public RandomnessTexture(GraphicsState graphics)
{
const int size = 2048;
var rf = graphics.Device.ResourceFactory;
Texture = rf.CreateTexture(new TextureDescription(size, size, 1, 1, 1, PixelFormat.R32_G32_B32_A32_Float,
TextureUsage.Sampled, TextureType.Texture2D));
Sampler = rf.CreateSampler(new SamplerDescription(SamplerAddressMode.Wrap, SamplerAddressMode.Wrap,
SamplerAddressMode.Wrap, SamplerFilter.MinPoint_MagPoint_MipPoint, null, 0, 0, 0, 0,
SamplerBorderColor.TransparentBlack));
ResourceLayout = rf.CreateResourceLayout(new ResourceLayoutDescription(
new ResourceLayoutElementDescription(nameof(Texture), ResourceKind.TextureReadOnly,
ShaderStages.Compute | ShaderStages.Fragment | ShaderStages.Vertex),
new ResourceLayoutElementDescription(nameof(Sampler), ResourceKind.Sampler,
ShaderStages.Compute | ShaderStages.Fragment | ShaderStages.Vertex)
));
ResourceSet = rf.CreateResourceSet(new ResourceSetDescription(ResourceLayout, Texture, Sampler));
var random = new TRandom(42);
var texture = new RgbaFloat[size * size];
for (var i = 0; i < size * size; i++)
{
var vec = Vector2.Normalize(new Vector2((float)random.Normal(0, 1), (float)random.Normal(0, 1)))
* (float)random.NextDouble().Squared().Squared().Squared() * 2;
texture[i] = new RgbaFloat(
vec.X, vec.Y, (float)random.NextDouble(), (float)random.NextDouble()
);
}
graphics.Device.UpdateTexture(Texture, texture, 0, 0, 0, size, size, 1, 0, 0);
}
private static IEnumerable <Order> GenerateRandom(
int orderCount,
string baseCurrency,
string quoteCurrency,
double minPrice,
double maxPrice)
{
var price = new TRandom();
var amount = new TRandom();
for (var i = 0; i < orderCount; i++)
{
yield return(new Order(
new CurrencyPair(baseCurrency, quoteCurrency),
Side.Buy,
decimal.Round((decimal)price.NextDouble(minPrice, maxPrice), 4),
amount.Next(1, 100)));
yield return(new Order(
new CurrencyPair(baseCurrency, quoteCurrency),
Side.Sell,
decimal.Round((decimal)price.NextDouble(minPrice, maxPrice), 4),
amount.Next(1, 100)));
}
}
public static Cell GenerateRandomCell(Type cell, Simulation simulation)
{
Vector startingVector = new Vector(random.NextDouble() * 20 - 10,
random.NextDouble() * 20 - 10,
random.NextDouble() * 20 - 10);
return((Cell)Activator.CreateInstance(cell, simulation, startingVector,
(0.875 + random.NextDouble() / 4), 0.8));
}
/// <summary>
/// Generates random normalized vector;
/// </summary>
/// <returns>Generated vector;</returns>
public static Vector Create(TRandom random)
{
double fi = random.NextDouble() * Math.PI * 2;
double fi1 = random.NextDouble() * Math.PI * 2;
Vector retval = new Vector(Math.Cos(fi) * Math.Cos(fi1), Math.Sin(fi) * Math.Cos(fi1), Math.Sin(fi1));
return(retval);
}
double GetGradient(int x, int y)
{
rndEngine.Reset(rowSeed[y]);
for (int i = 0; i < x; i++)
{
rndEngine.NextDouble();
}
return(rndEngine.NextDouble());
}
static List <GameObject> CreateGameObjects()
{
var random = new TRandom();
var gameObjects = new List <GameObject>();
var floor = new GameObject();
floor.Mesh = Primitives.CreatePlane();
floor.Transform.Scale.X = 100;
floor.Transform.Scale.Z = 100;
gameObjects.Add(floor);
_playerGO = new GameObject();
_playerGO.Transform.Position.Y = 2;
for (int i = 0; i < 1000; i++)
{
var newObstacleGO = new GameObject();
newObstacleGO.Mesh = Primitives.CreateCube36();
newObstacleGO.Transform.Position.X = (float)random.NextDouble(-100, 100);
newObstacleGO.Transform.Position.Z = (float)random.NextDouble(-100, 100);
newObstacleGO.Transform.Position.Y = (float)random.NextDouble(1, 10);
newObstacleGO.Transform.Scale.X = (float)random.NextDouble(0.1f, 3);
newObstacleGO.Transform.Scale.Y = (float)random.NextDouble(0.1f, 3);
newObstacleGO.Transform.Scale.Z = (float)random.NextDouble(0.1f, 3);
newObstacleGO.Transform.Rotation.X = (float)random.NextDouble(0, 360);
newObstacleGO.Transform.Rotation.Y = (float)random.NextDouble(0, 360);
newObstacleGO.Transform.Rotation.Z = (float)random.NextDouble(0, 360);
gameObjects.Add(newObstacleGO);
}
return(gameObjects);
}
public RequestBuilder(Client client, ISettings settings)
{
_client = client;
_settings = settings;
if (_sessionHash == null)
{
GenerateNewHash();
}
_course = (float)TRandomDevice.NextDouble(0, 359.9);
}
/// <summary>
/// Generates a few random <see cref="LocationFix"/>es to act like a real GPS sensor.
/// </summary>
/// <param name="requestEnvelope">The <see cref="RequestEnvelope"/> these <see cref="LocationFix"/>es are used for.</param>
/// <param name="timestampSinceStart">The milliseconds passed since starting the <see cref="Session"/> used by the current <see cref="RequestEnvelope"/>.</param>
/// <returns></returns>
private List <LocationFix> BuildLocationFixes(RequestEnvelope requestEnvelope, long timestampSinceStart)
{
var locationFixes = new List <LocationFix>();
TRandom Random = new TRandom();
if (requestEnvelope.Requests.Count == 0 || requestEnvelope.Requests[0] == null)
{
return(locationFixes);
}
var providerCount = Random.Next(4, 10);
for (var i = 0; i < providerCount; i++)
{
var timestampSnapshot = timestampSinceStart + (150 * (i + 1) + Random.Next(250 * (i + 1) - 150 * (i + 1)));
if (timestampSnapshot >= timestampSinceStart)
{
if (locationFixes.Count != 0)
{
break;
}
timestampSnapshot = timestampSinceStart - Random.Next(20, 50);
if (timestampSnapshot < 0)
{
timestampSnapshot = 0;
}
}
locationFixes.Insert(0, new LocationFix
{
TimestampSnapshot = (ulong)timestampSnapshot,
Latitude = (float)_client.CurrentLatitude,
Longitude = (float)_client.CurrentLongitude,
HorizontalAccuracy = (float)Random.NextDouble(5.0, 25.0),
VerticalAccuracy = (float)Random.NextDouble(5.0, 25.0),
Altitude = (float)_client.CurrentAltitude,
Provider = "fused",
ProviderStatus = 3,
LocationType = 1,
// Speed = ?,
Course = -1,
// Floor = 0
});
}
return(locationFixes);
}
public void Mutation()
{
bool first = true;
foreach (var specimen in Population)
{
if (first)
{
first = false;
continue;
}
var net = specimen.Value;
foreach (var layer in net.Layers)
{
foreach (var neuron in layer.Neurons)
{
var weights = neuron.GetWeights();
for (var i = 0; i < weights.Length; i++)
{
if (Random.NextDouble() < Config.MutationChance)
{
weights[i] += Config.RandOptions.Normal.NextDouble();
}
}
}
}
}
}
private static TIndividual GetRandomIndiviual <TIndividual>(IReadOnlyList <TIndividual> individuals, TRandom rnd)
{
double count = individuals.Count;
double p(int index)
{
double rank = count - index;
return(2 * rank / (count * (count + 1.0)));
}
var r = rnd.NextDouble(0, 1);
var minP = 0.0;
var i = 0;
foreach (var individual in individuals)
{
var maxP = p(i) + minP;
if (r >= minP && r <= maxP)
{
return(individual);
}
i++;
minP = maxP;
}
return(individuals.Last());
}
/// <summary>
/// Helper method assisting with generation of random telemetry data
/// </summary>
private static int GetRandomWeightedNumber(int max, int min, double probabilityPower)
{
var randomDouble = _random.NextDouble();
var result = Math.Floor(min + (max + 1 - min) * (Math.Pow(randomDouble, probabilityPower)));
return((int)result);
}
public static void Main()
{
// 1) Use TRandom to generate a few random numbers - via IGenerator methods.
Console.WriteLine("TRandom in action, used as an IGenerator");
var trandom = new TRandom();
Console.WriteLine(trandom.Next() - trandom.Next(5) + trandom.Next(3, 5));
Console.WriteLine(trandom.NextDouble() * trandom.NextDouble(5.5) * trandom.NextDouble(10.1, 21.9));
Console.WriteLine(trandom.NextBoolean());
Console.WriteLine();
// 2) Use TRandom to generate a few random numbers - via extension methods.
Console.WriteLine("TRandom in action, used as an IGenerator augmented with extension methods");
Console.WriteLine(string.Join(", ", trandom.Integers().Take(10)));
Console.WriteLine(string.Join(", ", trandom.Doubles().Take(10)));
Console.WriteLine(string.Join(", ", trandom.Booleans().Take(10)));
Console.WriteLine();
// 3) Use TRandom to generate a few distributed numbers.
Console.WriteLine("TRandom in action, used as to get distributed numbers");
Console.WriteLine(trandom.Normal(1.0, 0.1));
Console.WriteLine(string.Join(", ", trandom.NormalSamples(1.0, 0.1).Take(20)));
Console.WriteLine(trandom.Poisson(5));
Console.WriteLine(string.Join(", ", trandom.PoissonSamples(5).Take(20)));
Console.WriteLine();
// 4) There are many generators available - XorShift128 is the default.
var alf = new ALFGenerator(TMath.Seed());
var nr3 = new NR3Generator();
var std = new StandardGenerator(127);
// 5) You can also use distribution directly, even with custom generators.
Console.WriteLine("Showcase of some distributions");
Console.WriteLine("Static sample for Normal: " + NormalDistribution.Sample(alf, 1.0, 0.1));
Console.WriteLine("New instance for Normal: " + new NormalDistribution(1.0, 0.1).NextDouble());
Console.WriteLine();
}
/// <summary>
/// Generates a few random <see cref="LocationFix"/>es to act like a real GPS sensor.
/// </summary>
/// <param name="requestEnvelope">The <see cref="RequestEnvelope"/> these <see cref="LocationFix"/>es are used for.</param>
/// <param name="timestampSinceStart">The milliseconds passed since starting the <see cref="Session"/> used by the current <see cref="RequestEnvelope"/>.</param>
/// <returns></returns>
private List <Signature.Types.LocationFix> BuildLocationFixes(RequestEnvelope requestEnvelope, long timestampSinceStart)
{
var locationFixes = new List <Signature.Types.LocationFix>();
if (requestEnvelope.Requests.Count == 0 || requestEnvelope.Requests[0] == null)
{
return(locationFixes);
}
var providerCount = TRandomDevice.Next(4, 10);
for (var i = 0; i < providerCount; i++)
{
var timestampSnapshot = timestampSinceStart + (150 * (i + 1) + TRandomDevice.Next(250 * (i + 1) - 150 * (i + 1)));
if (timestampSnapshot >= timestampSinceStart)
{
if (locationFixes.Count != 0)
{
break;
}
timestampSnapshot = timestampSinceStart - TRandomDevice.Next(20, 50);
if (timestampSnapshot < 0)
{
timestampSnapshot = 0;
}
}
var tmpCourse = -1F;
var mpSpeed = 0F;
if (_client.Platform == Platform.Ios)
{
tmpCourse = (float)TRandomDevice.NextDouble(100, 330);
mpSpeed = (float)TRandomDevice.NextDouble(0.9, 2.2);
}
locationFixes.Insert(0, new Signature.Types.LocationFix {
TimestampSnapshot = (ulong)timestampSnapshot,
Latitude = (float)_client.CurrentLatitude,
Longitude = (float)_client.CurrentLongitude,
HorizontalAccuracy = (float)TRandomDevice.NextDouble(5.0, 25.0),
VerticalAccuracy = (float)TRandomDevice.NextDouble(5.0, 25.0),
Altitude = (float)_client.CurrentAltitude,
Provider = "fused",
ProviderStatus = 3,
LocationType = 1,
Speed = mpSpeed,
Course = tmpCourse,
// Floor = 0
});
}
return(locationFixes);
}
public static async Task HandleAccountAfterCreation(Configuration config, AccountCreationResult account)
{
var random = new TRandom();
POGOLib.Official.Configuration.Hasher = new PokeHashHasher(config.TutorialSettings.HashKey);
var client = await GetSession(new PtcLoginProvider(account.Username, account.Password),
config.TutorialSettings.Latitude, config.TutorialSettings.Longitude);
if (!await client.StartupAsync())
{
throw new SessionFailedError();
}
if (config.TutorialSettings.Level2 || config.TutorialSettings.Level5)
{
var ts = await Tutorial.GetTutorialState(client);
await Tutorial.CompleteTutorial(client, ts);
// Level 2: Stop here.
// Level 5: Keep going.
if (config.TutorialSettings.Level5)
{
while (client.Player.Stats.Level < 5)
{
var lat = client.Player.Latitude + random.NextDouble(0.005, -0.005);
var lng = client.Player.Longitude + random.NextDouble(0.005, -0.005);
client.Player.SetCoordinates(lat, lng);
foreach (var cell in client.Map.Cells)
{
foreach (var pokemon in cell.CatchablePokemons)
{
if (DistanceBetweenPlaces(client.Player.Longitude, client.Player.Latitude,
pokemon.Latitude, pokemon.Longitude) <= client.GlobalSettings.MapSettings
.EncounterRangeMeters / 1000)
{
var encRes = EncounterResponse.Parser.ParseFrom(await client.RpcClient.
SendRemoteProcedureCallAsync(new Request
{
RequestType = RequestType.Encounter,
RequestMessage = new EncounterMessage
{
EncounterId = pokemon.EncounterId,
SpawnPointId = pokemon.SpawnPointId,
PlayerLatitude = client.Player.Latitude,
PlayerLongitude = client.Player.Longitude
}.ToByteString()
}));
await Task.Delay(random.Next(825, 1250));
if (encRes.Status == EncounterResponse.Types.Status.EncounterSuccess)
{
while (true)
{
var r = CatchPokemonResponse.Parser.ParseFrom(
await client.RpcClient.SendRemoteProcedureCallAsync(new Request
{
RequestType = RequestType.CatchPokemon,
RequestMessage = new CatchPokemonMessage
{
EncounterId = pokemon.EncounterId,
HitPokemon = true,
SpawnPointId = pokemon.SpawnPointId,
NormalizedHitPosition = 1,
NormalizedReticleSize = random.NextDouble(1.7, 1.95),
Pokeball = ItemId.ItemPokeBall,
SpinModifier = 1
}.ToByteString()
}));
if (r.Status == CatchPokemonResponse.Types.CatchStatus.CatchSuccess ||
r.Status == CatchPokemonResponse.Types.CatchStatus.CatchEscape)
{
break;
}
}
}
}
}
foreach (var fort in cell.Forts)
{
if (DistanceBetweenPlaces(client.Player.Longitude, client.Player.Latitude,
fort.Longitude, fort.Latitude) <=
client.GlobalSettings.FortSettings.InteractionRangeMeters / 1000)
{
if (fort.Type == FortType.Checkpoint)
{
await client.RpcClient.SendRemoteProcedureCallAsync(new Request
{
RequestType = RequestType.FortDetails,
RequestMessage = new FortDetailsMessage
{
FortId = fort.Id,
Latitude = fort.Latitude,
Longitude = fort.Longitude
}.ToByteString()
});
await Task.Delay(random.Next(600, 750));
await client.RpcClient.SendRemoteProcedureCallAsync(new Request
{
RequestType = RequestType.FortSearch,
RequestMessage = new FortSearchMessage
{
FortId = fort.Id,
FortLatitude = fort.Latitude,
FortLongitude = fort.Longitude,
PlayerLatitude = client.Player.Latitude,
PlayerLongitude = client.Player.Longitude
}.ToByteString()
});
}
}
}
}
}
}
}
}
public ResponseMessage SortPoints([FromBody] PointsVm pointsVm)
{
try
{
var tspmode = TTSPmode.tspOpen;
var gf = TGISFormat.gfSHP;
var mTSP = new List <int>();
var sortedPoint = new List <GeoNode>();
//var point = JsonConvert.DeserializeObject<points>(w);
//var count = point.coordinates.Count - 1;
var shpfolder = _appSettings.RoutewareSettings.ShapeFolder.Replace("{{region}}", pointsVm.Region);
var binfolder = _appSettings.RoutewareSettings.BinFolder.Replace("{{region}}", pointsVm.Region);
var outfolder = _appSettings.RoutewareSettings.OutputFolder.Replace("{{region}}", pointsVm.Region);
var NW = new TNetwork();
NW.InitPassword(_appSettings.RoutewareSettings.Password);
NW.Directory = binfolder;
NW.Open(true, true, true, 0); // open attributes too, don't cache coord3 and open externID without caching
NW.OpenLimit(1, 1, false);
NW.OpenLimit(2, 2, true);
NW.OpenRoadName(1, false);
NW.CreateArrayTime(3); // 3 time arrays: 0,1,2
NW.CreateArrayCost(1); // 1 cost array: 0
// set speed as value based upon road classes 1,2,3,4,6 (store in index 0)
TRoadClassSpeed rcs = new TRoadClassSpeed();
rcs[1] = 110;
rcs[2] = 80;
rcs[3] = 65;
rcs[4] = 55;
rcs[5] = 45;
rcs[6] = 25;
NW.CalculateTime(0, rcs);
TRandom r = new TRandom();
r.SetSeed(987654321);
// read speed into ArrayTime[2] from field "speed" in link.dbf
NW.ReadSpeed(2, shpfolder + "\\link.dbf", 0, "speed", false);
int link;
// set speed as random value from 60-100 km/h (store in index 1)
for (link = 1; link <= NW.LinkCount; link++)
{
NW.SetSpeed(1, link, 60 + 40 * (float)r.NextDouble());
}
// set cost as the same as time from index 0
for (link = 1; link <= NW.LinkCount; link++)
{
NW.SetCost(0, link, NW.GetTime(0, link));
}
NW.UpdateAlphas();
TSpatialSearch ss = new TSpatialSearch(NW);
TLocationList ll = new TLocationList();
TBitArray TBA = new TBitArray(1000);
TIntegerList nl = new TIntegerList();
if (pointsVm.Nodes != null)
{
for (int i = 0; i < pointsVm.Nodes.Count; i++)
{
TFloatPoint fp;
fp.x = Convert.ToDouble(pointsVm.Nodes[i].Coordinates[0]);
fp.y = Convert.ToDouble(pointsVm.Nodes[i].Coordinates[1]);
TLocation ll1 = new TLocation();
int side = 0;
double distance = 0;
TFloatPoint fPnew = new TFloatPoint();
ss.NearestLocation(fp, out ll1, out side, out distance, out fPnew);
ll.Add1(ll1);
ll.Add3(fp);
ll.Add4(ll1, fp);
nl.Add(ss.NearestNodeSimple(fp));
}
ll.Sort();
nl.Sort();
nl.RemoveDuplicates();
}
TRouteCalc calc = new TRouteCalc(NW, false);
calc.SetTime(0);
calc.SetFastest(false);
calc.MaxSpeed = 110; // 90 > 80 and 110 > 80
float[][] matrix = calc.Matrix(nl, (tspmode != TTSPmode.tspRoundTrip), false);
// A faster and straight-line matrix
// TMatrix Matrix = NW.Matrix(NL,(mode != TTspmode.tspRoundTrip));
// optimize sequence of matrix
TTSP tsp = new TTSP {
Mode = tspmode
};
tsp.Execute(matrix);
for (int i = 0; i < nl.Count; i++)
{
mTSP.Add(tsp.SortedIndex[i]);
}
// Use TDrivingDirections for output
TGISWrite output = NW.GISoutputInit(outfolder + "tsp_driving", gf);
TDrivingDirections dd = new TDrivingDirections(calc)
{
ConcatenationMode = TConcatenationMode.cmCompact,
RoundTrip = (tspmode == TTSPmode.tspRoundTrip),
SortedIndex = tsp.SortedIndex
};
dd.RouteList(output, nl);
output = NW.GISoutputInit(outfolder + "tsp", gf);
output.StartHeader(1, TObjectTypes.otPline);
output.AddField("sequence", TGISField.gfInteger, 0, 0);
int d = 0;
if (tspmode != TTSPmode.tspRoundTrip)
{
d = 1;
}
for (int i = 0; i < nl.Count - d; i++)
{
int node1 = nl[tsp.SortedIndex[i]];
int node2 = i != nl.Count - 1 ? nl[tsp.SortedIndex[i + 1]] : nl[tsp.SortedIndex[0]];
calc.Route(node1, node2);
TRoute route = calc.RouteFind(node2);
TFloatPointArrayEx list = NW.GetGISSectionRoute(route);
output.AddObject(1, false, i.ToString(CultureInfo.InvariantCulture));
output.AddSection(1, ref list);
}
output.Close();
output = NW.GISoutputInit(outfolder + "tsppoint", gf);
output.StartHeader(1, TObjectTypes.otPoint);
output.AddField("sequence", TGISField.gfInteger, 0, 0);
for (int i = 0; i < nl.Count; i++)
{
int node1 = nl[tsp.SortedIndex[i]];
TFloatPoint p1 = NW.Node2Coordinate(node1);
output.AddPoint2(p1, i.ToString(CultureInfo.InvariantCulture));
}
output.Close();
for (int i = 0; i < mTSP.Count; i++)
{
sortedPoint.Add(pointsVm.Nodes[mTSP[i]]);
}
return(new ResponseMessage {
Status = "Ok", Data = sortedPoint
});
}
catch (Exception ex)
{
return(new ResponseMessage {
Status = "Error", Message = "Error sorting nodes."
});
}
}
private void worker_DoWork(object sender, DoWorkEventArgs e)
{
for (int i = 0; i < Pop_Size; i++)
{
Thread.Sleep((int)(Sleeper * 100));
_parameters.ListOfPoints.Add(new ObservablePoint(trandom.NextDouble(F1LeftConstraint, F1RightConstraint),
trandom.NextDouble(F2LeftConstraint, F2RightConstraint)
));
DomainChart.EditBSeriesCollection(_parameters.ListOfPoints);
}
while (_parameters.IterationNumber < _parameters.IterationLimit && !_Stop)
{
// inicjalizacja tablic
InitializePopulation(ref PopulationAfterSelection, Pop_Size / 2);
InitializePopulation(ref PopulationAfterMutation, Pop_Size / 2);
InitializePopulation(ref PopulationAfterCrossing, Pop_Size / 4);
InitializePopulation(ref PopulationFunctionValue, Pop_Size);
InitializePopulation(ref PopulationFunctionValueAfterSelection, Pop_Size / 2);
InitializePopulation(ref PopulationFunctionValueAfterCrossing, Pop_Size / 4);
// czas na obserwacje popsize'a i wykresu wartosci funkcji
// wszystkie operacje wykonujemy na tablicy znajdujacej sie w Parameters public double[][][] Population; // [2][popsize][popsize]
FillRandomValues(ref Population);
// operacja selekcji
// 2 warianty i tutaj trzeba zrobic ze na zasadzie losowej jest wybierana metoda selekcji
// selekcja turniejowa --> losujemy 2 punkty z populacji i wygrywa lepszy (o mniejszej wartosci),
// dzielimy popsize na 2 rowne zbiory i jeden zbior jest porownywany wzgledem f1 a drugi wzgledem f2
Selection(Population, ref PopulationAfterSelection);
// parametr, aby w nastepnej iteracji uzupelnic brakujace osobniki w populacji
refill = true;
Function2ValueCountForAllPopulation(PopulationAfterSelection, ref PopulationFunctionValueAfterSelection);
// selekcja ruletkowa --> obliczamy fitness, jaki to jest procent z calosci dla danego osobnika, obliczamy dystrybuante,
// generujemy liczby losowe i szeregujemy okreslajac ktore elementy maja przetrwac
// mozna tutaj juz wrzucic te osobniki na wykres dziedziny
_parameters.RewriteThePoints(PopulationAfterSelection);
DomainChart.EditASeriesCollection(_parameters.ListOfPoints);
CheckDomain(ref PopulationOutsideTheDomain, PopulationAfterSelection);
_parameters.RewriteThePoints(PopulationOutsideTheDomain);
DomainChart.SetPointsOutsideTheDomain(_parameters.ListOfPoints);
_parameters.RewriteThePoints(PopulationFunctionValueAfterSelection);
ParetoChart.EditSeriesCollection(_parameters.ListOfPoints);
ParetoChart.MakeParetoFunctions(FindMinAndMax(PopulationFunctionValueAfterSelection));
CheckParetoDomain(ref PopulationOutsideTheDomain, PopulationFunctionValueAfterSelection);
_parameters.RewriteThePoints(PopulationOutsideTheDomain);
ParetoChart.SetPointsOutsideTheDomain(_parameters.ListOfPoints);
MainChart.EditSeriesCollection(PopulationFunctionValueAfterSelection, _parameters.IterationNumber);
// operacja
Mutation(PopulationAfterSelection, ref PopulationAfterMutation);
// losujemy ktore punkty zostana poddane mutacji (sprawdzamy wszystkie pod wzgledem prawdopodobienstwa) (prawdopodobienstwo mutacji dla kazdego osobnika)
// jezeli wylosowano osobnika to losujemy kat oraz dlugosc wektora
// sprawdzamy czy zmutowany osobnik znajduje sie w dziedzinie
// jezeli nie wykorzystujemy funkcje kary aby zwiekszyc wartosc osobnika
// mozna tutaj juz wrzucic te osobniki na wykres dziedziny
// operacja krzyzowania
// to jest chyba najtrudniejsza operacja, duzo pierdolenia z przeksztalceniami
// ogolnie to staramy sie tak skrzyzowac aby np calkowicie odbic jeden punkt
// do dyskusji jak to robimy
Crossing(PopulationAfterMutation, ref PopulationAfterCrossing);
// mozna tutaj juz wrzucic te osobniki na wykres dziedziny
// obliczenie minimum
SearchForMinValue(PopulationFunctionValueAfterSelection, ref MinF1, ref MinF2);
_parameters.Minimum = $"{{{Math.Round(MinF1,2)};{Math.Round(MinF2,2)}}}";
// przepisywanie tablicy PopulationAfterCrossing do Population
Array.Clear(Population, 0, Population.Length);
Array.Copy(PopulationAfterCrossing, Population, PopulationAfterCrossing.Length);
// przepisywanie tablicy PopulationFunctionValueAfterCrossing do PopulationFunctionValue
Array.Clear(PopulationFunctionValue, 0, PopulationFunctionValue.Length);
Array.Copy(PopulationFunctionValueAfterCrossing, PopulationFunctionValue, PopulationFunctionValueAfterCrossing.Length);
// czyszczenie tablic
Array.Clear(PopulationAfterSelection, 0, PopulationAfterSelection.Length);
Array.Clear(PopulationAfterMutation, 0, PopulationAfterMutation.Length);
Array.Clear(PopulationAfterCrossing, 0, PopulationAfterCrossing.Length);
Array.Clear(PopulationFunctionValueAfterSelection, 0, PopulationFunctionValueAfterSelection.Length);
Array.Clear(PopulationFunctionValueAfterCrossing, 0, PopulationFunctionValueAfterCrossing.Length);
// finalne utworzenie wykresu dziedziny oraz pareto frontu a takze wykresu wartosci poszczegolnych funkcji
// jezeli przez 5 iteracji nie ma poprawy minimum zatrzymujemy algorytm
// musimy obliczyc jeszcze to spierdolone odchylenie
// suma po wszystkich punktach w populacji (od i do licznosci pareto frontu) |f(f1) - f2|
_parameters.IterationNumber++;
e.Cancel = true;
Thread.Sleep(4000);
}
}
public static decimal NextDecimal(this TRandom randomizer)
{
return(Convert.ToDecimal(randomizer.NextDouble()));
}
