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Container Image Overview

Provides the HEFS-FEWS Hub container image, designed for use on TEEHRHub and similar JupyterHub deployments, to support the exploration of HEFS ensembles using FEWS. Part of a CIROH-supported project.

The image is based on AlmaLinux 8.10 (chosen for official FEWS support), and includes:

  • JupyterLab for interactive Python development and dashboarding
  • XFCE desktop environment and TurboVNC for a full-featured remote desktop, allowing users to run FEWS in a graphical environment
  • Pre-installed FEWS binaries, and AWS CLI for data access
  • The hefs-fews-hub python package (also part of this repository)

This setup enables users to analyze hydrologic ensemble forecasts and interact with FEWS in a cloud-hosted desktop environment.

Warning! This is currently highly experimental!

Signing in to HEFS-FEWS at TEEHR-Hub

  1. Go to https://teehr-hub.rtiamanzi.org/hub/spawn
  2. Sign in with your github account (you'll need to create one if you don't have it)
  3. From the list, select HEFS-FEWS Evaluation System. Click Start
  4. When JupyterHub starts, Go to Desktop
  5. The first time you login, open the terminal in the Desktop and run cp /opt/hefs_fews_dashboard/dashboard.desktop . This will create a desktop icon to start the dashboard. You should only need to do this once.
  6. Select the RFC you wish to work with
  7. Specify a directory path. Data downloaded to the /home/jovyan directory will persist between sessions.
  8. After downloading the configuration, click the FEWS icon to start FEWS.

Things to watch out for:

  • If the remote desktop is idle for too long, you may get logged out and may need to restart TEEHRHub!

TODO: Selecting and configuring your FEWS standalone [WIP]

Dashboard approach:

  1. Start up TEEHRHub
  2. Select appropriate image
  3. Go to Remote Desktop
  4. Click on "Launch" icon to launch dashboard
  5. Select the desired standalone
  6. Click Configure Standalone button
  7. Double-click the FEWS desktop icon when it appears

OR, Notebook approach:

  1. Run the notebook dashboard.ipynb
  2. Follow steps 5-7 above

About

A Docker file and collection of python scripts supporting the exploration of HEFS ensembles using FEWS within the TEEHRHub jupyterhub deployment.

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  • Python 54.3%
  • Dockerfile 21.3%
  • Jupyter Notebook 19.9%
  • Shell 4.5%