PAN Blend xas packages

PyMca is set of applications and Python libraries for analysis of X-ray fluorescence spectra.

The applications included in this package are:

• edfviewer - Display and inspection of data files in ESRF Data Format
• elementsinfo - Displays element specific X-ray data
• mca2edf - Converts files from SPEC MCA format to EDF
• peakidentifier - Displays X-ray fluorescence peaks in a given energy range
• pymcabatch - Batch fitting of spectra
• pymcapostbatch - Post-processing of batch fitting results
• pymca - Interactive data-analysis
• pymcaroitool - Region-of-interest (ROI) imaging tool

The PyMca toolkit can read data files in SPEC, ESRF data file (EDF), OMNIC, HDF5, AIFIRA and SupaVisio formats.

This are the scripts of the package.

Quantum ESPRESSO (formerly known as PWscf) is an integrated suite of computer codes for electronic-structure calculations and materials modeling at the nanoscale. It is based on density-functional theory, plane waves, and pseudopotentials (both norm-conserving, ultrasoft, and PAW).

Features include:

• Ground-state single-point and band structure calculations using plane-wave self-consistent total energies, forces and stresses
• Separable norm-conserving and ultrasoft (Vanderbilt) pseudo-potentials, PAW (Projector Augmented Waves)
• Various exchange-correlation functionals, from LDA to generalized-gradient corrections (PW91, PBE, B88-P86, BLYP) to meta-GGA, exact exchange (HF) and hybrid functionals (PBE0, B3LYP, HSE)
• Car-Parrinello and Born-Oppenheimer Molecular Dynamics
• Structural Optimization including transition states and minimum energy paths
• Spin-orbit coupling and noncollinear magnetism
• Response properties including phonon frequencies and eigenvectors, effective charges and dielectric tensors, Infrared and Raman cross-sections, EPR and NMR chemical shifts
• Spectroscopic properties like K- and L1-edge X-ray Absorption Spectra (XAS) and electronic excitations

Larch is an open-source library and analysis toolkit for processing scientific data. Initially designed for x-ray spectroscopic and scattering data collected at modern synchrotrons and x-ray sources, Larch also provides many general-purpose processing and analysis tools for dealing with arrays of scientific data and organize complex data sets.

Larch is written in Python, making heavy use of the wonderful numpy, scipy, h5py, and matplotlib libraries, and can be used directly as a Python library or extended using Python. In addition, Larch provides a Python-like language (a macro language, or domain specific language) that is intended to be very easy to use for novices while also being complete enough for advanced data processing and analysis.

Larch has several related target application areas, including:

• XAFS analysis, becoming version 2 of the Ifeffit Package.
• Visualizing and analyzing micro-X-ray fluorescence maps.
• Quantitative X-ray fluorescence analysis.
• X-ray standing waves and surface scattering analysis.
• Data collection software for synchrotron data.

The essential idea is that having these different areas connected by a common macro language will strengthen the analysis tools available for all of them, and provide a very shallow barrier for those interested in scripting the manipulation and analysis of their data.

Currently, Larch provides a complete set of XAFS Analysis tools (replacing all of the Ifeffit package), has some support for visualizing and analyzing XRF maps and spectra, and has many extra tools for X-ray spectral analysis, data handling, and general-purpose data modeling.