public bool CalcRegressionWith(IRetentionTimeProvider retentionTimes, IEnumerable <DbIrtPeptide> standardPeptideList, DbIrtPeptide[] items)
{
if (items.Any())
{
// Attempt to get a regression based on shared peptides
var calculator = new CurrentCalculator(standardPeptideList, items);
var peptidesTimes = retentionTimes.PeptideRetentionTimes.ToArray();
var regression = RetentionTimeRegression.FindThreshold(RCalcIrt.MIN_IRT_TO_TIME_CORRELATION,
RetentionTimeRegression.ThresholdPrecision,
peptidesTimes,
new MeasuredRetentionTime[0],
peptidesTimes, null,
calculator,
RegressionMethodRT.linear,
() => false);
var startingCount = peptidesTimes.Length;
var regressionCount = regression != null ? regression.PeptideTimes.Count : 0;
if (regression != null && RCalcIrt.IsAcceptableStandardCount(startingCount, regressionCount))
{
// Finally must recalculate the regression, because it is transposed from what
// we want.
var statTimes = new Statistics(regression.PeptideTimes.Select(pt => pt.RetentionTime));
var statIrts = new Statistics(regression.PeptideTimes.Select(pt =>
calculator.ScoreSequence(pt.PeptideSequence) ?? calculator.UnknownScore));
RegressionRefined = new RegressionLine(statIrts.Slope(statTimes), statIrts.Intercept(statTimes));
RegressionSuccess = true;
return(true);
}
}
return(false);
}
private GraphData RefineCloned(double threshold, int?precision, Func <bool> isCanceled)
{
// Create list of deltas between predicted and measured times
_outlierIndexes = new HashSet <int>();
// Start with anything assigned a zero retention time as outliers
for (int i = 0; i < _peptidesTimes.Count; i++)
{
if (_peptidesTimes[i].RetentionTime == 0)
{
_outlierIndexes.Add(i);
}
}
// Now that we have added iRT calculators, RecalcRegression
// cannot go and mark as outliers peptides at will anymore. It must know which peptides, if any,
// are required by the calculator for a regression. With iRT calcs, the standard is required.
if (!_calculator.IsUsable)
{
return(null);
}
HashSet <string> standardNames;
try
{
var names = _calculator.GetStandardPeptides(_peptidesTimes.Select(pep => pep.PeptideSequence));
standardNames = new HashSet <string>(names);
}
catch (CalculatorException)
{
standardNames = new HashSet <string>();
}
var standardPeptides = _peptidesTimes.Where(pep => standardNames.Contains(pep.PeptideSequence)).ToArray();
var variablePeptides = _peptidesTimes.Where(pep => !standardNames.Contains(pep.PeptideSequence)).ToArray();
//Throws DatabaseNotConnectedException
_regressionRefined = (_regressionAll == null
? null
: _regressionAll.FindThreshold(threshold,
precision,
0,
variablePeptides.Length,
standardPeptides,
variablePeptides,
_statisticsAll,
_calculator,
_scoreCache,
isCanceled,
ref _statisticsRefined,
ref _outlierIndexes));
if (ReferenceEquals(_regressionRefined, _regressionAll))
{
return(null);
}
// Separate lists into acceptable and outliers
var listScoresRefined = new List <double>();
var listTimesRefined = new List <double>();
var listScoresOutliers = new List <double>();
var listTimesOutliers = new List <double>();
for (int i = 0; i < _scoresRefined.Length; i++)
{
if (_outlierIndexes.Contains(i))
{
listScoresOutliers.Add(_scoresRefined[i]);
listTimesOutliers.Add(_timesRefined[i]);
}
else
{
listScoresRefined.Add(_scoresRefined[i]);
listTimesRefined.Add(_timesRefined[i]);
}
}
_scoresRefined = listScoresRefined.ToArray();
_timesRefined = listTimesRefined.ToArray();
_scoresOutliers = listScoresOutliers.ToArray();
_timesOutliers = listTimesOutliers.ToArray();
return(this);
}