static ZergCharacter()
{
GOAL_PRIORITIES = new Dictionary<State, byte>(){
{State.AttackGoal, 16},
{State.FeedGoal, 8},
{State.RetreatGoal, 1},
{State.ServeGoal, 2}
};
var goals = new Stack<State>();
var goalEnums = (State[])Enum.GetValues(typeof(State));
foreach (var enumValue in goalEnums)
{
for (int i = 0; i < GOAL_PRIORITIES[enumValue]; i++)
{
goals.Push(enumValue);
}
}
int count = goals.Count;
RND = new DiscreteUniform(0, count - 1);
GOALS_LOOKUP_TABLE = new State[count];
var rnd = new ContinuousUniform(0.0, 1.0);
while (goals.Any())
{
int idx = (int)Math.Round(rnd.Sample() * (--count), 0);
GOALS_LOOKUP_TABLE[idx] = goals.Pop();
}
}
private void CreateUniformFromString(string distributionString)
{
var regex = new Regex(@"Uniform\(\s*(\d+)\s*,\s*(\d+)\s*\)", RegexOptions.IgnoreCase);
var match = regex.Match(distributionString);
var min = int.Parse(match.Groups[1].Value);
var max = int.Parse(match.Groups[2].Value);
_discreteUniform = new DiscreteUniform(min, max);
}
public void SetupDistributions()
{
dists = new IDistribution[8];
dists[0] = new Beta(1.0, 1.0);
dists[1] = new ContinuousUniform(0.0, 1.0);
dists[2] = new Gamma(1.0, 1.0);
dists[3] = new Normal(0.0, 1.0);
dists[4] = new Bernoulli(0.6);
dists[5] = new Weibull(1.0, 1.0);
dists[6] = new DiscreteUniform(1, 10);
dists[7] = new LogNormal(1.0, 1.0);
}
/// <summary>
/// Run example
/// </summary>
/// <a href="http://en.wikipedia.org/wiki/Discrete_uniform">DiscreteUniform distribution</a>
public void Run()
{
// 1. Initialize the new instance of the DiscreteUniform distribution class with parameters LowerBound = 2, UpperBound = 10
var discreteUniform = new DiscreteUniform(2, 10);
Console.WriteLine(@"1. Initialize the new instance of the DiscreteUniform distribution class with parameters LowerBound = {0}, UpperBound = {1}", discreteUniform.LowerBound, discreteUniform.UpperBound);
Console.WriteLine();
// 2. Distributuion properties:
Console.WriteLine(@"2. {0} distributuion properties:", discreteUniform);
// Cumulative distribution function
Console.WriteLine(@"{0} - Сumulative distribution at location '3'", discreteUniform.CumulativeDistribution(3).ToString(" #0.00000;-#0.00000"));
// Probability density
Console.WriteLine(@"{0} - Probability mass at location '3'", discreteUniform.Probability(3).ToString(" #0.00000;-#0.00000"));
// Log probability density
Console.WriteLine(@"{0} - Log probability mass at location '3'", discreteUniform.ProbabilityLn(3).ToString(" #0.00000;-#0.00000"));
// Entropy
Console.WriteLine(@"{0} - Entropy", discreteUniform.Entropy.ToString(" #0.00000;-#0.00000"));
// Largest element in the domain
Console.WriteLine(@"{0} - Largest element in the domain", discreteUniform.Maximum.ToString(" #0.00000;-#0.00000"));
// Smallest element in the domain
Console.WriteLine(@"{0} - Smallest element in the domain", discreteUniform.Minimum.ToString(" #0.00000;-#0.00000"));
// Mean
Console.WriteLine(@"{0} - Mean", discreteUniform.Mean.ToString(" #0.00000;-#0.00000"));
// Median
Console.WriteLine(@"{0} - Median", discreteUniform.Median.ToString(" #0.00000;-#0.00000"));
// Mode
Console.WriteLine(@"{0} - Mode", discreteUniform.Mode.ToString(" #0.00000;-#0.00000"));
// Variance
Console.WriteLine(@"{0} - Variance", discreteUniform.Variance.ToString(" #0.00000;-#0.00000"));
// Standard deviation
Console.WriteLine(@"{0} - Standard deviation", discreteUniform.StdDev.ToString(" #0.00000;-#0.00000"));
// Skewness
Console.WriteLine(@"{0} - Skewness", discreteUniform.Skewness.ToString(" #0.00000;-#0.00000"));
Console.WriteLine();
// 3. Generate 10 samples of the DiscreteUniform distribution
Console.WriteLine(@"3. Generate 10 samples of the DiscreteUniform distribution");
for (var i = 0; i < 10; i++)
{
Console.Write(discreteUniform.Sample().ToString("N05") + @" ");
}
Console.WriteLine();
Console.WriteLine();
// 4. Generate 100000 samples of the DiscreteUniform(2, 10) distribution and display histogram
Console.WriteLine(@"4. Generate 100000 samples of the DiscreteUniform(2, 10) distribution and display histogram");
var data = new double[100000];
for (var i = 0; i < data.Length; i++)
{
data[i] = discreteUniform.Sample();
}
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 5. Generate 100000 samples of the DiscreteUniform(-10, 10) distribution and display histogram
Console.WriteLine(@"5. Generate 100000 samples of the DiscreteUniform(-10, 10) distribution and display histogram");
discreteUniform.LowerBound = -10;
discreteUniform.UpperBound = 10;
for (var i = 0; i < data.Length; i++)
{
data[i] = discreteUniform.Sample();
}
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 6. Generate 100000 samples of the DiscreteUniform(0, 40) distribution and display histogram
Console.WriteLine(@"6. Generate 100000 samples of the DiscreteUniform(0, 40) distribution and display histogram");
discreteUniform.LowerBound = 0;
discreteUniform.UpperBound = 40;
for (var i = 0; i < data.Length; i++)
{
data[i] = discreteUniform.Sample();
}
ConsoleHelper.DisplayHistogram(data);
}
public void ValidateEntropy(int l, int u, double e)
{
var du = new DiscreteUniform(l, u);
AssertHelpers.AlmostEqualRelative(e, du.Entropy, 14);
}
public void CanCreateDiscreteUniform(int l, int u)
{
var du = new DiscreteUniform(l, u);
Assert.AreEqual(l, du.LowerBound);
Assert.AreEqual(u, du.UpperBound);
}
public void ValidateToString()
{
var b = new DiscreteUniform(0, 10);
Assert.AreEqual("DiscreteUniform(Lower = 0, Upper = 10)", b.ToString());
}
public void CanSampleSequence()
{
var n = new DiscreteUniform(0, 10);
var ied = n.Samples();
GC.KeepAlive(ied.Take(5).ToArray());
}
public void ValidateCumulativeDistribution(int l, int u, double x, double cdf)
{
var b = new DiscreteUniform(l, u);
Assert.AreEqual(cdf, b.CumulativeDistribution(x));
}
public void CanSample()
{
var n = new DiscreteUniform(0, 10);
n.Sample();
}
public void ValidateProbabilityLn(int l, int u, int x, double dln)
{
var b = new DiscreteUniform(l, u);
Assert.AreEqual(dln, b.ProbabilityLn(x));
}
public void ValidateMaximum()
{
var b = new DiscreteUniform(-10, 10);
Assert.AreEqual(10, b.Maximum);
}
public void ValidateMean(int l, int u, int m)
{
var du = new DiscreteUniform(l, u);
Assert.AreEqual(m, du.Mean);
}
public void ValidateSkewness(int l, int u)
{
var du = new DiscreteUniform(l, u);
Assert.AreEqual(0.0, du.Skewness);
}