Skip to main content

Agent-based modeling toolkit

Project description

Description

‘pyabm’ is an agent-based modeling toolkit written to simplify coding and running agent-based models int he Python programming language. pyabm includes tools to output model results (as text files, plots or ESRI shapefiles), and has a parameter handling system to ease the process of model testing and validation, and of running multiple scenarios with varying model parameters.

The model was constructed by Alex Zvoleff as part of his dissertation research at San Diego State University (SDSU) in the Department of Geography. Contact Alex Zvoleff or Prof. Li An at SDSU with any questions.

See the pyabm website for more information, past releases, publications, and recent presentations.

Getting the Code

Stable releases of pyabm are available from the Python Package Index (PyPI).

The latest version of the code (unstable) is available as a zipped snapshot from Github.

You can also browse the source at GitHub.

The source can also be downloaded via git from:

git://github.com/azvoleff/pyabm.git

Author Contact Information

Alex Zvoleff
SDSU/UCSB Joint Doctoral Candidate
Department of Geography
San Diego State University
5500 Campanile Dr.
San Diego, CA 92182-4493

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyabm-0.3.1.zip (52.3 kB view details)

Uploaded Source

Built Distributions

pyabm-0.3.1.win-amd64.exe (248.9 kB view details)

Uploaded Source

pyabm-0.3.1.win32.exe (221.3 kB view details)

Uploaded Source

pyabm-0.3.1-py2.7.egg (43.7 kB view details)

Uploaded Egg

File details

Details for the file pyabm-0.3.1.zip.

File metadata

  • Download URL: pyabm-0.3.1.zip
  • Upload date:
  • Size: 52.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for pyabm-0.3.1.zip
Algorithm Hash digest
SHA256 c0257bb23a5f27a09cbc7c3cb7b3b8c19bf755a66076cb6757c89ff18b37764a
MD5 890d1a83b900120d69e3e7d607f0e46e
BLAKE2b-256 cd63b69defe55215466ffbda905bee5692267d9dc1fed097c0363e2c9dda7097

See more details on using hashes here.

File details

Details for the file pyabm-0.3.1.win-amd64.exe.

File metadata

File hashes

Hashes for pyabm-0.3.1.win-amd64.exe
Algorithm Hash digest
SHA256 e99994e7634219c4e3f981f226af669e79e9f074846dfc6dbe10b6ee2ff7233d
MD5 6e9de0f35e7bf1062fcf040b61d28644
BLAKE2b-256 54b89eefbd6b0d465ce1b77b1658357b5bf66f71d5854e7de83f8f9df8f690f0

See more details on using hashes here.

File details

Details for the file pyabm-0.3.1.win32.exe.

File metadata

  • Download URL: pyabm-0.3.1.win32.exe
  • Upload date:
  • Size: 221.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for pyabm-0.3.1.win32.exe
Algorithm Hash digest
SHA256 0d4308fda5806e362a95565cad78f658d966fe58a8e5025bf04d28d36603603b
MD5 fe04efb421507dd0f350f164a4e35e97
BLAKE2b-256 b1800b0c7b4692753d878b347ecff4c2e815b6ef914de45e0efc553215de30ca

See more details on using hashes here.

File details

Details for the file pyabm-0.3.1-py2.7.egg.

File metadata

  • Download URL: pyabm-0.3.1-py2.7.egg
  • Upload date:
  • Size: 43.7 kB
  • Tags: Egg
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for pyabm-0.3.1-py2.7.egg
Algorithm Hash digest
SHA256 2cf63b9033a18d1d7d4a3166b5c56051c8897dc252ddb1109fca9b13bbbdede4
MD5 07cb9e6a9b22933989c792be23088c83
BLAKE2b-256 b8c7e17a9d6fe32457ab131d91339750de0b70d08ab3f183ffaf8823a34a5c6a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page