WSWED3: Scientific Python for Data Analysis at NSLS-II

Virtual Workshop (Zoom Link:

Virtual Workshop

Zoom Link:


Using the Python programming language, users can build on NSLS-II's data acquisition, data access, and data analysis tools to automate the rote parts of their process and focus on the science. This workshop is a hands-on tutorial on using scientific Python for image analysis, visualization, and machine learning. NSLS-II beamline staff and Python experts from the NSLS-II scientific software group ("DAMA") will team up to walk through examples from a range of scientific domains, working from data acquisition through analysis. Topics covered will include handling of larger-than-memory datasets, parallelism, and adaptive experiment steering. Basic familiarity with Python usage will be assumed. Please bring a laptop; this is an interactive session.

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    • 13:00 13:30
      Introduction to the Interactive Tutorial and Bluesky 30m
      Speaker: Daniel Allan (NSLS-II Data Science and Systems Integration)
    • 13:30 14:00
      Adaptive Experiment Sampling with a Reinforcement-Learning Agent 30m
      Speaker: Daniel Olds (Beamline Scientist for NSLS-II's Pair Distribution Function Beamline)
    • 14:00 14:40
      Anomaly Detection in Time Series Data 40m
      Speaker: Tatiana Konstantinova (Post-doctoral Associate)
    • 14:40 15:00
      Break 20m
    • 15:00 15:30
      Boost Beamtime Productivity 30m
      Speaker: Andi Barbour (Scientist in NSLS-II's Soft X-ray Scattering Program)
    • 15:30 16:00
      Customizing Bluesky for XAFS 30m
      Speaker: Bruce Ravel (Lead Beamline Scientist for NIST's Beamline for Materials Measurement)
    • 16:00 16:30
      Questions, live demo requests, etc. 30m