CADETProcess.optimization.Individual

class CADETProcess.optimization.Individual(x, x_transformed, cv_bounds, cv_lincon, cv_lineqcon, f, f_minimized, g, cv_nonlincon, cv_nonlincon_tol, m, m_minimized, is_feasible)

Set of variables evaluated during Optimization.

Attributes:

idstr

UUID for individual.

xnp.ndarray

Variable values in untransformed space.

x_transformednp.ndarray

Independent variable values in transformed space.

cv_boundsnp.ndarray

Vound constraint violations.

cv_linconnp.ndarray

Linear constraint violations.

cv_lineqconnp.ndarray

Linear equality constraint violations.

fnp.ndarray

Objective values.

f_minimizednp.ndarray

Minimized objective values.

gnp.ndarray

Nonlinear constraint values.

cv_nonlinconnp.ndarray

Nonlinear constraints violation.

mnp.ndarray

Meta score values.

m_minimizednp.ndarray

Minimized meta score values.

is_feasiblebool

True, if individual fulfills all constraints.

Methods

check_required_parameters()	Verify if all required parameters are set.
dominates(other)	Determine if individual dominates other.
dominates_f(other)	Determine if individual dominates other in terms of objectives.
dominates_m(other)	Determine if individual dominates other in terms of meta scores.
from_dict(data)	Create Individual from dictionary representation of its attributes.
is_similar(other[, tol])	Determine if individual is similar to other.
is_similar_f(other[, tol])	Determine if individual is similar to other based on objective values.
is_similar_g(other[, tol])	Determine if individual is similar to other based on constraint values.
is_similar_m(other[, tol])	Determine if individual is similar to other based on meta score values.
is_similar_x(other[, tol, use_transformed])	Determine if individual is similar to other based on parameter values.
to_dict()	Convert individual to a dictionary.

See also

CADETProcess.optimization.Population