The OptimizationLogic trait specifies the requirements for the logic to be used in each step of a L-BFGS variable minimization done by the lbfgsMain method of the LBFGS object. The methods provided in this trait are called directly by the code used by the LBFGS class.
Classes mixing in this trait must implement two methods: evaluate and progress. The evaluate method is used to evaluate the gradients and objective function for a given state of the variables. The progress method is used to report on how the minimization process is progressing.
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.
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