Difference between revisions of "Main Page"

From cctbx_xfel
Jump to: navigation, search
(cctbx.xfel resources)
(cctbx.xfel resources)
Line 24: Line 24:
 
* [[2014_workshop | Powerpoint presentations]]
 
* [[2014_workshop | Powerpoint presentations]]
 
* [[Experiment-day guidelines]]: a short, very hands-on set of notes for online monitoring and data-processing using cctbx.xfel. This page assumes that the setup and tutorial have been completed.
 
* [[Experiment-day guidelines]]: a short, very hands-on set of notes for online monitoring and data-processing using cctbx.xfel. This page assumes that the setup and tutorial have been completed.
 +
* [[File formats]]: for developers, information on file formats ''cctbx.xfel'' uses
  
 
This project is under active development.  For any assistance, please contact the authors.
 
This project is under active development.  For any assistance, please contact the authors.

Revision as of 17:48, 29 November 2015

Open-source tools for free-electron laser data processing

cctbx.xfel is a suite of software tools designed to process diffraction data from serial femtosecond crystallography (SFX) measurements at an X-ray free-electron laser (XFEL). Built on the Computational Crystallographic Toolbox (cctbx), the same toolbox on which PHENIX, LABELIT, and post-refinement and merging program, PRIME are built, it enables the user to solve difficult problems relating to processing XFEL data. The programs and modules provided by cctbx.xfel can reduce a large set of still diffraction images recorded at Stanford’s Linac Coherent Light Source (LCLS) to a single MTZ file containing merged reflection intensities suitable for structure solution.

cctbx.xfel resources

The tutorials on this wiki provide detailed instructions for indexing and integrating still diffraction images extracted from the raw data streams recorded at the LCLS, including pre-processing steps such as dark pedestal generation and refinement of the detector geometry of the Cornell–SLAC pixel array detectors (CSPAD) in use at the CXI and XPP end stations. The tutorials also cover tools to efficiently leverage the LCLS computing cluster to process the thousands to millions of diffraction images that can be recorded in a short time.

Other related information:

This project is under active development. For any assistance, please contact the authors.