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.

Back to main agenda

    • 1
      Introduction to the Interactive Tutorial and Bluesky
      Speaker: Daniel Allan (NSLS-II Data Science and Systems Integration)
    • 2
      Adaptive Experiment Sampling with a Reinforcement-Learning Agent
      Speaker: Daniel Olds (Beamline Scientist for NSLS-II's Pair Distribution Function Beamline)
    • 3
      Anomaly Detection in Time Series Data
      Speaker: Tatiana Konstantinova (Post-doctoral Associate)
    • 2:40 PM
    • 4
      Boost Beamtime Productivity
      Speaker: Andi Barbour (Scientist in NSLS-II's Soft X-ray Scattering Program)
    • 5
      Customizing Bluesky for XAFS
      Speaker: Bruce Ravel (Lead Beamline Scientist for NIST's Beamline for Materials Measurement)
    • 6
      Questions, live demo requests, etc.