A global coordinate system, with words
Converts Lat 43.258783, Lng 5.564971 to => brown, cat, house. Which is easier to remember or share.
It has an average precision of 1.45 meters. Take a look at the tests for a proof!
Try me!
How does it work?
Note: The algorithm has changed and this is not the current implementation.
This algorithm only gives a precision of 5 meters.
I'll write the description of the new algorithm soon.
| Step | Result |
|---|---|
| Start with the base coordinates | 43.258783, 5.564971 |
| Round to 4 digits after the dot | 43.2587, 5.5649 |
| Add 180 to the latitude, and 90 to the longitude in order to have only positive values | 133.2587, 185.5649 |
| Multiply by 10000, to have only integers | 1332587, 1855649 |
| Convert that to binary and concatenate them | 1010001010101011011010111000101000010100110 |
| Shuffle the bits | 1001100010101111110100110000001010010011100 |
| Split that into three binary numbers | 100110001010111, 111010011000000, 1010010011100 |
| Convert them back to base 10 | 19543, 29888, 5276 |
| Assign each number a word | brown, cat, house |
Contributing
Feel free to contribute, I love pull requests!
To run the project :
npm install
npm start
To build :
npm install
npm run build