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diff --git a/python-pyevaldata.spec b/python-pyevaldata.spec new file mode 100644 index 0000000..2e891e3 --- /dev/null +++ b/python-pyevaldata.spec @@ -0,0 +1,379 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pyEvalData +Version: 1.5.1 +Release: 1 +Summary: Python module to evaluate experimental data +License: MIT +URL: https://github.com/dschick/pyEvalData +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/96/b6/4a1ba329db5fe52fc141f13bcbb7ae802f062611a22cbca226ed22732af1/pyEvalData-1.5.1.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-matplotlib +Requires: python3-lmfit +Requires: python3-scipy +Requires: python3-uncertainties +Requires: python3-xrayutilities +Requires: python3-h5py +Requires: python3-nexusformat +Requires: python3-sphinx +Requires: python3-nbsphinx +Requires: python3-sphinxcontrib-napoleon +Requires: python3-flake8 +Requires: python3-pytest + +%description +# Welcome to pyEvalData + +[](https://pyevaldata.readthedocs.io/en/latest/?badge=latest) + + +[](https://codecov.io/gh/dschick/pyEvalData) + +This is a Python module to read and evaluate experimental data. It can handle +raw data from different sources such as +[spec](https://certif.com/content/spec/), +[hdf5](https://www.hdfgroup.org/solutions/hdf5/), +[NeXus](https://www.nexusformat.org/) files which are common data formats at +synchrotrons, FELs, as well as in a growing number of laboratories. The +evaluation provides common functionalities such as binning, error calculation, +and advanced data manipulation via algebraic expressions as well as pre- and +post-data-filters. Furthermore, advanced wrapper functions allow for plotting +and fitting sequences of one or multiple scans in dependence of an external +parameter. + +A minimal code example would look like this: + +```python +import pyEvalData as ped +# define your data source +spec = ped.io.Spec(file_name='data.spec') +# initialize the evaluation +ev = ped.Evaluation(spec) +# define the x- and y-data +ev.xcol = 'motor1' +ev.clist = ['ct1', 'ct2', 'ct1/ct2'] +# create a plot for scans 1-3 +ev.plot_scans([1, 2, 3]) +``` + +Please follow the [user guide](https://pyevaldata.readthedocs.io/en/latest/user_guide.html) +and [examples](https://pyevaldata.readthedocs.io/en/latest/examples.html) for +your first steps with `pyEvalData`. + +## Features + +- reading of several pre-defined raw data formats + * [spec](https://certif.com/content/spec/) + * [hdf5](https://www.hdfgroup.org/solutions/hdf5/) + * [NeXus](https://www.nexusformat.org/) + * user-defined text files + * camera images (Dectris Pilatus, Princeton MTE, Greateyes, ...) + * composite sources +- easy implementation of new raw-data formats using an `interface class` +- common methods for plotting and fitting of experimental data, including: + * data binning + * error calculation + * data manipulation via algebraic expressions + * common data pre- and post-filters + +## Installation + +You can either install directly from +[pypi.org](https://www.pypi.org/project/pyEvalData) using the command + + $ pip install pyEvalData + +or if you want to work on the latest develop release you can clone +`pyEvalData` from the main git repository: + + $ git clone https://github.com/dschick/pyEvalData.git pyEvalData + +To work in editable mode (source is only linked +but not copied to the python site-packages), just do: + + $ pip install -e ./pyEvalData + +Or to do a normal install with + + $ pip install ./pyEvalData + +Optionally, you can also let pip install directly from the repository: + + $ pip install git+https://github.com/dschick/pyEvalData.git + +You can have the following optional installations to enable unit tests, as well +as building the documentation: + + $ pip install pyEvalData[testing] + $ pip install pyEvalData[documentation] + +## Contribute & Support + +If you are having issues please let us know via the +[issue tracker](https://github.com/dschick/pyEvalData/issues). + +You can contribute to the project via pull-requests following the +[GitHub flow concept](https://docs.github.com/en/get-started/quickstart/github-flow). + +## License + +The project is licensed under the MIT license. + + + + +%package -n python3-pyEvalData +Summary: Python module to evaluate experimental data +Provides: python-pyEvalData +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-pyEvalData +# Welcome to pyEvalData + +[](https://pyevaldata.readthedocs.io/en/latest/?badge=latest) + + +[](https://codecov.io/gh/dschick/pyEvalData) + +This is a Python module to read and evaluate experimental data. It can handle +raw data from different sources such as +[spec](https://certif.com/content/spec/), +[hdf5](https://www.hdfgroup.org/solutions/hdf5/), +[NeXus](https://www.nexusformat.org/) files which are common data formats at +synchrotrons, FELs, as well as in a growing number of laboratories. The +evaluation provides common functionalities such as binning, error calculation, +and advanced data manipulation via algebraic expressions as well as pre- and +post-data-filters. Furthermore, advanced wrapper functions allow for plotting +and fitting sequences of one or multiple scans in dependence of an external +parameter. + +A minimal code example would look like this: + +```python +import pyEvalData as ped +# define your data source +spec = ped.io.Spec(file_name='data.spec') +# initialize the evaluation +ev = ped.Evaluation(spec) +# define the x- and y-data +ev.xcol = 'motor1' +ev.clist = ['ct1', 'ct2', 'ct1/ct2'] +# create a plot for scans 1-3 +ev.plot_scans([1, 2, 3]) +``` + +Please follow the [user guide](https://pyevaldata.readthedocs.io/en/latest/user_guide.html) +and [examples](https://pyevaldata.readthedocs.io/en/latest/examples.html) for +your first steps with `pyEvalData`. + +## Features + +- reading of several pre-defined raw data formats + * [spec](https://certif.com/content/spec/) + * [hdf5](https://www.hdfgroup.org/solutions/hdf5/) + * [NeXus](https://www.nexusformat.org/) + * user-defined text files + * camera images (Dectris Pilatus, Princeton MTE, Greateyes, ...) + * composite sources +- easy implementation of new raw-data formats using an `interface class` +- common methods for plotting and fitting of experimental data, including: + * data binning + * error calculation + * data manipulation via algebraic expressions + * common data pre- and post-filters + +## Installation + +You can either install directly from +[pypi.org](https://www.pypi.org/project/pyEvalData) using the command + + $ pip install pyEvalData + +or if you want to work on the latest develop release you can clone +`pyEvalData` from the main git repository: + + $ git clone https://github.com/dschick/pyEvalData.git pyEvalData + +To work in editable mode (source is only linked +but not copied to the python site-packages), just do: + + $ pip install -e ./pyEvalData + +Or to do a normal install with + + $ pip install ./pyEvalData + +Optionally, you can also let pip install directly from the repository: + + $ pip install git+https://github.com/dschick/pyEvalData.git + +You can have the following optional installations to enable unit tests, as well +as building the documentation: + + $ pip install pyEvalData[testing] + $ pip install pyEvalData[documentation] + +## Contribute & Support + +If you are having issues please let us know via the +[issue tracker](https://github.com/dschick/pyEvalData/issues). + +You can contribute to the project via pull-requests following the +[GitHub flow concept](https://docs.github.com/en/get-started/quickstart/github-flow). + +## License + +The project is licensed under the MIT license. + + + + +%package help +Summary: Development documents and examples for pyEvalData +Provides: python3-pyEvalData-doc +%description help +# Welcome to pyEvalData + +[](https://pyevaldata.readthedocs.io/en/latest/?badge=latest) + + +[](https://codecov.io/gh/dschick/pyEvalData) + +This is a Python module to read and evaluate experimental data. It can handle +raw data from different sources such as +[spec](https://certif.com/content/spec/), +[hdf5](https://www.hdfgroup.org/solutions/hdf5/), +[NeXus](https://www.nexusformat.org/) files which are common data formats at +synchrotrons, FELs, as well as in a growing number of laboratories. The +evaluation provides common functionalities such as binning, error calculation, +and advanced data manipulation via algebraic expressions as well as pre- and +post-data-filters. Furthermore, advanced wrapper functions allow for plotting +and fitting sequences of one or multiple scans in dependence of an external +parameter. + +A minimal code example would look like this: + +```python +import pyEvalData as ped +# define your data source +spec = ped.io.Spec(file_name='data.spec') +# initialize the evaluation +ev = ped.Evaluation(spec) +# define the x- and y-data +ev.xcol = 'motor1' +ev.clist = ['ct1', 'ct2', 'ct1/ct2'] +# create a plot for scans 1-3 +ev.plot_scans([1, 2, 3]) +``` + +Please follow the [user guide](https://pyevaldata.readthedocs.io/en/latest/user_guide.html) +and [examples](https://pyevaldata.readthedocs.io/en/latest/examples.html) for +your first steps with `pyEvalData`. + +## Features + +- reading of several pre-defined raw data formats + * [spec](https://certif.com/content/spec/) + * [hdf5](https://www.hdfgroup.org/solutions/hdf5/) + * [NeXus](https://www.nexusformat.org/) + * user-defined text files + * camera images (Dectris Pilatus, Princeton MTE, Greateyes, ...) + * composite sources +- easy implementation of new raw-data formats using an `interface class` +- common methods for plotting and fitting of experimental data, including: + * data binning + * error calculation + * data manipulation via algebraic expressions + * common data pre- and post-filters + +## Installation + +You can either install directly from +[pypi.org](https://www.pypi.org/project/pyEvalData) using the command + + $ pip install pyEvalData + +or if you want to work on the latest develop release you can clone +`pyEvalData` from the main git repository: + + $ git clone https://github.com/dschick/pyEvalData.git pyEvalData + +To work in editable mode (source is only linked +but not copied to the python site-packages), just do: + + $ pip install -e ./pyEvalData + +Or to do a normal install with + + $ pip install ./pyEvalData + +Optionally, you can also let pip install directly from the repository: + + $ pip install git+https://github.com/dschick/pyEvalData.git + +You can have the following optional installations to enable unit tests, as well +as building the documentation: + + $ pip install pyEvalData[testing] + $ pip install pyEvalData[documentation] + +## Contribute & Support + +If you are having issues please let us know via the +[issue tracker](https://github.com/dschick/pyEvalData/issues). + +You can contribute to the project via pull-requests following the +[GitHub flow concept](https://docs.github.com/en/get-started/quickstart/github-flow). + +## License + +The project is licensed under the MIT license. + + + + +%prep +%autosetup -n pyEvalData-1.5.1 + +%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-pyEvalData -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 1.5.1-1 +- Package Spec generated |