metaheuristic_designer.parameter_schedules.threshold_schedule module

Schedule that switches between two values at a fixed progress threshold.

class ThresholdSchedule(init_value, final_value, threshold=0.5)

Bases: SchedulableParameter

Schedule that returns init_value until progress reaches threshold, then switches to final_value.

Parameters:

init_valuefloat

Value used before the threshold.

final_valuefloat

Value used after the threshold.

thresholdfloat, optional

Progress point at which the switch occurs (default 0.5).

Parameters:

• init_value (float)

• final_value (float)

• threshold (float)

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.