%global _empty_manifest_terminate_build 0 Name: python-stcal Version: 1.3.7 Release: 1 Summary: STScI tools and algorithms used in calibration pipelines License: Copyright (C) 2020 Association of Universities for Research in Astronomy (AURA) Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. The name of AURA and its representatives may not be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY AURA ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL AURA BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. URL: https://pypi.org/project/stcal/ Source0: https://mirrors.nju.edu.cn/pypi/web/packages/53/8d/f254832f6c020ea4bf6afe0769a8da5bda1ccdc35eb0166859b848942fa1/stcal-1.3.7.tar.gz BuildArch: noarch Requires: python3-astropy Requires: python3-scipy Requires: python3-numpy Requires: python3-opencv-python Requires: python3-numpydoc Requires: python3-packaging Requires: python3-sphinx Requires: python3-sphinx-astropy Requires: python3-sphinx-rtd-theme Requires: python3-stsci-rtd-theme Requires: python3-tomli Requires: python3-psutil Requires: python3-pytest Requires: python3-pytest-cov Requires: python3-pytest-doctestplus %description # STCAL [![Documentation Status](https://readthedocs.org/projects/stcal/badge/?version=latest)](http://stcal.readthedocs.io/en/latest/?badge=latest) [![CI](https://github.com/spacetelescope/stcal/actions/workflows/ci.yml/badge.svg)](https://github.com/spacetelescope/stcal/actions/workflows/ci.yml) [![codecov](https://codecov.io/gh/spacetelescope/stcal/branch/main/graph/badge.svg?token=C1LO00W9CZ)](https://codecov.io/gh/spacetelescope/stcal) STScI Calibration algorithms and tools. ![STScI Logo](docs/_static/stsci_logo.png) **STCAL requires Python 3.9 or above and a C compiler for dependencies.** **Linux and MacOS platforms are tested and supported. Windows is not currently supported.** **If installing on MacOS Mojave 10.14, you must install into an environment with python 3.9. Installation will fail on python 3.10 due to lack of a stable build for dependency ``opencv-python``.** `STCAL` is intended to be used as a support package for calibration pipeline software, such as the `JWST` and `Roman` calibration pipelines. `STCAL` is a separate package because it is also intended to be software that can be reused by multiple calibration pipelines. Even though it is intended to be a support package for calibration pipelines, it can be installed and used as a stand alone package. This could make usage unwieldy as it is easier to use `STCAL` through calibration software. The main use case for stand alone installation is for development purposes, such as bug fixes and feature additions. When installing calibration pipelines that depend on `STCAL` this package automatically gets installed as a dependency. ## Installation The easiest way to install the latest `stcal` release into a fresh virtualenv or conda environment is pip install stcal ### Detailed Installation The `stcal` package can be installed into a virtualenv or conda environment via `pip`. We recommend that for each installation you start by creating a fresh environment that only has Python installed and then install the `stcal` package and its dependencies into that bare environment. If using conda environments, first make sure you have a recent version of Anaconda or Miniconda installed. If desired, you can create multiple environments to allow for switching between different versions of the `stcal` package (e.g. a released version versus the current development version). In all cases, the installation is generally a 3-step process: * Create a conda environment * Activate that environment * Install the desired version of the `stcal` package into that environment Details are given below on how to do this for different types of installations, including tagged releases and development versions. Remember that all conda operations must be done from within a bash/zsh shell. ### Installing latest releases You can install the latest released version via `pip`. From a bash/zsh shell: conda create -n python conda activate pip install stcal You can also install a specific version, for example `stcal 1.3.2`: conda create -n python conda activate pip install stcal==1.3.2 ### Installing the development version from Github You can install the latest development version (not as well tested) from the Github master branch: conda create -n python conda activate pip install git+https://github.com/spacetelescope/stcal ### Installing for Developers If you want to be able to work on and test the source code with the `stcal` package, the high-level procedure to do this is to first create a conda environment using the same procedures outlined above, but then install your personal copy of the code overtop of the original code in that environment. Again, this should be done in a separate conda environment from any existing environments that you may have already installed with released versions of the `stcal` package. As usual, the first two steps are to create and activate an environment: conda create -n python conda activate To install your own copy of the code into that environment, you first need to fork and clone the `stcal` repo: cd git clone https://github.com/spacetelescope/stcal cd stcal *Note: `python setup.py install` and `python setup.py develop` commands do not work.* Install from your local checked-out copy as an "editable" install: pip install -e . If you want to run the unit or regression tests and/or build the docs, you can make sure those dependencies are installed too: pip install -e ".[test]" pip install -e ".[docs]" pip install -e ".[test,docs]" Need other useful packages in your development environment? pip install ipython jupyter matplotlib pylint ipdb ## Contributions and Feedback We welcome contributions and feedback on the project. Please follow the [contributing guidelines](CONTRIBUTING.md) to submit an issue or a pull request. We strive to provide a welcoming community to all of our users by abiding with the [Code of Conduct](CODE_OF_CONDUCT.md). If you have questions or concerns regarding the software, please open an issue at https://github.com/spacetelescope/stcal/issues. ## Unit Tests Unit tests can be run via `pytest`. Within the top level of your local `stcal` repo checkout: pip install -e ".[test]" pytest Need to parallelize your test runs over all available cores? pip install pytest-xdist pytest -n auto %package -n python3-stcal Summary: STScI tools and algorithms used in calibration pipelines Provides: python-stcal BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-stcal # STCAL [![Documentation Status](https://readthedocs.org/projects/stcal/badge/?version=latest)](http://stcal.readthedocs.io/en/latest/?badge=latest) [![CI](https://github.com/spacetelescope/stcal/actions/workflows/ci.yml/badge.svg)](https://github.com/spacetelescope/stcal/actions/workflows/ci.yml) [![codecov](https://codecov.io/gh/spacetelescope/stcal/branch/main/graph/badge.svg?token=C1LO00W9CZ)](https://codecov.io/gh/spacetelescope/stcal) STScI Calibration algorithms and tools. ![STScI Logo](docs/_static/stsci_logo.png) **STCAL requires Python 3.9 or above and a C compiler for dependencies.** **Linux and MacOS platforms are tested and supported. Windows is not currently supported.** **If installing on MacOS Mojave 10.14, you must install into an environment with python 3.9. Installation will fail on python 3.10 due to lack of a stable build for dependency ``opencv-python``.** `STCAL` is intended to be used as a support package for calibration pipeline software, such as the `JWST` and `Roman` calibration pipelines. `STCAL` is a separate package because it is also intended to be software that can be reused by multiple calibration pipelines. Even though it is intended to be a support package for calibration pipelines, it can be installed and used as a stand alone package. This could make usage unwieldy as it is easier to use `STCAL` through calibration software. The main use case for stand alone installation is for development purposes, such as bug fixes and feature additions. When installing calibration pipelines that depend on `STCAL` this package automatically gets installed as a dependency. ## Installation The easiest way to install the latest `stcal` release into a fresh virtualenv or conda environment is pip install stcal ### Detailed Installation The `stcal` package can be installed into a virtualenv or conda environment via `pip`. We recommend that for each installation you start by creating a fresh environment that only has Python installed and then install the `stcal` package and its dependencies into that bare environment. If using conda environments, first make sure you have a recent version of Anaconda or Miniconda installed. If desired, you can create multiple environments to allow for switching between different versions of the `stcal` package (e.g. a released version versus the current development version). In all cases, the installation is generally a 3-step process: * Create a conda environment * Activate that environment * Install the desired version of the `stcal` package into that environment Details are given below on how to do this for different types of installations, including tagged releases and development versions. Remember that all conda operations must be done from within a bash/zsh shell. ### Installing latest releases You can install the latest released version via `pip`. From a bash/zsh shell: conda create -n python conda activate pip install stcal You can also install a specific version, for example `stcal 1.3.2`: conda create -n python conda activate pip install stcal==1.3.2 ### Installing the development version from Github You can install the latest development version (not as well tested) from the Github master branch: conda create -n python conda activate pip install git+https://github.com/spacetelescope/stcal ### Installing for Developers If you want to be able to work on and test the source code with the `stcal` package, the high-level procedure to do this is to first create a conda environment using the same procedures outlined above, but then install your personal copy of the code overtop of the original code in that environment. Again, this should be done in a separate conda environment from any existing environments that you may have already installed with released versions of the `stcal` package. As usual, the first two steps are to create and activate an environment: conda create -n python conda activate To install your own copy of the code into that environment, you first need to fork and clone the `stcal` repo: cd git clone https://github.com/spacetelescope/stcal cd stcal *Note: `python setup.py install` and `python setup.py develop` commands do not work.* Install from your local checked-out copy as an "editable" install: pip install -e . If you want to run the unit or regression tests and/or build the docs, you can make sure those dependencies are installed too: pip install -e ".[test]" pip install -e ".[docs]" pip install -e ".[test,docs]" Need other useful packages in your development environment? pip install ipython jupyter matplotlib pylint ipdb ## Contributions and Feedback We welcome contributions and feedback on the project. Please follow the [contributing guidelines](CONTRIBUTING.md) to submit an issue or a pull request. We strive to provide a welcoming community to all of our users by abiding with the [Code of Conduct](CODE_OF_CONDUCT.md). If you have questions or concerns regarding the software, please open an issue at https://github.com/spacetelescope/stcal/issues. ## Unit Tests Unit tests can be run via `pytest`. Within the top level of your local `stcal` repo checkout: pip install -e ".[test]" pytest Need to parallelize your test runs over all available cores? pip install pytest-xdist pytest -n auto %package help Summary: Development documents and examples for stcal Provides: python3-stcal-doc %description help # STCAL [![Documentation Status](https://readthedocs.org/projects/stcal/badge/?version=latest)](http://stcal.readthedocs.io/en/latest/?badge=latest) [![CI](https://github.com/spacetelescope/stcal/actions/workflows/ci.yml/badge.svg)](https://github.com/spacetelescope/stcal/actions/workflows/ci.yml) [![codecov](https://codecov.io/gh/spacetelescope/stcal/branch/main/graph/badge.svg?token=C1LO00W9CZ)](https://codecov.io/gh/spacetelescope/stcal) STScI Calibration algorithms and tools. ![STScI Logo](docs/_static/stsci_logo.png) **STCAL requires Python 3.9 or above and a C compiler for dependencies.** **Linux and MacOS platforms are tested and supported. Windows is not currently supported.** **If installing on MacOS Mojave 10.14, you must install into an environment with python 3.9. Installation will fail on python 3.10 due to lack of a stable build for dependency ``opencv-python``.** `STCAL` is intended to be used as a support package for calibration pipeline software, such as the `JWST` and `Roman` calibration pipelines. `STCAL` is a separate package because it is also intended to be software that can be reused by multiple calibration pipelines. Even though it is intended to be a support package for calibration pipelines, it can be installed and used as a stand alone package. This could make usage unwieldy as it is easier to use `STCAL` through calibration software. The main use case for stand alone installation is for development purposes, such as bug fixes and feature additions. When installing calibration pipelines that depend on `STCAL` this package automatically gets installed as a dependency. ## Installation The easiest way to install the latest `stcal` release into a fresh virtualenv or conda environment is pip install stcal ### Detailed Installation The `stcal` package can be installed into a virtualenv or conda environment via `pip`. We recommend that for each installation you start by creating a fresh environment that only has Python installed and then install the `stcal` package and its dependencies into that bare environment. If using conda environments, first make sure you have a recent version of Anaconda or Miniconda installed. If desired, you can create multiple environments to allow for switching between different versions of the `stcal` package (e.g. a released version versus the current development version). In all cases, the installation is generally a 3-step process: * Create a conda environment * Activate that environment * Install the desired version of the `stcal` package into that environment Details are given below on how to do this for different types of installations, including tagged releases and development versions. Remember that all conda operations must be done from within a bash/zsh shell. ### Installing latest releases You can install the latest released version via `pip`. From a bash/zsh shell: conda create -n python conda activate pip install stcal You can also install a specific version, for example `stcal 1.3.2`: conda create -n python conda activate pip install stcal==1.3.2 ### Installing the development version from Github You can install the latest development version (not as well tested) from the Github master branch: conda create -n python conda activate pip install git+https://github.com/spacetelescope/stcal ### Installing for Developers If you want to be able to work on and test the source code with the `stcal` package, the high-level procedure to do this is to first create a conda environment using the same procedures outlined above, but then install your personal copy of the code overtop of the original code in that environment. Again, this should be done in a separate conda environment from any existing environments that you may have already installed with released versions of the `stcal` package. As usual, the first two steps are to create and activate an environment: conda create -n python conda activate To install your own copy of the code into that environment, you first need to fork and clone the `stcal` repo: cd git clone https://github.com/spacetelescope/stcal cd stcal *Note: `python setup.py install` and `python setup.py develop` commands do not work.* Install from your local checked-out copy as an "editable" install: pip install -e . If you want to run the unit or regression tests and/or build the docs, you can make sure those dependencies are installed too: pip install -e ".[test]" pip install -e ".[docs]" pip install -e ".[test,docs]" Need other useful packages in your development environment? pip install ipython jupyter matplotlib pylint ipdb ## Contributions and Feedback We welcome contributions and feedback on the project. Please follow the [contributing guidelines](CONTRIBUTING.md) to submit an issue or a pull request. We strive to provide a welcoming community to all of our users by abiding with the [Code of Conduct](CODE_OF_CONDUCT.md). If you have questions or concerns regarding the software, please open an issue at https://github.com/spacetelescope/stcal/issues. ## Unit Tests Unit tests can be run via `pytest`. Within the top level of your local `stcal` repo checkout: pip install -e ".[test]" pytest Need to parallelize your test runs over all available cores? pip install pytest-xdist pytest -n auto %prep %autosetup -n stcal-1.3.7 %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-stcal -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri May 05 2023 Python_Bot - 1.3.7-1 - Package Spec generated