Cinema SuperComputing Tutorial 2020

This tutorial introduces core Cinema concepts and functionality. As part of this tutorial, you will export a Cinema database from ParaView and run a Jupyter notebook workflow that takes in a Cinema database, updates it by calculating various image statistics and then views the new Cinema database in a browser-based Cinema:Explorer viewer.

To run this tutorial, you will need:

• The latest version of ParaView: https://www.paraview.org/download/
• Python 3.7 or above
• pandas, numpy
• os, shutil
• cinemasci v1.1 or above
• openCV 4.4 or above
• skimage (scikit-image)
• notebook, jupyterlab

A Note on Browser Security

To use Cinema:Explorer, you must allow local file access. Do this in the following way, but be sure to reset these options when you are done:

• Firefox (preferred)
  • type about:config in the navigaion bar
    • set privacy.file_unique_origin to false
    • set security.fileuri.strict_origin_policy to false
• Safari
  • Safari->Preferences->Advanced->Show Develop menu in menu bar
  • Safari->Develop->Disable Local File Restrictions (on)
• Chrome
  • open chrome with the option --disable-web-security
  • Mac example:
    • open -na "Google Chrome" cinema_explorer.html --args --user-data-dir="YOUR_PATH_TO_REPO" --disable-web-security

Starting the server

    python -m cinemasci.server --port 8200 --viewer view --data data/sphere.cdb