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package org.apache.commons.math3.fitting.leastsquares;

An algorithm that can be applied to a non-linear least squares problem.
Since:
3.3/**
 * An algorithm that can be applied to a non-linear least squares problem.
 *
 * @since 3.3
 */
public interface LeastSquaresOptimizer {

    
Solve the non-linear least squares problem.
Params:
leastSquaresProblem – the problem definition, including model function and
                           convergence criteria.
Returns:
The optimum./**
     * Solve the non-linear least squares problem.
     *
     *
     * @param leastSquaresProblem the problem definition, including model function and
     *                            convergence criteria.
     * @return The optimum.
     */
    Optimum optimize(LeastSquaresProblem leastSquaresProblem);

    
The optimum found by the optimizer. This object contains the point, its value, and
some metadata.
/**
     * The optimum found by the optimizer. This object contains the point, its value, and
     * some metadata.
     */
    //TODO Solution?
    interface Optimum extends LeastSquaresProblem.Evaluation {

        
Get the number of times the model was evaluated in order to produce this
optimum.
Returns:
the number of model (objective) function evaluations/**
         * Get the number of times the model was evaluated in order to produce this
         * optimum.
         *
         * @return the number of model (objective) function evaluations
         */
        int getEvaluations();

        
Get the number of times the algorithm iterated in order to produce this optimum. In general least squares it is common to have one evaluation per iterations. 
Returns:
the number of iterations/**
         * Get the number of times the algorithm iterated in order to produce this
         * optimum. In general least squares it is common to have one {@link
         * #getEvaluations() evaluation} per iterations.
         *
         * @return the number of iterations
         */
        int getIterations();

    }

}