NSLS-II Software Documentation
  • Event-Based Architecture
  • Examples
    • Perform a simple scan with a data table and plot
    • Retrieve metadata, tabular data, and image data
    • Re-plot saved data
    • Interruptions: interactively pause and resume
    • Concatenating plans
    • Fit and analyze peaks
    • How metadata is organized: understand the contents of the header
    • Export tabular data as a CSV file
    • Export images as TIFF files
    • Inspect or rehearse a plan without touching hardware (“simulation mode”)
    • Take baseline readings at the beginning and end
    • Use scans with adaptive step sizes
    • Take successive readings spaced exponentially in time or space
    • Add a progress bar to a fly scan
    • Access EPICS Archiver Appliance via the data broker
    • Troubleshoot a slow or stalling plan
    • Re-scan until fit achieves desired confidence
    • Scan a grid around each sample in a grid
  • Tutorials
  • Remote Access
  • Sandbox
  • Installation at a Beamline
  • Recommended Resources

Data Collection

  • bluesky
  • ophyd

Data Access and Management

  • databroker
  • amostra
  • datamuxer
  • suitcase

Data Analysis

  • scikit-beam

GitHub Links

  • NSLS-II Repositories
  • Wish List
  • Bug Reports
NSLS-II Software Documentation
  • Docs »
  • Examples
  • View page source

ExamplesΒΆ

  • Perform a simple scan with a data table and plot
  • Retrieve metadata, tabular data, and image data
  • Re-plot saved data
  • Interruptions: interactively pause and resume
  • Concatenating plans
  • Fit and analyze peaks
  • How metadata is organized: understand the contents of the header
  • Export tabular data as a CSV file
  • Export images as TIFF files
  • Inspect or rehearse a plan without touching hardware (“simulation mode”)
  • Take baseline readings at the beginning and end
  • Use scans with adaptive step sizes
  • Take successive readings spaced exponentially in time or space
  • Add a progress bar to a fly scan
  • Access EPICS Archiver Appliance via the data broker
  • Troubleshoot a slow or stalling plan
  • Re-scan until fit achieves desired confidence
  • Scan a grid around each sample in a grid
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