| public Fitness ( double parameters, double fitnessLimit ) : double | ||
| parameters | double | Parameters to use for the Optimizer. |
| fitnessLimit | double | Preemptive Fitness Limit |
| 리턴 | double | |
static void Main(string[] args)
{
// Create and initialize PRNG.
Globals.Random = new RandomOps.MersenneTwister();
// Assign run-condition to problem.
Problem.RunCondition = RunCondition;
// Wrap the optimizer in a logger of result-statistics.
Statistics Statistics = new Statistics(Optimizer);
// Wrap it again in a repeater.
Repeat repeat = new RepeatSum(Statistics, NumRuns);
// Output optimization settings.
Console.WriteLine("Problem: {0}", Problem.Name);
Console.WriteLine("Optimizer: {0}", Optimizer.Name);
Console.WriteLine("Using following parameters:");
Tools.PrintParameters(Optimizer, Optimizer.DefaultParameters);
Console.WriteLine("Number of runs: {0}", NumRuns);
Console.WriteLine("Dimensionality: {0}", Dim);
Console.WriteLine("Dim-factor: {0}", DimFactor);
Console.WriteLine();
// Start-time.
DateTime t1 = DateTime.Now;
// Perform optimizations.
double fitness = repeat.Fitness();
// End-time.
DateTime t2 = DateTime.Now;
// Compute result-statistics.
Statistics.Compute();
// Output best results, as well as result-statistics.
Console.WriteLine("Best parameters found:");
Tools.PrintParameters(Problem, Statistics.BestParameters);
Console.WriteLine("With fitness: {0}", Tools.FormatNumber(Statistics.FitnessMin));
Console.WriteLine("Time usage: {0}", t2 - t1);
Console.WriteLine("Mean number of iterations: {0}", Statistics.IterationsMean);
Console.WriteLine();
Console.WriteLine("x\ty\tComputedY");
Console.WriteLine("--------------------");
// Output fitted curve.
for (int i=0; i<X.Length; i++)
{
double x = X[i];
double y = Y[i];
double computedY = Problem.ComputeY(Statistics.BestParameters, x);
Console.WriteLine("{0}\t{1}\t{2}", x, y, computedY);
}
}
/// <summary>
/// Optimize the given problem and output result-statistics.
/// </summary>
static void Optimize(Problem problem)
{
// Create a fitness trace for tracing the progress of optimization, mean.
int NumMeanIntervals = 3000;
FitnessTrace fitnessTraceMean = new FitnessTraceMean(NumIterations, NumMeanIntervals);
// Create a fitness trace for tracing the progress of optimization, quartiles.
// Note that fitnessTraceMean is chained to this object by passing it to the
// constructor, this causes both fitness traces to be used.
int NumQuartileIntervals = 10;
FitnessTrace fitnessTraceQuartiles = new FitnessTraceQuartiles(NumRuns, NumIterations, NumQuartileIntervals, fitnessTraceMean);
// Assign the problem etc. to the optimizer.
Optimizer.Problem = problem;
Optimizer.RunCondition = RunCondition;
Optimizer.FitnessTrace = fitnessTraceQuartiles;
// Wrap the optimizer in a logger of result-statistics.
Statistics Statistics = new Statistics(Optimizer);
// Wrap it again in a repeater.
Repeat Repeat = new RepeatSum(Statistics, NumRuns);
// Perform the optimization runs.
double fitness = Repeat.Fitness(Parameters);
// Compute result-statistics.
Statistics.Compute();
// Output result-statistics.
Console.WriteLine("{0} & {1} & {2} & {3} & {4} & {5} & {6} & {7} \\\\",
problem.Name,
Tools.FormatNumber(Statistics.FitnessMean),
Tools.FormatNumber(Statistics.FitnessStdDev),
Tools.FormatNumber(Statistics.FitnessQuartiles.Min),
Tools.FormatNumber(Statistics.FitnessQuartiles.Q1),
Tools.FormatNumber(Statistics.FitnessQuartiles.Median),
Tools.FormatNumber(Statistics.FitnessQuartiles.Q3),
Tools.FormatNumber(Statistics.FitnessQuartiles.Max));
// Output fitness trace, mean.
string traceFilenameMean = Optimizer.Name + "-FitnessTraceMean-" + problem.Name + ".txt";
fitnessTraceMean.WriteToFile(traceFilenameMean);
// Output fitness trace, quartiles.
string traceFilenameQuartiles = Optimizer.Name + "-FitnessTraceQuartiles-" + problem.Name + ".txt";
fitnessTraceQuartiles.WriteToFile(traceFilenameQuartiles);
}