metaheuristic_designer.benchmarks.img_funcs module

class ImgApprox(img_dim, reference, mode=None, img_name='', diff_func='MSE', name=None)

Bases: ObjectiveFunc

Attributes:

params

Access parameter values by attribute-style lookup.

Methods

__call__(population)	Shorthand for executing the objective function on a vector.
add_parameter_constraints(...)	Attach extra constraint handlers for extended encodings (e.g., PSO).
calculate_fitness(population)	Evaluate fitness for the whole population.
get_params()	Return a copy of the current parameter dictionary.
get_state()	Return a dictionary with the current configuration.
objective(solution)	Implementation of the objective function.
repair_population(population)	Transforms an invalid vector into one that satisfies the restrictions of the problem.
restart()	Reset the evaluation counter to zero.
store_kwargs([progress])	Store keyword arguments and evaluate them at the given progress.
update(progress)	Re-evaluate all stored parameters at the current progress.
update_kwargs([progress])	Add or replace parameters and immediately evaluate them.

objective(solution)

Implementation of the objective function.

Parameters:

solution: Any

The solution for which the fitness will be calculated.

Returns:

objective_value: VectorLike | ScalarLike

Value of the objective function given a solution.

class ImgEntropy(img_dim, nbins=10, mode=None)

Bases: ObjectiveFunc

Attributes:

params

Access parameter values by attribute-style lookup.

Methods

__call__(population)	Shorthand for executing the objective function on a vector.
add_parameter_constraints(...)	Attach extra constraint handlers for extended encodings (e.g., PSO).
calculate_fitness(population)	Evaluate fitness for the whole population.
get_params()	Return a copy of the current parameter dictionary.
get_state()	Return a dictionary with the current configuration.
objective(solution)	Implementation of the objective function.
repair_population(population)	Transforms an invalid vector into one that satisfies the restrictions of the problem.
restart()	Reset the evaluation counter to zero.
store_kwargs([progress])	Store keyword arguments and evaluate them at the given progress.
update(progress)	Re-evaluate all stored parameters at the current progress.
update_kwargs([progress])	Add or replace parameters and immediately evaluate them.

objective(solution)

Implementation of the objective function.

Parameters:

solution: Any

The solution for which the fitness will be calculated.

Returns:

objective_value: VectorLike | ScalarLike

Value of the objective function given a solution.

class ImgStd(img_dim, mode=None)

Bases: ObjectiveFunc

Attributes:

params

Access parameter values by attribute-style lookup.

Methods

__call__(population)	Shorthand for executing the objective function on a vector.
add_parameter_constraints(...)	Attach extra constraint handlers for extended encodings (e.g., PSO).
calculate_fitness(population)	Evaluate fitness for the whole population.
get_params()	Return a copy of the current parameter dictionary.
get_state()	Return a dictionary with the current configuration.
objective(solution)	Implementation of the objective function.
repair_population(population)	Transforms an invalid vector into one that satisfies the restrictions of the problem.
restart()	Reset the evaluation counter to zero.
store_kwargs([progress])	Store keyword arguments and evaluate them at the given progress.
update(progress)	Re-evaluate all stored parameters at the current progress.
update_kwargs([progress])	Add or replace parameters and immediately evaluate them.

objective(solution)

Implementation of the objective function.

Parameters:

solution: Any

The solution for which the fitness will be calculated.

Returns:

objective_value: VectorLike | ScalarLike

Value of the objective function given a solution.