C# (CSharp) Encog.ML.Genetic MateWorker.Run Examples

Run() public method

Mate the two chromosomes.

public Run ( ) : void
return	void

Example #1

        private void ThreadWorker(int i, int offspringIndex, int matingPopulationSize)
        {
            IGenome mother    = Population.Genomes[i];
            var     fatherInt = (int)(ThreadSafeRandom.NextDouble() * matingPopulationSize);
            IGenome father    = Population.Genomes[fatherInt];
            IGenome child1    = Population.Genomes[offspringIndex + i * 2];
            IGenome child2    = Population.Genomes[offspringIndex + i * 2 + 1];

            var worker = new MateWorker(mother, father, child1,
                                        child2);

            worker.Run();
        }

Example #2

File: BasicGeneticAlgorithm.cs Project: OperatorOverload/encog-cs

        /// <summary>
        /// Modify the weight matrix and bias values based on the last call to
        /// calcError.
        /// </summary>
        public override sealed void Iteration()
        {
            if (_first)
            {
                Population.Claim(this);
                _first = false;
            }

            var countToMate = (int) (Population.PopulationSize*PercentToMate);
            int offspringCount = countToMate*2;
            int offspringIndex = Population.PopulationSize
                                 - offspringCount;
            var matingPopulationSize = (int) (Population.PopulationSize*MatingPopulation);

            TaskGroup group = EngineConcurrency.Instance
                .CreateTaskGroup();

            // mate and form the next generation
            for (int i = 0; i < countToMate; i++)
            {
                IGenome mother = Population.Genomes[i];
                var fatherInt = (int)(ThreadSafeRandom.NextDouble()*matingPopulationSize);
                IGenome father = Population.Genomes[fatherInt];
                IGenome child1 = Population.Genomes[offspringIndex];
                IGenome child2 = Population.Genomes[offspringIndex + 1];

                var worker = new MateWorker(mother, father, child1,
                                            child2);

                if (MultiThreaded)
                {
                    EngineConcurrency.Instance.ProcessTask(worker, group);
                }
                else
                {
                    worker.Run();
                }

                offspringIndex += 2;
            }

            if (MultiThreaded)
            {
                group.WaitForComplete();
            }

            // sort the next generation
            Population.Sort();
        }

Example #3

File: BasicGeneticAlgorithm.cs Project: neismit/emds

        /// <summary>
        /// Modify the weight matrix and bias values based on the last call to
        /// calcError.
        /// </summary>
        public override sealed void Iteration()
        {
            if (_first)
            {
                Population.Claim(this);
                _first = false;
            }

            var countToMate = (int) (Population.PopulationSize*PercentToMate);
            int offspringCount = countToMate*2;
            int offspringIndex = Population.PopulationSize
                                 - offspringCount;
            var matingPopulationSize = (int) (Population.PopulationSize*MatingPopulation);

            // mate and form the next generation
            Parallel.For(0, countToMate, i =>
            {
                IGenome mother = Population.Genomes[i];
                var fatherInt = (int)(ThreadSafeRandom.NextDouble() * matingPopulationSize);
                IGenome father = Population.Genomes[fatherInt];
                IGenome child1 = Population.Genomes[offspringIndex];
                IGenome child2 = Population.Genomes[offspringIndex + 1];

                var worker = new MateWorker(mother, father, child1,
                                            child2);

                worker.Run();

                offspringIndex += 2;
            });

            // sort the next generation
            Population.Sort();
        }

Example #4

File: BasicGeneticAlgorithm.cs Project: Romiko/encog-dotnet-core

        private void ThreadWorker(int i, int offspringIndex, int matingPopulationSize)
        {
            IGenome mother = Population.Genomes[i];
            var fatherInt = (int)(ThreadSafeRandom.NextDouble() * matingPopulationSize);
            IGenome father = Population.Genomes[fatherInt];
            IGenome child1 = Population.Genomes[offspringIndex + i * 2];
            IGenome child2 = Population.Genomes[offspringIndex + i * 2 + 1];

            var worker = new MateWorker(mother, father, child1,
                                        child2);

            worker.Run();
        }