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/

Installation

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.

1. Install the Anaconda Python distribution (not strictly required, but makes things easier and more reliable)
2. Clone this repository
3. Create a Python environment with the current dependencies: conda env create -f baus-env-2023.yml
4. Activate the environment: conda activate baus-env-2023
5. Store a run_setup.yaml file in the repository's main directory and use it to specify a run name
6. Use run_setup.yaml to specify a path to source model inputs from (stored on MTC's servers for internal use)
7. Use run_setup.yaml to specify a path for model outputs to write to (it's helpful if the outputs folder name matches the model run name)
8. Run python baus.py from the main model directory (more info about the command line arguments: python baus.py --help)

Optional Slack Messenger

• The Slack SDK will be installed as part of the environment creation
• Slack task integration is enabled by default (--disable-slack flag set to False).
• Set environment variables as appropriate for API communication SLACK_TOKEN
• Set environment variable URBANSIM_SLACK = TRUE

Optional Asana Integration

• The Asana SDK will be installed as part of the environment creation
• Asana task integration is disabled by default (--enable-asana flag set to False).
• Set environment variables as appropriate for API communication (ASANA_TOKEN, ASANA_CLIENT_ID, ASANA_SECRET)

Optional Model Run Visualizer

• Configure the location that BAUS will write the visualizer files to in run_setup.yaml (typically stored on the M-drive)
• 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.csv to select the runs to be shown on the web tool

Documentation

• See the repository's gh-pages branch for instructions on installing the BAUS documentation packages and submitting documentation