public override void Solve(Model model)
{
if (Distribution == null)
throw new ArgumentNullException("Input distribution has not been initialized");
Output = Distribution;
}
public void ConstantTest()
{
var in1 = new ModelInput("in1") { Distribution = Distribution.InitGaussian(10, 0.31) };
var op1 = new ModelFormula("op1") { Formula = "in1 * 3" };
var model = new Model();
model.Add(in1, op1);
model.Solve();
Utils.AssertIsInRange(op1.Output.GetMean(), 30, 0.5);
}
public static void Main(string[] args)
{
var in1 = new ModelInput("in1") { Distribution = Distribution.InitGaussian(10, 0.31) };
var in2 = new ModelInput("in2") { Distribution = Distribution.InitGaussian(3, 0.31) };
var in3 = new ModelInput("in3") { Distribution = Distribution.InitGaussian(5, 0.61) };
var in4 = new ModelInput("c") { Distribution = Distribution.InitConstant(10) };
var op1 = new ModelFormula("op1") { Formula = "in1 * in2" };
var op2 = new ModelFormula("op2") { Formula = "op1 * in3 * c" };
var model = new Model();
model.Add(in1, in2, op1, in3, in4, op2);
model.Solve();
Console.WriteLine("Result: mean: {0} stddev: {1}", op2.Output.GetMean(), op2.Output.GetStdDeviation());
Console.WriteLine("Result histogram:");
PrintDistroChart(op2.Output.RawItems);
}
public override void Solve(Model model)
{
if (mInputs == null)
GetNeededInputs();
var e = new Expression(Formula,
EvaluateOptions.IterateParameters |
EvaluateOptions.IgnoreCase);
foreach (var inputName in mInputs)
{
var objectDistribution = model[inputName].Output;
e.Parameters[inputName] = objectDistribution;
}
var result = e.Evaluate() as List<object>;
if (result == null)
throw new Exception("");
Output = new Distribution(GetDoubleArray(result));
}
public abstract void Solve(Model model);