Publications about pyFAI#
PyFAI, a versatile library for azimuthal regrouping; J Kieffer and D Karkoulis; Journal of Physics: Conference Series (2013) 425 (20), pp202012; Initial publication where the usage of GPU is envisaged to overcome the speed limitation of azimuthal integration.
PyFAI: a Python library for high performance azimuthal integration on GPU; J Kieffer and J.P. Wright; Powder Diffraction (2013) 28 (S2), pp339-350; Introduces the concept of look-up table to register the pixel distribution.
- PyFAI: a Python library for high performance azimuthal integration on GPU;
Jérôme Kieffer and Giannis Ashiotis; PROC. OF THE 7th EUR. CONF. ON PYTHON IN SCIENCE (EUROSCIPY 2014); Presents the usage of sparse matrices to store the look-up table.
The fast azimuthal integration Python library: pyFAI; G. Ashiotis, A. Deschildre, Z. Nawaz, J. P. Wright, D. Karkoulis, F. E. Picca and J. Kieffer; Journal of Applied Crystallography (2015) 48 (2), 510-519; This publication provides a nice overview of the features introduced in version 0.11 and further developed in v0.12, v0.13 & v0.14.
New tools for calibrating diffraction setups; J. Kieffer, V. Valls, N. Blanc and C. Hennig; Journal of Synchrotron Radiation (2020) 27 (2), 558-566; Describes the new integration scheme, the new user interface and the calibration of goniometers.
Application of signal separation to diffraction image compression and serial crystallography; Jérôme Kieffer, Julien Orlans, Nicolas Coquelle, Samuel Debionne, Shibom Basu, Alejandro Homs, Gianluca Santonia and Daniele De Sanctis; Journal of Applied Crystallography (2025) 58 (1), 138-153; In depth explainaion of sigma-clipping background assessment and error models.
Which one should I cite? For the plain application of azimuthal averaging: JAC2015, for the calibration: JSR2020 and for advanced statistical analysis in azimuthal space: JAC2025. In case of doubt, the latest paper should be fine. There are already 1500 publications referring to pyFAI, some of them in the most prestigious scientific journals (Nature, Science, PNAS, …) and 44 other applications using pyFAI as a library.