private void LoadParameterInstructions()
{
XmlDocument doc = new XmlDocument();
doc.Load(ParameterInstructions);
List <ParameterSetting> parameters = new List <ParameterSetting>();
var children = doc["Root"]?.ChildNodes;
if (children != null)
{
foreach (XmlNode child in children)
{
if (child.Name == "Parameter")
{
var attributes = child.Attributes;
if (attributes != null)
{
ParameterSetting current = new ParameterSetting
{
ParameterName = attributes["Name"].InnerText,
MsNumber = int.Parse(attributes["MS"].InnerText),
Start = float.Parse(attributes["Start"].InnerText),
Stop = float.Parse(attributes["Stop"].InnerText)
};
current.Current = current.Start;
parameters.Add(current);
}
}
}
}
Parameters = parameters.ToArray();
}
public void Explore(ParameterSetting[] parameters, Action UpdateProgress, Func <ParameterSetting[], float> evaluationfunction)
{
this.Progress = 0;
Random rand = new Random((++this.NumberOfExplorations) * (this.RandomSeed));
var numberOfParameters = parameters.Length;
this.Kernel = parameters.Clone() as ParameterSetting[];
this.GenerateRandomSeed(rand);
float[,] explorationErrors = new float[numberOfParameters, 2];
float[,] explorationGradients = new float[numberOfParameters, 2];
ParameterSetting[, ][] explorationPoints = new ParameterSetting[numberOfParameters, 2][];
for (int i = 0; i < numberOfParameters; i++)
{
for (int j = 0; j < 2; j++)
{
explorationPoints[i, j] = parameters.Clone() as ParameterSetting[];
}
}
// Explore it for all of the pre-defined iterations
for (int iteration = 0; iteration < this.TotalIterations; iteration++)
{
this.CurrentIteration = iteration;
this.Progress = (float)iteration / this.TotalIterations;
UpdateProgress();
// figure out how good our point is
if (this.Exit)
{
break;
}
var kernelError = evaluationfunction(this.Kernel);
// Calculate all of the errors
GenerateExplorationPoints(numberOfParameters, this.Kernel, explorationPoints, explorationErrors, evaluationfunction, UpdateProgress);
// Calculate the gradients from the errors
ComputeGradients(numberOfParameters, explorationErrors, explorationGradients, kernelError);
MoveKernel(explorationGradients, rand);
}
this.Progress = 1;
}
private void LoadParameterInstructions()
{
XmlDocument doc = new XmlDocument();
doc.Load(this.ParameterInstructions);
List <ParameterSetting> parameters = new List <ParameterSetting>();
foreach (XmlNode child in doc["Root"].ChildNodes)
{
if (child.Name == "Parameter")
{
ParameterSetting current = new ParameterSetting();
current.ParameterName = child.Attributes["Name"].InnerText;
current.MSNumber = int.Parse(child.Attributes["MS"].InnerText);
current.Start = float.Parse(child.Attributes["Start"].InnerText);
current.Stop = float.Parse(child.Attributes["Stop"].InnerText);
current.Current = current.Start;
parameters.Add(current);
}
}
this.Parameters = parameters.ToArray();
}
public void Explore(ParameterSetting[] parameters, Action updateProgress, Func <ParameterSetting[], float> evaluationfunction)
{
Progress = 0;
Random rand = new Random((++NumberOfExplorations) * (RandomSeed));
var numberOfParameters = parameters.Length;
Kernel = parameters.Clone() as ParameterSetting[];
ParameterVolatility = new float[numberOfParameters];
Momentum = new float[numberOfParameters];
MoveChoice = new float[numberOfParameters];
PreviousMoveChoice = new float[numberOfParameters];
GenerateRandomSeed(rand);
float[,] explorationErrors = new float[numberOfParameters, 4];
float[,] explorationGradients = new float[numberOfParameters, 4];
ParameterSetting[, ][] explorationPoints = new ParameterSetting[numberOfParameters, 4][];
float bestSoFar = float.MaxValue;
int numberOfIterationSinceBest = 0;
for (int i = 0; i < numberOfParameters; i++)
{
for (int j = 0; j < 4; j++)
{
explorationPoints[i, j] = parameters.Clone() as ParameterSetting[];
}
}
// Explore it for all of the pre-defined iterations
for (int iteration = 0; iteration < TotalIterations; iteration++)
{
CurrentIteration = iteration;
Progress = (float)iteration / TotalIterations;
updateProgress();
// figure out how good our point is
if (Exit)
{
break;
}
var kernelError = evaluationfunction(Kernel);
if (kernelError < bestSoFar)
{
bestSoFar = kernelError;
numberOfIterationSinceBest = 0;
}
else if ((++numberOfIterationSinceBest) > IterationsFromBest)
{
break;
}
// Calculate all of the errors
GenerateExplorationPoints(numberOfParameters, Kernel, explorationPoints, explorationErrors, evaluationfunction, updateProgress);
// Calculate the gradients from the errors
ComputeGradients(numberOfParameters, explorationErrors, explorationGradients, kernelError);
ComputeVolatility(explorationGradients);
if (EarlyTermination())
{
break;
}
MoveKernel(explorationGradients, rand);
var moveChoiceTemp = PreviousMoveChoice;
PreviousMoveChoice = MoveChoice;
MoveChoice = moveChoiceTemp;
}
Progress = 1;
}
