Framework for stock-flow consistent agent-based modeling, being developed at the German Aerospace Center (DLR) for and in the scientific context of energy systems analysis, however, it is widely applicable in other scientific fields.
Project description
sfctools - A toolbox for stock-flow consistent, agent-based models
Sfctools is a lightweight and easy-to-use Python framework for agent-based macroeconomic, stock-flow consistent (ABM-SFC) modeling. It concentrates on agents in economics and helps you to construct agents, helps you to manage and document your model parameters, assures stock-flow consistency, and facilitates basic economic data structures (such as the balance sheet).
Installation
In a terminal of your choice, type:
pip install sfctools
see https://pypi.org/project/sfctools/
Usage
from sfctools import Agent,World
class MyAgent(Agent):
def __init__(self, a):
super().__init__(self)
self. = a
my_agent = MyAgent()
print(my_agent)
print(World().get_agents_of_type("MyAgent"))
| Author Thomas Baldauf, German Aerospace Center (DLR), Curiestr. 4 70563 Stuttgart | thomas.baldauf@dlr.de | version: 0.5 (Beta) | date: February 2022
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