private void initOptions()
{
int nIterations = _researchData.Updates[0].Count;
float[,] optionRange = SimOptions.optionRange;
int numberOfVars = (int)optionRange.GetLength(0);
float[] optionsValues = new float[numberOfVars];
SimOptions currentOption;
for (int o = 0; o < trialGroupSize; o++)
{
for (int i = 0; i < numberOfVars; i++)
{
optionsValues[i] = (float)rand.NextDouble() * (float)rand.NextDouble() * (float)rand.NextDouble() * (float)rand.NextDouble() * (optionRange[i, 1] - optionRange[i, 0]) + optionRange[i, 0];
}
currentOption = new SimOptions(optionsValues[0], optionsValues[1], optionsValues[2], optionsValues[3], optionsValues[4], optionsValues[5]);
//currentOption = new SimOptions(1, 1, 4.410256f, 1.1148f, 1.014489f);
currentOption.decayOfInteration = new float[nIterations];
for (int i = 0; i < nIterations; i++)
{
currentOption.decayOfInteration[i] = (float)rand.NextDouble() * (float)rand.NextDouble() * (float)rand.NextDouble() * (float)rand.NextDouble() * (optionRange[5, 1] - optionRange[5, 0]) + optionRange[5, 0];
}
options[o] = currentOption;
}
}
private void init()
{
_researchData = new ResearchData();
options = new SimOptions[trialGroupSize];
performances = new PredictionPerformances[trialGroupSize];
experiments = new Experiment[trialGroupSize];
bestOption = new SimOptions();
}
public static void WriteBest(SimOptions option)
{
using (FileStream fs = File.Open(@"bestOption.json", FileMode.Create))
using (StreamWriter sw = new StreamWriter(fs))
using (JsonWriter jw = new JsonTextWriter(sw))
{
jw.Formatting = Formatting.Indented;
JsonSerializer serializer = new JsonSerializer();
serializer.Serialize(jw, option);
}
}
private void findBestOption()
{
for (int e = 0; e < trialGroupSize; e++)
{
if (performances[e].occupancyPerformance > bestPerformanceNumber)
{
bestPerformanceNumber = performances[e].occupancyPerformance;
bestPerformance = performances[e];
bestOption = options[e];
}
}
}
private void initOptions()
{
float[,] optionRange = SimOptions.optionRange;
int numberOfVars = (int)optionRange.GetLength(0);
float[] optionsValues = new float[numberOfVars];
for (int o = 0; o < trialGroupSize; o++)
{
for (int i = 0; i < numberOfVars; i++)
{
optionsValues[i] = (float)rand.NextDouble() * (float)rand.NextDouble() * (float)rand.NextDouble() * (float)rand.NextDouble() * (optionRange[i, 1] - optionRange[i, 0]) + optionRange[i, 0];
}
options[o] = new SimOptions(optionsValues[0], optionsValues[1], optionsValues[2], optionsValues[3], optionsValues[4], optionsValues[5]);
}
}
public Experiment(ResearchData _data, SimOptions _options)
{
options = _options;
data = _data;
}
public ExperimentIterationSpecific(ResearchData _data, SimOptions _options)
{
options = _options;
_researchData = _data;
}
