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 void ValidateToString()
{
System.Threading.Thread.CurrentThread.CurrentCulture = System.Globalization.CultureInfo.InvariantCulture;
var n = new Triangular(0d, 2d, 1d);
Assert.AreEqual("Triangular(Lower = 0, Upper = 2, Mode = 1)", n.ToString());
}
public string Run()
{
var triangulars = new Triangular().GenerateWhileLessThan(TWO_MILLION + 1001).ToList();
long area = 0;
long minDiff = long.MaxValue;
int lowindex = 1;
long est;
int estIdx = int.MaxValue;
while (lowindex < estIdx)
{
est = TWO_MILLION / triangulars[lowindex];
estIdx = triangulars.BinarySearch(est);
if (estIdx < 0)
{
estIdx = -estIdx;
}
estIdx--;
if (Math.Abs(TWO_MILLION - triangulars[lowindex] * triangulars[estIdx]) < minDiff)
{
minDiff = Math.Abs(TWO_MILLION - triangulars[lowindex] * triangulars[estIdx]);
area = lowindex * estIdx;
}
if (Math.Abs(TWO_MILLION - triangulars[lowindex] * triangulars[estIdx + 1]) < minDiff)
{
minDiff = Math.Abs(TWO_MILLION - triangulars[lowindex] * triangulars[estIdx + 1]);
area = lowindex * estIdx + lowindex;
}
lowindex++;
}
return(area.ToString());
}
public void CanSampleSequence()
{
var n = new Triangular(0.1, 0.3, 0.2);
var ied = n.Samples();
GC.KeepAlive(ied.Take(5).ToArray());
}
public Distribution(String DistributionName, params double[] vs) // 构造函数 根据名字初始化分布
{
switch (DistributionName.ToUpper())
{
case "NORMAL":
normalDis = new Normal(vs[0], vs[1]); // double mean, double stddev
break;
case "CONTINUOUS":
continuousUniformDis = new ContinuousUniform(vs[0], vs[1]); // int lower, int upper
break;
case "TRIANGULAR":
triangularDis = new Triangular(vs[0], vs[1], vs[2]); //double lower, double upper, double mode (lower ≤ mode ≤ upper)
break;
case "STUDENTT":
studentTDis = new StudentT(vs[0], vs[1], vs[2]); //double location, double scale, double freedom
break;
case "BERNOULLI":
bernoulliDis = new Bernoulli(vs[0]);
break;
case "DISCRETEUNIFORM":
discreteUniform = new DiscreteUniform((int)vs[0], (int)vs[1]); // int lower, int upper
break;
}
this.DistributionName = DistributionName;
}
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));
}
protected override PixelShaderInput InterpolatePoint(PixelShaderInput va, PixelShaderInput vb, PixelShaderInput vc, Vector2 p, out bool outOfRange)
{
var v = new PixelShaderInput();
var vatp = va.TransformedPosition;
var vbtp = vb.TransformedPosition;
var vctp = vc.TransformedPosition;
var wp = Triangular.GetInterpolatedW(p, vatp, vbtp, vctp, out var successful);
outOfRange = !successful;
v.TransformedPosition = Triangular.InterpolateTransformedPosition(p, wp, vatp, vbtp, vctp, out successful);
if (!outOfRange)
{
outOfRange = !successful;
}
v.TexCoords = Triangular.Interpolate(va.TexCoords, vb.TexCoords, vc.TexCoords, p, wp, vatp, vbtp, vctp, out successful);
if (!outOfRange)
{
outOfRange = !successful;
}
return(v);
}
public void CanSampleSequenceStatic()
{
var ied = Triangular.Samples(new Random(0), 2.0, 3.0, 2.5);
GC.KeepAlive(ied.Take(5).ToArray());
ied = Triangular.Samples(10.0, 100.0, 30.0);
GC.KeepAlive(ied.Take(5).ToArray());
}
public void CanCreateTriangular(double lower, double upper, double mode)
{
var n = new Triangular(lower, upper, mode);
Assert.AreEqual(lower, n.LowerBound);
Assert.AreEqual(upper, n.UpperBound);
Assert.AreEqual(mode, n.Mode);
}
public static double[] triangular(double v1, double v2, double v3, int num)
{
var t = new Triangular(v1, v2, v3);
double[] ret = new double[num];
t.Samples(ret);
return(ret);
}
public void ResetAll()
{
Uniform.Reset();
Gaussian.Reset();
DoubleGaussian.Reset();
Exponential.Reset();
Triangular.Reset();
Sequence.Reset();
Grid.Reset();
Perlin.Reset();
GoldenRatio.Reset();
}
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 int GetRandomTriangularFavoredIndex(int length)
{
if (length > Triangular.MaxInt32)
{
throw new ArgumentOutOfRangeException(nameof(length), length, $"Exceeds maximum Int32 value of {Triangular.MaxInt32}.");
}
var possibilities = (int)Triangular.Forward(length);
var selected = RandomUtilities.Random.Next(possibilities);
var r = Triangular.Reverse(selected);
Debug.Assert(r < length);
return(r);
}
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 bool ShareVertex(Triangular t)
{
foreach (var v in p)
{
foreach (var tv in t.p)
{
if (v.Equals(tv))
{
return(true);
}
}
}
return(false);
}
public void GenerateDistPoints()
{
var N = 100000;
var dt = new DataTable("data");
dt.Columns.Add("trig", typeof(double));
for (int i = 1; i < N; i++)
{
dt.Rows.Add(
Triangular.Random(10, 50, 15)
);
}
Csv.Write(dt, fo2);
}
public void Setup()
{
// Debug
// Random rnd = new Random(0); // for repetability
// Triangular.Samples(rnd, damageJitter, 0.9, 1.1, 1.0);
Triangular.Samples(damageJitter, 0.9, 1.1, 1.0);
for (int i = 5000; i < 25000; i += 2500)
{
multipliersLarge.Add(i);
}
for (int i = 500; i < 3500; i += 500)
{
multipliers.Add(i);
}
}
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);
}
private Dictionary <double, double> GetOverlayData(double step, Chart cherte)
{
var min = cherte.Series[0].Points.Min(x => x.XValue);
var max = cherte.Series[0].Points.Max(x => x.XValue);
var overlayData = new Dictionary <double, double>();
Func <int, double, double> g = (tb, x) =>
{
switch (tabControl.SelectedIndex)
{
case 0:
return(1);
case 1:
return(1 / (max - min));
case 2:
return(Triangular.PDF(Convert.ToDouble(tb_tre_max.Text), Convert.ToDouble(tb_tre_min.Text), Convert.ToDouble(tb_tre_moda.Text), x));
case 3:
return(Erlang.PDF(Convert.ToInt32(nUD_erl_kol_norm.Value), 1.0 / Convert.ToDouble(tb_erl_moda.Text), x));
case 4:
return(Poisson.PMF(Convert.ToDouble(tb_puas_lambd.Text), (int)x));
case 5:
return(Normal.PDF(Convert.ToDouble(tb_norm_m.Text), Convert.ToDouble(tb_norm_d.Text), x));
case 6:
return(Exponential.PDF(1.0 / Convert.ToDouble(tb_exp_m.Text), x));
default:
return(double.NaN);
}
};
for (var x = min; x <= max; x += step)
{
overlayData[x] = g(tabControl.SelectedIndex, x);
}
return(overlayData);
}
private ISimulationResult ToggleDistribution(DistributionInput distributionInput, DistributionType distributionType)
{
ISimulationResult distributions = null;
switch (distributionType)
{
case DistributionType.Uniform:
distributions = new Uniform().GetDistribution(distributionInput.Delegate,
distributionInput.Iteration, distributionInput.UncertaintyArray);
break;
case DistributionType.Triangular:
distributions = new Triangular().GetDistribution(distributionInput.Delegate,
distributionInput.Iteration, distributionInput.UncertaintyArray);
break;
case DistributionType.Normal:
break;
case DistributionType.Log_Normal:
break;
}
return(distributions);
}
public void TriangularCompositeTest()
{
// First search for the lowest HCN that has more than 500 divisors.
// Any number less that than, triangular or not, will have no more than 500 divisors, by definition of HCN.
var index = 0;
while (HighComposites.Singleton[index].CountOfDivisors <= 500)
{
index++;
}
Console.WriteLine($"First HCN with over 500 divisors is {HighComposites.Singleton[index].Value} with {HighComposites.Singleton[index].CountOfDivisors} divisors.");
var triangular = Triangular.ClosestTriangularNumber(HighComposites.Singleton[index].Value);
Console.WriteLine($"Jump-starting the search at triangular number of order {triangular.Order} and value {triangular.Value}.");
while (triangular.Value.CountOfDivisors() < 500)
{
triangular = triangular.NextTriangularNumber();
}
Console.WriteLine($"The secret number is the triangular number of order {triangular.Order} and value {triangular.Value}.");
}
public void ValidateToString()
{
var n = new Triangular(0d, 2d, 1d);
Assert.AreEqual("Triangular(Lower = 0, Upper = 2, Mode = 1)", n.ToString());
}
public void CanSample()
{
var n = new Triangular(0.1, 0.3, 0.2);
n.Sample();
}
public void FailSampleSequenceStatic()
{
Assert.That(() => Triangular.Samples(new Random(0), 1.0, -1.0, 0.1).First(), 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>
/// Triangular Kernel:
/// x => Math.Abs(x) <= 1.0 ? (1.0-Math.Abs(x)) : 0.0
/// </summary>
public static double TriangularKernel(double x)
{
return(Triangular.PDF(-1.0, 1.0, 0.0, x));
}
/// <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);
}
public static void triangular_cdf_test()
//****************************************************************************80
//
// Purpose:
//
// TRIANGULAR_CDF_TEST tests TRIANGULAR_CDF.
//
// Licensing:
//
// This code is distributed under the GNU LGPL license.
//
// Modified:
//
// 31 March 2016
//
// Author:
//
// John Burkardt
//
{
int i;
int seed = 123456789;
Console.WriteLine("");
Console.WriteLine("TRIANGULAR_CDF_TEST");
Console.WriteLine(" TRIANGULAR_CDF evaluates the Triangular CDF;");
Console.WriteLine(" TRIANGULAR_CDF_INV inverts the Triangular CDF.");
Console.WriteLine(" TRIANGULAR_PDF evaluates the Triangular PDF;");
double a = 1.0;
double b = 10.0;
Console.WriteLine("");
Console.WriteLine(" PDF parameter A = " + a + "");
Console.WriteLine(" PDF parameter B = " + b + "");
if (!Triangular.triangular_check(a, b))
{
Console.WriteLine("");
Console.WriteLine("TRIANGULAR_CDF_TEST - Fatal error!");
Console.WriteLine(" The parameters are not legal.");
return;
}
Console.WriteLine("");
Console.WriteLine(" X PDF CDF CDF_INV");
Console.WriteLine("");
for (i = 1; i <= 10; i++)
{
double x = Triangular.triangular_sample(a, b, ref seed);
double pdf = Triangular.triangular_pdf(x, a, b);
double cdf = Triangular.triangular_cdf(x, a, b);
double x2 = Triangular.triangular_cdf_inv(cdf, a, b);
Console.WriteLine(" "
+ x.ToString(CultureInfo.InvariantCulture).PadLeft(12) + " "
+ pdf.ToString(CultureInfo.InvariantCulture).PadLeft(12) + " "
+ cdf.ToString(CultureInfo.InvariantCulture).PadLeft(12) + " "
+ x2.ToString(CultureInfo.InvariantCulture).PadLeft(12) + "");
}
}
