{"id":27944758,"url":"https://github.com/udst/bayarea_urbansim","last_synced_at":"2025-05-07T12:54:25.544Z","repository":{"id":55893143,"uuid":"12739394","full_name":"UDST/bayarea_urbansim","owner":"UDST","description":"UrbanSim implementation for the San Francisco Bay Area","archived":false,"fork":false,"pushed_at":"2024-02-23T01:35:02.000Z","size":67141,"stargazers_count":14,"open_issues_count":3,"forks_count":27,"subscribers_count":16,"default_branch":"master","last_synced_at":"2024-04-16T05:28:47.813Z","etag":null,"topics":["bay-area","data-science","modeling","simulation","urbansim"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/UDST.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2013-09-10T20:10:03.000Z","updated_at":"2023-04-24T19:07:33.000Z","dependencies_parsed_at":"2023-12-22T11:02:11.080Z","dependency_job_id":"b75a5bd8-0dd7-4b7f-80d4-4f02c2e2a5d8","html_url":"https://github.com/UDST/bayarea_urbansim","commit_stats":{"total_commits":1804,"total_committers":26,"mean_commits":69.38461538461539,"dds":0.6191796008869179,"last_synced_commit":"b78d5d68dc9b05b1433041f292b7ceb957c0242d"},"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UDST%2Fbayarea_urbansim","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UDST%2Fbayarea_urbansim/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UDST%2Fbayarea_urbansim/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UDST%2Fbayarea_urbansim/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/UDST","download_url":"https://codeload.github.com/UDST/bayarea_urbansim/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252882817,"owners_count":21819153,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bay-area","data-science","modeling","simulation","urbansim"],"created_at":"2025-05-07T12:54:24.360Z","updated_at":"2025-05-07T12:54:25.532Z","avatar_url":"https://github.com/UDST.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"DRAFT Bay Area UrbanSim (BAUS) Implementation\n=======\n\n[![Build Status](https://travis-ci.org/UDST/bayarea_urbansim.svg?branch=master)](https://travis-ci.org/UDST/bayarea_urbansim)\n\nThis is the DRAFT UrbanSim implementation for the Bay Area. Policy documentation for the Bay Area model is available [here](http://data.mtc.ca.gov/bayarea_urbansim/) and documentation for the UrbanSim framework is available [here](https://udst.github.io/urbansim/).\n\n* Install Python for your OS ([Anaconda](https://www.continuum.io/downloads) highly suggested)\n* Clone this repository\n* Install dependencies using `pip install -r requirements.txt` (may need to uncomment out pandana)\n* Get data using `python baus.py -c --mode fetch_data` (you will need an appropriately configured AWS credentials file which you must get from your MTC contact)\n* Preprocess data using `python baus.py -c --mode preprocessing`\n* Run a simulation using `python baus.py -c` (default mode is simulation)\n\n### An overview of baus.py\n \nbaus.py is a command line interface (cli) used to run Bay Area UrbanSim in various modes.  These modes currently include:\n\n* estimation, which runs a series of models to save parameter estimates for all statistical models\n* simulation, which runs all models to create a simulated regional growth forecast\n* fetch_data, which downloads large data files from Amazon S3 as inputs for BAUS\n* preprocessing, which performas long-running data cleaning steps and writes newly cleaned data back to the binary h5 file for use in the other steps\n* baseyearsim which runs a \"base year simulation\" which summarizes the data before the simulation runs (during simulation, summaries are written after each year, so the first year's summaries are *after* the base year is finished - a base year simulation writes the summaries before any models have run)\n\n### Urban Analytics Lab (UAL) Improvements\n\n#### Data schemas\n\n* Builds out the representation of individual housing units to include a semi-persistent tenure status, which is assigned based on characteristics of initial unit occupants\n* Joins additional race/ethnicity PUMS variables to synthetic households [NB: currently missing from the reconciled model, but will be re-added]\n* Adds a representation of market rents alongside market sale prices\n\n#### Model steps\n\n* Residential hedonics predict market rents and sale prices separately, with rents estimated from Craigslist listings\n* Household move-out choice is conditional on tenure status\n* Household location choice is modeled separately for renters and owners, and includes race/ethnicity measures as explanatory variables\n* Developer models are updated to produce both rental and ownership housing stock\n\nNotebooks, work history, code samples, etc are kept in a separate [bayarea_urbansim_work](https://github.com/ual/bayarea_urbansim_work) repository. \n\n#### Current status (August 2016)\n\n* All of the UAL alterations have been refactored as modular orca steps\n* This code is contained in `baus/ual.py`, `configs/ual_settings.yaml` and individual `yaml` files as needed for regression models that have been re-estimated\n* There are *no* changes to `urbansim`, `urbansim_defaults`, or MTC's orca initialization and model steps\n* MTC and UAL model steps can be mixed and matched by passing different lists to orca; see `run.py` for examples\n* The UAL model steps document and test for required data characteristics, using the [orca_test](https://github.com/udst/orca_test) library\n\n### Outputs from Simulation (written to the runs directory)\n\nALL OUTPUT IN THIS DIRECTORY IS NOT OFFICIAL OUTPUT. PLEASE CONTACT MTC FOR OFFICIAL OUTPUTS OF THE LAST PLAN BAY AREA.\n\n`[num]` = a positive integer used to identify each successive run.  This number usually starts at 1 and increments each time baus.py is called.\n\nMany files are output to the `runs/` directory. They are described below.\n\nfilename |description\n----------------------------|-----------\nrun[num]\\_topsheet\\_[year].csv | An overall summary of various housing and employment outcomes summarized by very coarse geographies.\nrun[num]_parcel_output.csv \t\t| A csv of all new built space in the region.  This has a few thousand rows and dozens of columns which contain various inputs and outputs, as well as debugging information which helps explain why each development was picked by UrbanSim.\nrun[num]\\_parcel_data\\_[year].csv \t\t\t|A CSV with parcel level output for *all* parcels with lat, lng and includes change in total_residential_units and change in total_job_spaces, as well as zoned capacity measures.\nrun[num]\\_building_data\\_[year].csv \t\t\t|The same as above but for buildings.\nrun[num]\\_taz\\_summarie\\s_[year].csv \t\t\t|A CSV for [input to the MTC travel model](http://analytics.mtc.ca.gov/foswiki/UrbanSimTwo/OutputToTravelModel)\nrun[num]\\_pda_summaries\\_[year].csv, run[num]\\_juris_summaries\\_[year].csv, run[num]\\_superdistrict_summaries\\_[year].csv | Similar outputs to the taz summaries but for each of these geographies.  Used for understanding the UrbanSim forecast at an aggregate level.\nrun[runnum]_dropped_buildings.csv     | A summary of buildings which were redeveloped during the simulated forecast.\nrun[runnum]_simulation_output.json | Used by the web output viewer.\n\n\n### Directory structure\n\n* baus/ contains all the Python code which runs the BAUS model.\n* data/ contains BAUS inputs which are small enough to store and render in GitHub (large files are stored on Amazon S3) - this also contains lots of scenario inputs in the form of csv files.  See the readme in the data directory for detailed docs on each file.\n* configs/ contains the model configuration files used by UrbanSim.  This also contains settings.yaml which provides simulation inputs and settings in a non-tabular form. \n* scripts/ these are one-off scripts which are used to perform various input munging and output analysis tasks.  See the docs in that directory for more information.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fudst%2Fbayarea_urbansim","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fudst%2Fbayarea_urbansim","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fudst%2Fbayarea_urbansim/lists"}