public void validate_pMCROfRhoAndTimeDetector_deserialized_class_is_correct_when_using_WriteReadDetectorToFile()
{
string detectorName = "testpmcrofrhoandtime";
IDetectorInput detectorInput = new pMCROfRhoAndTimeDetectorInput()
{
Rho = new DoubleRange(0, 10, 3),
Time = new DoubleRange(0, 1, 4),
PerturbedOps = new List <OpticalProperties>()
{
new OpticalProperties()
},
PerturbedRegionsIndices = new List <int>()
{
1
},
TallySecondMoment = true, // tally SecondMoment
Name = detectorName,
};
var detector = (pMCROfRhoAndTimeDetector)detectorInput.CreateDetector();
detector.Mean = new double[, ] {
{ 1, 2, 3 }, { 4, 5, 6 }
};
DetectorIO.WriteDetectorToFile(detector, "");
var dcloned = (pMCROfRhoAndTimeDetector)DetectorIO.ReadDetectorFromFile(detectorName, "");
Assert.AreEqual(dcloned.Name, detectorName);
Assert.AreEqual(dcloned.Mean[0, 0], 1);
Assert.AreEqual(dcloned.Mean[0, 1], 2);
Assert.AreEqual(dcloned.Mean[0, 2], 3);
Assert.AreEqual(dcloned.Mean[1, 0], 4);
Assert.AreEqual(dcloned.Mean[1, 1], 5);
Assert.AreEqual(dcloned.Mean[1, 2], 6);
}
public void validate_FluenceOfRhoAndZAndTime_deserialized_class_is_correct_when_using_WriteReadDetectorToFile()
{
string detectorName = "testfluenceofrhoandzandtime";
IDetectorInput detectorInput = new FluenceOfRhoAndZAndTimeDetectorInput()
{
Rho = new DoubleRange(0, 10, 3),
Z = new DoubleRange(0, 10, 3),
Time = new DoubleRange(0, 1, 4),
TallySecondMoment = true,
Name = detectorName,
};
var detector = (FluenceOfRhoAndZAndTimeDetector)detectorInput.CreateDetector();
detector.Mean = new double[, , ] {
{ { 1, 2, 3 }, { 4, 5, 6 } }, { { 7, 8, 9 }, { 10, 11, 12 } }
};
DetectorIO.WriteDetectorToFile(detector, "");
var dcloned = (FluenceOfRhoAndZAndTimeDetector)DetectorIO.ReadDetectorFromFile(detectorName, "");
Assert.AreEqual(dcloned.Name, detectorName);
Assert.AreEqual(dcloned.Mean[0, 0, 0], 1);
Assert.AreEqual(dcloned.Mean[0, 0, 1], 2);
Assert.AreEqual(dcloned.Mean[0, 0, 2], 3);
Assert.AreEqual(dcloned.Mean[0, 1, 0], 4);
Assert.AreEqual(dcloned.Mean[0, 1, 1], 5);
Assert.AreEqual(dcloned.Mean[0, 1, 2], 6);
Assert.AreEqual(dcloned.Mean[1, 0, 0], 7);
Assert.AreEqual(dcloned.Mean[1, 0, 1], 8);
Assert.AreEqual(dcloned.Mean[1, 0, 2], 9);
Assert.AreEqual(dcloned.Mean[1, 1, 0], 10);
Assert.AreEqual(dcloned.Mean[1, 1, 1], 11);
Assert.AreEqual(dcloned.Mean[1, 1, 2], 12);
}
public void validate_AOfRhoAndZDetector_deserialized_class_is_correct_when_using_WriteReadDetectorToFile()
{
string detectorName = "testaofrhoandz";
IDetectorInput detectorInput = new AOfRhoAndZDetectorInput()
{
Rho = new DoubleRange(0, 10, 3),
Z = new DoubleRange(0, 1, 4),
TallySecondMoment = false,
Name = detectorName,
};
var detector = (AOfRhoAndZDetector)detectorInput.CreateDetector();
detector.Mean = new double[, ] {
{ 1, 2, 3 }, { 4, 5, 6 }
};
DetectorIO.WriteDetectorToFile(detector, "");
var dcloned = (AOfRhoAndZDetector)DetectorIO.ReadDetectorFromFile(detectorName, "");
Assert.AreEqual(dcloned.Name, detectorName);
Assert.AreEqual(dcloned.Mean[0, 0], 1);
Assert.AreEqual(dcloned.Mean[0, 1], 2);
Assert.AreEqual(dcloned.Mean[0, 2], 3);
Assert.AreEqual(dcloned.Mean[1, 0], 4);
Assert.AreEqual(dcloned.Mean[1, 1], 5);
Assert.AreEqual(dcloned.Mean[1, 2], 6);
}
public void validate_pMCROfRhoDetector_deserialized_class_is_correct_when_using_WriteReadDetectorToFile()
{
string detectorName = "testpmcrofrho";
IDetectorInput detectorInput = new pMCROfRhoDetectorInput()
{
Rho = new DoubleRange(0, 10, 4),
PerturbedOps = new List <OpticalProperties>()
{
new OpticalProperties()
},
PerturbedRegionsIndices = new List <int>()
{
1
},
TallySecondMoment = true, // tally SecondMoment
Name = detectorName,
};
var detector = (pMCROfRhoDetector)detectorInput.CreateDetector();
detector.Mean = new double[] { 100, 200, 300 };
detector.SecondMoment = new double[] { 50, 150, 250 };
DetectorIO.WriteDetectorToFile(detector, "");
var dcloned = (pMCROfRhoDetector)DetectorIO.ReadDetectorFromFile(detectorName, "");
// ckh: not sure how I would read in 2nd moment data in detector + "_2"
Assert.AreEqual(dcloned.Name, detectorName);
Assert.AreEqual(dcloned.Mean[0], 100);
Assert.AreEqual(dcloned.Mean[1], 200);
Assert.AreEqual(dcloned.Mean[2], 300);
}
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);
}
}
public void validate_TDiffuseDetector_deserialized_class_is_correct_when_using_WriteReadDetectorToFile()
{
string detectorName = "testtdiffuse";
IDetectorInput detectorInput = new TDiffuseDetectorInput()
{
TallySecondMoment = false, Name = detectorName
};
var detector = (TDiffuseDetector)detectorInput.CreateDetector();
detector.Mean = 100;
DetectorIO.WriteDetectorToFile(detector, "");
var dcloned = (TDiffuseDetector)DetectorIO.ReadDetectorFromFile(detectorName, "");
Assert.AreEqual(dcloned.Name, detectorName);
Assert.AreEqual(dcloned.Mean, 100);
}
public void validate_ROfRhoDetector_deserialized_class_is_correct_when_using_WriteReadDetectorToFile()
{
string detectorName = "testrofrho";
IDetectorInput detectorInput = new ROfRhoDetectorInput()
{
Rho = new DoubleRange(0, 10, 4), TallySecondMoment = false, Name = detectorName
};
var detector = (ROfRhoDetector)detectorInput.CreateDetector();
detector.Mean = new double[] { 100, 200, 300 };
DetectorIO.WriteDetectorToFile(detector, "");
var dcloned = (ROfRhoDetector)DetectorIO.ReadDetectorFromFile(detectorName, "");
Assert.AreEqual(dcloned.Name, detectorName);
Assert.AreEqual(dcloned.Mean[0], 100);
Assert.AreEqual(dcloned.Mean[1], 200);
Assert.AreEqual(dcloned.Mean[2], 300);
}
public void validate_RDiffuseDetector_deserialized_class_is_correct_when_using_WriteReadDetectorToFile()
{
string detectorName = "testrdiffuse";
IDetectorInput detectorInput = new RDiffuseDetectorInput()
{
TallySecondMoment = true, Name = detectorName
};
var detector = (RDiffuseDetector)detectorInput.CreateDetector();
detector.Mean = 100;
detector.SecondMoment = 50;
DetectorIO.WriteDetectorToFile(detector, "");
var dcloned = (RDiffuseDetector)DetectorIO.ReadDetectorFromFile(detectorName, "");
Assert.AreEqual(dcloned.Name, detectorName);
Assert.AreEqual(dcloned.Mean, 100);
Assert.AreEqual(dcloned.SecondMoment, 50); // 0D detectors 2nd moment written to .txt file
}
public void validate_ROfRhoAndOmegaDetector_deserialized_class_is_correct_when_using_WriteReadDetectorToFile()
{
string detectorName = "testrofrhoandomega";
IDetectorInput detectorInput = new ROfRhoAndOmegaDetectorInput()
{
Rho = new DoubleRange(0, 10, 3),
Omega = new DoubleRange(0, 1, 4),
TallySecondMoment = true, // tally Second Moment
Name = detectorName,
};
var detector = (ROfRhoAndOmegaDetector)detectorInput.CreateDetector();
detector.Mean = new Complex[, ]
{
{
1 + Complex.ImaginaryOne * 1, 2 + Complex.ImaginaryOne * 2, 3 + Complex.ImaginaryOne * 3,
4 + Complex.ImaginaryOne * 4
},
{
5 + Complex.ImaginaryOne * 5, 6 + Complex.ImaginaryOne * 6, 7 + Complex.ImaginaryOne * 7,
8 + Complex.ImaginaryOne * 8
}
};
DetectorIO.WriteDetectorToFile(detector, "");
var dcloned = (ROfRhoAndOmegaDetector)DetectorIO.ReadDetectorFromFile(detectorName, "");
Assert.AreEqual(dcloned.Name, detectorName);
Assert.AreEqual(dcloned.Mean[0, 0], 1 + Complex.ImaginaryOne * 1);
Assert.AreEqual(dcloned.Mean[0, 1], 2 + Complex.ImaginaryOne * 2);
Assert.AreEqual(dcloned.Mean[0, 2], 3 + Complex.ImaginaryOne * 3);
Assert.AreEqual(dcloned.Mean[0, 3], 4 + Complex.ImaginaryOne * 4);
Assert.AreEqual(dcloned.Mean[1, 0], 5 + Complex.ImaginaryOne * 5);
Assert.AreEqual(dcloned.Mean[1, 1], 6 + Complex.ImaginaryOne * 6);
Assert.AreEqual(dcloned.Mean[1, 2], 7 + Complex.ImaginaryOne * 7);
Assert.AreEqual(dcloned.Mean[1, 3], 8 + Complex.ImaginaryOne * 8);
}
public void demonstrate_user_defined_detector_usage()
{
DetectorFactory.RegisterDetector(typeof(ROfXDetectorInput), typeof(ROfXDetector));
var detectorInput = new ROfXDetectorInput
{
TallyType = "ROfX",
Name = "My First R(x) Detector",
TallySecondMoment = true,
X = new DoubleRange(0, 10, 101),
};
var simInput = new SimulationInput
{
DetectorInputs = new[] { detectorInput },
N = 100,
};
var sim = simInput.CreateSimulation();
var results = sim.Run();
IDetector detector;
var detectorExists = results.ResultsDictionary.TryGetValue(detectorInput.Name, out detector);
Assert.IsTrue(detectorExists);
var firstValue = ((ROfXDetector)detector).Mean.FirstOrDefault();
Assert.IsTrue(firstValue != 0);
DetectorIO.WriteDetectorToFile(detector, "user_defined_detector");
var deserializedDetector = DetectorIO.ReadDetectorFromFile("user_defined_detector", "");
}
public void setup()
{
// set up MC simulation that generated the absorbed energy detector results in embedded resources
//var input = new SimulationInput(
//100,
//"test",
//new SimulationOptions(
// 0, // random number generator seed, -1=random seed, 0=fixed seed
// RandomNumberGeneratorType.MersenneTwister,
// AbsorptionWeightingType.Discrete,
// PhaseFunctionType.HenyeyGreenstein,
// new List<DatabaseType>() { }, // databases to be written
// false, // track statistics
// 0.0, // RR threshold -> no RR performed
// 0),
// new DirectionalPointSourceInput(
// new Position(0.0, 0.0, 0.0),
// new Direction(0.0, 0.0, 1.0),
// 0), // 0=start in air, 1=start in tissue
// new SingleInfiniteCylinderTissueInput(
// new InfiniteCylinderTissueRegion(
// new Position(0, 0, 1),
// 1.0,
// new OpticalProperties(0.05, 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))
// }
// ),
// new List<IDetectorInput>()
// {
// new AOfXAndYAndZDetectorInput(){
// X =new DoubleRange(-2, 2, 5),
// Y =new DoubleRange(-10, 10, 2),
// Z =new DoubleRange(0, 3, 4)}
// }
//);
//var output = new MonteCarloSimulation(input).Run(); //NOTE: this puts output in Vts.MCCL/bin/Debug
var name = Assembly.GetExecutingAssembly().FullName;
var assemblyName = new AssemblyName(name).Name;
_aOfXAndYAndZDetector = (dynamic)DetectorIO.ReadDetectorFromFileInResources(
"AOfXAndYAndZ", "Resources/sourcetest/", assemblyName);
// overwrite statistical data in Mean with deterministic values to test
int count = 1;
for (int i = 0; i < _aOfXAndYAndZDetector.X.Count - 1; i++)
{
for (int j = 0; j < _aOfXAndYAndZDetector.Y.Count - 1; j++)
{
for (int k = 0; k < _aOfXAndYAndZDetector.Z.Count - 1; k++)
{
_aOfXAndYAndZDetector.Mean[i, j, k] = count; // make all nonzero and unique
++count;
}
}
}
DetectorIO.WriteDetectorToFile(_aOfXAndYAndZDetector, "sourcetest");
FileIO.CopyFileFromResources(
"Resources/sourcetest/input.txt", "sourcetest/input.txt", assemblyName);
// following setup is used to test FluorescenceEmissionSource
_fluorescenceEmissionAOfXAndYAndZSource = new FluorescenceEmissionAOfXAndYAndZSource(
"sourcetest", "input.txt", 3);
// empty infileFolder will initialize AOfXAndYAndZLoader with no AOfXAndYAndZ read
_fluorescenceEmissionAOfXAndYAndZSource.Loader = new AOfXAndYAndZLoader(
"sourcetest", "input.txt", 3);
_loader = _fluorescenceEmissionAOfXAndYAndZSource.Loader;
_loader.InitializeFluorescentRegionArrays();
}
private void MC_ExecuteMonteCarloSolver_Executed(object sender, ExecutedEventArgs e)
{
if (!EnoughRoomInIsolatedStorage(50))
{
logger.Info(() => "\rSimulation not run. Please allocate more than 50MB of storage space.\r");
Commands.IsoStorage_IncreaseSpaceQuery.Execute();
return;
}
_newResultsAvailable = false;
var input = _simulationInputVM.SimulationInput;
var validationResult = SimulationInputValidation.ValidateInput(input);
if (!validationResult.IsValid)
{
logger.Info(() => "\rSimulation input not valid.\rRule: " + validationResult.ValidationRule +
(!string.IsNullOrEmpty(validationResult.Remarks) ? "\rDetails: " + validationResult.Remarks : "") + ".\r");
return;
}
_simulation = new MonteCarloSimulation(input);
_currentCancellationTokenSource = new CancellationTokenSource();
CancellationToken cancelToken = _currentCancellationTokenSource.Token;
TaskScheduler scheduler = TaskScheduler.FromCurrentSynchronizationContext();
var t = Task.Factory.StartNew(() => _simulation.Run(), TaskCreationOptions.LongRunning);
var c = t.ContinueWith((antecedent) =>
{
SolverDemoView.Current.Dispatcher.BeginInvoke(delegate()
{
_output = antecedent.Result;
_newResultsAvailable = _simulation.ResultsAvailable;
var rOfRhoDetectorInputs = _simulationInputVM.SimulationInput.DetectorInputs.
Where(di => di.Name == "ROfRho");
if (rOfRhoDetectorInputs.Any())
{
logger.Info(() => "Creating R(rho) plot...");
var detectorInput = (ROfRhoDetectorInput)rOfRhoDetectorInputs.First();
double[] independentValues = detectorInput.Rho.AsEnumerable().ToArray();
DoubleDataPoint[] points = null;
//var showPlusMinusStdev = true;
//if(showPlusMinusStdev && _output.R_r2 != null)
//{
// var stdev = Enumerable.Zip(_output.R_r, _output.R_r2, (r, r2) => Math.Sqrt((r2 - r * r) / nPhotons)).ToArray();
// var rMinusStdev = Enumerable.Zip(_output.R_r, stdev, (r,std) => r-std).ToArray();
// var rPlusStdev = Enumerable.Zip(_output.R_r, stdev, (r,std) => r+std).ToArray();
// points = Enumerable.Zip(
// independentValues.Concat(independentValues).Concat(independentValues),
// rMinusStdev.Concat(_output.R_r).Concat(rPlusStdev),
// (x, y) => new Point(x, y));
//}
//else
//{
points = Enumerable.Zip(
independentValues,
_output.R_r,
(x, y) => new DoubleDataPoint(x, y)).ToArray();
//}
PlotAxesLabels axesLabels = GetPlotLabels();
Commands.Plot_SetAxesLabels.Execute(axesLabels);
string plotLabel = GetPlotLabel();
Commands.Plot_PlotValues.Execute(new[] { new PlotData(points, plotLabel) });
logger.Info(() => "done.\r");
}
var fluenceDetectorInputs = _simulationInputVM.SimulationInput.DetectorInputs.
Where(di => di.Name == "FluenceOfRhoAndZ");
if (fluenceDetectorInputs.Any())
{
logger.Info(() => "Creating Fluence(rho,z) map...");
var detectorInput = (FluenceOfRhoAndZDetectorInput)fluenceDetectorInputs.First();
var rhosMC = detectorInput.Rho.AsEnumerable().ToArray();
var zsMC = detectorInput.Z.AsEnumerable().ToArray();
var rhos = Enumerable.Zip(rhosMC.Skip(1), rhosMC.Take(rhosMC.Length - 1), (first, second) => (first + second) / 2).ToArray();
var zs = Enumerable.Zip(zsMC.Skip(1), rhosMC.Take(zsMC.Length - 1), (first, second) => (first + second) / 2).ToArray();
var dRhos = Enumerable.Select(rhos, rho => 2 * Math.PI * Math.Abs(rho) * detectorInput.Rho.Delta).ToArray();
var dZs = Enumerable.Select(zs, z => detectorInput.Z.Delta).ToArray();
if (_mapArrayBuffer == null || _mapArrayBuffer.Length != _output.Flu_rz.Length * 2)
{
_mapArrayBuffer = new double[_output.Flu_rz.Length * 2];
}
// flip the array (since it goes over zs and then rhos, while map wants rhos and then zs
for (int zi = 0; zi < zs.Length; zi++)
{
for (int rhoi = 0; rhoi < rhos.Length; rhoi++)
{
_mapArrayBuffer[rhoi + rhos.Length + rhos.Length * 2 * zi] = _output.Flu_rz[rhoi, zi];
}
var localRhoiForReverse = 0;
for (int rhoi = rhos.Length - 1; rhoi >= 0; rhoi--, localRhoiForReverse++)
{
_mapArrayBuffer[localRhoiForReverse + rhos.Length * 2 * zi] = _output.Flu_rz[rhoi, zi];
}
}
var twoRhos = Enumerable.Concat(rhos.Reverse().Select(rho => - rho), rhos).ToArray();
var twoDRhos = Enumerable.Concat(dRhos.Reverse(), dRhos).ToArray();
var mapData = new MapData(_mapArrayBuffer, twoRhos, zs, twoDRhos, dZs);
Commands.Maps_PlotMap.Execute(mapData);
logger.Info(() => "done.\r");
}
// save results to isolated storage
logger.Info(() => "Saving simulation results to temporary directory...");
//var detectorFolder = Path.Combine(TEMP_RESULTS_FOLDER, input.OutputName);
//// create the root directory
//FileIO.CreateDirectory(TEMP_RESULTS_FOLDER);
// create the detector directory, removing stale files first if they exist
FileIO.CreateEmptyDirectory(TEMP_RESULTS_FOLDER);
// write detector to file
input.ToFile(Path.Combine(TEMP_RESULTS_FOLDER, "infile_" + input.OutputName + ".txt"));
foreach (var result in _output.ResultsDictionary.Values)
{
// save all detector data to the specified folder
DetectorIO.WriteDetectorToFile(result, TEMP_RESULTS_FOLDER);
}
var store = IsolatedStorageFile.GetUserStoreForApplication();
if (store.DirectoryExists(TEMP_RESULTS_FOLDER))
{
var currentAssembly = Assembly.GetExecutingAssembly();
// get all the files we want to zip up
var fileNames = store.GetFileNames(TEMP_RESULTS_FOLDER + @"\*");
// copy the MATLAB files to isolated storage and get their names so they can be included in the zip file
var matlabFiles = FileIO.CopyFolderFromEmbeddedResources("Matlab", TEMP_RESULTS_FOLDER, currentAssembly.FullName, false);
// then, zip all the files together and store *that* .zip to isolated storage as well (can't automatically copy to user folder due to security restrictions)
var allFiles = matlabFiles.Concat(fileNames).Distinct();
try
{
FileIO.ZipFiles(allFiles, TEMP_RESULTS_FOLDER, input.OutputName + ".zip");
}
catch (SecurityException)
{
logger.Error(() => "\rProblem saving results to file.\r");
}
}
logger.Info(() => "done.\r");
});
},
cancelToken,
TaskContinuationOptions.OnlyOnRanToCompletion,
scheduler);
}
public void validate_ReflectedMTOfRhoAndSubregionHistDetector_deserialized_class_is_correct_when_using_WriteReadDetectorToFile()
{
string detectorName = "testreflectedmtofrhoandsubregionhist";
var tissue = new MultiLayerTissue(
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, 0.7, 1.33)),
new LayerTissueRegion(
new DoubleRange(100.0, double.PositiveInfinity),
new OpticalProperties(0.0, 1e-10, 1.0, 1.0))
}
);
IDetectorInput detectorInput = new ReflectedMTOfRhoAndSubregionHistDetectorInput()
{
Rho = new DoubleRange(0, 10, 3),
MTBins = new DoubleRange(0, 10, 3),
FractionalMTBins = new DoubleRange(0, 1, 2),
TallySecondMoment = true, // tally SecondMoment
Name = detectorName,
};
var detector = (ReflectedMTOfRhoAndSubregionHistDetector)detectorInput.CreateDetector();
// need to initialize detector so that NumSubregions gets set
detector.Initialize(tissue, null);
// Mean has dimensions [Rho.Count - 1, MTBins.Count - 1]
detector.Mean = new double[, ] {
{ 1, 2 }, { 3, 4 }
};
// FractionalMT has dimensions [Rho.Count - 1, MTBins.Count - 1, NumSubregions, FractionalMTBins.Count + 1]=[2,2,3,3]
detector.FractionalMT = new double[, , , ] {
{ { { 1, 2, 3 }, { 4, 5, 6 }, { 7, 8, 9 } }, { { 10, 11, 12 }, { 13, 14, 15 }, { 16, 17, 18 } } }, { { { 19, 20, 21 }, { 22, 23, 24 }, { 25, 26, 27 } }, { { 28, 29, 30 }, { 31, 32, 33 }, { 34, 35, 36 } } }
};
DetectorIO.WriteDetectorToFile(detector, "");
var dcloned = (ReflectedMTOfRhoAndSubregionHistDetector)DetectorIO.ReadDetectorFromFile(detectorName, "");
Assert.AreEqual(dcloned.Name, detectorName);
Assert.AreEqual(dcloned.Mean[0, 0], 1);
Assert.AreEqual(dcloned.Mean[0, 1], 2);
Assert.AreEqual(dcloned.Mean[1, 0], 3);
Assert.AreEqual(dcloned.Mean[1, 1], 4);
Assert.AreEqual(dcloned.FractionalMT[0, 0, 0, 0], 1);
Assert.AreEqual(dcloned.FractionalMT[0, 0, 0, 1], 2);
Assert.AreEqual(dcloned.FractionalMT[0, 0, 0, 2], 3);
Assert.AreEqual(dcloned.FractionalMT[0, 0, 1, 0], 4);
Assert.AreEqual(dcloned.FractionalMT[0, 0, 1, 1], 5);
Assert.AreEqual(dcloned.FractionalMT[0, 0, 1, 2], 6);
Assert.AreEqual(dcloned.FractionalMT[0, 0, 2, 0], 7);
Assert.AreEqual(dcloned.FractionalMT[0, 0, 2, 1], 8);
Assert.AreEqual(dcloned.FractionalMT[0, 0, 2, 2], 9);
Assert.AreEqual(dcloned.FractionalMT[0, 1, 0, 0], 10);
Assert.AreEqual(dcloned.FractionalMT[0, 1, 0, 1], 11);
Assert.AreEqual(dcloned.FractionalMT[0, 1, 0, 2], 12);
Assert.AreEqual(dcloned.FractionalMT[0, 1, 1, 0], 13);
Assert.AreEqual(dcloned.FractionalMT[0, 1, 1, 1], 14);
Assert.AreEqual(dcloned.FractionalMT[0, 1, 1, 2], 15);
Assert.AreEqual(dcloned.FractionalMT[0, 1, 2, 0], 16);
Assert.AreEqual(dcloned.FractionalMT[0, 1, 2, 1], 17);
Assert.AreEqual(dcloned.FractionalMT[0, 1, 2, 2], 18);
Assert.AreEqual(dcloned.FractionalMT[1, 0, 0, 0], 19);
Assert.AreEqual(dcloned.FractionalMT[1, 0, 0, 1], 20);
Assert.AreEqual(dcloned.FractionalMT[1, 0, 0, 2], 21);
Assert.AreEqual(dcloned.FractionalMT[1, 0, 1, 0], 22);
Assert.AreEqual(dcloned.FractionalMT[1, 0, 1, 1], 23);
Assert.AreEqual(dcloned.FractionalMT[1, 0, 1, 2], 24);
Assert.AreEqual(dcloned.FractionalMT[1, 0, 2, 0], 25);
Assert.AreEqual(dcloned.FractionalMT[1, 0, 2, 1], 26);
Assert.AreEqual(dcloned.FractionalMT[1, 0, 2, 2], 27);
Assert.AreEqual(dcloned.FractionalMT[1, 1, 0, 0], 28);
Assert.AreEqual(dcloned.FractionalMT[1, 1, 0, 1], 29);
Assert.AreEqual(dcloned.FractionalMT[1, 1, 0, 2], 30);
Assert.AreEqual(dcloned.FractionalMT[1, 1, 1, 0], 31);
Assert.AreEqual(dcloned.FractionalMT[1, 1, 1, 1], 32);
Assert.AreEqual(dcloned.FractionalMT[1, 1, 1, 2], 33);
Assert.AreEqual(dcloned.FractionalMT[1, 1, 2, 0], 34);
Assert.AreEqual(dcloned.FractionalMT[1, 1, 2, 1], 35);
Assert.AreEqual(dcloned.FractionalMT[1, 1, 2, 2], 36);
}
public void setup()
{
var name = Assembly.GetExecutingAssembly().FullName;
var assemblyName = new AssemblyName(name).Name;
// AOfXAndYAndZ in resource is defined by:
// single layer tissue with embedded infinite cylinder center=(0,0,1) radius=1
// detector x=[-2 2] 4 bins, y=[-10 10] 1 bin, z=[0 3] 3 bins
_aOfXAndYAndZDetector = (dynamic)DetectorIO.ReadDetectorFromFileInResources(
"AOfXAndYAndZ", "Resources/sourcetest/", assemblyName);
// overwrite statistical data in Mean with deterministic values to test
int count = 1;
for (int i = 0; i < _aOfXAndYAndZDetector.X.Count - 1; i++)
{
for (int j = 0; j < _aOfXAndYAndZDetector.Y.Count - 1; j++)
{
for (int k = 0; k < _aOfXAndYAndZDetector.Z.Count - 1; k++)
{
_aOfXAndYAndZDetector.Mean[i, j, k] = count; // make all nonzero and unique
++count;
}
}
}
DetectorIO.WriteDetectorToFile(_aOfXAndYAndZDetector, "sourcetest");
FileIO.CopyFileFromResources(
"Resources/sourcetest/inputAOfXAndYAndZ.txt", "sourcetest/inputAOfXAndYAndZ.txt", assemblyName);
// following setup is used to test FluorescenceEmissionSource CDF sampling method
_fluorEmissionAOfXAndYAndZSourceCDF = new FluorescenceEmissionAOfXAndYAndZSource(
"sourcetest", "inputAOfXAndYAndZ.txt", 3, SourcePositionSamplingType.CDF);
// empty infileFolder will initialize AOfXAndYAndZLoader with no AOfXAndYAndZ read
_fluorEmissionAOfXAndYAndZSourceCDF.Loader = new AOfXAndYAndZLoader(
"sourcetest", "inputAOfXAndYAndZ.txt", 3);
_xyzLoaderCDF = _fluorEmissionAOfXAndYAndZSourceCDF.Loader;
_xyzLoaderCDF.InitializeFluorescentRegionArrays();
// following setup is used to test FluorescenceEmissionSource Unif sampling method
_fluorEmissionAOfXAndYAndZSourceUnif = new FluorescenceEmissionAOfXAndYAndZSource(
"sourcetest", "inputAOfXAndYAndZ.txt", 3, SourcePositionSamplingType.Uniform);
// empty infileFolder will initialize AOfXAndYAndZLoader with no AOfXAndYAndZ read
_fluorEmissionAOfXAndYAndZSourceUnif.Loader = new AOfXAndYAndZLoader(
"sourcetest", "inputAOfXAndYAndZ.txt", 3);
_xyzLoaderUnif = _fluorEmissionAOfXAndYAndZSourceCDF.Loader;
_xyzLoaderCDF.InitializeFluorescentRegionArrays();
// AOfRhoAndZ in resource is defined by:
// single layer tissue with embedded infinite cylinder center=(0,0,1) radius=4
// detector rho=[0 4] 4 bins, z=[0 2] 2 bins
_aOfRhoAndZDetector = (dynamic)DetectorIO.ReadDetectorFromFileInResources(
"AOfRhoAndZ", "Resources/sourcetest/", assemblyName);
// overwrite statistical data in Mean with deterministic values to test
count = 1;
for (int i = 0; i < _aOfRhoAndZDetector.Rho.Count - 1; i++)
{
for (int k = 0; k < _aOfRhoAndZDetector.Z.Count - 1; k++)
{
_aOfRhoAndZDetector.Mean[i, k] = count; // make all nonzero and unique
++count;
}
}
DetectorIO.WriteDetectorToFile(_aOfRhoAndZDetector, "sourcetest");
FileIO.CopyFileFromResources(
"Resources/sourcetest/inputAOfRhoAndZ.txt", "sourcetest/inputAOfRhoAndZ.txt", assemblyName);
// following setup is used to test FluorescenceEmissionSource CDF sampling method
_fluorEmissionAOfRhoAndZSourceCDF = new FluorescenceEmissionAOfRhoAndZSource(
"sourcetest", "inputAOfRhoAndZ.txt", 3, SourcePositionSamplingType.CDF);
// empty infileFolder will initialize AOfRhoAndZLoader with no AOfRhoAndZ read
_fluorEmissionAOfRhoAndZSourceCDF.Loader = new AOfRhoAndZLoader(
"sourcetest", "inputAOfRhoAndZ.txt", 3);
_rhozLoaderCDF = _fluorEmissionAOfRhoAndZSourceCDF.Loader;
_rhozLoaderCDF.InitializeFluorescentRegionArrays();
// following setup is used to test FluorescenceEmissionSource Unif sampling method
_fluorEmissionAOfRhoAndZSourceUnif = new FluorescenceEmissionAOfRhoAndZSource(
"sourcetest", "inputAOfRhoAndZ.txt", 3, SourcePositionSamplingType.Uniform);
// empty infileFolder will initialize AOfRhoAndZLoader with no AOfRhoAndZ read
_fluorEmissionAOfRhoAndZSourceUnif.Loader = new AOfRhoAndZLoader(
"sourcetest", "inputAOfRhoAndZ.txt", 3);
_rhozLoaderUnif = _fluorEmissionAOfRhoAndZSourceCDF.Loader;
_rhozLoaderCDF.InitializeFluorescentRegionArrays();
}
// need to work on following
/// <summary>
/// Runs the Monte Carlo Post-processor
/// </summary>
public static void RunPostProcessor(PostProcessorInput input, string outputFolderPath)
{
// 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);
}
SimulationOutput postProcessedOutput = null;
var databaseGenerationInputFile = SimulationInput.FromFile(Path.Combine(input.InputFolder, input.DatabaseSimulationInputFilename + ".txt"));
// check for pMC tallies first because could have ReflectanceTallies mixed in and want to load CollisionInfo
// Why not mirror the "on-the-fly" code, and allow for all kinds of detector inputs simultaneously? (dc 12/21/2011)
if (input.DetectorInputs.Where(di => di.TallyDetails.IspMCReflectanceTally).Any())
{
IList <IDetectorInput> pMCDetectorInputs;
pMCDetectorInputs = input.DetectorInputs;
var postProcessor = new PhotonDatabasePostProcessor(
VirtualBoundaryType.pMCDiffuseReflectance,
pMCDetectorInputs,
PhotonDatabaseFactory.GetpMCDatabase( // database filenames are assumed to be convention
VirtualBoundaryType.pMCDiffuseReflectance,
input.InputFolder),
databaseGenerationInputFile
);
postProcessedOutput = postProcessor.Run();
}
else if (input.DetectorInputs.Where(di => di.TallyDetails.IsReflectanceTally).Any())
{
var postProcessor = new PhotonDatabasePostProcessor(
VirtualBoundaryType.DiffuseReflectance,
input.DetectorInputs,
PhotonDatabaseFactory.GetPhotonDatabase( //database filenames are assumed to be convention
VirtualBoundaryType.DiffuseReflectance,
input.InputFolder),
databaseGenerationInputFile
);
postProcessedOutput = postProcessor.Run();
}
else if (input.DetectorInputs.Where(di => di.TallyDetails.IsTransmittanceTally).Any())
{
var postProcessor = new PhotonDatabasePostProcessor(
VirtualBoundaryType.DiffuseTransmittance,
input.DetectorInputs,
PhotonDatabaseFactory.GetPhotonDatabase( //database filenames are assumed to be convention
VirtualBoundaryType.DiffuseTransmittance,
input.InputFolder),
databaseGenerationInputFile
);
postProcessedOutput = postProcessor.Run();
}
else if (input.DetectorInputs.Where(di => di.TallyDetails.IsSpecularReflectanceTally).Any())
{
var postProcessor = new PhotonDatabasePostProcessor(
VirtualBoundaryType.SpecularReflectance,
input.DetectorInputs,
PhotonDatabaseFactory.GetPhotonDatabase( //database filenames are assumed to be convention
VirtualBoundaryType.SpecularReflectance,
input.InputFolder),
databaseGenerationInputFile
);
postProcessedOutput = postProcessor.Run();
}
var folderPath = input.OutputName;
if (!Directory.Exists(folderPath))
{
Directory.CreateDirectory(folderPath);
}
// save input file to output folder with results
input.ToFile(Path.Combine(resultsFolder, input.OutputName + ".txt"));
// save database generation input file to output folder
databaseGenerationInputFile.ToFile(Path.Combine(resultsFolder, input.OutputName + "_database_infile.txt"));
if (postProcessedOutput != null)
{
foreach (var result in postProcessedOutput.ResultsDictionary.Values)
{
// save all detector data to the specified folder
DetectorIO.WriteDetectorToFile(result, folderPath);
}
}
}