Resiliency is an ensemble technique that considers how frequently a geographic entity (e.g., county) falls in a particular bin across multiple comparable data binning methods.
- Open the command line/terminal on your machine and navigate to this project's top-level directory (i.e. where this file is).
- Download and install node, npm from https://nodejs.org/en/download/. We developed and tested the app on {Node, NPM}: {v14.15.5, 6.14.11}. Optionally, use the nvm (Node Version Manager) to quickly install and use different versions of node via the command line.
npm install -g @angular/cli@13.1.1to install the desired angular-cli used to run ng-* commands.npm install- installs required libraries from package.json.
ng serve- compile and serve the application locally- Open the browser at http://localhost:4200
- Enjoy!
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ng build --configuration production --build-optimizer --output-hashing=all- build the app and push the output into angular.json >outputPathdirectory (default value = "dist/"). -
ng build --configuration production --build-optimizer --baseHref=/resiliency-app/ --output-hashing=all- build the app for deploying at a public URL with /resiliency-app/ base prefix.
Resiliency was created by Arpit Narechania, Alex Endert, and Clio Andris of the Georgia Tech Visualization Lab. We thank the members of the Georgia Tech Visualization Lab for their support and constructive feedback.
@InProceedings{narechania2023resiliency,
author = {Narechania, Arpit and Endert, Alex and Andris, Clio},
title = {{Resiliency: A Consensus Data Binning Method}},
booktitle = {12th International Conference on Geographic Information Science (GIScience 2023)},
pages = {55:1--55:7},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
year = {2023},
volume = {277},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
doi = {10.4230/LIPIcs.GIScience.2023.55}
}The software is available under the MIT License.
If you have any questions, feel free to open an issue or contact Arpit Narechania.