Hands-On Exercises

The following hands-on exercises demonstrate various methods of analyzing and viewing x-ray detector images. All exercises (except the last one) require an activated CLASSE account and access to the CLASSE JupyterHub.

  1. Basic skills: Linux at CHESS, Python programming at CHESS

    • Skills: Linux command line, navigating CHESS filesystms, Python

  2. Data analysis (low complexity): Azimuthal integration of 2D diffraction patterns

    • Skills: CHAP, Python, Linux command line, navigating CHESS filesystems, Jupyter notebooks, matplotlib

  3. Data analysis (medium complexity): Tomographic reconstruction

    • Skills: CHAP, Python, Linux command line, navigating CHESS filesystems, NoMachine, NeXpy, Galaxy

  4. Viewing metadata (demo): Web tutorial

    • Skills: navigating and searching for CHESS datasets

  5. Scientific workflows (high complexity): Pegasus workflow management system

    • Skills: setting up and running Pegasus workflows at CHESS