private void FitScan(Scan s, double gateStart, double gateEnd)
{
double scanStart = SpectrumGateLow;
double scanEnd = SpectrumGateHigh;
double[] xDat = s.ScanParameterArray;
double[] yDat = s.GetTOFOnIntegralArray(0, gateStart, gateEnd);
spectrumFitter.Fit(
xDat,
yDat,
spectrumFitter.SuggestParameters(xDat, yDat, scanStart, scanEnd)
);
}
public override TSolution[] Apply(TSolution[] population)
{
Selector.BeforeSelection(population);
var parents = Selector.Select(population);
var children = new TSolution[parents.Length];
for (int i = 0; i < children.Length; i++)
{
children[i] = new TSolution();
}
Crossover.CrossCoordinates(parents, children);
Mutator.MutateCoordinates(children);
Evaluator.Evaluate(children);
Fitter.Fit(children);
return(children);
}
private void FitAverageTOF()
{
Scan averageScan = Controller.GetController().DataStore.AverageScan;
TOF tof;
if (window.GetTofFitDataSelection() == 0)
{
tof = (TOF)((ArrayList)averageScan.GetGatedAverageOnShot(
startSpectrumGate,
endSpectrumGate).TOFs)[0];
}
else
{
if (((ScanPoint)(averageScan.Points[0])).OffShots.Count == 0)
{
return; //make sure there are some offshots
}
tof = (TOF)((ArrayList)averageScan.GetGatedAverageOffShot(
startSpectrumGate,
endSpectrumGate).TOFs)[0];
}
double[] doubleTimes = new double[tof.Times.Length];
for (int i = 0; i < tof.Times.Length; i++)
{
doubleTimes[i] = (double)tof.Times[i];
}
tofFitter.Fit(
doubleTimes,
tof.Data,
tofFitter.SuggestParameters(
doubleTimes,
tof.Data,
tof.Times[0],
tof.Times[tof.Times.Length - 1])
);
window.ClearTOFFit();
window.PlotTOFFit(tof.GateStartTime, tof.ClockPeriod, tofFitter.FittedValues);
// update the parameter report
window.SetLabel(window.tofFitResultsLabel, tofFitter.ParameterReport);
}
public void Run(string path, Counter counter)
{
ISpectrumReader reader = new ThermoRawSpectrumReader();
reader.Init(path);
IGUIFinder finder = new BinarySearchFinder(PPM);
IProcess picking = new LocalNeighborPicking();
Dictionary <int, List <GUI> > pointMaps = new Dictionary <int, List <GUI> >();
int start = reader.GetFirstScan();
int end = reader.GetLastScan();
Parallel.For(start, end, (i) =>
{
if (reader.GetMSnOrder(i) < 2)
{
ISpectrum spectrum = picking.Process(reader.GetSpectrum(i));
lock (resultLock)
{
pointMaps[i] = finder.FindGlucoseUnits(spectrum);
}
}
counter.Add(end - start);
});
List <List <GUI> > points =
pointMaps.OrderBy(p => p.Key).Select(p => p.Value).ToList();
IGUISequencer sequencer = new DynamicProgrammingSequencer();
List <GUI> guiPoints = sequencer.Choose(points);
Dictionary <int, GUI> guiSelected = new Dictionary <int, GUI>();
foreach (GUI gui in guiPoints)
{
if (guiSelected.ContainsKey(gui.Unit))
{
if (guiSelected[gui.Unit].Peak.GetIntensity() < gui.Peak.GetIntensity())
{
guiSelected[gui.Unit] = gui;
}
}
else
{
guiSelected[gui.Unit] = gui;
}
}
Retention.Clear();
Guis.Clear();
List <GUI> looped = guiSelected.Values.OrderBy(g => g.Scan).ToList();
string output = Path.Combine(Path.GetDirectoryName(path),
Path.GetFileNameWithoutExtension(path) + ".csv");
using (FileStream ostrm = new FileStream(output, FileMode.OpenOrCreate, FileAccess.Write))
{
using (StreamWriter writer = new StreamWriter(ostrm))
{
writer.WriteLine("scan,time,gui,peak,intensity");
foreach (GUI gui in looped)
{
int scan = gui.Scan;
double time = reader.GetRetentionTime(scan);
Retention.Add(time);
Guis.Add(gui.Unit);
writer.WriteLine(scan.ToString() + "," +
time.ToString() + "," +
gui.Unit.ToString() + "," +
gui.Peak.GetMZ().ToString() + "," +
gui.Peak.GetIntensity().ToString());
}
writer.Flush();
}
}
Fitter.Fit(Retention, Guis);
}
public override void Initialize(TSolution[] population)
{
Initializer.InitializeCoordinates(population);
Evaluator.Evaluate(population);
Fitter.Fit(population);
}