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();
}
/// <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();
}
/// <summary>
/// Modify the weight matrix and bias values based on the last call to
/// calcError.
/// </summary>
public override sealed void Iteration()
{
if (_first)
{
EngineConcurrency.Instance.ThreadCount = ThreadCount;
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);
EngineConcurrency.Instance.ProcessTask(worker, group);
offspringIndex += 2;
}
group.WaitForComplete();
// sort the next generation
Population.Sort();
}
public override sealed void Iteration()
{
int num;
int num2;
int num3;
int num4;
TaskGroup group;
int num5;
IGenome genome;
IGenome genome2;
IGenome genome3;
IGenome genome4;
if (!this._x62584df2cb5d40dd)
{
goto Label_016F;
}
if ((((uint) num3) + ((uint) num2)) >= 0)
{
EngineConcurrency.Instance.ThreadCount = base.ThreadCount;
base.Population.Claim(this);
this._x62584df2cb5d40dd = false;
goto Label_016F;
}
goto Label_008B;
Label_0083:
if (num5 < num)
{
int num6;
genome = base.Population.Genomes[num5];
do
{
num6 = (int) (ThreadSafeRandom.NextDouble() * num4);
}
while ((((uint) num) + ((uint) num6)) < 0);
genome2 = base.Population.Genomes[num6];
goto Label_00FB;
}
if (0 == 0)
{
group.WaitForComplete();
base.Population.Sort();
return;
}
Label_008B:
genome4 = base.Population.Genomes[num3 + 1];
MateWorker task = new MateWorker(genome, genome2, genome3, genome4);
EngineConcurrency.Instance.ProcessTask(task, group);
num3 += 2;
num5++;
if ((((uint) num2) + ((uint) num2)) > uint.MaxValue)
{
goto Label_0184;
}
goto Label_0083;
Label_00FB:
genome3 = base.Population.Genomes[num3];
goto Label_008B;
Label_016F:
num = (int) (base.Population.PopulationSize * base.PercentToMate);
Label_0184:
num2 = num * 2;
num3 = base.Population.PopulationSize - num2;
num4 = (int) (base.Population.PopulationSize * base.MatingPopulation);
if (0 != 0)
{
goto Label_00FB;
}
group = EngineConcurrency.Instance.CreateTaskGroup();
num5 = 0;
goto Label_0083;
}
/// <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();
}
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();
}
