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.
Basic skills: Linux at CHESS, Python programming at CHESS
- Skills: Linux command line, navigating CHESS filesystms, Python
Data analysis (low complexity): Azimuthal integration of 2D diffraction patterns
- Skills: CHAP, Python, Linux command line, navigating CHESS filesystems, Jupyter notebooks, matplotlib
Data analysis (medium complexity): Tomographic reconstruction
- Skills: CHAP, Python, Linux command line, navigating CHESS filesystems, NoMachine, NeXpy, Galaxy
Viewing metadata (demo): Web tutorial
- Skills: navigating and searching for CHESS datasets
Data visualization (low complexity): Browser-based data visualization dashboard
- Practice choosing a dataset, navigating through an image stack, zooming in and out, changing the color palette, switching between lin/log scale, dropping probes in multiple locations
- Skills: Examining detector images