private static void InterpolateDimension(string name,
ISpectralAnalysisWriter writer,
List <double> xvalues,
List <double> yvalues,
List <SpectralAnchorPointMatch> anchorPoints,
Func <double, double, double> func)
{
var interpolator = new LoessInterpolator();
var pre = new List <double>();
var post = new List <double>();
var fit = interpolator.Smooth(xvalues, yvalues,
FitFunctionFactory.Create(FitFunctionTypes.TriCubic));
writer.WriteLine("");
WriteMatches(name,
writer,
xvalues,
yvalues,
fit,
interpolator,
anchorPoints,
pre,
post,
func);
WriteErrorHistogram(name, pre, post, writer);
}
private static void WriteErrorHistogram(string message, IEnumerable <double> pre, IEnumerable <double> post,
ISpectralAnalysisWriter writer)
{
writer.WriteLine("");
writer.WriteLine(message);
var preHist =
MatchCountHistogramBuilder.CreateResidualHistogram(-.5, .5, .01, pre);
var postHist =
MatchCountHistogramBuilder.CreateResidualHistogram(-.5, .5, .01, post);
writer.WriteLine("Value\t False Matches\t True Matches");
for (var index = 0; index < preHist.Bins.Count; index++)
{
var preValue = preHist.Bins[index];
writer.WriteLine(string.Format("{0}\t{1}\t{2}",
preValue,
preHist.Data[index],
postHist.Data[index]));
}
}
public static ISpectralAnalysisWriter Create(AlignmentFigureType type, string name)
{
ISpectralAnalysisWriter writer = null;
switch (type)
{
case AlignmentFigureType.Figure1:
writer = new SpectralWriterFigureOne(name, BasePath);
break;
case AlignmentFigureType.Figure2:
writer = new SpectralWriterFigureTwo(name, BasePath);
break;
case AlignmentFigureType.Figure3:
writer = new SpectralWriterFigureThree(name, BasePath);
break;
}
return(writer);
}
private static void WriteMatches(
string name,
ISpectralAnalysisWriter writer,
List <double> xvalues,
List <double> yvalues,
IList <double> fit,
LoessInterpolator interpolator,
List <SpectralAnchorPointMatch> anchorPoints,
List <double> preNet,
List <double> postNet,
Func <double, double, double> difference)
{
if (anchorPoints == null)
{
throw new ArgumentNullException("anchorPoints");
}
writer.WriteLine(string.Format(@"[{0}]", name));
writer.WriteLine("x\ty\tfit\tpre-diff\tpost-diff\tsim score\tvalid");
for (var index = 0; index < xvalues.Count; index++)
{
var x = xvalues[index];
var y = yvalues[index];
var value = interpolator.Predict(x);
var preDiff = difference(x, y);
var postDiff = difference(value, y);
writer.WriteLine(string.Format("{0}\t{1}\t{2}\t{3}\t{4}\t{5}\t{6}",
x,
y,
fit[index],
preDiff,
postDiff,
anchorPoints[index].SimilarityScore,
anchorPoints[index].IsValidMatch));
preNet.Add(preDiff);
postNet.Add(postDiff);
}
}
protected static void AlignMatches(SpectralAnalysis analysis, ISpectralAnalysisWriter writer)
{
var netXvalues = new List <double>();
var netYvalues = new List <double>();
var massXvalues = new List <double>();
var massYvalues = new List <double>();
var matches =
analysis.Matches.OrderBy(x => x.AnchorPointX.Net);
// 1. Find the best matches
// 2. Find only matches that have been made once.
var bestMatches = new Dictionary <int, SpectralAnchorPointMatch>();
foreach (var match in matches)
{
var scan = match.AnchorPointX.Scan;
if (bestMatches.ContainsKey(scan))
{
if (bestMatches[scan].SimilarityScore < match.SimilarityScore)
{
bestMatches[scan] = match;
}
}
else
{
bestMatches.Add(scan, match);
}
}
// 2. Find only those matched once
var all = new Dictionary <int, SpectralAnchorPointMatch>();
foreach (var match in bestMatches.Values)
{
var scan = match.AnchorPointY.Scan;
if (all.ContainsKey(scan))
{
if (all[scan].SimilarityScore < match.SimilarityScore)
{
all[scan] = match;
}
}
else
{
all.Add(scan, match);
}
}
// Write the analysis
writer.Write(analysis);
// Then generate the NET Alignment using R1
var anchorPoints =
all.Values.OrderBy(x => x.AnchorPointX.Net).ToList();
foreach (var match in anchorPoints)
{
netXvalues.Add(match.AnchorPointX.Net);
netYvalues.Add(match.AnchorPointY.Net);
}
Func <double, double, double> netFunc = (x, y) => x - y;
Func <double, double, double> massFunc = FeatureLight.ComputeMassPPMDifference;
InterpolateDimension("NET-R1", writer, netXvalues, netYvalues, anchorPoints, netFunc);
// Then generate the Mass Alignment using R1
// We also have to resort the matches based on mass now too
anchorPoints = all.Values.OrderBy(x => x.AnchorPointX.Mz).ToList();
foreach (var match in anchorPoints)
{
massXvalues.Add(match.AnchorPointX.Mz);
massYvalues.Add(match.AnchorPointY.Mz);
}
InterpolateDimension("Mass-R1", writer, massXvalues, massYvalues, anchorPoints, massFunc);
}
protected static void AlignMatches(SpectralAnalysis analysis, ISpectralAnalysisWriter writer)
{
var netXvalues = new List<double>();
var netYvalues = new List<double>();
var massXvalues = new List<double>();
var massYvalues = new List<double>();
var matches =
analysis.Matches.OrderBy(x => x.AnchorPointX.Net);
// 1. Find the best matches
// 2. Find only matches that have been made once.
var bestMatches = new Dictionary<int, SpectralAnchorPointMatch>();
foreach (var match in matches)
{
var scan = match.AnchorPointX.Scan;
if (bestMatches.ContainsKey(scan))
{
if (bestMatches[scan].SimilarityScore < match.SimilarityScore)
{
bestMatches[scan] = match;
}
}
else
{
bestMatches.Add(scan, match);
}
}
// 2. Find only those matched once
var all = new Dictionary<int, SpectralAnchorPointMatch>();
foreach (var match in bestMatches.Values)
{
var scan = match.AnchorPointY.Scan;
if (all.ContainsKey(scan))
{
if (all[scan].SimilarityScore < match.SimilarityScore)
{
all[scan] = match;
}
}
else
{
all.Add(scan, match);
}
}
// Write the analysis
writer.Write(analysis);
// Then generate the NET Alignment using R1
var anchorPoints =
all.Values.OrderBy(x => x.AnchorPointX.Net).ToList();
foreach (var match in anchorPoints)
{
netXvalues.Add(match.AnchorPointX.Net);
netYvalues.Add(match.AnchorPointY.Net);
}
Func<double, double, double> netFunc = (x, y) => x - y;
Func<double, double, double> massFunc = FeatureLight.ComputeMassPPMDifference;
InterpolateDimension("NET-R1", writer, netXvalues, netYvalues, anchorPoints, netFunc);
// Then generate the Mass Alignment using R1
// We also have to resort the matches based on mass now too
anchorPoints = all.Values.OrderBy(x => x.AnchorPointX.Mz).ToList();
foreach (var match in anchorPoints)
{
massXvalues.Add(match.AnchorPointX.Mz);
massYvalues.Add(match.AnchorPointY.Mz);
}
InterpolateDimension("Mass-R1", writer, massXvalues, massYvalues, anchorPoints, massFunc);
}
private static void WriteMatches(
string name,
ISpectralAnalysisWriter writer,
List<double> xvalues,
List<double> yvalues,
IList<double> fit,
LoessInterpolator interpolator,
List<SpectralAnchorPointMatch> anchorPoints,
List<double> preNet,
List<double> postNet,
Func<double, double, double> difference)
{
if (anchorPoints == null) throw new ArgumentNullException("anchorPoints");
writer.WriteLine(string.Format(@"[{0}]", name));
writer.WriteLine("x\ty\tfit\tpre-diff\tpost-diff\tsim score\tvalid");
for (var index = 0; index < xvalues.Count; index++)
{
var x = xvalues[index];
var y = yvalues[index];
var value = interpolator.Predict(x);
var preDiff = difference(x, y);
var postDiff = difference(value, y);
writer.WriteLine(string.Format("{0}\t{1}\t{2}\t{3}\t{4}\t{5}\t{6}",
x,
y,
fit[index],
preDiff,
postDiff,
anchorPoints[index].SimilarityScore,
anchorPoints[index].IsValidMatch));
preNet.Add(preDiff);
postNet.Add(postDiff);
}
}
private static void WriteErrorHistogram(string message, IEnumerable<double> pre, IEnumerable<double> post,
ISpectralAnalysisWriter writer)
{
writer.WriteLine("");
writer.WriteLine(message);
var preHist =
MatchCountHistogramBuilder.CreateResidualHistogram(-.5, .5, .01, pre);
var postHist =
MatchCountHistogramBuilder.CreateResidualHistogram(-.5, .5, .01, post);
writer.WriteLine("Value\t False Matches\t True Matches");
for (var index = 0; index < preHist.Bins.Count; index++)
{
var preValue = preHist.Bins[index];
writer.WriteLine(string.Format("{0}\t{1}\t{2}",
preValue,
preHist.Data[index],
postHist.Data[index]));
}
}
private static void InterpolateDimension(string name,
ISpectralAnalysisWriter writer,
List<double> xvalues,
List<double> yvalues,
List<SpectralAnchorPointMatch> anchorPoints,
Func<double, double, double> func)
{
var interpolator = new LoessInterpolator();
var pre = new List<double>();
var post = new List<double>();
var fit = interpolator.Smooth(xvalues, yvalues,
FitFunctionFactory.Create(FitFunctionTypes.TriCubic));
writer.WriteLine("");
WriteMatches(name,
writer,
xvalues,
yvalues,
fit,
interpolator,
anchorPoints,
pre,
post,
func);
WriteErrorHistogram(name, pre, post, writer);
}
