Python implementation of fast azimuthal integration
Project description
Main development website: https://github.com/silx-kit/pyFAI
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 option to perform an installation local to your user-space (not recommended). Under UNIX, you may have to run the command via sudo to gain root access and perform a system wide installation (which is neither recommended).
With conda
pyFAI is also available via conda:
conda install pyfai -c conda-forge
From source code
The current development version of pyFAI can be downloaded from Github. Presently the source code has been distributed as a zip package. Download it one and unpack it:
unzip pyFAI-main.zip
All files are unpacked into the directory pyFAI-main:
cd pyFAI-main
Install dependencies:
pip install -r requirements.txt
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 (not needed at ESRF):
export http_proxy=http://proxy.site.org:3128
Finally, install pyFAI in the virtualenv after testing it:
pip install .
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 .
If you want pyFAI to make use of your graphic card, please install pyopencl
Documentation
Documentation can be build using this command and Sphinx (installed on your computer):
python3 build-doc.py
Dependencies
Python 3.8, … 3.12 are well tested and officially supported. 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/
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 manually install a recent version of Python (>=3.8) prior to installing pyFAI. Apple provides only an outdated version of Python 2.7 which is now incomatible. If you want to build pyFAI from sources, you will also need Xcode which is available from the Apple store. 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 (>=3.8) prior to pyFAI. The Visual Studio C++ compiler is also needed when building from sources. 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)
Edgar Gutierrez Fernandez (ESRF)
Maciej Jankowski (ESRF)
Contributors
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
Project details
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