Tutorials

Tutorials explain the Python interface of pyFAI and use the jupyter notebook interface, formerly known as ipython notebooks. The two first tutorials are an introduction to the usage of pyFAI from Python for diffraction data reduction. The subsequent tutorials are more in depth explanation and require a good Python fluency and to a certain extent, of the pyFAI library.

• Introduction to the tutorials
• Geometries in pyFAI
• Orientation management
• Detector geometric distortions and corrections
• Calibrant selection and generation
• Re-calibration of a diffraction image with Jupyter
• Flatfied calibration
• Extracting ellipse parmeters from rings
• Pixel splitting
• Uncertainty propagation and error-models equivalence
• Azimuthal averaging in log-scaled bins
• Multi-geometry azimuthal integration
• Goniometer and translation table calibration
• Inpainting missing data
• Thick detectors
• Variance of SAXS data
• Weighted vs Unweighted average for azimuthal integration
• Signal separation
• High performance computing
• 2D Integration in non-azimuthal space
• Representation of a Fiber Diffraction / Grazing Incidence pattern
• Conclusions
• Using pyFAI with data from Synchrotron Soleil