/// <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 void validate_only_one_perturbed_region_index_specified()
{
var tissueInput = new MultiLayerTissueInput();
var input = new SimulationInput(
10,
"",
new SimulationOptions(),
new DirectionalPointSourceInput(),
tissueInput,
new List <IDetectorInput>()
{
new dMCdROfRhodMuaDetectorInput()
{
Rho = new DoubleRange(0.0, 100.0),
// set perturbed ops to reference ops
PerturbedOps = new List <OpticalProperties>()
{
tissueInput.Regions[0].RegionOP,
tissueInput.Regions[1].RegionOP,
tissueInput.Regions[2].RegionOP
},
PerturbedRegionsIndices = new List <int>()
{
1, 2
}
}
}
);
var result = SimulationInputValidation.ValidateInput(input);
Assert.IsFalse(result.IsValid);
}
public void validate_top_and_bottom_layers_are_air()
{
var input = new SimulationInput(
10,
"",
new SimulationOptions(),
new DirectionalPointSourceInput(),
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 List <IDetectorInput>()
{
}
);
var result = SimulationInputValidation.ValidateInput(input);
Assert.IsFalse(result.IsValid);
}
public void initialize_simulation_input()
{
// create input with two tissue layers
_input = new SimulationInput(
10,
"Output",
new SimulationOptions(),
new DirectionalPointSourceInput(),
new MultiLayerTissueInput(
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 0.0, 1.0)),
new LayerTissueRegion(
new DoubleRange(0.0, 1.0),
new OpticalProperties(0.01, 1.0, 0.8, 1.4)),
new LayerTissueRegion(
new DoubleRange(1.0, 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, 0.0, 1.0))
}
),
new List <IDetectorInput>
{
new RDiffuseDetectorInput(),
}
);
}
public void validate_at_least_one_tissue_layer_defined()
{
var input = new SimulationInput(
10,
"",
new SimulationOptions(),
new DirectionalPointSourceInput(),
new SingleVoxelTissueInput(
new VoxelTissueRegion(),
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, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
),
new List <IDetectorInput>()
{
}
);
var result = SimulationInputValidation.ValidateInput(input);
Assert.IsFalse(result.IsValid);
}
public void validate_voxel_has_nonzero_dimensions()
{
var input = new SimulationInput(
10,
"",
new SimulationOptions(),
new DirectionalPointSourceInput(),
new SingleVoxelTissueInput(
// set ellipsoid axis to 0.0
new VoxelTissueRegion(new DoubleRange(0, 0),
new DoubleRange(-10, 10),
new DoubleRange(1, 5),
new OpticalProperties()),
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))
}
),
new List <IDetectorInput>()
{
}
);
var result = SimulationInputValidation.ValidateInput(input);
Assert.IsFalse(result.IsValid);
}
public void validate_voxel_is_within_tissue_layer()
{
var input = new SimulationInput(
10,
"",
new SimulationOptions(),
new DirectionalPointSourceInput(),
new SingleVoxelTissueInput(
new VoxelTissueRegion(new DoubleRange(-5, 5),
new DoubleRange(-5, 5),
new DoubleRange(0, 10), // eheck that voxel not at surface
new OpticalProperties()),
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))
}
),
new List <IDetectorInput>()
{
}
);
var result = SimulationInputValidation.ValidateInput(input);
Assert.IsFalse(result.IsValid);
}
private bool ShouldPressButton()
{
bool lightSignalOn = SimulationInput.PollBoolean(LightsKey);
float carUnitOffset = Subscene.Vehicle.CarUnitOffset;
if (lightSignalOn)
{
if (carUnitOffset > VehicleAgentController.ExitsTunnel && !ForgetsToTurnLightsOff)
{
return(true);
}
else
{
return(false);
}
}
else
{
if (carUnitOffset > VehicleAgentController.EntersTunnelSoon && carUnitOffset < VehicleAgentController.ExitsTunnel)
{
return(true);
}
else
{
return(false);
}
}
}
public static void RunSimulation(SimulationInput input, string outputFolderPath)
{
var mc = new MonteCarloSimulation(input);
// locate root folder for output, creating it if necessary
var path = string.IsNullOrEmpty(outputFolderPath)
? Path.GetFullPath(Directory.GetCurrentDirectory())
: Path.GetFullPath(outputFolderPath);
if (!Directory.Exists(path))
{
Directory.CreateDirectory(path);
}
// locate destination folder for output, creating it if necessary
var resultsFolder = Path.Combine(path, input.OutputName);
if (!Directory.Exists(resultsFolder))
{
Directory.CreateDirectory(resultsFolder);
}
mc.SetOutputPathForDatabases(path);
SimulationOutput detectorResults = mc.Run();
input.ToFile(Path.Combine(resultsFolder, input.OutputName + ".txt"));
foreach (var result in detectorResults.ResultsDictionary.Values)
{
// save all detector data to the specified folder
DetectorIO.WriteDetectorToFile(result, resultsFolder);
}
}
/// <summary>
/// method to read the simulation input from a specified or default file
/// </summary>
public static SimulationInput ReadSimulationInputFromFile(string inputFile)
{
try
{
if (string.IsNullOrEmpty(inputFile))
{
logger.Info(" *** No input file specified ***\n\nDefine an input file using mc.exe infile=infile_name.txt");
return(null);
}
//get the full path for the input file
var fullFilePath = Path.GetFullPath(inputFile);
string extension = Path.GetExtension(inputFile);
if (File.Exists(fullFilePath))
{
return(SimulationInput.FromFile(fullFilePath));
}
if (File.Exists(fullFilePath + ".txt"))
{
return(SimulationInput.FromFile(fullFilePath + ".txt"));
}
//throw a file not found exception
throw new FileNotFoundException("\nThe following input file could not be found: " + fullFilePath + " - type mc help=infile for correct syntax");
}
catch (Exception e)
{
Console.WriteLine(e.Message);
//Console.WriteLine(VtsJsonSerializer.TraceWriter.GetTraceMessages());
return(null);
}
}
/// <summary>
/// constructor that load excitation simulation AOfRhoAndZ
/// </summary>
public AOfRhoAndZLoader(string inputFolder, string infile, int fluorescentTissueRegionIndex)
{
if (infile != "")
{
var inputPath = "";
if (inputFolder == "")
{
inputPath = infile;
}
else
{
inputPath = inputFolder + @"/" + infile;
}
var aOfRhoAndZDetector = (AOfRhoAndZDetector) DetectorIO.ReadDetectorFromFile(
"AOfRhoAndZ", inputFolder);
// use DoubleRange X,Y,Z to match detector dimensions
Rho = ((AOfRhoAndZDetector) aOfRhoAndZDetector).Rho;
Z = ((AOfRhoAndZDetector) aOfRhoAndZDetector).Z;
AOfRhoAndZ = ((AOfRhoAndZDetector) aOfRhoAndZDetector).Mean;
var exciteInfile = SimulationInput.FromFile(inputPath);
FluorescentTissueRegion = exciteInfile.TissueInput.Regions[fluorescentTissueRegionIndex];
// separate setup of arrays so can unit test method
InitializeFluorescentRegionArrays();
SetupRegionIndices();
}
else
{
throw new ArgumentException("infile string is empty");
}
}
public void validate_layers_have_ZRange_Count_set_to_2()
{
var input = new SimulationInput(
10,
"",
new SimulationOptions(),
new DirectionalPointSourceInput(),
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)
{
Count = 10
},
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))
}
),
new List <IDetectorInput>()
{
}
);
var result = SimulationInputValidation.ValidateInput(input);
Assert.IsFalse(result.IsValid);
}
public void validate_voxel_refractive_index_matches_that_of_surrounding_layer()
{
var input = new SimulationInput(
10,
"",
new SimulationOptions(),
new DirectionalPointSourceInput(),
new SingleVoxelTissueInput(
new VoxelTissueRegion(new DoubleRange(-5, 5),
new DoubleRange(-5, 5),
new DoubleRange(1, 2),
new OpticalProperties(0.01, 1.0, 0.9, 1.3)),
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))
}
),
new List <IDetectorInput>()
{
}
);
var result = SimulationInputValidation.ValidateInput(input);
Assert.IsFalse(result.IsValid);
}
public void validate_ellipsoid_is_within_tissue_layer()
{
var input = new SimulationInput(
10,
"",
new SimulationOptions(),
new DirectionalPointSourceInput(),
new SingleEllipsoidTissueInput(
new EllipsoidTissueRegion(new Position(0, 0, 0), 1.0, 1.0, 1.0, new OpticalProperties()),
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))
}
),
new List <IDetectorInput>()
{
}
);
var result = SimulationInputValidation.ValidateInput(input);
Assert.IsFalse(result.IsValid);
}
public void execute_Monte_Carlo()
{
// delete any previously generated files and folders
clear_folders_and_files();
_input = new SimulationInput(
10000, // 1e4 needed to get enough photons to Td
"results",
new SimulationOptions(
0,
RandomNumberGeneratorType.MersenneTwister,
AbsorptionWeightingType.Continuous,
PhaseFunctionType.Bidirectional,
new List <DatabaseType>()
{
}, // databases to be written
true, // track statistics
0.0, // RR threshold -> 0 = no RR performed
0),
new DirectionalPointSourceInput(
new Position(0.0, 0.0, 0.0),
new Direction(0.0, 0.0, 1.0),
0
),
new MultiLayerTissueInput(
new ITissueRegion[]
{
new LayerTissueRegion(
new DoubleRange(double.NegativeInfinity, 0.0),
new OpticalProperties(0.0, 1e-10, 0.0, 1.0)),
//new LayerTissueRegion( // debug layer
// new DoubleRange(0.0, _topLayerThickness),
// new OpticalProperties(_mua, _musp, _g, 1.0)), // index matched slab
new LayerTissueRegion(
new DoubleRange(0, _slabThickness),
new OpticalProperties(_mua, _musp, _g, 1.0)), // index matched slab
new LayerTissueRegion(
new DoubleRange(_slabThickness, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 0.0, 1.0))
}
),
new List <IDetectorInput>()
{
new RDiffuseDetectorInput()
{
TallySecondMoment = true
},
new ATotalDetectorInput()
{
TallySecondMoment = true
},
new TDiffuseDetectorInput()
{
TallySecondMoment = true
}
}
);
_output = new MonteCarloSimulation(_input).Run();
}
static void Main(string[] args)
{
var input = new SimulationInput();
SolverMGRTE.ExecuteMGRTE(input);
Console.ReadLine();
}
/// <summary>
/// Calculates the next simulation step.
/// It will read the SimulationInput values and stores in the end the new values to the SimulationOutput.
/// </summary>
protected override void CalculateNextStep(int timeMs)
{
_topTrafficLight.SetToGreen(SimulationInput.PollBoolean(_topTrafficLightKey));
_botTrafficLight.SetToGreen(SimulationInput.PollBoolean(_botTrafficLightKey));
_trafficController.CalculateNextStep(timeMs);
SimulationOutput.SetValue(_topTrafficSensorKey, _topTrafficLight.IsCarInRange());
SimulationOutput.SetValue(_botTrafficSensorKey, _botTrafficLight.IsCarInRange());
}
public void validate_deserialized_class_is_correct_when_using_FileIO()
{
new SimulationInput {
N = 10
}.ToFile("test.txt");
var iCloned = SimulationInput.FromFile("test.txt");
Assert.AreEqual(iCloned.N, 10);
}
private void UpdateInputs()
{
FieldGeneratorInput = SimulationInput.PollBoolean(FieldGeneratorKey);
LaserInput = SimulationInput.PollBoolean(LaserKey);
EmitterInput = SimulationInput.PollBoolean(EmitterKey);
FocusInput = SimulationInput.PollBoolean(FocusKey);
EmitterMotorInput = SimulationInput.PollInteger(EmitterMotorKey);
FocusMotorInput = SimulationInput.PollInteger(FocusMotorKey);
}
/// <summary>
/// Creates an instance of PhotonDatabasePostProcessor for standard (photon) database processing
/// </summary>
/// <param name="virtualBoundaryType">virtual boundary type</param>
/// <param name="detectorInputs">List of IDetectorInputs designating binning</param>
/// <param name="photonDatabase">PhotonTerminationDatabase</param>
/// <param name="databaseInput">Database information needed for post-processing</param>
public PhotonDatabasePostProcessor(
VirtualBoundaryType virtualBoundaryType,
IList <IDetectorInput> detectorInputs,
PhotonDatabase photonDatabase,
SimulationInput databaseInput)
: this(virtualBoundaryType, detectorInputs, databaseInput)
{
_photonDatabase = photonDatabase;
_ispMCPostProcessor = false;
}
public void validate_deserialized_class_is_correct()
{
var i = new SimulationInput {
N = 10
};
var iCloned = i.Clone();
Assert.AreEqual(iCloned.N, 10);
}
public SimulationOutput Post([FromBody] SimulationInput input)
{
var log = new DefaultLogService();
var output = Utilities.RunWithTimeLimit(() => Simulation.Simulate(input), Utilities.GetTimeLimitFromConfig());
if (output.ErrorMessages != null && output.ErrorMessages.Length > 0)
{
var contents = new LogContents(output.DebugMessages, output.ErrorMessages);
faultLogger.Add(DateTime.Now, typeof(JobController).Assembly.GetName().Version.ToString(), input, contents);
}
return(output);
}
public void validate_null_detector_input_is_invalid_when_no_database_specified()
{
// generate input without any detector inputs and no database specified
var input = new SimulationInput() // default constructor has empty list of databases
{
DetectorInputs = new List <IDetectorInput> {
}
};
var result = SimulationInputValidation.ValidateInput(input);
Assert.IsFalse(result.IsValid);
}
public void validate_null_detector_input_gets_converted_to_empty_list_correctly()
{
var si = new SimulationInput(
100,
"results",
new SimulationOptions(),
new Vts.MonteCarlo.Sources.DirectionalPointSourceInput(),
new Vts.MonteCarlo.Tissues.MultiLayerTissueInput(),
null
);
Assert.IsTrue(si.DetectorInputs.Count == 0);
}
public static IEnumerable <SimulationInput> ApplyParameterSweeps(SimulationInput input, IEnumerable <ParameterSweep> parameterSweeps)
{
IEnumerable <SimulationInput> batchInputs = input.AsEnumerable();
foreach (var parameterSweep in parameterSweeps)
{
var sweepValues = parameterSweep.Values.ToEnumerable <double>();
batchInputs = batchInputs.WithParameterSweep(sweepValues, parameterSweep.Name.ToLower());
}
return(batchInputs.ToArray());
}
public SimulationInputViewModel(SimulationInput input)
{
_simulationInput = input; // use the property to invoke the appropriate change notification
_simulationOptionsVM = new SimulationOptionsViewModel(_simulationInput.Options);
_outputName = input.OutputName;
#if WHITELIST
TissueTypeVM = new OptionViewModel <string>("Tissue Type:", true, _simulationInput.TissueInput.TissueType, WhiteList.TissueTypes);
#else
TissueTypeVM = new OptionViewModel <string>("Tissue Type:", true, _simulationInput.TissueInput.TissueType,
new[]
{
"MultiLayer",
"SingleEllipsoid",
"SingleVoxel"
});
#endif
UpdateTissueTypeVM(_simulationInput.TissueInput.TissueType);
_simulationOptionsVM.PropertyChanged += (sender, args) =>
{
if (_simulationOptionsVM.TrackStatistics && _simulationOptionsVM.OutputFolder != null)
{
_simulationInput.OutputName = Path.Combine(_simulationOptionsVM.OutputFolder, _outputName);
}
};
_tissueTypeVM.PropertyChanged += (sender, args) =>
{
switch (_tissueTypeVM.SelectedValue)
{
case "MultiLayer":
_simulationInput.TissueInput = new MultiLayerTissueInput();
break;
case "SingleEllipsoid":
_simulationInput.TissueInput = new SingleEllipsoidTissueInput();
break;
case "SingleVoxel":
_simulationInput.TissueInput = new SingleVoxelTissueInput();
break;
default:
throw new InvalidEnumArgumentException(StringLookup.GetLocalizedString("Error_NoTissueTypeExists"));
}
UpdateTissueTypeVM(_simulationInput.TissueInput.TissueType);
};
UpdateTissueInputVM(_simulationInput.TissueInput);
}
/// <summary>
/// Initializes the whole page. Called before the node is added to the tree by the lesson controller.
/// </summary>
public override void InitialiseWith(IMainNode mainNode, ILessonEntity openedLesson)
{
_topTrafficLight = GetNode <TrafficControlSystem>("Signalisation/TrafficControlSystemTop");
_topTrafficLight.SetToGreen(SimulationInput.PollBoolean(_topTrafficLightKey));
_botTrafficLight = GetNode <TrafficControlSystem>("Signalisation/TrafficControlSystemBot");
_botTrafficLight.SetToGreen(SimulationInput.PollBoolean(_botTrafficLightKey));
PathController topPath = GetNode <PathController>("DynamicCars/TopPath");
topPath.Setup(_topTrafficLight);
PathController botPath = GetNode <PathController>("DynamicCars/BotPath");
botPath.Setup(_botTrafficLight);
_trafficController = new TrafficController(topPath, botPath);
SpawnTimeGenerator.ResetGenerator();
}
public void validate_angled_source_and_cylindrical_detectors_are_not_defined_together()
{
// generate input with angled source and cylindrical detector
var input = new SimulationInput()
{
SourceInput = new DirectionalPointSourceInput(
new Position(0, 0, 0), new Direction(1.0 / Math.Sqrt(2), 0, 1.0 / Math.Sqrt(2)), 1),
DetectorInputs = new List <IDetectorInput> {
new ROfRhoDetectorInput()
}
};
var result = SimulationInputValidation.ValidateInput(input);
Assert.IsFalse(result.IsValid);
}
public void execute_Monte_Carlo()
{
// delete previously generated files
clear_folders_and_files();
var input = new SimulationInput(
100,
"Output",
new SimulationOptions(
0,
RandomNumberGeneratorType.MersenneTwister,
AbsorptionWeightingType.Analog,
PhaseFunctionType.HenyeyGreenstein,
new List <DatabaseType>()
{
}, // databases to be written
false, // track statistics
0.0, // RR threshold -> 0 = no RR performed
0),
new DirectionalPointSourceInput(
new Position(0.0, 0.0, 0.0),
new Direction(0.0, 0.0, 1.0),
0 // start in air
),
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))
}
),
new List <IDetectorInput>
{
new RSpecularDetectorInput(),
}
);
_specularReflectance = Optics.Specular(input.TissueInput.Regions[0].RegionOP.N,
input.TissueInput.Regions[1].RegionOP.N);
_output = new MonteCarloSimulation(input).Run();
}
public void validate_dependencies_can_be_constructed_by_providers()
{
var si = new SimulationInput(
100,
"results",
new SimulationOptions(),
SourceInputProvider.DirectionalPointSourceInput(),
TissueInputProvider.MultiLayerTissueInput(),
new[] { DetectorInputProvider.RDiffuseDetectorInput() }
);
Assert.NotNull(si.SourceInput);
Assert.NotNull(si.TissueInput);
Assert.NotNull(si.DetectorInputs);
Assert.IsTrue(si.DetectorInputs.Count == 1);
}
