public void TestLinearEquationCalculation()
{
List <UMCLight> observedUmcList = null;
List <UMCLight> targetUmcList = null;
CreateObservedAndTargetUmcLists(ref observedUmcList, ref targetUmcList);
var xyDataList =
observedUmcList.Select((t, i) => new XYData(t.DriftTime, targetUmcList[i].DriftTime)).ToList();
var regression = new LinearRegressionModel();
var linearEquation = regression.CalculateRegression(xyDataList);
Assert.AreEqual(Math.Round(linearEquation.Slope, 4), 0.7142);
Assert.AreEqual(Math.Round(linearEquation.Intercept, 4), 1.1324);
}
/// <summary>
/// Aligns features to the baseline correcting for drift time.
/// </summary>
/// <param name="fullObservedEnumerable">All features.</param>
/// <param name="observedEnumerable">Filtered features to use for drift time correction.</param>
/// <param name="targetEnumerable">Expected features that should be filtered.</param>
/// <param name="massTolerance">PPM Mass Tolerance.</param>
/// <param name="netTolerance">Normalized Elution Time Tolerance.</param>
public static DriftTimeAlignmentResults <TTarget, TObserved> AlignObservedEnumerable(IEnumerable <UMCLight> fullObservedEnumerable, IEnumerable <TTarget> observedEnumerable, IEnumerable <TObserved> targetEnumerable, double massTolerance, double netTolerance)
{
// Setup Tolerance for Feature Matching
var featureMatcherParameters = new FeatureMatcherParameters();
featureMatcherParameters.SetTolerances(massTolerance, netTolerance, DRIFT_TIME_TOLERANCE);
featureMatcherParameters.UseDriftTime = true;
// Find all matches based on defined tolerances
var featureMatcher = new FeatureMatcher <TTarget, TObserved>(observedEnumerable.ToList(), targetEnumerable.ToList(), featureMatcherParameters);
var matchList = featureMatcher.FindMatches(observedEnumerable.ToList(), targetEnumerable.ToList(), featureMatcherParameters.UserTolerances, 0);
// Create <ObservedDriftTime, TargetDriftTime> XYData List
var xyDataList = new List <XYData>();
foreach (var featureMatch in matchList)
{
var xyData = new XYData(featureMatch.ObservedFeature.DriftTime, featureMatch.TargetFeature.DriftTime);
xyDataList.Add(xyData);
}
var linearRegression = new LinearRegressionModel();
// Find the Linear Equation for the <ObservedDriftTime, TargetDriftTime> XYData List
var linearEquation = linearRegression.CalculateRegression(xyDataList);
// Set the Aligned Drift Time value for each of the observed Features, even if they were not found in matching
foreach (var observedT in fullObservedEnumerable)
{
observedT.DriftTimeAligned = linearRegression.Transform(linearEquation, observedT.DriftTime);
}
var results = new DriftTimeAlignmentResults <TTarget, TObserved>(matchList, linearEquation);
return(results);
}
