LogInfo

class ioh.iohcpp.LogInfo(self, evaluations: int, raw_y: float, raw_y_best: float, transformed_y: float, transformed_y_best: float, y: float, y_best: float, x: collections.abc.Sequence[float], violations: collections.abc.Sequence[float], penalties: collections.abc.Sequence[float], optimum: ioh.iohcpp.RealSolution, has_improved: bool = False)

Bases: object

LogInfo struct. Gets passed to the call method of a logger when it is invoked.

Parameters:

• evaluations (int) – The current number of evaluations

• raw_y (float) – The raw current fitness value

• raw_y_best (float) – The raw current best fitness value

• transformed_y (float) – The transformed current fitness value

• transformed_y_best (float) – The transformed current best fitness value

• y (float) – The transformed current fitness value with constraints applied

• y_best (float) – The transformed current best fitness value with constraints applied

• x (numpy.ndarray | list) – The current solution passed to problem

• violations (numpy.ndarray | list) – The current solution constraint violations

• penalties (numpy.ndarray | list) – The current solution constraint penalties

• optimum (Solution) – The optimum solution for the problem

• has_improved (bool = False) – Whether the evaluation has caused an improvement in the objective value

Attributes Summary

evaluations	The number of function evaluations performed on the current problem so far
has_improved	Whether the last call to problem has caused global improvement.
objective	The optimum of the problem and its objective value, as a new RealSolution (a copy)
penalties	first the total, then one per constraint
raw_y	(self) -> float
raw_y_best	(self) -> float
transformed_y	(self) -> float
transformed_y_best	(self) -> float
violations	first the total, then one per constraint
x	The current solution passed to problem, as a new numpy array (float64, also for integer problems)
y	(self) -> float
y_best	(self) -> float

Attributes Documentation

evaluations

The number of function evaluations performed on the current problem so far

has_improved

Whether the last call to problem has caused global improvement.

objective

The optimum of the problem and its objective value, as a new RealSolution (a copy)

penalties

first the total, then one per constraint

Type:

The constraint penalties of the current solution, as a new numpy array (float64)

raw_y

(self) -> float

raw_y_best

(self) -> float

transformed_y

(self) -> float

transformed_y_best

(self) -> float

violations

first the total, then one per constraint

Type:

The constraint violations of the current solution, as a new numpy array (float64)

x

The current solution passed to problem, as a new numpy array (float64, also for integer problems)

y

(self) -> float

y_best

(self) -> float