/// <summary>
/// Generally two termination criteria are available. Iteration count and best fitness value.
/// </summary>
/// <param name="tc"></param>
/// <param name="counter"></param>
/// <param name="bestFitness"></param>
/// <returns></returns>
private bool isCriteriaSatisfied(TerminationCriteria tc, int counter, float bestFitness)
{
if (tc.IsIteration)
{
return(counter >= tc.Value);
}
else
{
return(bestFitness >= tc.Value);
}
}
public async Task RunAsync(Action <ProgressReport, Parameters> reportProgress, TerminationCriteria tc, CancellationToken ct)
{
m_TerminationCriteria = tc;
await Task.Run(() => startEvolution(reportProgress, tc, ct));
}
/// <summary>
/// Start with evolution
/// </summary>
/// <param name="reportProgress"></param>
/// <param name="tc"></param>
/// <param name="ct"></param>
private void startEvolution(Action <ProgressReport, Parameters> reportProgress, TerminationCriteria tc, CancellationToken ct)
{
Stopwatch sp = new Stopwatch();
try
{
//send report population initialized and evaluated
m_History.Add(initEvolution(m_progresReport));
reportProgress(m_progresReport, m_Parameters);
//init termination criteria
int iterationCount = m_progresReport.Iteration;
m_progresReport.IterationStatus = IterationStatus.Runing;
//
float bestFitness = 0;
bool breakLoop = false;
while (!breakLoop)
{
//report progress
sp.Restart();
m_progresReport.IterationStatus = IterationStatus.Runing;
iterationCount++;
//
performIteration(m_progresReport, ct);
//get best solution for the current iteration
bestFitness = m_progresReport.BestSolution.Fitness;
//check for termination criteria
if (isCriteriaSatisfied(tc, iterationCount, bestFitness) || bestFitness == 1000)
{
//stopping iteration
m_progresReport.IterationStatus = IterationStatus.Compleated;
breakLoop = true;
}
//check for cancellation criteria
if (ct.IsCancellationRequested)
{
//canceling iteration
m_progresReport.IterationStatus = IterationStatus.Stopped;
breakLoop = true;
}
//report progress
m_progresReport.Iteration = iterationCount;
//pr.BestSolution= bestFitness
m_progresReport.IterationStatistics.IterationSeconds = (float)sp.Elapsed.TotalSeconds;
//send report and store in history
m_History.Add(initEvolution(m_progresReport));
reportProgress(m_progresReport, m_Parameters);
}
}
catch (Exception ex)
{
m_progresReport.IterationStatus = IterationStatus.Exception;
m_progresReport.Message = ex.Message;
m_History.Add(initEvolution(m_progresReport));
reportProgress(m_progresReport, m_Parameters);
// throw;
}
}
public void GPFactoryFromString(string strFactory)
{
if (string.IsNullOrEmpty(strFactory))
{
return;
}
try
{
Evolution[] hist = null;
JsonSerializerSettings sett = new JsonSerializerSettings();
sett.NullValueHandling = NullValueHandling.Ignore;
var obj = JsonConvert.DeserializeObject(strFactory, sett);
var param = ((dynamic)obj)["m_Parameters"] as Newtonsoft.Json.Linq.JObject;
var ter = ((dynamic)obj)["m_TerminalSet"] as Newtonsoft.Json.Linq.JArray;
var fun = ((dynamic)obj)["m_FunctionSet"] as Newtonsoft.Json.Linq.JArray;
var prog = ((dynamic)obj)["m_progresReport"] as Newtonsoft.Json.Linq.JObject;
var tc = ((dynamic)obj)["m_TerminationCriteria"] as Newtonsoft.Json.Linq.JObject;
var hi = ((dynamic)obj)["history"] as Newtonsoft.Json.Linq.JArray;
var pop = ((dynamic)obj)["popStr"] as Newtonsoft.Json.Linq.JValue;
if (param != null)
{
m_Parameters = param.ToObject <Parameters>();
}
if (ter != null)
{
m_TerminalSet = ter.ToObject <int[]>();
}
if (fun != null)
{
m_FunctionSet = fun.ToObject <Function[]>();
}
if (prog != null)
{
m_progresReport = prog.ToObject <ProgressReport>();
}
if (tc != null)
{
m_TerminationCriteria = tc.ToObject <TerminationCriteria>();
}
if (hi != null)
{
hist = hi.ToObject <Evolution[]>();
}
//create history
if (hist != null)
{
m_History = new List <Evolution>(hist);
}
m_Population = new Population();
if (pop != null)
{
var popStr = pop.ToObject <string>();
m_Population.PopulationFromString(popStr);
}
}
catch (Exception)
{
throw;
}
}
