Green Urban Scenarios - A digital twin representation, simulation of urban forests and their impact analysis.
Project description
gus
Green Urban Scenarios - A digital twin representation, simulation of urban forests and their impact analysis.
Getting Started
Visit the GUS website documentation for help with installing GUS, code documentation, and a basic tutorial to get you started.
Install from PyPi
We publish GUS as pyGus package in PyPi. Dependencies can be found in the .toml file on the GUS GitHub page. Even though installation with Poetry is possible, the most stable installation can be done via pip.
$ pip install pygus
For further instructions and code documentation, visit GUS Code Documentation
Who maintains GUS?
The GUS is currently developed and maintained by Lucidminds and Dark Matter Labs members as part of their joint project TreesAI.
Notes
- The GUS is open for PRs.
- PRs will be reviewed by the current maintainers of the project.
- Extensive development guidelines will be provided soon.
- To report bugs, fixes, and questions, please use the GitHub issues.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file pygus-2.0.2.tar.gz.
File metadata
- Download URL: pygus-2.0.2.tar.gz
- Upload date:
- Size: 3.6 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.3.1 CPython/3.8.13 Darwin/20.6.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 4a9a9f1d3ebba4fd9f99c4bd1fff13bcc273f1b076a5e66888a3df1cea8aeab2 |
|
| MD5 | a8f3de1a2dbbdc4840b54f709fa5fa9e |
|
| BLAKE2b-256 | 28def1e33c2c9bdc45f6f84e90ef1b192c6220f2f7853e6a891f264920cd10e8 |
File details
Details for the file pygus-2.0.2-py3-none-any.whl.
File metadata
- Download URL: pygus-2.0.2-py3-none-any.whl
- Upload date:
- Size: 3.9 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.3.1 CPython/3.8.13 Darwin/20.6.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 8b19d0c7b82923ec8f50c3e159111fb3460e812ed65a28a34257c82a33c0cd7e |
|
| MD5 | bd9ec8248182f1725851e1c8e84b358c |
|
| BLAKE2b-256 | 0681e11bbcfb21a0046b8d81df59e18ce3fc73886f7dab165d8b3ec758595f20 |
