The FunctionOptimization case class to store the definition of a function optimization in a format that adheres to the optimization logic format used by the implementation of the Limited memory Broyden–Fletcher–Goldfarb–Shanno (BFGS) for unconstrained optimization (L-BFGS) algorithm.
Evaluates the gradients and objective function according to the state of the variables during the minimization process.
Evaluates the gradients and objective function according to the state of the variables during the minimization process.
Value parameters
instance
user data provided by each call of the lbfgsMain method. Can have Any type defined by the user as long as the same type is utilized in other instances that rely on this EvaluationLogic
n
the number of variables
step
current step chosen by the line search routine.
x
VectorD with the current values of the variables
Attributes
Returns
LBFGSVarEvaluationResults, results obtained from evaluating the variables
Receives the progress of each iteration of the optimization process. Can be used to display or record said progress and to determine if the optimization should continue or be cancelled. A default implementation is provided to just print the contents of the current iteration of the optimization.
Receives the progress of each iteration of the optimization process. Can be used to display or record said progress and to determine if the optimization should continue or be cancelled. A default implementation is provided to just print the contents of the current iteration of the optimization.
Value parameters
fx
Current value of the objective function.
g
VectorD with the current value of the gradient vector.
gnorm
Euclidean norm of the gradient vector.
instance
User data provided by each call of the lbfgsMain method of the LBFGS object. Can have Any type defined by the user as long as the same type is utilized in the evaluate method implementation for the class extending this trait and on the corresponding lbfgsMain calls from the LBFGS object that relies on this OptimizationLogic.
k
Iteration count.
ls
The number of evaluations called for this iteration.
n
The number of variables.
step
Step used by the line search routine in this iteration.
x
VectorD with the current values of the variables.
xnorm
Euclidean norm of the variables.
Attributes
Returns
int Determines if optimization should continue. Zero continues optimization. Non-zero values cancel the optimization.