| Name | pyFAI JSON |
| Version |
2024.2.0
JSON |
| download |
| home_page | http://www.silx.org |
| Summary | Python implementation of fast azimuthal integration |
| upload_time | 2024-02-01 16:28:45 |
| maintainer | |
| docs_url | None |
| author | Gael Goret, Brian Pauw |
| requires_python | >=3.7 |
| license | Format: http://www.debian.org/doc/packaging-manuals/copyright-format/1.0/ Upstream-Name: pyfai Source: https://github.com/silx-kit/pyFAI Files-Excluded: pyFAI/third_party/_local Files: * Copyright: 2011-2017 European Synchrotron Radiation Facility License: MIT/X11 (BSD like) Files: package/debian?/* Copyright: 2012-2014 Jerome Kieffer <jerome.kieffer@esrf.fr> 2013-2016 Picca Frédéric-Emmanuel <picca@debian.org> 2015-2016 European Synchrotron Radiation Facility License: GPL-3.0+ Files: pyFAI/resources/openCL/bitonic.cl openCL/bsort.cl Copyright: Matthew Scarpino License: public-domain Files: doc/source/mathjax.py Copyright: 2007-2013 by the Sphinx team License: BSD-3 Files: pyFAI/third_party/transformation.py Copyright: 2006-2018, Christoph Gohlke, University of California License: BSD-3 License: BSD-3 Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * 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. * Neither the name of the <organization> nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. . THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "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 <COPYRIGHT HOLDER> 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. License: GPL-3.0+ This package is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version. . This package is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. . You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/> . On Debian systems, the complete text of the GNU General Public License version 3 can be found in "/usr/share/common-licenses/GPL-3". License: public-domain You can use this free for any purpose. It's in the public domain. It has no warranty License: MIT/X11 (BSD like) Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: . The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. . THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
wheel
meson-python
ninja
numpy
cython
fabio
scipy
matplotlib
numexpr
h5py
silx
PyOpenGL
PyQt5
hdf5plugin
nbsphinx
|
| Travis-CI |
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| coveralls test coverage |
No coveralls.
|
pyFAI: Fast Azimuthal Integration in Python
===========================================
Main development website: https://github.com/silx-kit/pyFAI
|Github Actions| |Appveyor Status| |myBinder Launcher| |RTD docs| |Zenodo DOI|
PyFAI is an azimuthal integration library that tries to be fast (as fast as C
and even more using OpenCL and GPU).
It is based on histogramming of the 2theta/Q positions of each (center of)
pixel weighted by the intensity of each pixel, but parallel version uses a
SparseMatrix-DenseVector multiplication.
Neighboring output bins get also a contribution of pixels next to the border
thanks to pixel splitting.
Finally pyFAI provides also tools to calibrate the experimental setup using Debye-Scherrer
rings of a reference compound.
References
----------
* The philosophy of pyFAI is described in the proceedings of SRI2012: https://doi.org/10.1088/1742-6596/425/20/202012
* Implementation in parallel is described in the proceedings of EPDIC13: https://doi.org/10.1017/S0885715613000924
* Benchmarks and optimization procedure is described in the proceedings of EuroSciPy2014: https://doi.org/10.48550/arXiv.1412.6367
* Calibration procedures are described in J. Synch. Radiation 2020: https://doi.org/10.1107/S1600577520000776
Installation
------------
With PIP
........
As most Python packages, pyFAI is available via PIP::
pip install pyFAI[gui]
It is advised to run this in a vitural environment.
Provide the *--user* to perform an installation local to your user (not recommended).
Under UNIX, you may have to run the command via *sudo* to gain root access an
perform a system wide installation (neither recommended).
With conda
..........
pyFAI is also available via conda::
conda install pyfai -c conda-forge
To install conda please see either `conda <https://conda.io/docs/install/quick.html>`_ or `Anaconda <https://www.continuum.io/downloads>`_.
From source code
................
The latest release of pyFAI can be downloaded from
`Github <https://github.com/silx-kit/pyFAI/archive/main.zip>`_.
Presently the source code has been distributed as a zip package.
Download it one and unpack it::
unzip pyFAI-main.zip
As developement is also done on Github,
`development branch is also available <https://github.com/silx-kit/pyFAI/archive/main.zip>`_
All files are unpacked into the directory pyFAI-main::
cd pyFAI-main
Build it & test it::
python3 run_tests.py
For its tests, pyFAI downloads test images from the internet.
Depending on your network connection and your local network configuration,
you may have to setup a proxy configuration like this (no more needed at ESRF)::
export http_proxy=http://proxy.site.org:3128
Finally, install pyFAI in the virtualenv after testing it::
pip install --upgrade .
The newest development version can also be obtained by checking out from the git
repository::
git clone https://github.com/silx-kit/pyFAI.git
cd pyFAI
pip install --upgrade .
If you want pyFAI to make use of your graphic card, please install
`pyopencl <http://mathema.tician.de/software/pyopencl>`_
Documentation
-------------
Documentation can be build using this command and Sphinx (installed on your computer)::
pip install -r requirements.txt
python3 build-doc.py
Dependencies
------------
Python 3.7, ... 3.11 are well tested and officially supported.
For python 3.12, it requires silx version 2 which is still unreleased for now.
For full functionality of pyFAI the following modules need to be installed.
* ``numpy`` - http://www.numpy.org
* ``scipy`` - http://www.scipy.org
* ``matplotlib`` - http://matplotlib.sourceforge.net/
* ``fabio`` - http://sourceforge.net/projects/fable/files/fabio/
* ``h5py`` - http://www.h5py.org/
* ``pyopencl`` - http://mathema.tician.de/software/pyopencl/
* ``pyqt5`` - http://www.riverbankcomputing.co.uk/software/pyqt/intro
* ``silx`` - http://www.silx.org
* ``numexpr`` - https://github.com/pydata/numexpr
Those dependencies can simply be installed by::
pip install -r requirements.txt
Ubuntu and Debian-like Linux distributions
------------------------------------------
To use pyFAI on Ubuntu/Debian the needed python modules
can be installed either through the Synaptic Package Manager
(found in System -> Administration)
or using apt-get on from the command line in a terminal::
sudo apt-get install pyfai
The extra Ubuntu packages needed are:
* ``python3-numpy``
* ``python3-scipy``
* ``python3-matplotlib``
* ``python3-dev``
* ``python3-fabio``
* ``python3-pyopencl``
* ``python3-pyqt5``
* ``python3-silx``
* ``python3-numexpr``
using apt-get these can be installed as::
sudo apt-get build-dep pyfai
MacOSX
------
One needs to install `Python` (>=3.7) and `Xcode` prior to start installing pyFAI.
The compiled extension will use only one core due to the limitation of the compiler.
OpenCL is hence greately adviced on Apple systems.
Then install the missing dependencies with `pip`::
pip install -r requirements.txt
Windows
-------
Under Windows, one needs to install `Python` (>=3.7) and the Visual Studio C++ compiler.
Then install the missing dependencies with `pip`::
pip install -r requirements.txt
Getting help
------------
A mailing-list, pyfai@esrf.fr, is available to get help on the program and how to use it.
One needs to subscribe by sending an email to sympa@esrf.fr with a subject "subscribe pyfai".
Maintainers
-----------
* Jérôme Kieffer (ESRF)
Contributors
------------
* Edgar Gutierrez Fernandez (ESRF)
* Valentin Valls (ESRF)
* Frédéric-Emmanuel Picca (Soleil)
* Thomas Vincent (ESRF)
* Dimitris Karkoulis (Formerly ESRF)
* Aurore Deschildre (Formerly ESRF)
* Giannis Ashiotis (Formerly ESRF)
* Zubair Nawaz (Formerly Sesame)
* Jon Wright (ESRF)
* Amund Hov (Formerly ESRF)
* Dodogerstlin @github
* Gunthard Benecke (Desy)
* Gero Flucke (Desy)
Indirect contributors (ideas...)
--------------------------------
* Peter Boesecke
* Manuel Sánchez del Río
* Vicente Armando Solé
* Brian Pauw
* Veijo Honkimaki
.. |Github Actions| image:: https://github.com/silx-kit/pyFAI/actions/workflows/python-package.yml/badge.svg
.. |Appveyor Status| image:: https://ci.appveyor.com/api/projects/status/github/silx-kit/pyfai?svg=true
:target: https://ci.appveyor.com/project/ESRF/pyfai
.. |myBinder Launcher| image:: https://mybinder.org/badge_logo.svg
:target: https://mybinder.org/v2/gh/silx-kit/pyFAI/main?filepath=binder%2Findex.ipynb
.. |RTD docs| image:: https://readthedocs.org/projects/pyFAI/badge/?version=main
:alt: Documentation Status
:scale: 100%
:target: https://pyfai.readthedocs.io/en/main/?badge=main
.. |Zenodo DOI| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.832896.svg
:target: https://doi.org/10.5281/zenodo.832896
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"description": "pyFAI: Fast Azimuthal Integration in Python\n===========================================\n\nMain development website: https://github.com/silx-kit/pyFAI\n\n|Github Actions| |Appveyor Status| |myBinder Launcher| |RTD docs| |Zenodo DOI|\n\nPyFAI is an azimuthal integration library that tries to be fast (as fast as C\nand even more using OpenCL and GPU).\nIt is based on histogramming of the 2theta/Q positions of each (center of)\npixel weighted by the intensity of each pixel, but parallel version uses a\nSparseMatrix-DenseVector multiplication.\nNeighboring output bins get also a contribution of pixels next to the border\nthanks to pixel splitting.\nFinally pyFAI provides also tools to calibrate the experimental setup using Debye-Scherrer\nrings of a reference compound.\n\nReferences\n----------\n\n* The philosophy of pyFAI is described in the proceedings of SRI2012: https://doi.org/10.1088/1742-6596/425/20/202012\n* Implementation in parallel is described in the proceedings of EPDIC13: https://doi.org/10.1017/S0885715613000924\n* Benchmarks and optimization procedure is described in the proceedings of EuroSciPy2014: https://doi.org/10.48550/arXiv.1412.6367\n* Calibration procedures are described in J. Synch. Radiation 2020: https://doi.org/10.1107/S1600577520000776\n\nInstallation\n------------\n\nWith PIP\n........\n\nAs most Python packages, pyFAI is available via PIP::\n\n pip install pyFAI[gui]\n\nIt is advised to run this in a vitural environment.\nProvide the *--user* to perform an installation local to your user (not recommended).\nUnder UNIX, you may have to run the command via *sudo* to gain root access an\nperform a system wide installation (neither recommended).\n\n\nWith conda\n..........\n\npyFAI is also available via conda::\n\n conda install pyfai -c conda-forge\n\nTo install conda please see either `conda <https://conda.io/docs/install/quick.html>`_ or `Anaconda <https://www.continuum.io/downloads>`_.\n\nFrom source code\n................\n\nThe latest release of pyFAI can be downloaded from\n`Github <https://github.com/silx-kit/pyFAI/archive/main.zip>`_.\nPresently the source code has been distributed as a zip package.\nDownload it one and unpack it::\n\n unzip pyFAI-main.zip\n\nAs developement is also done on Github,\n`development branch is also available <https://github.com/silx-kit/pyFAI/archive/main.zip>`_\n\nAll files are unpacked into the directory pyFAI-main::\n\n cd pyFAI-main\n\nBuild it & test it::\n\n python3 run_tests.py\n\nFor its tests, pyFAI downloads test images from the internet.\nDepending on your network connection and your local network configuration,\nyou may have to setup a proxy configuration like this (no more needed at ESRF)::\n\n export http_proxy=http://proxy.site.org:3128\n\nFinally, install pyFAI in the virtualenv after testing it::\n\n pip install --upgrade .\n\nThe newest development version can also be obtained by checking out from the git\nrepository::\n\n git clone https://github.com/silx-kit/pyFAI.git\n cd pyFAI\n pip install --upgrade .\n\nIf you want pyFAI to make use of your graphic card, please install\n`pyopencl <http://mathema.tician.de/software/pyopencl>`_\n\nDocumentation\n-------------\n\nDocumentation can be build using this command and Sphinx (installed on your computer)::\n\n pip install -r requirements.txt\n python3 build-doc.py\n\n\nDependencies\n------------\n\nPython 3.7, ... 3.11 are well tested and officially supported.\nFor python 3.12, it requires silx version 2 which is still unreleased for now.\nFor full functionality of pyFAI the following modules need to be installed.\n\n* ``numpy`` - http://www.numpy.org\n* ``scipy`` \t - http://www.scipy.org\n* ``matplotlib`` - http://matplotlib.sourceforge.net/\n* ``fabio`` \t - http://sourceforge.net/projects/fable/files/fabio/\n* ``h5py``\t - http://www.h5py.org/\n* ``pyopencl``\t - http://mathema.tician.de/software/pyopencl/\n* ``pyqt5``\t - http://www.riverbankcomputing.co.uk/software/pyqt/intro\n* ``silx`` - http://www.silx.org\n* ``numexpr`` - https://github.com/pydata/numexpr\n\nThose dependencies can simply be installed by::\n\n pip install -r requirements.txt\n\n\nUbuntu and Debian-like Linux distributions\n------------------------------------------\n\nTo use pyFAI on Ubuntu/Debian the needed python modules\ncan be installed either through the Synaptic Package Manager\n(found in System -> Administration)\nor using apt-get on from the command line in a terminal::\n\n sudo apt-get install pyfai\n\nThe extra Ubuntu packages needed are:\n\n* ``python3-numpy``\n* ``python3-scipy``\n* ``python3-matplotlib``\n* ``python3-dev``\n* ``python3-fabio``\n* ``python3-pyopencl``\n* ``python3-pyqt5``\n* ``python3-silx``\n* ``python3-numexpr``\n\nusing apt-get these can be installed as::\n\n sudo apt-get build-dep pyfai\n\nMacOSX\n------\n\nOne needs to install `Python` (>=3.7) and `Xcode` prior to start installing pyFAI.\nThe compiled extension will use only one core due to the limitation of the compiler.\nOpenCL is hence greately adviced on Apple systems.\nThen install the missing dependencies with `pip`::\n\n pip install -r requirements.txt\n\n\nWindows\n-------\n\nUnder Windows, one needs to install `Python` (>=3.7) and the Visual Studio C++ compiler.\nThen install the missing dependencies with `pip`::\n\n pip install -r requirements.txt\n\nGetting help\n------------\n\nA mailing-list, pyfai@esrf.fr, is available to get help on the program and how to use it.\nOne needs to subscribe by sending an email to sympa@esrf.fr with a subject \"subscribe pyfai\".\n\n\nMaintainers\n-----------\n\n* J\u00e9r\u00f4me Kieffer (ESRF)\n\nContributors\n------------\n\n* Edgar Gutierrez Fernandez (ESRF)\n* Valentin Valls (ESRF)\n* Fr\u00e9d\u00e9ric-Emmanuel Picca (Soleil)\n* Thomas Vincent (ESRF)\n* Dimitris Karkoulis (Formerly ESRF)\n* Aurore Deschildre (Formerly ESRF)\n* Giannis Ashiotis (Formerly ESRF)\n* Zubair Nawaz (Formerly Sesame)\n* Jon Wright (ESRF)\n* Amund Hov (Formerly ESRF)\n* Dodogerstlin @github\n* Gunthard Benecke (Desy)\n* Gero Flucke (Desy)\n\nIndirect contributors (ideas...)\n--------------------------------\n\n* Peter Boesecke\n* Manuel S\u00e1nchez del R\u00edo\n* Vicente Armando Sol\u00e9\n* Brian Pauw\n* Veijo Honkimaki\n\n.. |Github Actions| image:: https://github.com/silx-kit/pyFAI/actions/workflows/python-package.yml/badge.svg\n.. |Appveyor Status| image:: https://ci.appveyor.com/api/projects/status/github/silx-kit/pyfai?svg=true\n :target: https://ci.appveyor.com/project/ESRF/pyfai\n.. |myBinder Launcher| image:: https://mybinder.org/badge_logo.svg\n :target: https://mybinder.org/v2/gh/silx-kit/pyFAI/main?filepath=binder%2Findex.ipynb\n.. |RTD docs| image:: https://readthedocs.org/projects/pyFAI/badge/?version=main\n :alt: Documentation Status\n :scale: 100%\n :target: https://pyfai.readthedocs.io/en/main/?badge=main\n.. |Zenodo DOI| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.832896.svg\n :target: https://doi.org/10.5281/zenodo.832896\n",
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