Getting Started with Larch

Larch provides both GUI applications and a programming library for visualizing and analyzing X-ray spectroscopy data. It can be slightly overwhelming to know where to get started with Larch. We’ll try to get you started using Larch, and then point to next places to go for getting the most out of it.

First, install Larch

If you are new to Larch, we recommend installing from the appropriate installer for your operating system listed in the Table of Larch Installers.

If you are familiar with Python and want to use Larch as a library, see the Downloading and Installation chapter.

Second, XASViewer and/or GSEMapViewer

If you are mostly interested in using Larch as a backend for the Athena and Artemis programs for XAFS Analysis, just install Larch and the latest version of Demeter, and Demeter should find and use Larch for EXAFS Analysis, replacing the older Ifeffit library and its many limitations.

However, Athena still has some limitations for XAFS Analysis, and development and support for it have declined in recent years. You may be interested in the XAS Viewer program for XAFS processing and visualization. At this writing, XAS Viewer is nearly a complete replacement for Athena, with several improvements in graphics and handling of large data sets. XAS Viewer is especially aimed at XANES Analysis, and so includes robust tools for peak-fitting, and machine-learning methods such as Principal Component Analysis, Partial Least Squares and LASSO regression.

If you are a user of the GSECARS microprobe beamline, you’ll want to start using the GSE Mapviewer program for reading, displaying, and working with X-ray fluorescence maps. Much of the documentation here discusses commands you can type in the “Larch Buffer”, available from the Mapviewer program for scripting and more detailed access to the data in the XRF map HDF5 files.

If you are a general-purpose user or ready for more control over data analysis for many types of data, the Larch GUI can help you browse through the available commands and data, and provide a good starting point for interactive, exploratory data analysis.

Third, start scripting with Larch and/or Python

Once you’ve done a little bit of GUI or interactive work, you may be ready to write scripts. Such scripts can help you automate repeated tasks and can build and remember more complex analyses. The combination of the high level commands of Larch and the interactive command-line GUI for exploratory data analysis are a great way to get started in writing your own scripts and building up more sophisticated programs.