public void EvaluateTest(DateTime startDate, DateTime endDate, int folds, string[] expectedDates, double[] expectedValues)
{
var config = new OptimizerConfiguration
{
StartDate = startDate,
EndDate = endDate,
FitnessTypeName = "Optimization.OptimizerFitness",
EnableFitnessFilter = true,
Genes = SetupGenes(),
Fitness = new FitnessConfiguration {
Folds = folds
}
};
var unit = new Wrapper(config);
GeneFactory.Initialize(config.Genes);
var actual = unit.Evaluate(new Chromosome(true, config.Genes));
Assert.AreEqual(1, actual);
var actualDates = new List <DateTime>();
var actualValues = new List <double>();
for (int i = 0; i < unit.ActualInSampleConfig.Count(); i++)
{
actualDates.Add(unit.ActualInSampleConfig[i].StartDate.Value);
actualDates.Add(unit.ActualInSampleConfig[i].EndDate.Value);
actualDates.Add(unit.ActualOutSampleConfig[i].StartDate.Value);
actualDates.Add(unit.ActualOutSampleConfig[i].EndDate.Value);
actualValues.Add((double)unit.ActualInSampleChromosome[i].ToDictionary()["Key"]);
actualValues.Add((double)unit.ActualInSampleChromosome[i].ToDictionary()["Key2"]);
actualValues.Add((double)unit.ActualOutSampleList[i]["Key"]);
actualValues.Add((double)unit.ActualOutSampleList[i]["Key2"]);
}
expectedDates.Select(s => DateTime.Parse(s)).ShouldDeepEqual(actualDates);
expectedValues.ShouldDeepEqual(actualValues);
}
public void GenerateTest()
{
var config = new[] { new GeneConfiguration {
Key = "slow", Actual = 200
}, new GeneConfiguration {
Key = "take", Precision = 2, Max = 0.06,
Min = 0.04, Actual = 0.05
} };
RandomizationProvider.Current = new BasicRandomization();
GeneFactory.Initialize(config);
var actual = GeneFactory.Generate(config[0], true);
Assert.AreEqual(200, (double)((KeyValuePair <string, object>)actual.Value).Value);
RandomizationProvider.Current = new BasicRandomization();
actual = GeneFactory.Generate(config[1], false);
Assert.IsTrue(double.TryParse(((KeyValuePair <string, object>)actual.Value).Value.ToString(), out var parsed));
Assert.AreEqual(2, GeneFactory.GetPrecision(parsed));
}
public void MinimizeTest()
{
var genes = new[]
{
new GeneConfiguration
{
Key = "1",
Actual = 1.23
},
new GeneConfiguration
{
Key = "2",
Actual = 123,
Min = 1,
Max = 123
},
new GeneConfiguration
{
Key = "3",
Min = 1,
Max = 2
}
};
var config = new OptimizerConfiguration
{
Genes = genes,
FitnessTypeName = "Optimization.OptimizerFitness",
EnableFitnessFilter = true,
};
var unit = new Mock <SharpeMaximizer>(config, new FitnessFilter())
{
CallBase = true
};
unit.Setup(x => x.RunAlgorithm(It.IsAny <Dictionary <string, object> >(), It.IsAny <IOptimizerConfiguration>())).Returns <Dictionary <string, object>, IOptimizerConfiguration>((l, c) =>
{
return(new Dictionary <string, decimal> {
{ "SharpeRatio", 1 }, { "CompoundingAnnualReturn", 1 }, { "TotalNumberOfTrades", 1 },
{ "LossRate", 0.1m }
});
});
GeneFactory.Initialize(config.Genes);
RandomizationProvider.Current = new BasicRandomization();
var chromosome = new Chromosome(true, genes, false);
var actual = unit.Object.Minimize(new[] { 3.21, 321, 456 }, chromosome);
Assert.AreEqual(0.999, actual.Error);
Assert.AreEqual(1.23, actual.ParameterSet[0]);
Assert.AreEqual(123, actual.ParameterSet[1]);
Assert.AreEqual(456, actual.ParameterSet[2]);
var nextActual = unit.Object.Minimize(new[] { 3.21, 321, 789 }, chromosome);
Assert.AreEqual(0.999, nextActual.Error);
Assert.AreEqual(3.21, nextActual.ParameterSet[0]);
Assert.AreEqual(321, nextActual.ParameterSet[1]);
Assert.AreEqual(789, nextActual.ParameterSet[2]);
}
public void InitializeTest()
{
GeneFactory.Initialize(new GeneConfiguration[0]);
Assert.IsNotNull(GeneFactory.Config);
}
