FIT2D is a general purpose 1 and 2 dimensional data analysis program. It is used for both interactive and "batch" data processing, and is used for different purposes. Calibration and correction of detector distortions is one of the main uses of FIT2D. Difficult data analysis problems may be tackled using fitting of user specified models. To enable model fitting to be performed on a wide variety of input data, many other more basic data analysis operations are also available. A wide variety of performant graphical display methods are available.
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
X-ray Fluorescence Toolkit (visualization and analysis of energy-dispersive X-ray fluorescence data). . The program allows both interactive and batch processing of large data sets and is particularly well suited for X-ray imaging. Its implementation of a complete description of the M shell is particularly helpful for analysis of data collected at low energies. It features, among many other things, the fundamental parameters method
Python toolkit for accelerated Nano-structures Crystallography and Coherent X-ray Imaging techniques. The software included in this package can be used for: 1. the computing of X-ray scattering using graphical processing units 2. X-ray wavefield propagation (from near to far field) 3. simulation and GPU-accelerated analysis of experiments using the ptychography and coherent diffraction imaging techniques See the full documentation at: http://ftp.esrf.fr/pub/scisoft/PyNX/doc/
software package developed by the Antwerp X-ray Imaging/Instrumentation Laboratory (AXiL) at the University of Antwerp. Its main purpose is to automate the processing of two dimensional x-ray diffraction images from scanning micro-XRPD or micro-XRPD tomography. It accepts images from flat area detectors and allows correction, calibration and modeling (Rietveld, Pawley, Pattern Decomposition). The primary goal is to visualize crystalline phase distributions in projection (2D scanning) or in a virtual cross section (tomography) of the object under investigation. Apart from the amount of material, structural properties and their changes within the object can be calculated and visualized as well.
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