public void mutate_all(Random rand, double tau1, double tau2, FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_Mutate type_mutate, double b_ro)
{
for (int i = 0; i < the_childs.Count; i++)
{
the_childs[i].mutate(rand, tau1, tau2, type_mutate, b_ro);
}
}
public virtual void Init(ILearnAlgorithmConf Conf)
{
Config = Conf as ESConfig;
count_populate = Config.ESCPopulationSize;
count_child = Config.ESCCountChild;
count_iterate = Config.ESCCountIteration;
coef_t1 = Config.ESCT1;
coef_t2 = Config.ESCT2;
param_crossover = Config.ESCCrossoverPropability;
alg_cross = Config.ESCCrossoverType;
type_init = Config.ESCInitType;
count_Multipoint = Config.ESCCountCrossoverPoint;
type_mutate = Config.ESCMutateAlg;
b_ro = Config.ESCAngleRotateB;
main_pop = new Population(count_populate, count_child, result.CountFeatures, result.LearnSamplesSet);
main_pop.init_first(result.RulesDatabaseSet[0], rand, type_init);
}
public Individ mutate(Random rand, double tau1, double tau2, FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_Mutate type_mutate, double b_ro)
{
switch (type_mutate)
{
case FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_Mutate.СКО:
{
hrom_vector.mutate_SKO(step_sko, rand);
for (int i = 0; i < step_sko.Count; i++)
{
step_sko[i] = step_sko[i] * Math.Exp(tau1 * GaussRandom.Random_gaussian(rand) + tau2 * GaussRandom.Random_gaussian(rand));
}
break;
}
case FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_Mutate.СКО_РО:
{
List <double> Covariance_matrix_pruned = new List <double>();
for (int i = 0; i < step_sko.Count; i++) // mutate
{
step_sko[i] = step_sko[i] * Math.Exp(tau1 * GaussRandom.Random_gaussian(rand) + tau2 * GaussRandom.Random_gaussian(rand));
step_rotate[i] = step_rotate[i] + b_ro * GaussRandom.Random_gaussian(rand);
}
double avr_ro = step_rotate.Sum() / step_rotate.Count;
double avr_sko = step_sko.Sum() / step_sko.Count;
for (int i = 0; i < step_sko.Count; i++) //calc covariance_matrix_pruned
{
Covariance_matrix_pruned.Add(Math.Abs(
(step_sko[i] - avr_sko) * (step_rotate[i] - avr_ro)
)
);
}
hrom_vector.mutate_SKO_RO(Covariance_matrix_pruned, rand);
break;
}
}
return(this);
}
protected override void fill_params(string[] args)
{
file_in = (args.Where(x => x.Contains("in"))).ToArray()[0];
Console.WriteLine("Before cut {0}", file_in);
file_in = file_in.Remove(0, 3);
Console.WriteLine("After cut {0}", file_in);
file_out = (args.Where(x => x.Contains("out"))).ToArray()[0];
file_out = file_out.Remove(0, 4);
string temp = (args.Where(x => x.Contains("init_alg"))).ToArray()[0];
temp = temp.Split(':')[1];
switch (temp)
{
case "Random": type_init = FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_init.Случайная; break;
case "Constrain": type_init = FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_init.Ограниченная; break;
default: type_init = FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_init.Ограниченная; break;
}
temp = (args.Where(x => x.Contains("type_mutate"))).ToArray()[0];
temp = temp.Split(':')[1];
switch (temp)
{
case "Adaptive": type_mutate = FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_Mutate.СКО; break;
case "CovarianceMatrix": type_mutate = FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_Mutate.СКО_РО; break;
default: type_mutate = FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_Mutate.СКО_РО; break;
}
temp = (args.Where(x => x.Contains("type_cross"))).ToArray()[0];
temp = temp.Split(':')[1];
switch (temp)
{
case "Unified": type_cross = FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Alg_crossover.Унифицированный; break;
case "Multipoint": type_cross = FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Alg_crossover.Многоточечный; break;
default: type_cross = FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Alg_crossover.Унифицированный; break;
}
temp = (args.Where(x => x.Contains("pcross"))).ToArray()[0];
temp = temp.Split(':')[1];
string comma = System.Globalization.CultureInfo.CurrentCulture.NumberFormat.NumberDecimalSeparator;
temp = temp.Replace(".", comma);
double.TryParse(temp, out pcross);
temp = (args.Where(x => x.Contains("cpcross"))).ToArray()[0];
temp = temp.Split(':')[1];
temp = temp.Replace(".", comma);
double.TryParse(temp, out cpcross);
temp = (args.Where(x => x.Contains("angleR"))).ToArray()[0];
temp = temp.Split(':')[1];
temp = temp.Replace(".", comma);
double.TryParse(temp, out angleR);
temp = (args.Where(x => x.Contains("iterate"))).ToArray()[0];
temp = temp.Split(':')[1];
temp = temp.Replace(".", comma);
double.TryParse(temp, out iterate);
temp = (args.Where(x => x.Contains("cindiv"))).ToArray()[0];
temp = temp.Split(':')[1];
temp = temp.Replace(".", comma);
double.TryParse(temp, out cindiv);
temp = (args.Where(x => x.Contains("cchild"))).ToArray()[0];
temp = temp.Split(':')[1];
temp = temp.Replace(".", comma);
double.TryParse(temp, out cchild);
temp = (args.Where(x => x.Contains("coeft1"))).ToArray()[0];
temp = temp.Split(':')[1];
temp = temp.Replace(".", comma);
double.TryParse(temp, out coeft1);
temp = (args.Where(x => x.Contains("coeft2"))).ToArray()[0];
temp = temp.Split(':')[1];
temp = temp.Replace(".", comma);
double.TryParse(temp, out coeft2);
}