private void bttnLoadScript_Click(object sender, RoutedEventArgs e)
{
try
{
var script = new ConfigScript();
script.Load(txtScriptFile.Text);
script.Analyze(script.TrainingFile);
UpdateButtons();
lblPopFile.Content = script.PopulationFile;
lblEvaluateFilesIn.Content = "Input: " + script.EvaluationFile;
lblEvaluateFilesOut.Content = "Output: " + script.EvaluationFile;
ApplicationSingleton.Instance.Config = script;
}
catch (Exception ex)
{
MessageBox.Show(ex.Message, ex.GetType().Name );
}
}
public static Genome GenerateRandomGenome(Random rnd, ConfigScript script, int genomeSize)
{
var result = new Genome(genomeSize);
for (int i = 0; i < result.Genes.Length; i++)
{
result.Genes[i] = rnd.NextDouble();
}
return result;
}
/// <summary>
/// Setup the population.
/// </summary>
/// <param name="config"></param>
public void Init(ConfigScript config)
{
_config = config;
}
public void Init(ConfigScript script, string config)
{
_inputCount = script.DetermineRawInputCount();
_outputCount = script.DetermineRawOutputCount();
// parse out name-value pairs
Dictionary<string, string> pairs =
config.Split(',')
.Select(x => x.Split('='))
.ToDictionary(y => y[0], y => y[1]);
_rbfCount = int.Parse(pairs["rbf"]);
// calculate input and output weight counts
// add 1 to output to account for an extra bias node
int inputWeightCount = _inputCount*_rbfCount;
int outputWeightCount = (_rbfCount + 1)*_outputCount;
int rbfParams = (_inputCount + 1)*_rbfCount;
_genomeSize = inputWeightCount + outputWeightCount + rbfParams;
_indexInputWeights = 0;
_indexRBFParams = inputWeightCount;
_indexOutputWeights = _indexRBFParams + rbfParams;
_cutLength = _genomeSize/script.MaxParents;
if (_cutLength < 1)
{
_cutLength = 1;
}
}
public Genome GenerateRandomGenome(Random rnd, ConfigScript script)
{
return TypicalGAModel.GenerateRandomGenome(rnd, script, _genomeSize);
}
public DataFile(ConfigScript config)
{
_config = config;
}
