This work is protected by the CC BY-NC-ND 4. license
The system visualises the acctual Solar System data provided by the NASA JPL Horizons service. There are two visualisation modes:
- Solar System,
- Planet & its satellites.
Both are dependend on the user selected parameters.
"Solar System" mode:
- Start date - Defines the beginning of the time frame used in the visualisation.
- End date (optional) - Defines the end date of the time frame. The visualisation freezes once it reaches the end date. If not set, the visualisation will continue in real time.
- Speed mode & Defines the visualisation speed which is defined by the time needed for one jump - transition between two subsequent orbit points.
The available speed modes are defined as follows:
- Real Time - one jump* corresponds to 1 second in the real world.
- Medium - one jump corresponds to 2.4 hours in the real world.
- Fast - one jump corresponds to 4.8 hours in the real world.
"Planet & its satellites" mode:
- Planet - To be selected from the planets of the solar system.
- Start date - Defines the beginning of the time frame used in the visualisation.
- End date (optional) - Defines the end date of the time frame. The visualisation freezes once it reaches the end date. If not set, the visualisation will continue in real time.
- Speed mode & Defines the visualisation speed which is defined by the time needed for one jump - transition between two subsequent orbit points.
jump - trasnition from one orbit point to another
Frontend part is build using BabylonJS web rendering engine along with TypeScript and React for the UI.
Backend part is build using Flask and MongoDB.
To run the project locally:
cd frontend
npm install
npm start
Then go to http://localhost:3000/ page in your browser.
To run tests:
cd frontend
yarn test
For backend setup there is a need to create .env file under /app directory.
To backend server and database locally:
cd app
docker-compose up --build
See logs:
sudo docker logs <app_image_id>
Run tests:
sudo docker exec -it <app_image_id> pytest test.py
Useful docker commands: To check app_image_id please run
sudo docker container ls
and find the ID of app_web image.
To remove all images
docker prune -a