Earth Time series Visualization

An application visualizing gridded geospatial time series data

A live demo can be viewed at: http://etv.ryandillon.net

Requirements

• Python3.4+
• An up-to-date web-browser that handles HTML5 and CSS Flexbox

Install

It is best to use a Python virtual environment when running Etv, particularly for ensuring the correct version of Django. A good place you virtual environment could be where the directory where you put your processed JSON data:

# Create a path for your Etv projects
mkdir ~/etv_projects

# Create your virtual environment for Python3
cd ~/etv_projects
virtualenv --python=python3 venv

Then just activate your virtual environment and install Etv via pip:

source venv/bin/activate
pip install etv

Quickstart

After installation, use the Etv command-line-interface (CLI) to create sample data and run the application. The first argument for all CLI commands is the path to your processed JSON data.

First, create some sample data from the NOAA NCOM regional ocean model, focussed on the waters off of Humboldt County, California:

Note

If you installed Etv in your virtual environment, you must activate it before runing the Etv CLI.

mkdir json
etv ./json create_sample_data

Then run the app via standard Django manage.py commands:

etv ./json manage runserver

• The default location for the app is http://localhost:8000
• Type Control-C on the terminal to close the app.

Authors

Ryan J. Dillon and Radovan Bast

Contributors

Hans Kristian Djuve

License

MPL 2.0 License. See the included license file.