metaheuristic_designer.parameter_schedules.step_schedule module

Schedule that changes value at discrete progress thresholds.

class StepSchedule(steps)

Bases: SchedulableParameter

Schedule defined by a dictionary of progress-value pairs.

At progress p, the schedule returns the value associated with the largest key ≤ p. This produces a step function.

Parameters:

stepsdict

Mapping of progress thresholds (floats in [0, 1]) to the values that should be active at or after that threshold.

Parameters:

steps (dict[float, Any])

Methods

__call__(progress)	Shorthand for evaluate().
evaluate(progress)	Return the parameter value at the given progress.

evaluate(progress)

Return the parameter value at the given progress.

Return type:

float

Parameters:

progressfloat

Current progress, a number between 0 (start) and 1 (end).

Returns:

Any

The parameter value at this stage of the optimization.

Parameters:

progress (float)

Notes

The return value is not restricted to numbers. You can return: * a float (e.g., a linearly decaying mutation strength), * an int (e.g., a discrete number of mutated components), * a bool (e.g., switching on/off a feature after a threshold), * a string (e.g., switching between strategies), or * any other object that the consuming component expects.

This makes schedules suitable for changing discrete algorithm choices as well as continuous numerical parameters.