Behavior

This class is the base class for all behavior classes. It contains the common methods for all behavior classes.

Constructor

Behavior(parameters, scenarios, variables[, ...])

Base class for the behavior of the MacroStat model.

Simulation and Behavior

Behavior.forward()	Forward pass of the behavior.
Behavior.initialize()	Initialize the behavior.
Behavior.step(t, scenario)	Step function of the behavior.

Differentiable Operations

Behavior.diffwhere(condition, x1, x2)	Where condition that is differentiable with respect to the condition.
Behavior.tanhmask(x)	Convert a variable into 0 (x<0) and 1 (x>0)
Behavior.diffmin(x1, x2)	Smooth approximation to the minimum B: https://mathoverflow.net/questions/35191/a-differentiable-approximation-to-the-minimum-function
Behavior.diffmax(x1, x2)	Smooth approximation to the minimum B: https://mathoverflow.net/questions/35191/a-differentiable-approximation-to-the-minimum-function
Behavior.diffmin_v(x)	Smooth approximation to the minimum.
Behavior.diffmax_v(x)	Smooth approximation to the maximum for a tensor.

Notes

The Behavior class is designed to be a flexible base class that allows users to implement their own model behavior while maintaining a consistent interface. The key methods that users need to implement are initialize() and step(), which define the model’s initialization and simulation behavior respectively.

Example

A typical implementation of a behavior class might look like:

>>> class MyBehavior(Behavior):
...     def initialize(self):
...         # Initialize state variables
...         self.state['x'] = torch.zeros(1)
...
...     def step(self, t, scenario):
...         # Update state variables
...         self.state['x'] = self.state['x'] + 1