private static void MakeDecision()
{
Console.Write("Please type the number of your desired action: ");
switch (Console.ReadKey().Key)
{
case ConsoleKey.D1:
ConstantGenerator.Run(BASE_MAP_PATH, SOURCE_CODE_PROJECT_FOLDER_PATH, new ConstantGeneratorOptions
{
IncludeCode = false
});
break;
case ConsoleKey.D2:
Build(false);
break;
case ConsoleKey.D3:
Build(true);
break;
default:
Console.WriteLine($"{Environment.NewLine}Invalid input. Please choose again.");
MakeDecision();
break;
}
}
private ITaskListGenerator CreateGenerator(int taskLength, int maxDelay, int taskPerTick)
{
var taskLengthGenerator = new ConstantGenerator();
var maxDelayGenerator = CreateConstantNumberGenerator <IMaxDelayGenerator>(maxDelay);
var taskPerTickGenerator = CreateConstantNumberGenerator <ITaskPerTickGenerator>(taskPerTick);
var configuration = CreateConfiguration(0, taskLength);
var listGenerator = new TaskListGenerator(taskLengthGenerator, maxDelayGenerator, taskPerTickGenerator, configuration, new TaskQuantityCalculator(), new AverageTaskDurationCalculator());
return(listGenerator);
}
/// <summary>
/// Constructs a new potential function modeling Hidden Markov Models.
/// </summary>
///
/// <param name="states">The number of states.</param>
/// <param name="symbols">The number of symbols.</param>
/// <param name="initialization">The random number generator to use when initializing weights.</param>
///
public MarkovDiscreteFunction(int states, int symbols, IRandomNumberGenerator <double> initialization = null)
{
if (initialization == null)
{
initialization = new ConstantGenerator(0);
}
this.Symbols = symbols;
var factorParams = new List <double>();
var factorFeatures = new List <IFeature <int> >();
var stateParams = new List <double>();
var stateFeatures = new List <IFeature <int> >();
var edgeParams = new List <double>();
var edgeFeatures = new List <IFeature <int> >();
// Create features for initial state probabilities
for (int i = 0; i < states; i++)
{
edgeParams.Add(initialization.Generate());
edgeFeatures.Add(new InitialFeature <int>(this, 0, i));
}
// Create features for state transition probabilities
for (int i = 0; i < states; i++)
{
for (int j = 0; j < states; j++)
{
edgeParams.Add(initialization.Generate());
edgeFeatures.Add(new TransitionFeature <int>(this, 0, i, j));
}
}
// Create features for symbol emission probabilities
for (int i = 0; i < states; i++)
{
for (int k = 0; k < symbols; k++)
{
stateParams.Add(initialization.Generate());
stateFeatures.Add(new EmissionFeature(this, 0, i, k));
}
}
// 1. edges
factorFeatures.AddRange(edgeFeatures);
factorParams.AddRange(edgeParams);
// 2. states
factorFeatures.AddRange(stateFeatures);
factorParams.AddRange(stateParams);
this.Features = factorFeatures.ToArray();
this.Weights = factorParams.ToArray();
this.Factors = new[] // First features and parameters always belong to edges
{
new MarkovDiscreteFactor(this, states, 0, symbols,
edgeIndex: 0, edgeCount: edgeParams.Count, // 1. edges
stateIndex: edgeParams.Count, stateCount: stateParams.Count) // 2. states
};
}
void before_each()
{
generator = new ConstantGenerator();
}
public void TestInitialize()
{
Generator = new ConstantGenerator();
}
