Bay Area UrbanSim (BAUS) Implementation
This is the UrbanSim implementation for the Bay Area. Documentation for the UrbanSim framework is available here. All documentation for Bay Area Urbansim is at: http://bayareametro.github.io/bayarea_urbansim/main/
Bay Area UrbanSim is written in Python and runs in a command line environment. It's compatible with Mac, Windows, and Linux, and with Python 2.7 and 3.5+. Python 3 is recommended.
- Install the Anaconda Python distribution (not strictly required, but makes things easier and more reliable)
- Clone this repository
- Create a Python environment with the current dependencies:
conda env create -f baus-env-2023.yml - Activate the environment:
conda activate baus-env-2023 - Store a
run_setup.yamlfile in the repository's main directory and use it to specify a run name - Use
run_setup.yamlto specify a path to source model inputs from (stored on MTC's servers for internal use) - Use
run_setup.yamlto specify a path for model outputs to write to (it's helpful if the outputs folder name matches the model run name) - Run
python baus.pyfrom the main model directory (more info about the command line arguments:python baus.py --help)
- Install the Slack SDK using
pip install slack_sdk - Set environment variable
SLACK_TOKEN = token(you will need an appropriate slack token from your MTC contact) - Set environment variable
URBANSIM_SLACK = TRUE
- Configure the location that BAUS will write the visualizer files to in
run_setup.yaml(stored on MTC's servers for internal visualization) - Open the visualizer from the BAUS repository to explore the model run, and/or
- Open the visualizer from the BAUS repository and publish it to the web (hosted on MTC's Tableau account). At this time runs can be removed from
model_run_inventory.csvto select the runs to be shown on the web tool
- See the repository's
gh-pagesbranch for instructions on installing the BAUS documentation packages and submitting documentation