Synchrotron X-ray data analysis in python
Project description
Documentation: http://xraypy.github.io/xraylarch
Larch is an open-source library and set of applications for processing and analyzing X-ray absorption and fluorescence spectroscopy data and X-ray fluorescence and diffraction image data from synchrotron beamlines. It is especially focussed on X-ray absorption fine-structure spectroscopy (XAFS) including X-ray absorption near-edge spectroscopy (XANES) and extended X-ray absorption fine-structure spectroscopy (EXAFS). It also supports visualization and analysis tools for X-ray fluorescence (XRF) spectra and XRF and X-ray diffraction (XRD) images as collected at scanning X-ray microprobe beamlines.
Larch is written in Python, making heavy use of the excellent scientific python libraries (numpy, scipy, h5py, matplotlib, and many more). Larch can be used as a Python library for processing and analyzing X-ray spectroscopy and imaging data. In addition, the applications built with it also use a built-in Python-like macro language for interactive and batch processing. This embedded “miniPython” language is intended to be very easy to use for novices while also being complete enough to automate data processing and analysis and to encourage and facilitate a gentle transition to transition from GUI-only analyses to scripted and programmatic analysis of larger data sets, and allows Larch to be run as a service, interacting with other processes or languages via XML-RPC, and so be used by the popular Demeter XAFS application suite.
Larch is distributed under an open-source license that is nearly identical to the BSD license. It is under active and open development centered at the GeoScoilEnviroCARS sector of the Center for Advanced Radiation Sources at the University of Chicago has been supported by the US National Science Foundation - Earth Sciences (EAR-1128799), and Department of Energy GeoSciences (DE-FG02-94ER14466). In addition, funding specifically for Larch was granted by the National Science Foundation - Advanced CyberInfrastructure (ACI-1450468).
The best citable reference for Larch is M. Newville, Larch: An Analysis Package For XAFS And Related Spectroscopies. Journal of Physics: Conference Series, 430:012007 (2013).
Larch Applications
These applications installed with Larch, in addition to a basic Python library. Here, GUI = Graphical User Interface, CLI = Command Line Interface, and beta indicates a work in progress.
Application Name |
GUI/CLI |
Description |
---|---|---|
larch |
CLI |
simple shell command-line interface |
Larch GUI |
GUI |
enhanced command-line interface with data browser |
Larix (was XAS Viewer) |
GUI |
XAFS Processing and Analysis: XANES pre-edge peak fitting, linear analysis, PCA/LASSO, EXAFS processing, Running Feff, fitting EXAFS data to Feff paths. |
GSE Map Viewer |
GUI |
XRF Map Viewer for GSECARS X-ray microprobe data. |
larch_xrf |
GUI |
Display and analyze XRF Spectra. |
larch_xrd1d |
GUI |
Display and work with 1-D XRD patterns, integrate XRD images, search for XRD patterns of known structures |
feff6l |
CLI |
Feff 6 EXAFS calculations |
feff8l |
CLI |
Feff 8 EXAFS calculations (no XANES) |
qtrixs |
GUI beta |
Display RIXS planes, take profiles |
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file xraylarch-0.9.81.tar.gz
.
File metadata
- Download URL: xraylarch-0.9.81.tar.gz
- Upload date:
- Size: 21.5 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 34ca8da369176d89ff89e1d969972c139cd6a2a8a8b602a5afaac1ca52425108 |
|
MD5 | 3cd028e1488d02c08c0738f4d3b01fa0 |
|
BLAKE2b-256 | 5a93f19717fd580ed2f4000e362d24f5fefdc20857a9a80ce593a7f7813160f3 |
File details
Details for the file xraylarch-0.9.81-py3-none-any.whl
.
File metadata
- Download URL: xraylarch-0.9.81-py3-none-any.whl
- Upload date:
- Size: 21.2 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3a7eb4fe22825c7fb4ff58f5c4f1e45ec701a0caf8e0593a7d02e0d3725bd654 |
|
MD5 | 553ea5495bf52d8a9aa95ad319f8f484 |
|
BLAKE2b-256 | 10497b5343ce1eca058607f96cb472fb4fc767b9ed437cacd9bd19859835e515 |