/// <summary>
/// Define SimulationInput to describe homogeneous and two layer tissue
/// </summary>
/// <returns></returns>
private void GenerateReferenceDatabase()
{
var simulationOptions = new SimulationOptions(
0,
RandomNumberGeneratorType.MersenneTwister,
AbsorptionWeightingType.Discrete,
PhaseFunctionType.HenyeyGreenstein,
new List <DatabaseType>()
{
DatabaseType.pMCDiffuseReflectance
},
false, // track statistics
0.0, // RR threshold -> 0 = no RR performed
0);
var sourceInput = new DirectionalPointSourceInput(
new Position(0.0, 0.0, 0.0),
new Direction(0.0, 0.0, 1.0),
1);
var detectorInputs = new List <IDetectorInput>()
{
new ROfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101)
},
new ROfRhoAndTimeDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Time = new DoubleRange(0.0, 1.0, 101)
}
};
_referenceInputTwoLayerTissue = new SimulationInput(
100,
"",
simulationOptions,
sourceInput,
new MultiLayerTissueInput(
new ITissueRegion[]
{
new LayerRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerRegion(
new DoubleRange(0.0, _layerThickness),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerRegion(
new DoubleRange(_layerThickness, 20.0),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerRegion(
new DoubleRange(20.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
),
detectorInputs);
_factor = 1.0 - Optics.Specular(
_referenceInputTwoLayerTissue.TissueInput.Regions[0].RegionOP.N,
_referenceInputTwoLayerTissue.TissueInput.Regions[1].RegionOP.N);
_referenceOutputTwoLayerTissue = new MonteCarloSimulation(_referenceInputTwoLayerTissue).Run();
_databaseTwoLayerTissue = pMCDatabase.FromFile("DiffuseReflectanceDatabase", "CollisionInfoDatabase");
}
public SimulationOptionsViewModel(SimulationOptions options)
{
_simulationOptions = options; // use the property to invoke the appropriate change notification
#if WHITELIST
_absorptionWeightingTypeVM = new OptionViewModel <AbsorptionWeightingType>("Absorption Weighting Type:", false, _simulationOptions.AbsorptionWeightingType, WhiteList.AbsorptionWeightingTypes);
_randomNumberGeneratorTypeVM = new OptionViewModel <RandomNumberGeneratorType>("Random Number Generator Type:", false, _simulationOptions.RandomNumberGeneratorType, WhiteList.RandomNumberGeneratorTypes);
_phaseFunctionTypeVM = new OptionViewModel <PhaseFunctionType>("Phase Function Type:", false, _simulationOptions.PhaseFunctionType, WhiteList.PhaseFunctionTypes);
#else
_absorptionWeightingTypeVM = new OptionViewModel <AbsorptionWeightingType>("Absorption Weighting Type:",
false, _simulationOptions.AbsorptionWeightingType);
_randomNumberGeneratorTypeVM = new OptionViewModel <RandomNumberGeneratorType>("Random Number Generator:",
false, _simulationOptions.RandomNumberGeneratorType);
_phaseFunctionTypeVM = new OptionViewModel <PhaseFunctionType>("Phase Function Type:", false,
_simulationOptions.PhaseFunctionType);
#endif
SetStatisticsFolderCommand = new RelayCommand(() => MC_SetStatisticsFolder_Executed(null, null));
_absorptionWeightingTypeVM.PropertyChanged += (sender, args) =>
_simulationOptions.AbsorptionWeightingType = _absorptionWeightingTypeVM.SelectedValue;
_randomNumberGeneratorTypeVM.PropertyChanged += (sender, args) =>
_simulationOptions.RandomNumberGeneratorType = _randomNumberGeneratorTypeVM.SelectedValue;
_phaseFunctionTypeVM.PropertyChanged += (sender, args) =>
_simulationOptions.PhaseFunctionType = _phaseFunctionTypeVM.SelectedValue;
}
public IEnumerable <SimulationResult> Run(SimulationOptions options)
{
var cardPairs = GeneratePairs(GenerateCards());
foreach (var cards in cardPairs)
{
IntermediateSimulationResult result = ComputeChances(options, cards.ToList());
var wonRate = (double)result.Won / result.Runs;
var wonSingleRate = (double)result.WonSingle / result.Runs;
var drawRate = (double)result.Draw / result.Runs;
var loseRate = (double)(result.Runs - result.Won) / result.Runs;
yield return(new SimulationResult
{
Card1 = cards[0],
Card2 = cards[1],
WonRate = wonRate,
WonSingleRate = wonSingleRate,
DrawRate = drawRate,
LoseRate = loseRate,
Runs = result.Runs,
ConfidenceLevel = options.ConfidenceLevel,
PlayerCount = options.PlayerCount,
WinLoseRatesRelativeError = options.WinLoseRatesDesiredRelativeError,
Balance = result.Balance / result.Runs
});
}
}
public void Start(SimulationOptions options)
{
if (!_callCenter.IsRunning)
{
_callCenter.Start(options);
}
}
/// <summary>
/// Initializes a new instance of the ModuleBlackboardServer class
/// </summary>
/// <param name="name">Module name</param>
/// <param name="port">Port for accepting incoming connections</param>
internal ModuleBlackboardServer(string name, int port)
{
if ((port < 1024) || (port > 65535))
{
throw new ArgumentException("Port must be between 1024 and 65535", "port");
}
if (!Regex.IsMatch(name, @"\w[\w\-_\d]{2,}"))
{
throw new ArgumentException("Invalid module name", "name");
}
this.name = name;
this.port = port;
this.busy = false;
//this.waitingResponse = new List<Command>(10);
//this.responses = new List<Response>();
//this.commands = new List<Command>();
this.prototypes = new PrototypeCollection(this);
this.lockList = new List <Command>();
this.restartActions = new ActionCollection(this);
this.restartTestActions = new ActionCollection(this);
this.startupActions = new ActionCollection(this);
this.stopActions = new ActionCollection(this);
this.dataReceived = new Queue <byte[]>(10);
this.restartRequested = false;
this.restartTestRequested = false;
this.simOptions = SimulationOptions.SimulationDisabled;
}
private void CreateNewProject()
{
// Устанавливаем дефолтные значения
testTabControl.Items.Clear();
drawAreas.Clear();
processes.Clear();
mainProcess = new SimulationOptions();
mainProcessNumber = 0;
processNamesCounter = 1;
// Создаём процесс
//Process process = new Process() { Description = mainProcess.Description };
processes.Add(mainProcess); // Добавляем в список процессов
var tabItem = new TabItem()
{
Header = mainProcess
};
testTabControl.SelectedItem = tabItem;
// Создаём область рисования
var drawArea = new DrawArea()
{
Processes = processes
};
drawAreas.Add(drawArea);
tabItem.Content = drawArea;
testTabControl.Items.Add(tabItem);
SetTheme();
}
private void InitComponents(SimulationOptions options)
{
m_PrSimulator = new PrSimulator(options);
m_StSimulator = new StSimulator(options);
m_DiffGenerator = new DiffGenerator(m_PrSimulator, m_StSimulator);
m_Visualizer = new Visualizer2D();
}
protected virtual List <Player> MakePlayers(SimulationOptions options, int startingPot)
{
return(Enumerable
.Range(0, options.PlayerCount)
.Select(i => new Player()
{
PlayerPot = startingPot,
Strategy = new AllInStrategy()
}).ToList());
}
public SimulationOptionsDialog(SimulationOptions options)
{
InitializeComponent();
DataContext = this;
WidthSetting = options.Size.Width;
HeightSetting = options.Size.Height;
StartXSetting = options.StartLocation.J + 1;
StartYSetting = options.StartLocation.I + 1;
}
public void UpdateChildControlsWithNewOptions(SimulationOptions newOptions)
{
for (int i = 0; i <= 8; i++)
{
CheckedListBox_BirthConditions.SetItemChecked(i, newOptions.birthConditions[i]);
CheckedListBox_KillConditions.SetItemChecked(i, newOptions.killConditions[i]);
}
CheckBox_ConnectEdges.Checked = newOptions.connectEdges;
NumericUpDown_FPS.Value = (decimal)(1000.0 / newOptions.frameDuration);
}
public void validate_random_number_seed_is_correct()
{
var random1 = new SimulationOptions(-1);
var deterministic = new SimulationOptions(1);
Assert.AreNotEqual(random1.Seed, deterministic.Seed);
// Setting a random seed now performed in RNGFactory
//System.Threading.Thread.Sleep(1000);
//var random2 = new SimulationOptions(-1);
//Assert.AreNotEqual(random1.Seed, random2.Seed);
}
protected override List <Player> MakePlayers(SimulationOptions options, int startingPot)
{
return(Enumerable
.Range(0, options.PlayerCount)
.Select(i => new Player()
{
PlayerPot = startingPot,
Strategy = i == 0
? new AllInStrategy()
: (IPlayerStrategy) new FoldBadCardsOrAllInStrategy()
}).ToList());
}
static void Main(string[] args)
{
var options = new SimulationOptions(new GridSize(11, 11), new GridIndex(5, 5));
PrSimulator pr = new PrSimulator(options);
StSimulator st = new StSimulator(options);
Func <double, double, double> u = (x, y) => Math.Log(Math.Sqrt((x / 10 + 3) * (x / 10 + 3) + (y / 10 + 3) * (y / 10 + 3)));
File.WriteAllLines("comp_pr.csv", CalcPr(pr, u).Select(x => $"{x.Item1.ToString("E20")};{x.Item2.ToString("E20")}"), Encoding.UTF8);
Console.WriteLine("Finished pr");
File.WriteAllLines("comp_st.csv", CalcSt(st, u).Select(x => $"{x.Item1.ToString("E20")};{x.Item2.ToString("E20")}"), Encoding.UTF8);
}
public void validate_null_database_input_gets_converted_to_empty_list_correctly()
{
var so = new SimulationOptions(
0,
RandomNumberGeneratorType.MersenneTwister,
AbsorptionWeightingType.Discrete,
PhaseFunctionType.Bidirectional,
null,
false,
0.0,
0);
Assert.IsTrue(so.Databases.Count == 0);
}
public static SimulationOptions loadSimulationOptionsFromDisk()
{
try
{
if (File.Exists(SIM_SETTINGS_FILE_NAME))
{
SimulationOptions simulationOptions = null;
FileStream fileStream = new FileStream(SIM_SETTINGS_FILE_NAME, FileMode.Open);
simulationOptions = (SimulationOptions)formatter.Deserialize(fileStream);
fileStream.Close();
return(simulationOptions);
}
return(new SimulationOptions());
}
catch
{
return(new SimulationOptions());
}
}
public void StartSimulation(SimulationData simulationData, SimulationOptions options = new SimulationOptions())
{
var containerObject = new GameObject("SimulationConfig");
containerObject.tag = "SimulationConfig";
var configContainer = containerObject.AddComponent <SimulationConfigContainer>();
configContainer.Config = new SimulationConfig();
configContainer.Config.SimulationData = simulationData;
configContainer.Config.Options = options;
DontDestroyOnLoad(containerObject);
InputRegistry.shared.Deregister(this);
Physics.autoSimulation = false;
Physics.autoSyncTransforms = false;
// Load simulation scene
SceneController.LoadSync(SceneController.Scene.SimulationContainer);
}
public MainViewModel()
{
var logger = Logger.New(typeof(MainViewModel));
using (logger.LogPerf("Init"))
{
SettingsCommand = new DelegateCommand(_ =>
{
var dlg = new SettingsDialog {
ViewModel = new SettingsViewModel()
};
dlg.ShowDialog();
});
SimulationOptions options = new SimulationOptions(new GridSize(9, 9), new GridIndex(4, 4));
Tabs.Add(new PrTabViewModel(options));
Tabs.Add(new StTabViewModel(options));
Tabs.Add(new CpTabViewModel(options));
Tabs.Add(new СlTabViewModel());
SelectedTab = Tabs.First();
}
}
public void Start(SimulationOptions options)
{
CallCenterHubAppendLine("Simulation starting");
if (_isRunning)
{
throw new Exception("Already started");
}
_options = options;
var id = 1;
var callId = 1;
for (var i = 0; i < _options.OperatorCount; i++)
{
var @operator = new Operator(id++, OperatorTitle.Operator);
_operators.Add(@operator);
}
for (var i = 0; i < _options.ManagerCount; i++)
{
var @operator = new Operator(id++, OperatorTitle.Manager);
_operators.Add(@operator);
}
for (var i = 0; i < _options.SeniorManagerCount; i++)
{
var @operator = new Operator(id++, OperatorTitle.SeniorManager);
_operators.Add(@operator);
}
for (var i = 0; i < _options.CallsAmount; i++)
{
var duration = _random.Next(_options.MinSecAnswer, _options.MaxSecAnswer);
var call = new Call {
Id = callId++, Duration = duration, IsActive = true
};
_calls.Add(call);
}
foreach (var @operator in _operators)
{
@operator.StatusChanged += operator_StatusChanged;
var thread = new Thread(() => @operator.Start());
thread.Start();
}
_isRunning = true;
CallCenterHubAppendLine("Simulation started");
CallCenterHubAppendLine("Operators starts answer the calls.");
while (_calls.Any() || _awaitingCalls.Any())
{
Task task = null;
if (_calls.Any() || _awaitingCalls.Any())
{
var call = _calls.FirstOrDefault();
if (call == null)
{
call = _awaitingCalls.Where(x => x.IsActive == true).FirstOrDefault();
if (call == null)
{
CallCenterHubAppendLine("Calls are ended");
_awaitingCalls.Clear();
}
}
if (call != null)
{
Thread.Sleep(call.Duration * 1000 / 15);
CallCenterHubAppendLine("Sending a call");
task = Task.Run(() => SendingCallsAsync());
task.Wait();
}
}
}
WaitForEmployeeEndsCalls();
Stop();
}
public void execute_Monte_Carlo()
{
// delete previously generated files
clear_folders_and_files();
// instantiate common classes
var simulationOptions = new SimulationOptions(
0,
RandomNumberGeneratorType.MersenneTwister,
AbsorptionWeightingType.Discrete,
PhaseFunctionType.HenyeyGreenstein,
new List <DatabaseType>()
{
}, // databases to be written
false, // track statistics
0.0, // RR threshold -> 0 = no RR performed
0);
var source = new DirectionalPointSourceInput(
new Position(0.0, 0.0, 0.0),
new Direction(0.0, 0.0, 1.0),
1); // start inside tissue
var oneLayerDetectors = new List <IDetectorInput>
{
new ROfFxDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 11), TallySecondMoment = true
},
new TOfFxDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 11)
},
new ReflectedDynamicMTOfFxAndSubregionHistDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 11), // fx bins MAKE SURE AGREES with ROfFx fx specification for unit test below
Z = new DoubleRange(0.0, 10.0, 21),
MTBins = new DoubleRange(0.0, 500.0, 51), // MT bins
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
BloodVolumeFraction = new List <double>()
{
0, 0.5, 0
}
},
new TransmittedDynamicMTOfFxAndSubregionHistDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 11), // fx bins MAKE SURE AGREES with TOfFx fx specification for unit test below
Z = new DoubleRange(0.0, 10.0, 21),
MTBins = new DoubleRange(0.0, 500.0, 51), // MT bins
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
BloodVolumeFraction = new List <double>()
{
0, 0.5, 0
}
},
};
_inputOneLayerTissue = new SimulationInput(
100,
"",
simulationOptions,
source,
new MultiLayerTissueInput(
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerTissueRegion(
new DoubleRange(0.0, 20.0),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(20.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
),
oneLayerDetectors);
_outputOneLayerTissue = new MonteCarloSimulation(_inputOneLayerTissue).Run();
var twoLayerDetectors = new List <IDetectorInput>
{
new ReflectedDynamicMTOfFxAndSubregionHistDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 11),
Z = new DoubleRange(0.0, 10.0, 21),
MTBins = new DoubleRange(0.0, 500.0, 51), // MT bins
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
BloodVolumeFraction = new List <double>()
{
0, 0.2, 0.5, 0
}
},
new TransmittedDynamicMTOfFxAndSubregionHistDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 11),
Z = new DoubleRange(0.0, 10.0, 21),
MTBins = new DoubleRange(0.0, 500.0, 51), // MT bins
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
BloodVolumeFraction = new List <double>()
{
0, 0.2, 0.5, 0
}
}
};
_inputTwoLayerTissue = new SimulationInput(
100,
"",
simulationOptions,
source,
new MultiLayerTissueInput(
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerTissueRegion(
new DoubleRange(0.0, _layerThickness),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(_layerThickness, 20.0),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(20.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
),
twoLayerDetectors);
_outputTwoLayerTissue = new MonteCarloSimulation(_inputTwoLayerTissue).Run();
}
public void execute_Monte_Carlo()
{
// delete previously generated files
clear_folders_and_files();
var simulationOptions = new SimulationOptions(
0,
RandomNumberGeneratorType.MersenneTwister,
AbsorptionWeightingType.Continuous,
PhaseFunctionType.HenyeyGreenstein,
new List <DatabaseType>()
{
DatabaseType.pMCDiffuseReflectance
},
false, // track statistics
0.0, // RR threshold -> 0 = no RR performed
0);
var sourceInput = new DirectionalPointSourceInput(
new Position(0.0, 0.0, 0.0),
new Direction(0.0, 0.0, 1.0),
1);
var detectorInputs = new List <IDetectorInput>()
{
new ROfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101)
},
new ROfRhoAndTimeDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Time = new DoubleRange(0.0, 1.0, 101)
},
new ROfFxDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 11)
},
new ROfFxAndTimeDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 11), Time = new DoubleRange(0.0, 1.0, 101)
}
};
_referenceInputOneLayerTissue = new SimulationInput(
100,
"", // can't create folder in isolated storage
simulationOptions,
sourceInput,
new MultiLayerTissueInput(
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerTissueRegion(
new DoubleRange(0.0, 20.0),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(20.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
),
detectorInputs);
_factor = 1.0 - Optics.Specular(
_referenceInputOneLayerTissue.TissueInput.Regions[0].RegionOP.N,
_referenceInputOneLayerTissue.TissueInput.Regions[1].RegionOP.N);
_referenceOutputOneLayerTissue = new MonteCarloSimulation(_referenceInputOneLayerTissue).Run();
_databaseOneLayerTissue = pMCDatabase.FromFile("DiffuseReflectanceDatabase", "CollisionInfoDatabase");
}
public void execute_Monte_Carlo()
{
// delete previously generated files
clear_folders_and_files();
// instantiate common classes
var simulationOptions = new SimulationOptions(
0,
RandomNumberGeneratorType.MersenneTwister,
AbsorptionWeightingType.Discrete,
PhaseFunctionType.HenyeyGreenstein,
new List <DatabaseType>()
{
}, // databases to be written
false, // track statistics
0.0, // RR threshold -> 0 = no RR performed
0);
var source = new DirectionalPointSourceInput(
new Position(0.0, 0.0, 0.0),
new Direction(0.0, 0.0, 1.0),
1); // start inside tissue
var detectors =
new List <IDetectorInput>
{
new RDiffuseDetectorInput(),
new ROfAngleDetectorInput()
{
Angle = new DoubleRange(Math.PI / 2, Math.PI, 2)
},
new ROfXAndYDetectorInput()
{
X = new DoubleRange(-200.0, 200.0, 401), Y = new DoubleRange(-200.0, 200.0, 401)
},
new TDiffuseDetectorInput(),
new TOfAngleDetectorInput()
{
Angle = new DoubleRange(0.0, Math.PI / 2, 2)
},
new ATotalDetectorInput(),
};
_inputOneRegionTissue = new SimulationInput(
100,
"",
simulationOptions,
source,
new MultiLayerTissueInput(
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerTissueRegion(
new DoubleRange(0.0, 20.0),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(20.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
),
detectors);
_outputOneRegionTissue = new MonteCarloSimulation(_inputOneRegionTissue).Run();
_inputTwoRegionTissue = new SimulationInput(
100,
"",
simulationOptions,
source,
new SingleVoxelTissueInput(
new VoxelTissueRegion(
new DoubleRange(-5, 5),
new DoubleRange(-5, 5),
new DoubleRange(1e-9, 5), // smallest Z.Start with tests passing is 1e-9
new OpticalProperties(0.01, 1.0, 0.8, 1.4) //debug with g=1
),
new LayerTissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerTissueRegion(
new DoubleRange(0.0, 20.0), // debug with thin slab d=2
new OpticalProperties(0.01, 1.0, 0.8, 1.4)), // debug with g=1
new LayerTissueRegion(
new DoubleRange(20.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
),
detectors);
_outputTwoRegionTissue = new MonteCarloSimulation(_inputTwoRegionTissue).Run();
_factor = 1.0 - Optics.Specular(
_inputOneRegionTissue.TissueInput.Regions[0].RegionOP.N,
_inputOneRegionTissue.TissueInput.Regions[1].RegionOP.N);
}
public void execute_Monte_Carlo()
{
// delete previously generated files
clear_folders_and_files();
// instantiate common classes
var simulationOptions = new SimulationOptions(
0,
RandomNumberGeneratorType.MersenneTwister,
AbsorptionWeightingType.Discrete,
PhaseFunctionType.HenyeyGreenstein,
new List <DatabaseType>()
{
}, // databases to be written
false, // track statistics
0.0, // RR threshold -> 0 = no RR performed
0);
var source = new DirectionalPointSourceInput(
new Position(0.0, 0.0, 0.0),
new Direction(0.0, 0.0, 1.0),
1); // start inside tissue
var detectors = new List <IDetectorInput>
{
new RDiffuseDetectorInput(),
new ROfAngleDetectorInput()
{
Angle = new DoubleRange(Math.PI / 2, Math.PI, 2)
},
new ROfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), TallySecondMoment = true
},
new ROfRhoAndAngleDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Angle = new DoubleRange(Math.PI / 2, Math.PI, 2)
},
new ROfRhoAndTimeDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Time = new DoubleRange(0.0, 1.0, 101), TallySecondMoment = true
},
new ROfXAndYDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 101), Y = new DoubleRange(-10.0, 10.0, 101)
},
new ROfRhoAndOmegaDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Omega = new DoubleRange(0.05, 1.0, 20)
}, // DJC - edited to reflect frequency sampling points (not bins)
new ROfFxDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 51)
},
new TDiffuseDetectorInput(),
new TOfAngleDetectorInput()
{
Angle = new DoubleRange(0.0, Math.PI / 2, 2)
},
new TOfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101)
},
new TOfRhoAndAngleDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Angle = new DoubleRange(0.0, Math.PI / 2, 2)
},
new TOfXAndYDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 101), Y = new DoubleRange(-10.0, 10.0, 101)
},
new TOfFxDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 51)
},
new AOfRhoAndZDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Z = new DoubleRange(0.0, 10.0, 101)
},
new AOfXAndYAndZDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 101),
Y = new DoubleRange(-10.0, 10.0, 101),
Z = new DoubleRange(0.0, 10.0, 101),
TallySecondMoment = true
},
new ATotalDetectorInput()
{
TallySecondMoment = true
},
new FluenceOfRhoAndZDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Z = new DoubleRange(0.0, 10.0, 101)
},
new FluenceOfXAndYAndZDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11),
Y = new DoubleRange(-10.0, 10.0, 11),
Z = new DoubleRange(0.0, 10.0, 11),
TallySecondMoment = true
},
new FluenceOfXAndYAndZAndOmegaDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11),
Y = new DoubleRange(-10.0, 10.0, 11),
Z = new DoubleRange(0.0, 10.0, 11),
Omega = new DoubleRange(0.05, 1.0, 20)
},
new RadianceOfRhoAtZDetectorInput()
{
ZDepth = _dosimetryDepth, Rho = new DoubleRange(0.0, 10.0, 101)
},
new RadianceOfRhoAndZAndAngleDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Z = new DoubleRange(0.0, 10.0, 101), Angle = new DoubleRange(0, Math.PI, 5)
},
new RadianceOfFxAndZAndAngleDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 51), Z = new DoubleRange(0.0, 10, 101), Angle = new DoubleRange(0, Math.PI, 5)
},
new RadianceOfXAndYAndZAndThetaAndPhiDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11),
Y = new DoubleRange(-10.0, 10.0, 11),
Z = new DoubleRange(0.0, 10.0, 11),
Theta = new DoubleRange(0.0, Math.PI, 5), // theta (polar angle)
Phi = new DoubleRange(-Math.PI, Math.PI, 5), // phi (azimuthal angle)
},
new ReflectedMTOfRhoAndSubregionHistDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), // rho bins MAKE SURE AGREES with ROfRho rho specification for unit test below
MTBins = new DoubleRange(0.0, 500.0, 51), // MT bins
FractionalMTBins = new DoubleRange(0.0, 1.0, 11)
},
new TransmittedMTOfRhoAndSubregionHistDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), // rho bins MAKE SURE AGREES with TOfRho rho specification for unit test below
MTBins = new DoubleRange(0.0, 500.0, 51), // MT bins
FractionalMTBins = new DoubleRange(0.0, 1.0, 11)
},
new ReflectedMTOfXAndYAndSubregionHistDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 101),
Y = new DoubleRange(-10.0, 10.0, 101),
MTBins = new DoubleRange(0.0, 500.0, 51), // MT bins
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
TallySecondMoment = true
},
new TransmittedMTOfXAndYAndSubregionHistDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 101),
Y = new DoubleRange(-10.0, 10.0, 101),
MTBins = new DoubleRange(0.0, 500.0, 51), // MT bins
FractionalMTBins = new DoubleRange(0.0, 1.0, 11)
}
};
_inputOneLayerTissue = new SimulationInput(
100,
"",
simulationOptions,
source,
new MultiLayerTissueInput(
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerTissueRegion(
new DoubleRange(0.0, 20.0),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(20.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
),
detectors);
_outputOneLayerTissue = new MonteCarloSimulation(_inputOneLayerTissue).Run();
_inputTwoLayerTissue = new SimulationInput(
100,
"",
simulationOptions,
source,
new MultiLayerTissueInput(
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerTissueRegion(
new DoubleRange(0.0, _layerThickness),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(_layerThickness, 20.0),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(20.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
),
detectors);
_outputTwoLayerTissue = new MonteCarloSimulation(_inputTwoLayerTissue).Run();
_factor = 1.0 - Optics.Specular(
_inputOneLayerTissue.TissueInput.Regions[0].RegionOP.N,
_inputOneLayerTissue.TissueInput.Regions[1].RegionOP.N);
}
public void execute_Monte_Carlo()
{
// delete any previously generated files
clear_folders_and_files();
// instantiate common classes
var simulationOptions = new SimulationOptions(
0, // rng seed = same as linux (0)
RandomNumberGeneratorType.MersenneTwister,
AbsorptionWeightingType.Continuous,
PhaseFunctionType.HenyeyGreenstein,
new List <DatabaseType>()
{
}, // databases to be written
false, // track statistics
0.0, // RR threshold -> 0 = no RR performed
0);
var source = new DirectionalPointSourceInput(
new Position(0.0, 0.0, 0.0),
new Direction(0.0, 0.0, 1.0),
1); // start inside tissue
var detectors =
new List <IDetectorInput>
{
new ATotalDetectorInput(),
new RDiffuseDetectorInput()
{
TallySecondMoment = true
},
new ROfAngleDetectorInput()
{
Angle = new DoubleRange(Math.PI / 2, Math.PI, 2)
},
new ROfRhoAndAngleDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Angle = new DoubleRange(Math.PI / 2, Math.PI, 2)
},
new ROfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), TallySecondMoment = true
},
new ROfRhoAndTimeDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Time = new DoubleRange(0.0, 1.0, 101)
},
new ROfXAndYDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 101), Y = new DoubleRange(-10.0, 10.0, 101)
},
new ROfRhoAndOmegaDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Omega = new DoubleRange(0.05, 1.0, 20)
}, // DJC - edited to reflect frequency sampling points (not bins)
new TDiffuseDetectorInput(),
new TOfAngleDetectorInput()
{
Angle = new DoubleRange(0.0, Math.PI / 2, 2)
},
new TOfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101)
},
new TOfRhoAndAngleDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Angle = new DoubleRange(0.0, Math.PI / 2, 2)
},
new TOfXAndYDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 101), Y = new DoubleRange(-10.0, 10.0, 101)
},
new ReflectedTimeOfRhoAndSubregionHistDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 101), Time = new DoubleRange(0.0, 1.0, 101)
},
};
// one tissue layer
var inputOneLayerTissue = new SimulationInput(
100,
"",
simulationOptions,
source,
new MultiLayerTissueInput(
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerTissueRegion(
new DoubleRange(0.0, 20.0),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(20.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
),
detectors);
_outputOneLayerTissue = new MonteCarloSimulation(inputOneLayerTissue).Run();
// two tissue layers with same optical properties
var inputTwoLayerTissue = new SimulationInput(
100,
"Output",
simulationOptions,
source,
new MultiLayerTissueInput(
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerTissueRegion(
new DoubleRange(0.0, _layerThickness),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(_layerThickness, 20.0),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(20.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
),
detectors);
_outputTwoLayerTissue = new MonteCarloSimulation(inputTwoLayerTissue).Run();
_factor = 1.0 - Optics.Specular(
inputOneLayerTissue.TissueInput.Regions[0].RegionOP.N,
inputOneLayerTissue.TissueInput.Regions[1].RegionOP.N);
}
public void execute_Monte_Carlo()
{
// instantiate common classes
var simulationOptions = new SimulationOptions(
0,
RandomNumberGeneratorType.MersenneTwister,
AbsorptionWeightingType.Discrete,
PhaseFunctionType.HenyeyGreenstein,
new List <DatabaseType>()
{
DatabaseType.pMCDiffuseReflectance
}, // write database for pMC tests
false, // track statistics
0.0, // RR threshold -> 0 = no RR performed
0);
var source = new DirectionalPointSourceInput(
new Position(0.0, 0.0, 0.0),
new Direction(0.0, 0.0, 1.0),
0); // start in air
var tissue = new MultiLayerTissueInput(
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerTissueRegion(
new DoubleRange(0.0, 10.0), // make tissue layer thin so transmittance results improved
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(10.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
});
var detectorsNA0 = new List <IDetectorInput>
{
new RDiffuseDetectorInput()
{
FinalTissueRegionIndex = 0, NA = 0.0
},
new ROfAngleDetectorInput()
{
Angle = new DoubleRange(Math.PI / 2, Math.PI, 2), FinalTissueRegionIndex = 0, NA = 0.0
},
new ROfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), FinalTissueRegionIndex = 0, NA = 0.0
},
new ROfRhoAndAngleDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), Angle = new DoubleRange(Math.PI / 2, Math.PI, 2), FinalTissueRegionIndex = 0, NA = 0.0
},
new ROfRhoAndTimeDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), Time = new DoubleRange(0.0, 1.0, 11), FinalTissueRegionIndex = 0, NA = 0.0
},
new ROfRhoAndOmegaDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), Omega = new DoubleRange(0.05, 1.0, 20), FinalTissueRegionIndex = 0, NA = 0.0
},
new ROfXAndYDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11), Y = new DoubleRange(-10.0, 10.0, 11), FinalTissueRegionIndex = 0, NA = 0.0
},
new ROfXAndYAndTimeDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11), Y = new DoubleRange(-10.0, 10.0, 11), Time = new DoubleRange(0, 1, 11), FinalTissueRegionIndex = 0, NA = 0.0
},
new ROfXAndYAndMaxDepthDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11), Y = new DoubleRange(-10.0, 10.0, 11), MaxDepth = new DoubleRange(0, 10.0, 11), FinalTissueRegionIndex = 0, NA = 0.0
},
new ROfFxDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 51), FinalTissueRegionIndex = 0, NA = 0.0
},
new ROfFxAndTimeDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 51), Time = new DoubleRange(0.0, 1.0, 11), FinalTissueRegionIndex = 0, NA = 0.0
},
new RSpecularDetectorInput()
{
FinalTissueRegionIndex = 0, NA = 0.0
},
new TDiffuseDetectorInput()
{
FinalTissueRegionIndex = 2, NA = 0.0
},
new TOfAngleDetectorInput()
{
Angle = new DoubleRange(0.0, Math.PI / 2, 2), FinalTissueRegionIndex = 2, NA = 0.0
},
new TOfRhoAndAngleDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), Angle = new DoubleRange(0.0, Math.PI / 2, 2), FinalTissueRegionIndex = 2, NA = 0.0
},
new TOfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), FinalTissueRegionIndex = 2, NA = 0.0
},
new TOfXAndYDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11), Y = new DoubleRange(-10.0, 10.0, 11), FinalTissueRegionIndex = 2, NA = 0.0
},
new RadianceOfRhoAtZDetectorInput()
{
ZDepth = _dosimetryDepth, Rho = new DoubleRange(0.0, 10.0, 11), FinalTissueRegionIndex = 1, NA = 0.0
},
new ReflectedMTOfRhoAndSubregionHistDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11),
MTBins = new DoubleRange(0.0, 500.0, 5),
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
FinalTissueRegionIndex = 0,
NA = 0.0
},
new ReflectedMTOfXAndYAndSubregionHistDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11),
Y = new DoubleRange(-10.0, 10.0, 11),
MTBins = new DoubleRange(0.0, 500.0, 5),
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
FinalTissueRegionIndex = 0,
NA = 0.0
},
new TransmittedMTOfRhoAndSubregionHistDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11),
MTBins = new DoubleRange(0.0, 500.0, 5),
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
FinalTissueRegionIndex = 2,
NA = 0.0
},
new TransmittedMTOfXAndYAndSubregionHistDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11),
Y = new DoubleRange(-10.0, 10.0, 11),
MTBins = new DoubleRange(0.0, 500.0, 5),
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
FinalTissueRegionIndex = 2,
NA = 0.0
},
};
var input = new SimulationInput(
100,
"",
simulationOptions,
source,
tissue,
detectorsNA0);
_outputNA0 = new MonteCarloSimulation(input).Run();
_inputForPMC = input; // set pMC input to one that specified database generation
_pMCDatabase = pMCDatabase.FromFile("DiffuseReflectanceDatabase", "CollisionInfoDatabase"); // grab database
var detectorsNA0p3 = new List <IDetectorInput>
{
new RDiffuseDetectorInput()
{
FinalTissueRegionIndex = 0, NA = 0.3
},
new ROfAngleDetectorInput()
{
Angle = new DoubleRange(Math.PI / 2, Math.PI, 2), FinalTissueRegionIndex = 0, NA = 0.3
},
new ROfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), FinalTissueRegionIndex = 0, NA = 0.3
},
new ROfRhoAndAngleDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), Angle = new DoubleRange(Math.PI / 2, Math.PI, 2), FinalTissueRegionIndex = 0, NA = 0.3
},
new ROfRhoAndTimeDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), Time = new DoubleRange(0.0, 1.0, 11), FinalTissueRegionIndex = 0, NA = 0.3
},
new ROfRhoAndOmegaDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), Omega = new DoubleRange(0.05, 1.0, 20), FinalTissueRegionIndex = 0, NA = 0.3
},
new ROfXAndYDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11), Y = new DoubleRange(-10.0, 10.0, 11), FinalTissueRegionIndex = 0, NA = 0.3
},
new ROfXAndYAndTimeDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11), Y = new DoubleRange(-10.0, 10.0, 11), Time = new DoubleRange(0, 1, 11), FinalTissueRegionIndex = 0, NA = 0.3
},
new ROfXAndYAndMaxDepthDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11), Y = new DoubleRange(-10.0, 10.0, 11), MaxDepth = new DoubleRange(0, 10.0, 11), FinalTissueRegionIndex = 0, NA = 0.3
},
new ROfFxDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 51), FinalTissueRegionIndex = 0, NA = 0.3
},
new ROfFxAndTimeDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 5), Time = new DoubleRange(0.0, 1.0, 11), FinalTissueRegionIndex = 0, NA = 0.3
},
new RSpecularDetectorInput()
{
FinalTissueRegionIndex = 0, NA = 0.3
},
new TDiffuseDetectorInput()
{
FinalTissueRegionIndex = 2, NA = 0.3
},
new TOfAngleDetectorInput()
{
Angle = new DoubleRange(0.0, Math.PI / 2, 2), FinalTissueRegionIndex = 2, NA = 0.3
},
new TOfRhoAndAngleDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), Angle = new DoubleRange(0.0, Math.PI / 2, 2), FinalTissueRegionIndex = 2, NA = 0.3
},
new TOfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), FinalTissueRegionIndex = 2, NA = 0.3
},
new TOfXAndYDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11), Y = new DoubleRange(-10.0, 10.0, 11), FinalTissueRegionIndex = 2, NA = 0.3
},
new RadianceOfRhoAtZDetectorInput()
{
ZDepth = _dosimetryDepth, Rho = new DoubleRange(0.0, 10.0, 11), FinalTissueRegionIndex = 1, NA = 0.3
},
new ReflectedMTOfRhoAndSubregionHistDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11),
MTBins = new DoubleRange(0.0, 500.0, 5),
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
FinalTissueRegionIndex = 0,
NA = 0.3
},
new ReflectedMTOfXAndYAndSubregionHistDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11),
Y = new DoubleRange(-10.0, 10.0, 11),
MTBins = new DoubleRange(0.0, 500.0, 5),
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
FinalTissueRegionIndex = 0,
NA = 0.3
},
new TransmittedMTOfRhoAndSubregionHistDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11),
MTBins = new DoubleRange(0.0, 500.0, 5),
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
FinalTissueRegionIndex = 2,
NA = 0.3
},
new TransmittedMTOfXAndYAndSubregionHistDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11),
Y = new DoubleRange(-10.0, 10.0, 11),
MTBins = new DoubleRange(0.0, 500.0, 5),
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
FinalTissueRegionIndex = 2,
NA = 0.3
},
};
input = new SimulationInput(
100,
"",
simulationOptions,
source,
tissue,
detectorsNA0p3);
_outputNA0p3 = new MonteCarloSimulation(input).Run();
var detectorsNoNASpecified = new List <IDetectorInput>
{
new RDiffuseDetectorInput()
{
},
new ROfAngleDetectorInput()
{
Angle = new DoubleRange(Math.PI / 2, Math.PI, 2)
},
new ROfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11)
},
new ROfRhoAndAngleDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), Angle = new DoubleRange(Math.PI / 2, Math.PI, 2)
},
new ROfRhoAndTimeDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), Time = new DoubleRange(0.0, 1.0, 11)
},
new ROfRhoAndOmegaDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), Omega = new DoubleRange(0.05, 1.0, 20)
},
new ROfXAndYDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11), Y = new DoubleRange(-10.0, 10.0, 11)
},
new ROfXAndYAndTimeDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11), Y = new DoubleRange(-10.0, 10.0, 11), Time = new DoubleRange(0, 1, 11), FinalTissueRegionIndex = 0, NA = 0.3
},
new ROfXAndYAndMaxDepthDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11), Y = new DoubleRange(-10.0, 10.0, 11), MaxDepth = new DoubleRange(0, 10.0, 11), FinalTissueRegionIndex = 0, NA = 0.3
},
new ROfFxDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 51)
},
new ROfFxAndTimeDetectorInput()
{
Fx = new DoubleRange(0.0, 0.5, 5), Time = new DoubleRange(0.0, 1.0, 11)
},
new RSpecularDetectorInput()
{
},
new TDiffuseDetectorInput()
{
},
new TOfAngleDetectorInput()
{
Angle = new DoubleRange(0.0, Math.PI / 2, 2)
},
new TOfRhoAndAngleDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11), Angle = new DoubleRange(0.0, Math.PI / 2, 2)
},
new TOfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11)
},
new TOfXAndYDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11), Y = new DoubleRange(-10.0, 10.0, 11)
},
new RadianceOfRhoAtZDetectorInput()
{
ZDepth = _dosimetryDepth, Rho = new DoubleRange(0.0, 10.0, 11)
},
new ReflectedMTOfRhoAndSubregionHistDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11),
MTBins = new DoubleRange(0.0, 500.0, 5),
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
},
new ReflectedMTOfXAndYAndSubregionHistDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11),
Y = new DoubleRange(-10.0, 10.0, 11),
MTBins = new DoubleRange(0.0, 500.0, 5),
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
},
new TransmittedMTOfRhoAndSubregionHistDetectorInput()
{
Rho = new DoubleRange(0.0, 10.0, 11),
MTBins = new DoubleRange(0.0, 500.0, 5),
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
},
new TransmittedMTOfXAndYAndSubregionHistDetectorInput()
{
X = new DoubleRange(-10.0, 10.0, 11),
Y = new DoubleRange(-10.0, 10.0, 11),
MTBins = new DoubleRange(0.0, 500.0, 5),
FractionalMTBins = new DoubleRange(0.0, 1.0, 11),
},
};
input = new SimulationInput(
100,
"",
simulationOptions,
source,
tissue,
detectorsNoNASpecified);
_outputNoNASpecified = new MonteCarloSimulation(input).Run();
}
public SimulationRenderHelper(Panel gamePanel, RenderZoneOptions renderZoneOptions, SimulationOptions options)
{
if (gamePanel == null)
{
throw new ArgumentNullException(nameof(gamePanel));
}
gamePanel.Controls.Clear();
SimulationSession = new SimulationSession(options);
_zoneSelectionPanel.Width = 160;
_zoneSelectionPanel.Dock = DockStyle.Left;
_viewportPanel.Dock = DockStyle.Fill;
_viewportPanel.AutoScroll = true;
gamePanel.Controls.Add(_viewportPanel);
gamePanel.Controls.Add(_zoneSelectionPanel);
_zoneSelectionPanel.BringToFront();
_viewportPanel.BringToFront();
if (renderZoneOptions == null)
{
throw new ArgumentNullException(nameof(renderZoneOptions));
}
_canvasPanel = new Panel
{
BackColor = EmptyZoneConsumption.DefaultColor,
Size = _tilesetAccessor.GetAreaSize(SimulationSession.Area),
Dock = DockStyle.None
};
_viewportPanel.Controls.Add(_canvasPanel);
_zoneSelectionPanelBehaviour = new ZoneSelectionPanelCreator(
area: SimulationSession.Area,
targetPanel: _zoneSelectionPanel
);
MouseEventHandler eventHandler = (sender, e) =>
{
var point = _canvasPanel.PointToClient(Cursor.Position);
var zone = GetZoneStateFor(point);
var zoneConsumption = (e.Button == MouseButtons.Right)
? new EmptyZoneConsumption()
: _zoneSelectionPanelBehaviour.CreateNewCurrentZoneConsumption();
var result = SimulationSession.ConsumeZoneAt(zone, zoneConsumption);
if (result == null)
{
throw new InvalidOperationException();
}
};
_canvasPanel.MouseDown += eventHandler;
_canvasPanel.MouseMove += (sender, e) =>
{
if (e.Button != MouseButtons.None && _zoneSelectionPanelBehaviour.IsCurrentlyNetworkZoning)
{
eventHandler(sender, e);
}
};
_zoneRenderInfos = SimulationSession.Area
.EnumerateZoneInfos()
.ToDictionary(x => x,
zoneRenderInfo =>
new ZoneRenderInfo(
zoneInfo: zoneRenderInfo,
createRectangle: zonePoint => new Rectangle(
x: zonePoint.Point.X * _tilesetAccessor.TileWidthAndSizeInPixels,
y: zonePoint.Point.Y * _tilesetAccessor.TileWidthAndSizeInPixels,
width: _tilesetAccessor.TileWidthAndSizeInPixels,
height: _tilesetAccessor.TileWidthAndSizeInPixels
),
tilesetAccessor: _tilesetAccessor,
renderZoneOptions: renderZoneOptions
));
_graphicsManager = CreateGraphicsManagerWrapperWithFactory(renderZoneOptions.SelectedGraphicsManager.Factory);
}
//public void Map(UIElementCollection uIElementCollection, SimulationOptions simOptions)
//{
// Dictionary<ProcedureWPF, Procedure> procedures = new Dictionary<ProcedureWPF, Procedure>();
// Dictionary<ResourceWPF, Resource> resources = new Dictionary<ResourceWPF, Resource>();
// var resultProcedures = new List<Procedure>();
// foreach (var element in uIElementCollection)
// {
// //смотрим все соединения процедур
// if (element is ProcConnectionWPF)
// {
// var connection = (element as ProcConnectionWPF);
// //TODO типа можно здесь всё обработать
// // Комментарий от 28.05.19: facepalm
// if (connection.StartBlock is StartBlockWPF && connection.EndBlock is EndBlockWPF)
// {
// throw new Exception("Нельзя просто соединить начало с концом!");
// }
// //обработка стартового блока
// if (connection.StartBlock is StartBlockWPF)
// {
// Procedure block;
// //если в первый раз встерчаем блок
// if (!(procedures.ContainsKey(connection.EndBlock as ProcedureWPF)))
// {
// //первого нет, второй значимый
// block = (connection.EndBlock as ProcedureWPF).BlockModel;
// //добавляем его в список
// procedures.Add(connection.EndBlock as ProcedureWPF, block);
// //добавляем его в список всех блоков процесса
// resultProcedures.Add(block);
// }
// //иначе просто берём из базы
// else
// block = procedures[connection.EndBlock as ProcedureWPF];
// //process.StartBlock = block;
// //соединение будет когда-то потом
// }
// //обработка конечного блока
// else if (connection.EndBlock is EndBlockWPF)
// {
// Procedure block = null;
// //если в первый раз такое встречаем
// if (!(procedures.ContainsKey(connection.StartBlock as ProcedureWPF)))
// {
// block = (connection.StartBlock as ProcedureWPF).BlockModel;
// procedures.Add(connection.StartBlock as ProcedureWPF, block);
// resultProcedures.Add(block);
// }
// else
// {
// block = procedures[connection.StartBlock as ProcedureWPF];
// }
// //process.EndBlock = block;
// //соединение будет когда-то потом
// }
// //обработка всех остальных блоков
// else
// {
// Procedure block = null;
// //если в первый раз такое встречаем
// if (!(procedures.ContainsKey(connection.StartBlock as ProcedureWPF)))
// {
// block = (connection.StartBlock as ProcedureWPF).BlockModel;
// procedures.Add(connection.StartBlock as ProcedureWPF, block);
// resultProcedures.Add(block);
// }
// //если в первый раз такое встречаем
// if (!(procedures.ContainsKey(connection.EndBlock as ProcedureWPF)))
// {
// block = (connection.EndBlock as ProcedureWPF).BlockModel;
// procedures.Add(connection.EndBlock as ProcedureWPF, block);
// resultProcedures.Add(block);
// }
// //к счастью там только один вход и выход
// //process.Connections.Connect(procedures[connection.StartBlock as ProcedureWPF], connection.StartPort,
// // procedures[connection.EndBlock as ProcedureWPF], connection.EndPort);
// }
// }
// //сотрим соединения ресурсов
// else if (element is ResConnectionWPF)
// {
// var connection = (element as ResConnectionWPF);
// ProcedureWPF procedure;
// ResourceWPF resourceWPF;
// if (connection.StartBlock is ProcedureWPF)
// {
// procedure = connection.StartBlock as ProcedureWPF;
// resourceWPF = connection.EndBlock as ResourceWPF;
// }
// else
// {
// procedure = connection.EndBlock as ProcedureWPF;
// resourceWPF = connection.StartBlock as ResourceWPF;
// }
// Procedure block = null;
// //если в первый раз такое встречаем
// if (!(procedures.ContainsKey(procedure)))
// {
// block = procedure.BlockModel;
// procedures.Add(procedure, block);
// resultProcedures.Add(block);
// }
// else
// block = procedures[procedure];
// Resource resource = null; ;
// //если в первый раз такое встречаем
// if (!(resources.ContainsKey(resourceWPF)))
// {
// resource = this.ConvertWpfResourceToModel(resourceWPF);
// resources.Add(resourceWPF, resource);
// //process.Resources.Add(resource); // WTF???
// }
// else
// resource = resources[resourceWPF];
// if (block is Procedure)
// (block as Procedure).Resources.Add(resource);
// else
// throw new ArgumentException("Ресурсы поддерживает только блоки типа Procedure");
// }
// }
// simOptions.Procedures = resultProcedures;
//}
private void StartModeling_Executed(object sender, RoutedEventArgs e)
{
try
{
var tabs = testTabControl.Items.OfType <TabItem>().ToList();
var drawArea = tabs[0].Content as DrawArea;
var proceduresConnections = drawArea.Children.OfType <ProcConnectionWPF>()
.Where(x => x.startPoint == null || x.startPoint.ConnectType == ConnectPointWPF_Type.outPut)
.ToList();
var backLinksConnections = drawArea.Children.OfType <ProcConnectionWPF>()
.Where(x => x.startPoint != null && x.startPoint.ConnectType == ConnectPointWPF_Type.backOutput)
.ToList();
var resourcesConnections = drawArea.Children.OfType <ResConnectionWPF>().ToList();
var procedures = drawArea.Children.OfType <ProcedureWPF>().ToList();
var resources = drawArea.Children.OfType <ResourceWPF>().ToList();
var resourcesDictionary = resourcesConnections
.Select(x => new
{
Connection = x,
Resource = x.StartBlock is ResourceWPF ? x.StartBlock as ResourceWPF : x.EndBlock as ResourceWPF,
Procedure = x.StartBlock is ProcedureWPF ? x.StartBlock as ProcedureWPF : x.EndBlock as ProcedureWPF
})
.GroupBy(x => x.Procedure)
.ToDictionary(x => x.Key.BlockModel, x => x.Select(y => y.Resource).ToList());
var proceduresDictionary = proceduresConnections
.Where(x => x.StartBlock as ProcedureWPF != null && x.EndBlock as ProcedureWPF != null)
.Select(x => new
{
StartProcedure = x.StartBlock as ProcedureWPF,
EndProcedure = x.EndBlock as ProcedureWPF
})
.Select(x => new
{
Connection = new Connection()
{
Begin = x.StartProcedure.BlockModel,
End = x.EndProcedure.BlockModel
},
x.StartProcedure,
x.EndProcedure
})
.ToList();
var proceduresBackLinkDictionary = backLinksConnections
.Select(x => new
{
StartProcedure = x.StartBlock as ProcedureWPF,
EndProcedure = x.EndBlock as ProcedureWPF
})
.Select(x => new
{
Connection = new Connection()
{
Begin = x.StartProcedure.BlockModel,
End = x.EndProcedure.BlockModel
},
x.StartProcedure,
x.EndProcedure
})
.ToList();
var allProcedures = new List <Procedure>();
allProcedures.AddRange(proceduresDictionary.SelectMany(x => new[] { x.Connection.Begin, x.Connection.End }).Cast <Procedure>());
allProcedures.AddRange(proceduresBackLinkDictionary.SelectMany(x => new[] { x.Connection.Begin, x.Connection.End }).Cast <Procedure>());
allProcedures.AddRange(resourcesDictionary.Keys.Select(x => x));
var totalProcedures = allProcedures.Distinct();
foreach (var procedure in totalProcedures)
{
procedure.Resources = resourcesDictionary.ContainsKey(procedure) ? resourcesDictionary[procedure].Select(res => res.ResourceModel).ToList() : new List <Resource>();
procedure.Inputs = proceduresDictionary.Where(x => x.EndProcedure.BlockModel == procedure).Select(x => x.Connection).ToList();
procedure.Outputs = proceduresDictionary.Where(x => x.StartProcedure.BlockModel == procedure).Select(x => x.Connection).ToList();
procedure.BackLinks = proceduresBackLinkDictionary.Where(x => x.StartProcedure.BlockModel == procedure).Select(x => x.Connection).ToList();
}
var options = new SimulationOptions()
{
Procedures = totalProcedures
.Cast <BaseProcedure>()
.ToList()
};
var simulator = new Simulator();
try
{
var results = simulator.Simulate(options);
var successString = results.IsSuccess ? "успешно" : "неудачно";
string resultMsg = $"Моделирование завершено {successString}";
if (results.IsSuccess)
{
resultMsg += $"{Environment.NewLine}Время моделирования: {results.ModelingTime}";
foreach (var log in results.Logs.Where(log => !string.IsNullOrEmpty(log.Procedure.Name)))
{
resultMsg += $"{Environment.NewLine}===" +
$"{Environment.NewLine}Процедура: {log.Procedure?.Name}" +
$"{Environment.NewLine}Начало: {log.SimulationResult.StartTime}" +
$"{Environment.NewLine}Продолжительность: {log.SimulationResult.Duration}" +
$"{Environment.NewLine}Конец: {log.SimulationResult.EndTime}" +
$"{Environment.NewLine}Входное качество: {(int)(log.SimulationResult.StartQuality * 100.0)}" +
$"{Environment.NewLine}Выходное качество: {(int)(log.SimulationResult.ResultQuality * 100.0)}";
}
var resultsWindow = new ResultWindow(
results.ModelingTime.Value,
resources.Select(x => x.ResourceModel.Cost).Sum(),
results.Logs.Where(log => !string.IsNullOrEmpty(log.Procedure.Name)).ToArray()
);
resultsWindow.Show();
}
else
{
throw new Exception("Моделирование завершено неудачно");
}
listBox1.Items.Clear();
}
catch (Exception err)
{
MessageBox.Show(err.Message);
}
}
catch (Exception ex)
{
MessageBox.Show(ex.Message);
}
finally
{
foreach (var process in processes)
{
//process = new SimulationOptions();
}
}
}
public void execute_Monte_Carlo()
{
// instantiate common classes
_simulationOptions = new SimulationOptions(
0,
RandomNumberGeneratorType.MersenneTwister,
AbsorptionWeightingType.Discrete,
PhaseFunctionType.HenyeyGreenstein,
new List <DatabaseType>(),
false, // track statistics
0.0, // RR threshold -> 0 = no RR performed
0);
_source = new DirectionalPointSourceInput(
new Position(0.0, 0.0, 0.0),
new Direction(0.0, 0.0, 1.0),
1);
_tissue =
new MultiLayerWithSurfaceFiberTissueInput(
new SurfaceFiberTissueRegion(
new Position(0, 0, 0),
_detectorRadius, // needs to match SurfaceFiberDetectorInput
new OpticalProperties(0.01, 1.0, 0.8, 1.4)
),
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerTissueRegion(
new DoubleRange(0.0, 100.0),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(100.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
);
// tissue specification to verify MultiLayerWithSurfaceFiberTissue
// increases reflectance. If use this tissue need to change FinalTissueRegion
// for ALL detectors to 0
//new MultiLayerTissueInput(
// new ITissueRegion[]
// {
// new LayerTissueRegion(
// new DoubleRange(double.NegativeInfinity, 0.0),
// new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
// new LayerTissueRegion(
// new DoubleRange(0.0, 100.0),
// new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
// new LayerTissueRegion(
// new DoubleRange(100.0, double.PositiveInfinity),
// new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
// }
//);
_detectorOpen = new List <IDetectorInput>
{
new SurfaceFiberDetectorInput()
{
Center = new Position(0, 0, 0),
Radius = _detectorRadius,
TallySecondMoment = true,
N = 1.4,
NA = 1.4,
FinalTissueRegionIndex = 3
},
new ROfRhoDetectorInput() // 1mm wide ring to match fiber and 2 because beyond goes into 2nd
{
Rho = new DoubleRange(0.0, 2 * _detectorRadius, 3),
// since tissue w fiber specified -> photon will be in 3 upon exit
FinalTissueRegionIndex = 3,
NA = 1.4,
TallySecondMoment = true
},
};
_detectorNA = new List <IDetectorInput>
{
new SurfaceFiberDetectorInput()
{
Center = new Position(0, 0, 0),
Radius = _detectorRadius,
TallySecondMoment = true,
N = 1.4,
FinalTissueRegionIndex = 3,
NA = 0.39
},
new ROfRhoDetectorInput() // ring to match fiber detector
{
Rho = new DoubleRange(0.0, 2 * _detectorRadius, 3),
// since tissue w fiber specified -> photon will be in 3 upon exit
FinalTissueRegionIndex = 3,
NA = 0.39,
TallySecondMoment = true
},
};
_detectorNAOffCenter = new List <IDetectorInput>
{
new SurfaceFiberDetectorInput()
{
Center = new Position(_detectorRadius, 0, 0), // diam = [0, 2*radius]
Radius = _detectorRadius,
TallySecondMoment = true,
N = 1.4,
FinalTissueRegionIndex = 3,
NA = 1.4
},
new ROfRhoDetectorInput() // ring to match fiber detector
{
// place 1st rho bin center at _detectorRadius with width = 2*radius
Rho = new DoubleRange(_detectorRadius / 2, 2 * _detectorRadius + _detectorRadius / 2, 3),
// since tissue w fiber specified -> photon will be in 3 upon exit
FinalTissueRegionIndex = 3,
NA = 1.4,
TallySecondMoment = true
},
};
var _inputOpen = new SimulationInput(
100,
"",
_simulationOptions,
_source,
_tissue,
_detectorOpen);
_outputOpen = new MonteCarloSimulation(_inputOpen).Run();
var _inputNA = new SimulationInput(
100,
"",
_simulationOptions,
_source,
_tissue,
_detectorNA);
_outputNA = new MonteCarloSimulation(_inputNA).Run();
var _inputNAOffCenter = new SimulationInput(
100,
"",
_simulationOptions,
_source,
_tissue,
_detectorNAOffCenter);
_outputNAOffCenter = new MonteCarloSimulation(_inputNAOffCenter).Run();
}
public void execute_Monte_Carlo()
{
// delete previously generated files
clear_folders_and_files();
var cylinderRadius = 5.0;
var tissueThickness = 2.0;
// instantiate common classes
var simulationOptions = new SimulationOptions(
0, // reproducible
RandomNumberGeneratorType.MersenneTwister,
AbsorptionWeightingType.Discrete,
PhaseFunctionType.HenyeyGreenstein,
new List <DatabaseType>()
{
}, // databases to be written
false, // track statistics
0.0, // RR threshold -> 0 = no RR performed
0);
var source = new CustomCircularSourceInput(
cylinderRadius - 0.01, // outer radius
0.0, // inner radius
new FlatSourceProfile(),
new DoubleRange(0.0, 0.0), // polar angle emission range
new DoubleRange(0.0, 0.0), // azimuthal angle emission range
new Direction(0, 0, 1), // normal to tissue
new Position(0, 0, 0), // center of beam on surface
new PolarAzimuthalAngles(0, 0), // no beam rotation
0); // 0=start in air, 1=start in tissue
// debug with point source
//var source = new DirectionalPointSourceInput(
// new Position(0.0, 0.0, 0.0),
// new Direction(0.0, 0.0, 1.0),
// //new Direction(1/Math.Sqrt(2), 0.0, 1/Math.Sqrt(2)),// debug with 45 degree direction and g=1.0
// 1); // start inside tissue
var detectors =
new List <IDetectorInput>
{
new RSpecularDetectorInput(),
new RDiffuseDetectorInput(), new ROfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, cylinderRadius, 11)
},
new TDiffuseDetectorInput(),
new TOfRhoDetectorInput()
{
Rho = new DoubleRange(0.0, cylinderRadius, 11)
},
new AOfRhoAndZDetectorInput()
{
Rho = new DoubleRange(0.0, cylinderRadius, 11),
Z = new DoubleRange(0, tissueThickness, 11)
},
new ATotalDetectorInput(),
new ATotalBoundingVolumeDetectorInput()
};
_inputBoundedTissue = new SimulationInput(
100,
"",
simulationOptions,
source,
new BoundingCylinderTissueInput(
new CaplessCylinderTissueRegion(
new Position(0, 0, tissueThickness / 2),
cylinderRadius,
tissueThickness,
new OpticalProperties(0.0, 1e-10, 1.0, 1.4)
),
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0)),
new LayerTissueRegion( // note two layer and one layer give same results Yay!
new DoubleRange(0.0, 1.0),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)), // debug g=1.0
new LayerTissueRegion(
new DoubleRange(1.0, tissueThickness),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)), // debug g=1.0
new LayerTissueRegion(
new DoubleRange(tissueThickness, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
),
detectors);
_outputBoundedTissue = new MonteCarloSimulation(_inputBoundedTissue).Run();
}
public PrTabViewModel(SimulationOptions simulationOptions) : base("ІПРАЙ")
{
var logger = Logger.New(typeof(PrTabViewModel));
using (logger.LogPerf("Init"))
{
m_SimulationOptions = simulationOptions;
m_Simulator = new PrSimulator(m_SimulationOptions);
m_VisualizationProvider = GridDataVisualizationProvider.Table();
m_Player = new Player(() =>
{
using (logger.LogPerf("Step simulation"))
{
m_Simulator.SimulateSteps();
}
}, () =>
{
using (logger.LogPerf("Auto simulation"))
{
m_Simulator.SimulateSteps(5);
}
}, () =>
{
UpdateVisualization.Execute().Subscribe();
}, TimeSpan.FromMilliseconds(10), DispatcherPriority.ContextIdle);
UpdateVisualization = ReactiveCommand.Create(() =>
{
using (logger.LogPerf("Visualization"))
{
Visualization = m_VisualizationProvider.ProvideVisualization(m_Simulator.GetData());
SimulationInfo = m_Simulator.SimulationInfo;
}
});
var notRunningOrPlaying = m_Player.WhenAny(x => x.RunningOrPlaying, r => !r.Value);
var notSingleStepRunning = m_Player.WhenAny(x => x.SingleStepRunning, r => !r.Value);
Step = ReactiveCommand.Create(() =>
{
m_Player.StepOnce();
}, notRunningOrPlaying);
PlayPause = new ReactivePlayPauseCommand("Програти", "Пауза", notSingleStepRunning);
PlayPause.Subscribe(p =>
{
if (p)
{
m_Player.Start();
}
else
{
m_Player.Stop();
}
});
Restart = ReactiveCommand.Create(() =>
{
m_Simulator.Reset();
}, notRunningOrPlaying);
Restart.InvokeCommand(UpdateVisualization);
VisualTypeSelector = new ReactiveSelectorCommand <string>(x => (string)x, "Table");
VisualTypeSelector.Selected
.Subscribe(option =>
{
switch (option)
{
case "Table":
m_VisualizationProvider = GridDataVisualizationProvider.Table();
break;
case "2D":
m_VisualizationProvider = GridDataVisualizationProvider.Color();
break;
case "3D":
m_VisualizationProvider = GridDataVisualizationProvider.Model3D(m_SimulationOptions.Size);
break;
}
});
VisualTypeSelector.Selected
.ToSignal()
.InvokeCommand(UpdateVisualization);
OpenSimulationOptions = ReactiveCommand.Create(() =>
{
SimulationOptionsDialog dialog = new SimulationOptionsDialog(m_SimulationOptions);
dialog.ShowDialog();
if (!dialog.DialogResult.GetValueOrDefault(false))
{
return;
}
m_SimulationOptions = dialog.SimulationOptions;
m_Simulator = new PrSimulator(m_SimulationOptions);
m_VisualizationProvider = m_VisualizationProvider.Copy(m_SimulationOptions.Size);
}, notRunningOrPlaying);
OpenSimulationOptions
.InvokeCommand(UpdateVisualization);
ExportToCsv = ReactiveCommand.Create(() =>
{
SaveFileDialog saveFileDialog = new SaveFileDialog()
{
Filter = "Файл CSV (*.csv)|*.csv"
};
if (saveFileDialog.ShowDialog(Application.Current.MainWindow).GetValueOrDefault())
{
CsvUtil.ExportToFile(m_Simulator.GetData(), saveFileDialog.FileName);
}
});
Settings.SettingsChange
.InvokeCommand(UpdateVisualization);
Settings.SettingsChange
.Subscribe(_ =>
{
Pallete = Settings.Current.VisualizationOptions.Pallete;
});
Pallete = Settings.Current.VisualizationOptions.Pallete;
}
}
public void CopyTo(SimulationOptions other)
{
other.NumberOfParticles = this.m_NumberOfParticles;
other.ParticleScale = this.m_ParticleScale;
other.BerendsenThermostatCoupling = this.m_BerendsenThermostatCoupling;
other.EquilibriumTemperature = this.m_EquilibriumTemperature;
other.GradientScaleFactor = this.m_GradientScaleFactor;
other.PotentialEnergy = this.m_PotentialEnergy;
for (int i = 0; i < ParticleTypes.Count; i++)
{
ParticleTypes[i].CopyTo(other.ParticleTypes[i]);
}
}
public void LoadDefaults()
{
mode = "dataset";
loggingEnabled = false;
simulationOptions = new SimulationOptions()
{
videoPort = 44209,
webAPIPort = 44210,
videoQuality = 60,
selectedWaterContainer = "waterpool1",
fixedDeltaTime = 0.001f,
depthMapQuality = 90,
depthMapScale = 0.1f,
videoFeedQuality = 90,
videoFeedScale = 0.5f
};
datasetOptions = new DatasetOptions()
{
selectedWaterContainer = "waterpool1",
classDetectedFrameNum = 11,
classMultipleFrameNum = 11,
classBlankFrameNum = 11,
classObstacleFrameNum = 11,
minVisibleMultipleObjectsNum = 2,
minCameraDistanceToObject = 0,
maxCameraDistanceToObject = 30,
minObjectFill = .01f,
minObjectColorPercentVisible = 0.15f,
checkFogVisibility = true,
percentClosest = 0.05f,
closestMaxDistanceOffset = 2f,
objectFillOffset = .01f,
overrideDataset = true,
datasetDirPath = "dataset",
cameraLookAtObjectPitchOffset = 30,
cameraLookAtObjectYawOffset = 30,
cameraLookAtObjectRollOffset = 30,
cameraLookRandomlyPitchOffset = 45,
cameraLookRandomlyRollOffset = 45,
testPointsNum = 1000
};
datasetOptions.graphicsOptions = new GraphicsOptions()
{
fogEnabled = true,
randomizeFogDensity = true,
fogDensity = 0.15f,
fogColorRandomized = true,
fogColor = new List <float>()
{
0f, 0.64f, 1f
},
cameraBackgroundColor = new List <float>()
{
0f, 0.64f, 1f
},
bloomIntensity = 1.89f,
ambientOcclusionIntensity = 0.26f,
mixerRedOutRedIn = 62,
mixerGreenOutGreenIn = 100,
mixerBlueOutBlueIn = 100,
grainIntesity = 0.3f,
randomizeLightIntesity = true,
lightIntesity = 1f,
ambientLightColor = new List <float>()
{
0f, 0.64f, 1f
},
ambientLightIntesity = 0.1f,
cameraFocalLength = 2.550718f,
cameraSensorSize = new List <float>()
{
4.8f, 3.6f
}
};
datasetOptions.debugOptions = new DatasetOptions.DebugOptions()
{
drawDetectionRect = true,
drawPostProcessDebug = false,
disableScreenshot = false,
logDetection = true
};
//TODO
}