本文整理汇总了C#中IChromosome.Where方法的典型用法代码示例。如果您正苦于以下问题:C# IChromosome.Where方法的具体用法?C# IChromosome.Where怎么用?C# IChromosome.Where使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类IChromosome
的用法示例。
在下文中一共展示了IChromosome.Where方法的2个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的C#代码示例。
示例1: Select
/// <summary>
/// Realizuje algorytm selekcji.
/// </summary>
/// <param name="population">Populacja poddawana selekcji.</param>
/// <returns>Zbiór osobników populacji, wybranych w wyniku selekcji do następnej generacji.</returns>
public IChromosome[] Select(IChromosome[] population)
{
if (population.Length < 2)
{
return population;
}
IChromosome[] subpopulation = population.Where(ch => ch.Evaluate() > 0).ToArray();
Double totalFitness = subpopulation.Sum(ch => ch.Evaluate());
Int32 newPopulationSize = (Int32)PopulationSize.ComputeSize(subpopulation);
IChromosome[] result = new IChromosome[newPopulationSize];
for (Int32 i = 0; i < newPopulationSize; i++)
{
Double ptr = RandomGenerator.NextDouble();
Double sum = 0.0;
for (Int32 j = 0; j < subpopulation.Length; ++j)
{
sum += subpopulation[j].Evaluate() / totalFitness;
if (sum > ptr)
{
result[i] = subpopulation[j];
break;
}
}
}
return result;
}
示例2: Select
/// <summary>
/// Realizuje algorytm selekcji.
/// </summary>
/// <param name="population">Populacja poddawana selekcji.</param>
/// <returns>Zbiór osobników populacji, wybranych w wyniku selekcji do następnej generacji.</returns>
public IChromosome[] Select(IChromosome[] population)
{
if (population.Length < 2)
{
return population;
}
IChromosome[] subpopulation = population.Where(ch => ch.Evaluate() > 0).ToArray();
Double totalFitness = subpopulation.Sum(ch => ch.Evaluate());
Int32 newPopulationSize = (Int32)PopulationSize.ComputeSize(subpopulation);
IChromosome[] result = new IChromosome[newPopulationSize];
Double ptrstep = 1.0 / newPopulationSize;
Double ptr = RandomGenerator.NextDouble() * ptrstep;
Int32 pos = 0;
Double sum = 0.0;
for (Int32 i = 0; i < subpopulation.Length; i++)
{
for (sum += subpopulation[i].Evaluate() / totalFitness; sum > ptr; ptr += ptrstep)
{
result[pos++] = subpopulation[i];
if (pos == newPopulationSize)
{
return result;
}
}
}
// it shouldn't happen
Debug.Assert(false);
return result;
}