/// <exception cref="System.Exception"/>
protected internal override void InitFromParameters()
{
base.InitFromParameters();
_effort = 0;
string cases = GetParam("test-cases", true);
string casesClass = GetParam("test-case-class", true);
if (cases == null && casesClass == null)
{
throw new Exception("No acceptable test-case parameter.");
}
if (casesClass != null)
{
// Get test cases from the TestCasesClass.
Type iclass = Type.GetType(casesClass);
object iObject = System.Activator.CreateInstance(iclass);
if (!(iObject is TestCaseGenerator))
{
throw (new Exception("test-case-class must inherit from class TestCaseGenerator"));
}
TestCaseGenerator testCaseGenerator = (TestCaseGenerator)iObject;
int numTestCases = testCaseGenerator.TestCaseCount();
for (int i = 0; i < numTestCases; i++)
{
ObjectPair testCase = testCaseGenerator.TestCase(i);
float @in = (float)testCase._first;
float @out = (float)testCase._second;
Print(";; Fitness case #" + i + " input: " + @in + " output: " + @out + "\n");
_testCases.Add(new GATestCase(@in, @out));
}
}
else
{
// Get test cases from test-cases.
Program caselist = new Program(cases);
for (int i = 0; i < caselist.Size(); i++)
{
Program p = (Program)caselist.DeepPeek(i);
if (p.Size() < 2)
{
throw new Exception("Not enough elements for fitness case \"" + p + "\"");
}
float @in = System.Convert.ToSingle(p.DeepPeek(0).ToString());
float @out = System.Convert.ToSingle(p.DeepPeek(1).ToString());
Print(";; Fitness case #" + i + " input: " + @in + " output: " + @out + "\n");
_testCases.Add(new GATestCase(@in, @out));
}
}
// Create and initialize predictors
_predictorEffortPercent = GetFloatParam("PREDICTOR-effort-percent", true);
_predictorGA = PredictionGA.PredictionGAWithParameters(this, GetPredictorParameters(_parameters));
}
// Note: Oldest trainer has the lowest index; newest trainer has the highest
// index.
// The solution population and genetic algorithm.
/// <summary>
/// Customizes GA.GAWithParameters to allow the inclusion of the solution GA,
/// which is required for the initialization of the prediction GA.
/// </summary>
/// <param name="ceFloatSymbolicRegression"/>
/// <param name="getPredictorParameters"/>
/// <returns/>
/// <exception cref="System.Exception"></exception>
public static PredictionGA PredictionGAWithParameters(PushGP inSolutionGA, Dictionary <string, string> inParams)
{
Type cls = Type.GetType(inParams["problem-class"]);
object gaObject = System.Activator.CreateInstance(cls);
if (!(gaObject is PredictionGA))
{
throw (new Exception("Predictor problem-class must inherit from" + " class PredictorGA"));
}
PredictionGA ga = (PredictionGA)gaObject;
// Must set the solution GA before InitFromParameters, since the latter
// uses _solutionGA while creating the predictor population.
ga.SetSolutionGA(inSolutionGA);
ga.SetParams(inParams);
ga.InitFromParameters();
return(ga);
}