GoalRefinement GenerateGoalRefinement(Goal parent)
{
var mode = (_options.MinGoalBranchingFactor + _options.MaxGoalBranchingFactor) / 2;
var nbchild = Triangular.Sample(_random, _options.MinGoalBranchingFactor,
_options.MaxGoalBranchingFactor,
mode);
var refinement = new GoalRefinement(_model)
{
ParentGoalIdentifier = parent.Identifier
};
do
{
refinement.RefinementPattern = _faker.PickRandom <RefinementPattern> ();
} while (refinement.RefinementPattern == RefinementPattern.None ||
refinement.RefinementPattern == RefinementPattern.Case);
for (int i = 0; i < nbchild; i++)
{
var c = GenerateGoal();
refinement.Add(c);
}
_model.Add(refinement);
return(refinement);
}
public static double estimationDepensVD(double vl)
{
double dMin, dMax, vlMin, vlMax;
if (vl < 0)
{
throw new ArgumentOutOfRangeException("valeur litigieuse inférieure à zero");
}
else if (vl >= 0 && vl < 30000)
{
dMin = 1000; dMax = 9000; vlMin = 0; vlMax = 30000;
}
else if (vl >= 30000 && vl < 100000)
{
dMin = 3000; dMax = 15000; vlMin = 30000; vlMax = 100000;
}
else if (vl >= 100000 && vl < 250000)
{
dMin = 6000; dMax = 25000; vlMin = 100000; vlMax = 250000;
}
else if (vl >= 250000 && vl < 500000)
{
dMin = 9000; dMax = 40000; vlMin = 250000; vlMax = 500000;
}
else
{
throw new NotImplementedException(String.Format("Pas de formule pour les dépens pour VD pour VL={0}", vl));
}
double dMode = dMin + 0.5 * (dMax - dMin) * (vl - vlMin) / (vlMax - vlMin);
return(Triangular.Sample(dMin, dMax, dMode));
}
public double RandomValue(Estimate estimate)
{
// All values are the same, return the value
if (estimate.Max - estimate.Min <= 0)
{
return(estimate.Max);
}
var triangle = new Triangular(estimate.Min, estimate.Max, estimate.Mode);
return(triangle.Sample());
}
public void OnCollisionStay2D(Collision2D collision)
{
if (collision.collider.tag == "Player")
{
monsterSpeed = 0;
}
else
{
monsterSpeed = maxMonsterSpeed;
}
if (collision.collider.tag == "Magic")
{
Destroy(collision.gameObject);
AnimatorStateInfo monsterName = gameObject.GetComponent <Animator>().GetCurrentAnimatorStateInfo(0);
int armor = 0;
if (monsterName.IsName("Deserto0") || monsterName.IsName("Floresta0") || monsterName.IsName("Noturno0") || monsterName.IsName("Gelado0"))
{
armor = 25;
}
else if (monsterName.IsName("Deserto1") || monsterName.IsName("Floresta1") || monsterName.IsName("Noturno1") || monsterName.IsName("Gelado1"))
{
armor = 50;
}
else if (monsterName.IsName("Deserto2") || monsterName.IsName("Floresta2") || monsterName.IsName("Noturno2") || monsterName.IsName("Gelado2"))
{
armor = 75;
}
else if (monsterName.IsName("Deserto3") || monsterName.IsName("Floresta3") || monsterName.IsName("Noturno3") || monsterName.IsName("Gelado3"))
{
armor = 100;
}
int min_attack = 1;
int max_attack = 100;
int mode = (max_attack - armor <= min_attack ? min_attack : max_attack - armor);
int damage = (int)Triangular.Sample(min_attack, max_attack, mode);
healthbar.SetLife(healthbar.getLife() - damage);
if (healthbar.getLife() == 0)
{
gameObject.SetActive(false);
healthbar.SetLife(healthbar.getMaxLife());
healthbar.gameObject.SetActive(false);
score_time.addScore(armor);
}
}
}
public static double estimateHonoraires(double valeurLitigieuse)
{
double min = 5 * 180 * 1.05 * 1.077; // 5h au tarif AJ, + débours et TVA
double max = (61.38 / 100) * valeurLitigieuse;
if (max < min)
{
return(min); // case where valeurLitigieuse is so small
}
else
{
return(Triangular.Sample(min, max, (max + min) / 2));
}
}
public void TestMeanAndVariacneConsistency()
{
const int numSamples = 100000;
double mean, stdev;
RunningStat rs = new RunningStat();
Random defaultrs = new Random();
Triangular tri = new Triangular();
rs.Clear();
var a = tri.LowerBound; var b = tri.UpperBound; var c = tri.Mode;
mean = (a + b + c) / 3; stdev = Math.Sqrt((a * a + b * b + c * c - a * b - a * c - b * c) / 18);
for (int i = 0; i < numSamples; ++i)
{
rs.Push(tri.Sample(defaultrs));
}
PrintResult.CompareMeanAndVariance("Triangular", mean, stdev * stdev, rs.Mean(), rs.Variance());
}
ObstacleRefinement GenerateObstacleRefinement(Obstacle parent)
{
var mode = (_options.MinObstacleANDBranchingFactor + _options.MaxObstacleANDBranchingFactor) / 2;
var nbchild = Triangular.Sample(_random, _options.MinObstacleANDBranchingFactor,
_options.MaxObstacleANDBranchingFactor,
mode);
var refinement = new ObstacleRefinement(_model)
{
ParentObstacleIdentifier = parent.Identifier
};
for (int i = 0; i < nbchild; i++)
{
var c = GenerateObstacle();
refinement.Add(c);
}
_model.Add(refinement);
return(refinement);
}
public double getSample() // 获取当前分布样本
{
double ret = 0;
switch (DistributionName)
{
case "Normal":
ret = normalDis.Sample(); break;
case "ContinuousUniform":
ret = continuousUniformDis.Sample(); break;
case "Triangular":
ret = triangularDis.Sample(); break;
case "StudentT":
ret = studentTDis.Sample(); break;
case "DiscreteUniform":
ret = discreteUniform.Sample(); break;
}
return(ret);
}
public void CanSample()
{
var n = new Triangular(0.1, 0.3, 0.2);
n.Sample();
}
public void FailSampleStatic()
{
Assert.That(() => Triangular.Sample(new Random(0), 1.0, -1.0, 0.1), Throws.ArgumentException);
}
public void CanSampleStatic()
{
Triangular.Sample(new Random(0), 2.0, 3.0, 2.5);
Triangular.Sample(10.0, 100.0, 30.0);
}
/// <summary>
/// Run example
/// </summary>
/// <a href="https://en.wikipedia.org/wiki/Triangular_distribution">Triangular distribution</a>
public void Run()
{
// 1. Initialize
var triangular = new Triangular(0, 1, 0.3);
Console.WriteLine(@"1. Initialize the new instance of the Triangular distribution class with parameters Lower = {0}, Upper = {1}, Mode = {2}", triangular.LowerBound, triangular.UpperBound, triangular.Mode);
Console.WriteLine();
// 2. Distributuion properties:
Console.WriteLine(@"2. {0} distributuion properties:", triangular);
// Cumulative distribution function
Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", triangular.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000"));
// Probability density
Console.WriteLine(@"{0} - Probability density at location '0.3'", triangular.Density(0.3).ToString(" #0.00000;-#0.00000"));
// Log probability density
Console.WriteLine(@"{0} - Log probability density at location '0.3'", triangular.DensityLn(0.3).ToString(" #0.00000;-#0.00000"));
// Entropy
Console.WriteLine(@"{0} - Entropy", triangular.Entropy.ToString(" #0.00000;-#0.00000"));
// Largest element in the domain
Console.WriteLine(@"{0} - Largest element in the domain", triangular.Maximum.ToString(" #0.00000;-#0.00000"));
// Smallest element in the domain
Console.WriteLine(@"{0} - Smallest element in the domain", triangular.Minimum.ToString(" #0.00000;-#0.00000"));
// Mean
Console.WriteLine(@"{0} - Mean", triangular.Mean.ToString(" #0.00000;-#0.00000"));
// Median
Console.WriteLine(@"{0} - Median", triangular.Median.ToString(" #0.00000;-#0.00000"));
// Mode
Console.WriteLine(@"{0} - Mode", triangular.Mode.ToString(" #0.00000;-#0.00000"));
// Variance
Console.WriteLine(@"{0} - Variance", triangular.Variance.ToString(" #0.00000;-#0.00000"));
// Standard deviation
Console.WriteLine(@"{0} - Standard deviation", triangular.StdDev.ToString(" #0.00000;-#0.00000"));
// Skewness
Console.WriteLine(@"{0} - Skewness", triangular.Skewness.ToString(" #0.00000;-#0.00000"));
Console.WriteLine();
// 10 samples
Console.WriteLine(@"3. Generate 10 samples of the Triangular distribution");
for (var i = 0; i < 10; i++)
{
Console.Write(triangular.Sample().ToString("N05") + @" ");
}
Console.WriteLine();
Console.WriteLine();
// 10000 samples with starting parameters
Console.WriteLine(@"4. Generate 100000 samples of the Triangular({0}, {1}, {2}) distribution and display histogram", triangular.LowerBound, triangular.UpperBound, triangular.Mode);
var data = new double[100000];
for (var i = 0; i < data.Length; i++)
{
data[i] = triangular.Sample();
}
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 10000 with different parameters
triangular.UpperBound = 10;
triangular.Mode = 8;
triangular.LowerBound = 2;
Console.WriteLine(@"4. Generate 100000 samples of the Triangular({0}, {1}, {2}) distribution and display histogram", triangular.LowerBound, triangular.UpperBound, triangular.Mode);
for (var i = 0; i < data.Length; i++)
{
data[i] = triangular.Sample();
}
ConsoleHelper.DisplayHistogram(data);
}
static double GetTriangular(Random random, double lower, double mode, double upper)
{
return(Triangular.Sample(random, lower, upper, mode));
}