public static void Cleanup()
{
var randomizersList = new Dictionary <Type, IRandomizeble>();
randomizersList[typeof(decimal)] = new DecimalRandom();
randomizersList[typeof(string)] = new StringRandom();
randomizersList[typeof(char)] = new CharRandom();
randomizersList[typeof(int)] = new Int32Random();
randomizersList[typeof(long)] = new Int64Random();
randomizersList[typeof(bool)] = new BoolRandom();
randomizersList[typeof(byte)] = new ByteRandom();
randomizersList[typeof(sbyte)] = new SByteRandom();
randomizersList[typeof(float)] = new FloatRandom();
randomizersList[typeof(double)] = new DoubleRandom();
randomizersList[typeof(short)] = new Int16Random();
randomizersList[typeof(uint)] = new UInt32Random();
randomizersList[typeof(ushort)] = new UInt16Random();
randomizersList[typeof(ulong)] = new UInt64Random();
randomizersList[typeof(DateTime)] = new DateTimeRandom();
UniversalRandom.AddRandomizers(randomizersList);
UniversalRandom.AddInterceptors(new List <IInterceptor>
{
new ListInterceptor(),
new EnumInterceptor(),
new ArrayInterceptor()
});
}
public RealGaussianMutation(List <double> sigmas, IEvaluationProfile <double> evaluationProfile, int?seed = null, double probability = 1.0)
: base(probability, evaluationProfile)
{
uniformRNG = new BoolRandom(seed);
gaussianRNG = new NormalRealRandom(seed);
this.sigmas = new List <double>(sigmas);
}
public APopulationCrossover(ACrossover crossover, double prob, int?seed = null)
{
CrossoverMethod = crossover;
Probability = prob;
crossoverRNG = new BoolRandom(seed);
integerRNG = new UniformIntegerRandom(seed);
}
public RealGaussianMutation(double sigma, IEvaluationProfile <double> evaluationProfile, int?seed = null, double probability = 1.0)
: base(probability, evaluationProfile)
{
uniformRNG = new BoolRandom(seed);
gaussianRNG = new NormalRealRandom(seed);
sigmas = new List <double>(evaluationProfile.iSize);
for (int i = 0; i < evaluationProfile.iSize; ++i)
{
sigmas.Add(sigma);
}
}
static UniversalRandom()
{
_randomizers[typeof(decimal)] = new DecimalRandom();
_randomizers[typeof(string)] = new StringRandom();
_randomizers[typeof(char)] = new CharRandom();
_randomizers[typeof(int)] = new Int32Random();
_randomizers[typeof(long)] = new Int64Random();
_randomizers[typeof(bool)] = new BoolRandom();
_randomizers[typeof(byte)] = new ByteRandom();
_randomizers[typeof(sbyte)] = new SByteRandom();
_randomizers[typeof(float)] = new FloatRandom();
_randomizers[typeof(double)] = new DoubleRandom();
_randomizers[typeof(short)] = new Int16Random();
_randomizers[typeof(uint)] = new UInt32Random();
_randomizers[typeof(ushort)] = new UInt16Random();
_randomizers[typeof(ulong)] = new UInt64Random();
_randomizers[typeof(DateTime)] = new DateTimeRandom();
_interceptors.Add(new ArrayInterceptor());
_interceptors.Add(new EnumInterceptor());
_interceptors.Add(new ListInterceptor());
}
public BinaryRandomGenerator(IConstraint <bool> constraint, int?seed = null)
: base(constraint)
{
rng = new BoolRandom(seed);
}
public ACrossover(double probability, int?seed = null)
{
Probability = probability;
crossoverRNG = new BoolRandom(seed);
}
public UniformCrossover(double probability, int?seed = null)
: base(probability, seed)
{
rng = new BoolRandom(seed);
}
public BinaryBitFlipMutation(double probability, IEvaluationProfile <bool> evaluationProfile, int?seed = null)
: base(probability, evaluationProfile)
{
rng = new BoolRandom(seed);
}
