public void TwoVarsTreeOps()
{
var service = new SampleGenerator.SampleGenerator(2, 3, 0.001);
var formula = service.GetFormula();
var noiseFormula = formula.Clone <INode>();
NoisyConstants(noiseFormula);
var algorithm = new RegressionAlgorithm(noiseFormula, service.InSamples, service.ExactResult);
algorithm.Run();
Assert.AreNotEqual(null, algorithm.GetResult());
}
public static void Run(RegressionAlgorithm regressionAlgorithm, int iterationShowRate, String formula, int iterationCount = 1000, int iterationCursorPosition = 2)
{
Console.SetCursorPosition(0, iterationCursorPosition);
Console.WriteLine("Functional: {0}", regressionAlgorithm.Formula);
for (var count = 0; regressionAlgorithm.CurrentIteration < iterationCount; count++)
{
regressionAlgorithm.MakeIteration();
if (count % iterationShowRate != 0)
{
continue;
}
Console.SetCursorPosition(0, iterationCursorPosition + 2);
Console.WriteLine("Iteration #:\t{0}", regressionAlgorithm.CurrentIteration);
Console.WriteLine("Constant set:\t[{0}]", string.Join(" ; ", regressionAlgorithm.InConstant));
Console.WriteLine("ApproximationError:\t{0}", regressionAlgorithm.ApproximationError);
}
}
static void Main()
{
var sampleGenerator = new SampleGenerator(2, 6, 0.001);
var randomFormula = sampleGenerator.GetFormula();
Console.WriteLine("Formula before making constants noisy: {0}", randomFormula);
GenerateNoisyConstantsForNodeLeafes(randomFormula);
Console.WriteLine("Formula after making constants noisy: {0}", randomFormula);
Console.WriteLine("Press any key to start regression...");
Console.ReadKey(true);
var alg = new RegressionAlgorithm(randomFormula, sampleGenerator.InSamples, sampleGenerator.ExactResult);
ConsoleGui.Run(alg, 5, "");
Console.WriteLine("Result: {0}", alg.GetResult());
}
