Pythagora is an agent-based modeling package that allows for the construction of experiments to test the impact of select types of social networks on production and consumption outcomes. Specifically, _Pythagora_ tests how individuals (agents) in small-world social networks and scale-free social networks (as well as control versions of these networks) buy and sell new types of pottery based on interactions within their social networks.
Agents in Pythagora have complex social lives: they belong to communities and are connected in social networks both inside and outside those communities. The purpose of this multidimensional social landscape is to test the impact of different types of social relationships on what individual agents buy and sell, and how these individual transactions build over time to create long-term production and consumption trends.
While Pythagora was designed to test popularity changes in pottery styles in the ancient Mediterranean world, it can be used to test popularity changes for any type of object during any time period.
Pythagora was developed by Sarah T. Wilker, PhD & Annie K. Lamar, PhD.
| Module | agents |
This module contains the constructors and all methods for agents in the marketplace. There are currently two types of marketplace agents you can implement: |
| Module | controls |
This module implements support methods for the control experiments for both the small world and scale free network protocols. This includes initialization methods and information file generation. This file is the equivalent of `scalefree... |
| Module | experiments |
The experiments module is the primary module with which users will interact. From this module, you can run every kind of experiment and adjust every parameter. |
| Module | generate |
Includes all methods needed to generate initial marketplace environment. |
| Module | groups |
This file implements group structures for markets, including Community objects (groups of buyers) and CommunitySet objects (groups of communities). |
| Module | logger |
This module implements the Logger class and its supporting methods. The Logger class is the key to accessing results from social network experiments without writing any analysis code in Python. |
| Module | market |
This module contains methods that support the purchasing and removal of items in the market. |
| Module | scalefree |
This module contains methods to initialize and compute metrics for a scale free simulation. |
| Module | smallworld |
This module contains methods to initialize and compute metrics for a small-world simulation. |