%description help +Copyright (2015-2021) C. Le Losq and co. +lelosq@ipgp.fr +[![Build Status](https://travis-ci.org/charlesll/rampy.svg?branch=master)](https://travis-ci.org/charlesll/rampy) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1168729.svg)](https://doi.org/10.5281/zenodo.1168729) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/charlesll/rampy.git/master) +Rampy is a Python library that aims at helping processing spectroscopic data, such as Raman, Infrared or XAS spectra. It offers, for instance, functions to subtract baselines as well as to stack, resample or smooth spectra. It aims at facilitating the use of Python in processing spectroscopic data. It integrates within a workflow that uses Numpy/Scipy as well as optimisation libraries such as lmfit or emcee, for instance. +The /examples/ folder contain various examples. +# REQUIREMENTS +Rampy is tested on Python 3.8 (see Travis badge; no garantee that it works on other Python versions) +The following libraries are required and indicated in setup.cfg: +- Scipy +- Numpy >= 1.12 +- sklearn +- pandas & xlrd +Optional dependencies: +- gcvspline (you need a working FORTRAN compiler for its installation. To avoid this problem under Windows, wheels for Python 2.7, 3.4 and 3.6 are provided for 64 bit Windows, and a wheel for Python 3.6 is provided for Windows 32 bits. If installation fails, please check if is due to a fortran compiler issue.) +- xlrd and matplotlib +*Installation of gcvspline as well as matplotlib and xlrd are necessary for use of the `rampy.rameau()` class.* +- cvxpy v 1.1 or higher. As for gcvspline, the installation of cvxpy can cause problems for Windows users due to missing compiler. See instructions from cvxpy in this case. +*Installation of cvxpy is necessary for use of the `rampy.mixing()` class.* +Additional libraries for model fitting may be wanted: +- lmfit & aeval (http://cars9.uchicago.edu/software/python/lmfit/) +- emcee +# INSTALLATION +Install with pip: + `pip install rampy` +If you want to use gcvspline and cvxpy, also install it: + `pip install gcvspline` + `pip install cvxpy` +# EXAMPLES +Given a signal [x y] containing a peak, and recorded in a text file myspectrum.txt. +You can import it, remove a automatic background, plot the result, and print the centroid of the peak as: +``` +import matplotlib.pyplot as plt +import numpy as np +import rampy as rp +spectrum = np.genfromtxt("myspectrum.txt") +bir = np.array([[0,100., 200., 1000]]) # the frequency regions devoid of signal, used by rp.baseline() +y_corrected, background = rp.baseline(spectrum[:,0],spectrum[:,1],bir,"arPLS",lam=10**10) +plt.figure() +plt.plot(spectrum[:,0],spectrum[:,1],"k",label="raw data") +plt.plot(spectrum[:,0],background,"k",label="background") +plt.plot(spectrum[:,0],y_corrected,"k",label="corrected signal") +plt.show() +print("Signal centroid is %.2f" % rp.centroid(spectrum[:,0],y_corrected)) +``` +See the /example folder for further examples. +# Other packages +rampy can be used also to analyse the output of the [RADIS](https://radis.readthedocs.io/en/latest/) package. +See for instance https://github.com/charlesll/rampy/issues/13 +Updated September 2021 + +%prep +%autosetup -n rampy-0.4.9 + +%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-rampy -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Jun 20 2023 Python_Bot - 0.4.9-1 +- Package Spec generated diff --git a/sources b/sources new file mode 100644 index 0000000..95b7eea --- /dev/null +++ b/sources @@ -0,0 +1 @@ +fc1554b07122460abd16fff6f9d13a69 rampy-0.4.9.tar.gz -- cgit v1.2.3