public static void Main()
{
const double epsilon = 0.5;
const int minNeighbors = 2;
var points = new List <Point>();
points.AddRange(MakeGaussianCircle(1, 100));
points.AddRange(MakeGaussianCircle(2, 100));
points.AddRange(MakeGaussianCircle(3, 100));
double EuclideanDistance(Point p1, Point p2)
{
var(x1, y1) = p1;
var(x2, y2) = p2;
return(Math.Sqrt(Math.Pow(x1 - x2, 2) + Math.Pow(y1 - y2, 2)));
}
var clustered = new Dbscan <Point, double>(EuclideanDistance, epsilon, minNeighbors);
var clusters = clustered.Cluster(points);
foreach (var cluster in clusters)
{
Console.WriteLine($"Cluster no. {cluster.Key} has {cluster.Value.Count} points");
}
}
private void Calculations()
{
List <Point> leftPoints;
List <Cluster> clusters;
Dbscan dbscan = new Dbscan(double.Parse(minPointsTextBox.Text), double.Parse(epsilonTextBox.Text), Points);
dbscan.Calculate(out leftPoints, out clusters);
UpdateGraphData(clusters, leftPoints);
MessageBox.Show(@"Done");
}
public void ClusterTest()
{
var vehicles = new List <Vehicle>
{
CreateVehicle(1, 1, 1),
CreateVehicle(2, 2, 1),
CreateVehicle(3, 1, 2),
CreateVehicle(4, 15, 1),
CreateVehicle(5, 100, 100),
CreateVehicle(6, 101, 110),
CreateVehicle(7, 105, 110),
CreateVehicle(8, 101, 110),
CreateVehicle(9, 401, 410),
CreateVehicle(10, 401, 410),
CreateVehicle(11, 401, 410),
CreateVehicle(12, 501, 510),
CreateVehicle(13, 501, 510),
};
var clusters = Dbscan.Cluster(vehicles, 15, 3);
Assert.AreEqual(3, clusters.Count);
var firstCluster = clusters.ElementAt(0).Select(v => v.Id).ToList();
Assert.AreEqual(4, firstCluster.Count);
Assert.True(firstCluster.Contains(1));
Assert.True(firstCluster.Contains(2));
Assert.True(firstCluster.Contains(3));
Assert.True(firstCluster.Contains(4));
var secondCluster = clusters.ElementAt(1).Select(v => v.Id).ToList();
Assert.AreEqual(4, secondCluster.Count);
Assert.True(secondCluster.Contains(5));
Assert.True(secondCluster.Contains(6));
Assert.True(secondCluster.Contains(7));
Assert.True(secondCluster.Contains(8));
var thirdCluster = clusters.ElementAt(2).Select(v => v.Id).ToList();
Assert.AreEqual(3, thirdCluster.Count);
Assert.True(thirdCluster.Contains(9));
Assert.True(thirdCluster.Contains(10));
Assert.True(thirdCluster.Contains(11));
}
public void BenchmarkTest(int unitsCount, double radius, int minimumClusterSize, int runsCount, double threshold)
{
var stopwatch = new Stopwatch();
for (var i = 0; i < runsCount; i++)
{
var vehicles = GenerateVehicles(unitsCount);
stopwatch.Start();
var clusters = Dbscan.Cluster(vehicles, radius, minimumClusterSize);
stopwatch.Stop();
Console.WriteLine($"Clusters found: {clusters.Count}, current time spent: {stopwatch.Elapsed}");
}
var average = TimeSpan.FromMilliseconds((double)stopwatch.ElapsedMilliseconds / runsCount);
Console.WriteLine($"Avarage: {average}");
Assert.Less(average, TimeSpan.FromMilliseconds(threshold));
}
private static void TryIntroduceNewFormations()
{
var newVehicleIds = VehicleRegistry
.GetNewCreatedVehicleIds()
.ToList();
if (!newVehicleIds.Any())
{
return;
}
var newVehicles = VehicleRegistry.GetVehiclesByIds(newVehicleIds);
var clusters = Dbscan.Cluster(newVehicles, 80, 33);
if (!clusters.Any())
{
return;
}
foreach (var cluster in clusters)
{
var ids = cluster.Select(v => v.Id).ToList();
formations.Add(new NewVehiclesFormation(MagicConstants.NextFormationId++, ids, CommandManager, VehicleRegistry));
VehicleRegistry.RemoveFromNewVehicles(ids);
}
}
public override VehicleFormationResult PerformAction(World world, Player me, Game game)
{
var army = new VehiclesGroup(Id, VehicleIds, VehicleRegistry, CommandManager);
if (!binded)
{
Bind(army);
return(new VehicleFormationResult(this));
}
commands.RemoveAll(c => c.IsStarted() && c.IsFinished(world.TickIndex, VehicleRegistry));
if (FormationHelper.IsNukeAlert(world.GetOpponentPlayer()) && world.TickIndex - nukePreventionTick > game.BaseTacticalNuclearStrikeCooldown / 2)
{
commands.Clear();
CommandManager.ClearCommandsQueue(Id);
this.PreventNuke(army, world, game, commands);
nukePreventionTick = world.TickIndex;
return(new VehicleFormationResult(this));
}
if (commands.Any())
{
return(new VehicleFormationResult(this));
}
var closestUncapturedFacility = VehicleRegistry.GetUncapturedFacilities(world, me, Id)
.Where(f => f.Type == FacilityType.VehicleFactory)
.OrderBy(f => army.Center.GetDistanceTo(f.ToPoint(game)))
.FirstOrDefault();
var myGroudForcesCenter = VehicleRegistry.GetVehiclesByIds(
VehicleRegistry.GetVehicleIdsByFormationId(MagicConstants.GroundFormationGroupId))
.ToList()
.GetCenterPoint();
var enemyVehicles = VehicleRegistry.EnemyVehicles(me);
var enemies = Dbscan.GetEnemiesClusters(enemyVehicles, DbscanRadius, DbscanMinimumClusterSize, world.TickIndex);
var nearestEnemy = enemies.OrderBy(c => c.GetCenterPoint().GetDistanceTo(army.Center)).FirstOrDefault();
if (nearestEnemy != null &&
this.TryNuke(army, VehicleRegistry.GetVehiclesByIds(army.VehicleIds), nearestEnemy, me, game, world, commands))
{
return(new VehicleFormationResult(new ShrinkAirVehicleFormation(Id, VehicleIds, CommandManager, VehicleRegistry)));
}
if (nearestEnemy != null &&
army.Center.GetDistanceTo(nearestEnemy.GetCenterPoint()) < game.TankVisionRange * 0.8 &&
nearestEnemy.Count > 1.2 * VehicleIds.Count)
{
army
.Select(Id)
.MoveByVector(nearestEnemy.GetCenterPoint().To(army.Center), game.TankSpeed);
commands.Add(CommandManager.PeekLastCommand(Id));
return(new VehicleFormationResult(this));
}
var nextTarget = closestUncapturedFacility?.ToPoint(game) ?? myGroudForcesCenter;
if (army.Center.GetDistanceTo(myGroudForcesCenter) < MagicConstants.NewVehiclesJoinRadius)
{
army
.Select(Id)
.Assign(MagicConstants.GroundFormationGroupId);
return(new VehicleFormationResult());
}
var direction = army.Center.To(nextTarget);
army
.Select(Id)
.MoveByVector(direction.Length() > 20
? direction.Mul(0.1)
: direction,
game.TankSpeed);
#if DEBUG
RewindClient.Instance.Line(army.Center.X, army.Center.Y, nextTarget.X, nextTarget.Y, Color.Fuchsia);
#endif
commands.Add(CommandManager.PeekLastCommand(Id));
return(new VehicleFormationResult(this));
}
private static IEnumerable <Vehicle> NextEnemyGroup(Point2D myArmyCenter, List <Vehicle> enemyVehicles, int tick)
{
var clusters = Dbscan.GetEnemiesClusters(enemyVehicles, DbscanRadius, DbscanMinimumClusterSize, tick);
return(clusters.OrderBy(c => c.GetCenterPoint().GetDistanceTo(myArmyCenter)).FirstOrDefault());
}
public string CreateGraph(Stud dataA, Stud dataB, bool kmeans, bool dbscan, bool linearregression,
bool polynomialregression, bool pearsoncorrelation, bool spearmancorrelation, bool knearest, bool naivebayes)
{
var gradedStudents = Students.StudentsGraded;
var classifyungraded = knearest || naivebayes;
if (classifyungraded)
{
var grades = new Dictionary <int, double>();
var clusters = new Dbscan(210, 3,
Students.StudentsGraded.Select(x => x.ToGenericVector(Stud.Attempts, Stud.Class, Stud.FailRatio,
Stud.Fails, Stud.Succeeds, Stud.SuccessRatio, Stud.Grade)));
foreach (var cluster in clusters.DataClusters)
{
grades[cluster.Key] = cluster.Value.Sum(x => x[6]) / cluster.Value.Count();
}
Classification classification = new NaiveBayesClassification(clusters.DataClusters, 50000);
if (knearest)
{
classification = new KnearestClassification(clusters.DataClusters, 5);
}
foreach (var student in Students.StudentsUngraded)
{
var cluster = classification.ClassifyPoint(student.ToGenericVector(Stud.Attempts, Stud.Class,
Stud.FailRatio, Stud.Fails, Stud.Succeeds, Stud.SuccessRatio, Stud.Grade));
student.Grade = (int)grades[cluster];
gradedStudents.Add(student);
}
}
var list = new List <int>();
var a = list
.GroupBy(x => x)
.Select(x => x.OrderBy(y => y))
.Select(x => x.First());
foreach (var student in gradedStudents)
{
student.Filter();
}
var data = new Dataset(gradedStudents.Select(x => x.ToGenericVector(dataA, dataB)));
var highChart = new HighchartsAdapter(Highchart.Scatterplot);
//Dbscan removes outliers, so we have to change are dataset afterwards
if (dbscan)
{
var newData = new List <GenericVector>();
var dBscan = new Dbscan(50, 3, data);
foreach (var cluster in dBscan.DataClusters)
{
newData.AddRange(cluster.Value);
}
data = new Dataset(newData);
highChart.AddClusters(dBscan);
}
if (kmeans)
{
highChart.AddClusters(new Kmeans(4, 100, data));
}
if (linearregression)
{
highChart.AddRegression(new LinearRegression(data.Select(x => x.ToVector2())));
}
if (polynomialregression)
{
highChart.AddRegression(new PolynomialRegression(data.Select(x => x.ToVector2()), 3));
}
if (pearsoncorrelation)
{
highChart.AddCorrelation(new PearsonCorrelation(data.Select(x => x.ToVector2())));
}
if (spearmancorrelation)
{
highChart.AddCorrelation(new SpearmanCorrelation(data.Select(x => x.ToVector2())));
}
highChart.SetDivId("plotkmeans");
highChart.SetTitle($"{dataA} vs {dataB}");
highChart.SetXlabel(dataA.ToString());
highChart.SetYlabel(dataB.ToString());
return(highChart.CreateTemplate());
}
