public void Test58Percent()
{
var path = Path.Combine(TestContext.TestDir, Guid.NewGuid().ToString() + ".tpg");
var workspace = CreateWorkspace(path, TracerDef.GetD3LeuEnrichment());
var turnoverCalculator = new TurnoverCalculator(workspace, "LL");
var dict = new Dictionary<TracerFormula, double>();
// initialize the dictionary with 70% newly synthesized from 58% precursor pool
dict.Add(TracerFormula.Parse("Tracer2"), Math.Pow(.58, 2) * .7);
dict.Add(TracerFormula.Parse("Tracer1"), 2 * .58 * .42 * .7);
dict.Add(TracerFormula.Empty, 1- dict.Values.Sum());
double turnover;
double turnoverScore;
IDictionary<TracerFormula, double> bestMatch;
var precursorEnrichment = turnoverCalculator.ComputePrecursorEnrichmentAndTurnover(dict, out turnover, out turnoverScore, out bestMatch);
Assert.AreEqual(.7, turnover);
Assert.AreEqual(58, precursorEnrichment["Tracer"]);
}
public void Test58Percent()
{
var path = Path.Combine(TestContext.TestDir, Guid.NewGuid().ToString() + ".tpg");
var workspace = CreateWorkspace(path, TracerDef.GetD3LeuEnrichment());
var turnoverCalculator = new TurnoverCalculator(workspace, "LL");
var dict = new Dictionary <TracerFormula, double>();
// initialize the dictionary with 70% newly synthesized from 58% precursor pool
dict.Add(TracerFormula.Parse("Tracer2"), Math.Pow(.58, 2) * .7);
dict.Add(TracerFormula.Parse("Tracer1"), 2 * .58 * .42 * .7);
dict.Add(TracerFormula.Empty, 1 - dict.Values.Sum());
double turnover;
double turnoverScore;
IDictionary <TracerFormula, double> bestMatch;
var precursorEnrichment = turnoverCalculator.ComputePrecursorEnrichmentAndTurnover(dict, out turnover, out turnoverScore, out bestMatch);
Assert.AreEqual(.7, turnover);
Assert.AreEqual(58, precursorEnrichment["Tracer"]);
}
private void BtnGoOnClick(object sender, EventArgs e)
{
graphDetails.GraphPane.CurveList.Clear();
int pointCount = PointCount;
double precursorPool = PrecursorPool;
double turnover = Turnover;
int labelCount = LabelCount;
double noise = Noise;
var points = new PointPairList();
var tracerDef = Workspace.GetTracerDefs().FirstOrDefault(td => td.AminoAcidSymbol.HasValue);
if (tracerDef == null)
{
MessageBox.Show(
"The simulation cannot be run because there is no amino acid tracer defined in this workspace");
return;
}
Debug.Assert(tracerDef.AminoAcidSymbol.HasValue);
string peptide = new string(tracerDef.AminoAcidSymbol.Value, labelCount);
var turnoverCalculator = new TurnoverCalculator(Workspace, peptide);
var initialTracerPercents = TracerPercentFormula.Parse("").SetElementCount(tracerDef.Name, tracerDef.InitialApe);
var newTracerPercents = TracerPercentFormula.Parse("").SetElementCount(tracerDef.Name, precursorPool);
var initialDistribution = turnoverCalculator.GetDistribution(initialTracerPercents);
var newDistribution = turnoverCalculator.GetDistribution(newTracerPercents);
var currentMixture = Mix(initialDistribution, (100.0 - turnover) / 100, newDistribution, turnover / 100);
var keys = new List <TracerFormula>();
for (int i = 0; i <= labelCount; i++)
{
keys.Add(TracerFormula.Parse("").SetElementCount(tracerDef.Name, i));
}
var bestMatches = new List <IDictionary <TracerFormula, double> >();
var precursorEnrichments = new List <TracerPercentFormula>();
var observedResults = new List <IDictionary <TracerFormula, double> >();
while (points.Count < pointCount)
{
var noisyMixture = Perturb(keys, currentMixture, noise / 100);
double calcTurnover;
double calcTurnoverScore;
double calcPrecursorPool;
IDictionary <TracerFormula, double> bestMatch;
var calcMixture = turnoverCalculator.ComputePrecursorEnrichmentAndTurnover(noisyMixture, out calcTurnover, out calcTurnoverScore, out bestMatch);
if (calcMixture == null)
{
continue;
}
calcMixture.TryGetValue(tracerDef.Name, out calcPrecursorPool);
points.Add(new PointPair(calcTurnover * 100, calcPrecursorPool));
bestMatches.Add(bestMatch);
precursorEnrichments.Add(calcMixture);
observedResults.Add(noisyMixture);
}
graphResults.GraphPane.CurveList.Clear();
graphResults.GraphPane.GraphObjList.Clear();
var lineItem = graphResults.GraphPane.AddCurve(null, points, Color.Black);
lineItem.Line.IsVisible = false;
graphResults.GraphPane.XAxis.Title.Text = "% newly synthesized";
graphResults.GraphPane.YAxis.Title.Text = "Precursor pool";
graphResults.GraphPane.AxisChange();
graphResults.Invalidate();
dataGridView.Rows.Clear();
var row = dataGridView.Rows[dataGridView.Rows.Add()];
row.Cells[colQuantity.Index].Value = "% newly synthesized";
var statsTurnover = new Statistics(points.Select(p => p.X).ToArray());
row.Cells[colMean.Index].Value = statsTurnover.Mean();
row.Cells[colMedian.Index].Value = statsTurnover.Median();
row.Cells[colStdDev.Index].Value = statsTurnover.StdDev();
row = dataGridView.Rows[dataGridView.Rows.Add()];
var statsPrecursorPool = new Statistics(points.Select(p => p.Y).ToArray());
row.Cells[colQuantity.Index].Value = "Precursor Pool";
row.Cells[colMean.Index].Value = statsPrecursorPool.Mean();
row.Cells[colMedian.Index].Value = statsPrecursorPool.Median();
row.Cells[colStdDev.Index].Value = statsPrecursorPool.StdDev();
_precursorEnrichmentsByPoint = points.Select(p => p.Y).ToArray();
_bestMatches = bestMatches;
_observedResults = observedResults;
_scatterPlotCurve = lineItem;
_expected = currentMixture;
_turnovers = points.Select(p => p.X).ToArray();
_tracerFormulas = keys;
ShowResult(-1);
}
