/// <summary>
/// Performs the actual work not the most efficient way but I'll work it out
/// </summary>
public void Evaluate(IMathematics mathematics, bool fuzzy)
{
Model.DoseMatrixOptimal sourceDose = new Model.DoseMatrixOptimal(_source.DoseMatrix());
Model.DoseMatrixOptimal targetDose = new Model.DoseMatrixOptimal(_target.DoseMatrix());
TotalCount = targetDose.Length;
Debug.WriteLine("\n\n\nEvaluating " + _source.FileName + " and " + _target.FileName + " Dimensions disagree");
Debug.WriteLine("Max dose: Source - " + sourceDose.MaxPointDose.Dose + " Target - " + targetDose.MaxPointDose.Dose);
Tuple <int, int> ret;
for (int i = 0; i < _dtas.Length; i++)
{
if (_dtas[i].Relative)
{
ret = mathematics.CompareRelative(sourceDose, targetDose, _dtas[i].Tolerance, _dtas[i].Threshhold, fuzzy);
}
else
{
ret = mathematics.CompareAbsolute(sourceDose, targetDose, _dtas[i].Tolerance, _dtas[i].Threshhold, fuzzy);
}
_comparisons[i] = new Controller.SingleComparison();
_comparisons[i].TotalCompared = ret.Item2;
_comparisons[i].TotalFailed = ret.Item1;
_comparisons[i]._dta = _dtas[0];
}
IsEvaluated = true;
}
/// <summary>
/// Performs the actual work not the most efficient way but I'll work it out
/// </summary>
public void Evaluate(IMathematics mathematics)
{
Model.DoseMatrixOptimal sourceDose = new Model.DoseMatrixOptimal(_source.DoseMatrix());
Model.DoseMatrixOptimal targetDose = new Model.DoseMatrixOptimal(_target.DoseMatrix());
TotalCount = targetDose.Length;
Debug.WriteLine("\n\n\nEvaluating " + _source.FileName + " and " + _target.FileName + " Dimensions disagree");
Debug.WriteLine("Max dose: Source - " + sourceDose.MaxPointDose.Dose + " Target - " + targetDose.MaxPointDose.Dose);
Model.SingleComparison ret;
for (int i = 0; i < _dtas.Length; i++)
{
if (_dtas[i].Relative)
{
ret = mathematics.CompareRelative(sourceDose, targetDose, _dtas[i]);
}
else
{
ret = mathematics.CompareAbsolute(sourceDose, targetDose, _dtas[i]);
}
_comparisons[i] = ret;
}
IsEvaluated = true;
}
/// <summary>
/// Performs the actual work not the most efficient way but I'll work it out
/// </summary>
public void Evaluate(IMathematics mathematics, bool fuzzy)
{
Model.DoseMatrixOptimal sourceDose = new Model.DoseMatrixOptimal(_source.DoseMatrix());
Model.DoseMatrixOptimal targetDose = new Model.DoseMatrixOptimal(_target.DoseMatrix());
TotalCount = targetDose.Length;
if (sourceDose.CompareDimensions(targetDose))
//if (false)
{
Debug.WriteLine("\n\n\nEvaluating " + _source.FileName + " and " + _target.FileName);
Tuple <int, int> ret;
ret = mathematics.CompareAbsolute(sourceDose, targetDose, TightTol, ThreshholdTol, fuzzy);
TotalFailedTightTolAbs = ret.Item1;
TotalComparedTightTolAbs = ret.Item2;
if (ret.Item1 == 0) // if failed tightest evaluation skip further evaluation Requires tight < main to work.
{
TotalFailedMainTolAbs = ret.Item1;
TotalComparedMainTolAbs = ret.Item2;
TotalFailedTightTolRel = ret.Item1;
TotalComparedTightTolRel = ret.Item2;
TotalFailedMainTolRel = ret.Item1;
TotalComparedMainTolRel = ret.Item2;
}
else
{
ret = mathematics.CompareAbsolute(sourceDose, targetDose, MainTol, ThreshholdTol, fuzzy);
TotalFailedMainTolAbs = ret.Item1;
TotalComparedMainTolAbs = ret.Item2;
ret = mathematics.CompareRelative(sourceDose, targetDose, TightTol, ThreshholdTol, fuzzy);
TotalFailedTightTolRel = ret.Item1;
TotalComparedTightTolRel = ret.Item2;
ret = mathematics.CompareRelative(sourceDose, targetDose, MainTol, ThreshholdTol, fuzzy);
TotalFailedMainTolRel = ret.Item1;
TotalComparedMainTolRel = ret.Item2;
}
IsEvaluated = true;
}
else
{
Debug.WriteLine("\n\n\nEvaluating " + _source.FileName + " and " + _target.FileName + " Dimensions disagree");
Debug.WriteLine("Max dose: Source - " + sourceDose.MaxPointDose.Dose + " Target - " + targetDose.MaxPointDose.Dose);
Tuple <int, int> ret;
ret = mathematics.CompareAbsolute(sourceDose, targetDose, TightTol, ThreshholdTol, fuzzy);
TotalFailedTightTolAbs = ret.Item1;
TotalComparedTightTolAbs = ret.Item2;
if (ret.Item1 == 0)
{
TotalFailedMainTolAbs = ret.Item1;
TotalComparedMainTolAbs = ret.Item2;
TotalFailedTightTolRel = ret.Item1;
TotalComparedTightTolRel = ret.Item2;
TotalFailedMainTolRel = ret.Item1;
TotalComparedMainTolRel = ret.Item2;
}
else
{
ret = mathematics.CompareAbsolute(sourceDose, targetDose, MainTol, ThreshholdTol, fuzzy);
TotalFailedMainTolAbs = ret.Item1;
TotalComparedMainTolAbs = ret.Item2;
ret = mathematics.CompareRelative(sourceDose, targetDose, TightTol, ThreshholdTol, fuzzy);
TotalFailedTightTolRel = ret.Item1;
TotalComparedTightTolRel = ret.Item2;
ret = mathematics.CompareRelative(sourceDose, targetDose, MainTol, ThreshholdTol, fuzzy);
TotalFailedMainTolRel = ret.Item1;
TotalComparedMainTolRel = ret.Item2;
}
IsEvaluated = true;
}
}
public DscDataHandler(DicomStrictCompare.Controller.Settings settings)
{
this.Settings = settings;
DosePairsList = new ConcurrentBag <MatchedDosePair>();
mathematics = new X86Mathematics();
}
public DscDataHandler()
{
DosePairsList = new ConcurrentBag <MatchedDosePair>();
mathematics = new X86Mathematics();
}
public void Run(bool runDoseComparisons, bool runPDDComparisons, string SaveDirectory, object sender)
{
// Maximum number of CPU threads
ParallelOptions cpuParallel = new ParallelOptions {
MaxDegreeOfParallelism = Environment.ProcessorCount
};
//ParallelOptions cpuParallel = new ParallelOptions { MaxDegreeOfParallelism = 1 };
ParallelOptions parallel = cpuParallel;
// Sets the system to use the correct resources without doubling down on GPU
mathematics = new X86Mathematics();
parallel = cpuParallel;
double progress = 0;
#region safetyChecks
try
{
_ = SourceDirectory.IsNormalized();
}
catch (NullReferenceException)
{
throw new NullReferenceException("Source directory cannot be null");
}
try
{
_ = TargetDirectory.IsNormalized();
}
catch (NullReferenceException)
{
throw new NullReferenceException("Target directory cannot be null");;
}
if (SourceListStrings.Length <= 0)
{
throw new InvalidOperationException("There are no Dose files in the source directory Tree");
}
if (TargetListStrings.Length <= 0)
{
throw new InvalidOperationException("There are no Dose files in the Target directory Tree");
}
#endregion
#region setup
(sender as BackgroundWorker).ReportProgress((int)progress, "Setup: Scanning Source Doses ");
SourceDosesList = FileHandler.DoseFiles(SourceListStrings);
(sender as BackgroundWorker).ReportProgress((int)progress, "Setup: Scanning Source Plans ");
SourcePlanList = FileHandler.PlanFiles(SourceListStrings);
(sender as BackgroundWorker).ReportProgress((int)progress, "Setup: Scanning Target Doses ");
TargetDosesList = FileHandler.DoseFiles(TargetListStrings);
(sender as BackgroundWorker).ReportProgress((int)progress, "Setup: Scanning Target Plans ");
TargetPlanList = FileHandler.PlanFiles(TargetListStrings);
#endregion
DosePairsList = new ConcurrentBag <MatchedDosePair>();
progress += 5;
(sender as BackgroundWorker).ReportProgress((int)progress, "Scanning Source Folder");
_ = Parallel.ForEach(SourceDosesList, new ParallelOptions {
MaxDegreeOfParallelism = Environment.ProcessorCount
}, doseFile =>
{
doseFile.SetFieldName(SourcePlanList);
});
progress += 5;
(sender as BackgroundWorker).ReportProgress((int)progress, "Scanning Target Folder");
_ = Parallel.ForEach(TargetDosesList, new ParallelOptions {
MaxDegreeOfParallelism = Environment.ProcessorCount
}, doseFile =>
{
doseFile.SetFieldName(TargetPlanList);
});
double ProgressIncrimentor = 10.0 / TargetDosesList.Count;
(sender as BackgroundWorker).ReportProgress((int)progress, "Matching");
// match each pair for analysis
_ = Parallel.ForEach(TargetDosesList, cpuParallel, (dose) =>
{
progress += ProgressIncrimentor;
progress %= 100;
(sender as BackgroundWorker).ReportProgress((int)progress, "Matching");
var sourceDose = SourceDosesList.Find(x => x.MatchIdentifier == dose.MatchIdentifier);
if (sourceDose != null)
{
Debug.WriteLine("matched " + dose.FileName + " and " + sourceDose.FileName);
DosePairsList.Add(new MatchedDosePair(sourceDose, dose, Settings));
}
});
if (DosePairsList.Count <= 0)
{
return;
}
progress = 39;
ProgressIncrimentor = 30.0 / DosePairsList.Count;
progress %= 100;
(sender as BackgroundWorker).ReportProgress((int)progress, "PDD Production");
if (runPDDComparisons)
{
_ = Parallel.ForEach(DosePairsList, cpuParallel, pair =>
{
progress += ProgressIncrimentor;
progress %= 100;
(sender as BackgroundWorker).ReportProgress((int)progress, "PDD Production");
pair.GeneratePDD();
Debug.WriteLine("Saving " + pair.ChartTitle + " to " + SaveDirectory);
try
{
SaveFile saveFile = new SaveFile(pair.ChartTitle, SaveDirectory);
pair.PDDoutString = saveFile.Save(pair.SourcePDD, pair.TargetPDD, pair.ChartFileName, SaveDirectory, pair.ChartTitle, SourceAliasName, TargetAliasName);
}
catch (Exception)
{
Debug.WriteLine("Failed to save " + pair.ChartTitle);
}
});
progress = 69;
//fix for memory abuse is to limit the number of cores, Arbitrarily I have hard coded it to half the logical cores of the system.
if (runDoseComparisons)
{
ProgressIncrimentor = 30.0 / DosePairsList.Count;
ResultMessage += MatchedDosePair.StaticResultHeader(Settings.Dtas);
_ = Parallel.ForEach(DosePairsList, parallel, pair =>
{
progress += ProgressIncrimentor;
progress %= 100;
(sender as BackgroundWorker).ReportProgress((int)progress, "Comparing " + progress);
try
{
pair.Evaluate(mathematics, Settings.Fuzzy);
ResultMessage += pair.ResultString + '\n';
}
// Will catch array misalignment problems
catch (Exception e)
{
string temp = pair.Name + ",Was not Evaluated ,\n";
ResultMessage += temp;
Debug.WriteLine(temp);
Debug.WriteLine(e.Message.ToString());
Debug.Write(e.StackTrace.ToString());
}
});
}
}
}
