private void UpdateStats()
{
if (Stats.Count > 0)
{
Last.SolveTime = Stats[Stats.Count - 1].SolveTime;
Last.Info = Stats[Stats.Count - 1].Info;
if (Best.Ticks == 0 || Best > Last.SolveTime)
{
Best = ((Best.Subtract(Best)).Add(Last.SolveTime));
}
if (Worst < Last.SolveTime)
{
Worst = ((Worst.Subtract(Worst)).Add(Last.SolveTime));
}
Average = ((Average.Subtract(Average)).Add(new TimeSpan(((Average.Ticks * (Stats.Count - 1)) + Last.SolveTime.Ticks) / Stats.Count)));
List <Statistic> temp = new List <Statistic>();
temp.AddRange(Stats);
temp = temp.OrderBy(s => s.SolveTime).ToList();
Median = ((Median.Subtract(Median)).Add((temp.Count % 2 == 1) ? (temp[(temp.Count - 1) / 2].SolveTime) : (new TimeSpan((((temp[(temp.Count / 2) - 1]).SolveTime.Ticks) + ((temp[temp.Count / 2]).SolveTime.Ticks)) / 2))));
temp.Clear();
Statistic b = null, w = null;
long a = 0;
if (Stats.Count >= 5)
{
temp.AddRange(Stats.Where((s) => { return((Stats.IndexOf(s) + 5) >= Stats.Count); }));
temp.ForEach((s) => { a += s.SolveTime.Ticks; if (b == null || b > s)
{
b = s;
}
if (w == null || w < s)
{
w = s;
}
});
AvgLastFive = ((AvgLastFive.Subtract(AvgLastFive)).Add(new TimeSpan(a / 5)));
if (AvgBestFive.Ticks == 0 || AvgBestFive > AvgLastFive)
{
AvgBestFive = ((AvgBestFive.Subtract(AvgBestFive)).Add(AvgLastFive));
}
temp.Remove(b);
temp.Remove(w);
a = 0;
temp.ForEach((s) => { a += s.SolveTime.Ticks; });
AvgLastThreeFive = ((AvgLastThreeFive.Subtract(AvgLastThreeFive)).Add(new TimeSpan(a / 3)));
if (AvgBestThreeFive.Ticks == 0 || AvgBestThreeFive > AvgLastThreeFive)
{
AvgBestThreeFive = ((AvgBestThreeFive.Subtract(AvgBestThreeFive)).Add(AvgLastThreeFive));
}
temp.Clear();
a = 0;
b = null;
w = null;
if (Stats.Count >= 10)
{
temp.AddRange(Stats.Where((s) => { return((Stats.IndexOf(s) + 10) >= Stats.Count); }));
temp.ForEach((s) => { a += s.SolveTime.Ticks; });
AvgLastTen = ((AvgLastTen.Subtract(AvgLastTen)).Add(new TimeSpan(a / 10)));
if (AvgBestTen.Ticks == 0 || AvgBestTen > AvgLastFive)
{
AvgBestTen = ((AvgBestTen.Subtract(AvgBestTen)).Add(AvgLastTen));
}
temp.Clear();
a = 0;
if (Stats.Count >= 12)
{
temp.AddRange(Stats.Where((s) => { return((Stats.IndexOf(s) + 12) >= Stats.Count); }));
temp.ForEach((s) => { if (b == null || b > s)
{
b = s;
}
if (w == null || w < s)
{
w = s;
}
});
temp.Remove(b);
temp.Remove(w);
temp.ForEach((s) => { a += s.SolveTime.Ticks; });
AvgLastTenTwelve = ((AvgLastTenTwelve.Subtract(AvgLastTenTwelve)).Add(new TimeSpan(a / 10)));
if (AvgBestTenTwelve.Ticks == 0 || AvgBestTenTwelve > AvgLastTenTwelve)
{
AvgBestTenTwelve = ((AvgBestTenTwelve.Subtract(AvgBestTenTwelve)).Add(AvgLastTenTwelve));
}
temp.Clear();
a = 0;
b = null;
w = null;
}
#region Resets
else
{
ResetTwelves();
}
}
else
{
ResetTens();
ResetTwelves();
}
}
else
{
ResetFives();
ResetTens();
ResetTwelves();
}
#endregion
}
else
{
ResetStats();
}
#region UpdateProperty() calls
UpdateProperty("Last");
UpdateProperty("Best");
UpdateProperty("Worst");
UpdateProperty("Average");
UpdateProperty("Median");
UpdateProperty("AvgLastFive");
UpdateProperty("AvgBestFive");
UpdateProperty("AvgLastTen");
UpdateProperty("AvgBestTen");
UpdateProperty("AvgLastThreeFive");
UpdateProperty("AvgBestThreeFive");
UpdateProperty("AvgLastTenTwelve");
UpdateProperty("AvgBestTenTwelve");
#endregion
}
public Population Breed()
{
if (indexes == null)
{
indexes = new List <int>();
for (var i = 0; i < Individuals.Count; i++)
{
for (var j = 0; j <= i; j++)
{
indexes.Add(j);
}
}
indexes.Sort();
}
var ranked = Rank().Individuals.ToList();
var bitmap = new System.Drawing.Bitmap(32, 32);
System.Drawing.Graphics graphics = System.Drawing.Graphics.FromImage(bitmap);
foreach (var chromosome in ranked.First().Chromosomes)
{
var argb = (chromosome.Color.A << 24) | (chromosome.Color.R << 16) | (chromosome.Color.G << 8) | chromosome.Color.B;
var brush = new System.Drawing.SolidBrush(System.Drawing.Color.FromArgb(argb));
graphics.FillRectangle(brush, chromosome.X, chromosome.Y, chromosome.Radius, chromosome.Radius);
}
FittestFile = Path.GetTempFileName() + ".ga.png";
bitmap.Save(FittestFile, System.Drawing.Imaging.ImageFormat.Png);
Best = ((int)Math.Abs(ranked[0].Fitness)).ToString("n0");
Worst = ((int)Math.Abs(ranked[ranked.Count - 1].Fitness)).ToString("n0");
Total = ranked.Sum(x => Math.Abs((long)x.Fitness)).ToString("n0");
Average = (((long)ranked.Average(x => Math.Abs((long)x.Fitness)))).ToString("n0");
Console.WriteLine($"{Utility.Generation.ToString().PadRight(6)}Best/Worst/Total/Average: {Best.PadLeft(15)}{Worst.PadLeft(15)}{Total.PadLeft(15)}{Average.PadLeft(15)}");
var nextGeneration = new List <Individual>();
while (nextGeneration.Count < Individuals.Count)
{
var twoRandoms = new[] { indexes[Utility.Random.Next(indexes.Count)], indexes[Utility.Random.Next(indexes.Count)] };
var momIndex = (twoRandoms[0] * twoRandoms[0]) / ranked.Count;
var popIndex = (twoRandoms[1] * twoRandoms[1]) / ranked.Count;
var mom = ranked[momIndex];
var pop = ranked[popIndex];
var child = Individual.Breed(mom, pop);
nextGeneration.Add(child);
}
return(new Population(nextGeneration.ToArray()));
}
public void AddPoints(Population population)
{
Best.Add(new Point(Best.Count, population.CalculateBestDistance()));
Worst.Add(new Point(Worst.Count, population.CalculateWorstDistance()));
Average.Add(new Point(Average.Count, population.CalculateAverageDistance()));
}
