This repository contains the source code for COVID-19 EnsembleVis, a visual analytics system that allows the assessment of ensembles and individual models at the county level, by enabling users to effortlessly navigate through and compare ensemble members considering their space and time dimensions. This visual interface provides an overview summary of ensemble data to assess uncertainty, identifies spatiotemporal trends, i.e., how a group of members change over space and time, and visually identifies differences between two or more ensemble members.
The team includes:
- Sanjana Srabanti (University of Illinois at Chicago)
- G. Elisabeta (Liz) Marai (University of Illinois at Chicago)
- Fabio Miranda (University of Illinois at Chicago)
You will need to install Node.js and Angular to build the interface and Jupyter to preprocess the data. You can install all prerequisites by first installing Anaconda (or miniconda) and running the following command:
conda install nodejs jupyter
COVID-19 EnsembleVis makes use of forecasts collected by the COVID-19 Forecast Hub, a site that maintains up-to-data records for forecasts of COVID-19 cases, deaths and hospitalizations in the US. The data is hosted on their GitHub repository, so in order to pre-process the data, first clone the repository:
git clone https://github.com/reichlab/covid19-forecast-hub
Next, run our parser notebook inside the preprocessing folder. The notebook considers that the COVID-19 Forecast Hub repository was cloned at the same level of the COVID-19 EnsembleVis repository. In other words:
./
../
covid-19-ensemblevis/
covid19-forecast-hub/
The jupyter notebook parser.ipynb will save a json file (models.json) inside the folder vis/src/assets/ containing the pre-processed data required by the interface.
The project was generated with Angular CLI version 12.2.0. First install Angular CLI using npm (the default package manager for Node.js):
npm install –g @angular/cli
Next, run ng build inside the vis folder to build the project, and ng serve to create a server and serve the COVID-19 EnsembleVis application. The interface will be available at http://localhost:4200/.