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This site documents the usage of "psana python", which is software that can be used to analyze LCLS data.  Using relatively simple python code, it is possible to analyze LCLS data in parallel on hundreds of CPU cores, both offline and in real-time while data is being taken. NOTE: the graphical LCLS analysis tool AMI is used for many routine real-time monitoring plots.  psana-python is typically used for real-time analysis that cannot be done in AMI and for offline analysis.

Getting Started

Before getting started, please consider if the LCLS supported frameworks will work for you. Due to the complexity of our systems and the changing nature of our hardware and setup, there some non-negligible overhead in writing your own analysis code at the psana-level.

• One choice is a crystallography pipeline as Cheetah or CCTBX. LCLS staff can help you to make connections with experts and support the necessary facility setup. 
• A second, often used model is to use the small data & cube/binning setup described here: smalldata_tools: Analysis tools for aligned data
  • This code wraps the psana code described below and saved hdf5 files that can be further analyzed as the user group desires.

To get started with a simple 17-line introductory script, and see a list of psana features click here.  This link also shows you how to login to the analysis computers.

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• Get a computer 

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  PCDS:Accounts PCDS:Accounts linkText account href PCDS:Accounts

  at LCLS

• Learn how to use the batch system to run analysis jobs.

• Locate the 

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  linkText data of your experiment href PCDS:Managing Files

• Look through our 

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  PCDS:Data Retention Policy PCDS:Data Retention Policy linkText Data Retention Policies href PCDS:Data Retention Policy

• The LCLS real-time online graphical analysis tool 

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  linkText AMI href PCDS:AMI Online Monitoring

• How to get remote computer graphics working (e.g. on your laptop) 

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  linkText Remote Visualization href PCDS:Remote Visualization

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