public void AnalyzeSample()
{
try
{
ResultSpectrum.Clear();
PlotPoints.Clear();
foreach (var peaks in Peaks.Zip(SamplePeaks, Tuple.Create))
{
var newspec = new AnalyzedSpectrum();
newspec.PeakIntensity = Math.Abs(peaks.Item2.PeakIntensity - peaks.Item1.PeakIntensity);
newspec.PeakPixel = peaks.Item1.PeakPixel;
ResultSpectrum.Add(newspec);
var _point = new DataPoint(newspec.PeakPixel, newspec.PeakIntensity);
PlotPoints.Add(_point);
}
firstAnalyze = true; //reset flag allows to make next measure
//select and add extrema to result list
double x0 = 0;
double y0 = 0;
foreach (var resspec in ResultSpectrum)
{
//1. find maximum
if (resspec.PeakIntensity > x0)
{
x0 = resspec.PeakIntensity;
y0 = x0;
}
else
{
//2. find minimum
if (resspec.PeakIntensity > y0)
{
//3. Add it to collection
var diffirence = x0 - y0;
if (diffirence > 30)
{
var s = new AnalyzedSpectrum();
s.PeakIntensity = y0;
s.PeakPixel = resspec.PeakPixel - 1;
Result.Add(s);
}
//reset variables
x0 = resspec.PeakIntensity;
y0 = x0;
}
else
{
y0 = resspec.PeakIntensity;
}
}
}
}
catch (Exception e)
{
MessageBox.Show(e.ToString());
}
}
public void ShouldCountBlocksOfA(int[] A, int expected)
{
Peaks counter = new Peaks();
int actual = counter.Count(A);
Assert.AreEqual(expected, actual);
}
public PeptideDistribution ComputeTracerAmounts(Peaks peaks, out IList <double> observedIntensities,
out IDictionary <TracerFormula, IList <double> > predictedIntensities)
{
if (peaks.GetChildCount() == 0)
{
observedIntensities = null;
predictedIntensities = null;
return(null);
}
observedIntensities = peaks.GetAverageIntensities();
var result = new PeptideDistribution(this, PeptideQuantity.tracer_count)
{
Parent = this
};
PeptideFileAnalysis.TurnoverCalculator.GetTracerAmounts(
result, peaks.GetAverageIntensitiesExcludedAsNaN(), out predictedIntensities);
if (result.ChildCount > 2)
{
double turnover;
IDictionary <TracerFormula, double> bestMatch;
result.PrecursorEnrichmentFormula = PeptideFileAnalysis.TurnoverCalculator.ComputePrecursorEnrichmentAndTurnover(result.ToDictionary(), out turnover, out bestMatch);
if (result.PrecursorEnrichmentFormula != null)
{
result.PrecursorEnrichment = result.PrecursorEnrichmentFormula.Values.Sum() / 100.0;
}
result.Turnover = turnover;
}
return(result);
}
public void test_methodName_withCertainState_shouldDoSomething(int[] given, int expected)
{
var target = new Peaks();
var actual = target.solution(given);
Assert.AreEqual(expected, actual);
}
public string ToOutputString()
{
StringBuilder sb = new StringBuilder();
sb.Append(SpectraFileName);
sb.Append('\t');
sb.Append(OneBasedScan);
sb.Append('\t');
sb.Append(RetentionTime);
sb.Append('\t');
sb.Append(MonoisotopicMass);
sb.Append('\t');
sb.Append(MonoisotopicMass);
sb.Append('\t');
sb.Append(Charge);
sb.Append('\t');
sb.Append(string.Join(",", Peaks.Select(p => p.ExperimentalMz.ToString("F4"))));
sb.Append('\t');
sb.Append(Peaks.First().ExperimentalMz.ToMass(Charge));
sb.Append('\t');
sb.Append(SignalToNoise);
sb.Append('\t');
sb.Append(DeltaScore);
sb.Append('\t');
sb.Append(Math.Log(Peaks.Sum(p => p.ExperimentalIntensity)));
sb.Append('\t');
sb.Append(TotalScanDeconvolutedIntensity);
sb.Append('\t');
sb.Append(string.Join(",", Peaks.Select(p =>
(Math.Log(p.ExperimentalIntensity, 2) - Math.Log(p.TheoreticalIntensity, 2)) +
";" +
(p.ExperimentalIntensity - this.Baseline) / this.NoiseFwhm)));
return(sb.ToString());
}
public void GetBlockNumber_Sample_3()
{
var input = new[] { 1, 2, 3, 4, 3, 4, 1, 2, 3, 4, 6, 2 };
var solver = new Peaks();
var peaksNumber = solver.GetBlockNumber(input);
peaksNumber.Should().Be(3);
}
public void GetBlockNumber_PrimeLength_1()
{
var input = new[] { 1, 2, 3, 4, 3, 4, 1, 2, 3, 4, 6 };
var solver = new Peaks();
var peaksNumber = solver.GetBlockNumber(input);
peaksNumber.Should().Be(1);
}
public void GetBlockNumber_Empty_0()
{
var input = new int[0];
var solver = new Peaks();
var peaksNumber = solver.GetBlockNumber(input);
peaksNumber.Should().Be(0);
}
public void GetBlockNumber_OneItem_0()
{
var input = new[] { 1 };
var solver = new Peaks();
var peaksNumber = solver.GetBlockNumber(input);
peaksNumber.Should().Be(0);
}
public void GetBlockNumber_AllItemsTheSame_0(int arrayLength)
{
var input = Enumerable.Repeat(1, arrayLength).ToArray();
var solver = new Peaks();
var peaksNumber = solver.GetBlockNumber(input);
peaksNumber.Should().Be(0);
}
private void CalculateIntensityErrors()
{
double sumNormalizedAbundance = Peaks.Sum(p => p.TheoreticalNormalizedAbundance);
double sumExperimentalIntensity = Peaks.Sum(p => p.ExperimentalIntensity);
foreach (var peak in Peaks)
{
double fractionOfTotalEnvelopeAbundance = peak.TheoreticalNormalizedAbundance / sumNormalizedAbundance;
double theoreticalIntensity = fractionOfTotalEnvelopeAbundance * sumExperimentalIntensity;
peak.TheoreticalIntensity = theoreticalIntensity;
}
}
public void Basic()
{
// Arrange
int[] A = new int[] { 1, 2, 3, 4, 3, 4, 1, 2, 3, 4, 6, 2 };
int expected = 3;
Peaks solution = new Peaks();
// Act
int result = solution.Solution(A);
// Assert
Assert.AreEqual(expected, result);
}
public void WithZeros()
{
// Arrange
int[] A = new int[] { 0, 0, 0, 0, 0, 0, 0 };
int expected = 0;
Peaks solution = new Peaks();
// Act
int result = solution.Solution(A);
// Assert
Assert.AreEqual(expected, result);
}
public void WithoutPeek()
{
// Arrange
int[] A = new int[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 };
int expected = 0;
Peaks solution = new Peaks();
// Act
int result = solution.Solution(A);
// Assert
Assert.AreEqual(expected, result);
}
public void WithPrimeNumber()
{
// Arrange
int[] A = new int[] { 1, 2, 3, 4, 3, 4, 1, 2, 3, 4, 6, 2, 4 };
int expected = 1;
Peaks solution = new Peaks();
// Act
int result = solution.Solution(A);
// Assert
Assert.AreEqual(expected, result);
}
public void WithSingleElement()
{
// Arrange
int[] A = new int[] { 1 };
int expected = 0;
Peaks solution = new Peaks();
// Act
int result = solution.Solution(A);
// Assert
Assert.AreEqual(expected, result);
}
public void GetBlockNumber_BigDecreaseIncrease_2()
{
int size = 55_000;
var input = Enumerable.Range(1, size).Reverse().Concat(Enumerable.Range(1, size)).ToArray();
Swap(input, 0, 1);
Swap(input, input.Length - 1, input.Length - 2);
var solver = new Peaks();
var peaksNumber = solver.GetBlockNumber(input);
peaksNumber.Should().Be(2);
}
protected bool Equals(PeptideFileAnalysisData other)
{
return(MsDataFileId == other.MsDataFileId &&
ChromatogramStartTime.Equals(other.ChromatogramStartTime) &&
ChromatogramEndTime.Equals(other.ChromatogramEndTime) &&
AutoFindPeak.Equals(other.AutoFindPeak) &&
Peaks.Equals(other.Peaks) &&
ChromatogramSetId == other.ChromatogramSetId &&
Equals(PsmTimes, other.PsmTimes) &&
Equals(ChromatogramSet, other.ChromatogramSet) &&
Equals(ValidationStatus, other.ValidationStatus) &&
Equals(Note, other.Note));
}
public override int GetHashCode()
{
unchecked
{
int hashCode = MsDataFileId.GetHashCode();
hashCode = (hashCode * 397) ^ ChromatogramStartTime.GetHashCode();
hashCode = (hashCode * 397) ^ ChromatogramEndTime.GetHashCode();
hashCode = (hashCode * 397) ^ AutoFindPeak.GetHashCode();
hashCode = (hashCode * 397) ^ Peaks.GetHashCode();
hashCode = (hashCode * 397) ^ ChromatogramSetId.GetHashCode();
hashCode = (hashCode * 397) ^ (null == PsmTimes ? 0 : PsmTimes.GetHashCode());
hashCode = (hashCode * 397) ^ (null == ChromatogramSet ? 0 : ChromatogramSet.GetHashCode());
return(hashCode);
}
}
public void Calculate(Peaks peaks)
{
IList <double> observedIntensities;
IDictionary <TracerPercentFormula, IList <double> > tracerPercentPredictedIntensities;
var precursorEnrichment = ComputePrecursorEnrichments(peaks, out observedIntensities,
out tracerPercentPredictedIntensities);
if (precursorEnrichment != null)
{
AddChild(PeptideQuantity.precursor_enrichment, precursorEnrichment);
}
IDictionary <TracerFormula, IList <double> > tracerPredictedIntensities;
var tracerCount = ComputeTracerAmounts(peaks, out observedIntensities, out tracerPredictedIntensities);
if (tracerCount != null)
{
AddChild(PeptideQuantity.tracer_count, tracerCount);
}
}
public PeptideDistribution ComputePrecursorEnrichments(
Peaks peaks, out IList <double> observedIntensities,
out IDictionary <TracerPercentFormula, IList <double> > predictedIntensities)
{
if (peaks.ChildCount == 0)
{
observedIntensities = null;
predictedIntensities = null;
return(null);
}
observedIntensities = peaks.GetAverageIntensities();
var result = new PeptideDistribution(this, PeptideQuantity.precursor_enrichment)
{
Parent = this
};
PeptideFileAnalysis.TurnoverCalculator.GetEnrichmentAmounts(result, peaks.GetAverageIntensitiesExcludedAsNaN(),
PeptideFileAnalysis.PeptideAnalysis.IntermediateLevels, out predictedIntensities);
return(result);
}
public static void GetPeaks(string[] args)
{
var fileName = args.Length < 2 ? "data/xResult" : args[1];
var epsilon = args.Length < 3 ? 50 : Int32.Parse(args[2]);
var treshold = args.Length < 4 ? 300 : Int32.Parse(args[3]);
string[] lines = File.ReadAllLines(String.Format("{0}.txt", fileName));
var data = lines.Aggregate(new List <int>(), (p, c) =>
{
var value = Int32.Parse(c.Split(' ')[1]);
p.Add(value);
return(p);
}).ToArray();
var peaksFile = String.Format("{0}_peaks", fileName);
Peaks.GetPeaks(peaksFile, data, epsilon, treshold);
return;
}
//fucntion generates random peaks, based off of values set in the game manager
public void RandomlyCreatePeaks()
{
Random.InitState(GM_.Instance.config.seed);
int amount_of_peaks = Random.Range((int)GM_.Instance.config.random_peaks_values.peaks_amount.x, (int)GM_.Instance.config.random_peaks_values.peaks_amount.y); //determine amount of peaks
peaks.Clear(); //clear any already potential peaks
for (int i = 0; i < amount_of_peaks; i++) //loop for maoutn of peaks
{
//create new peak with random radius and position based on user defined vlaues
Peaks new_peak = new Peaks();
new_peak.radius = Random.Range(GM_.Instance.config.random_peaks_values.radius_size_range.x, GM_.Instance.config.random_peaks_values.radius_size_range.y);
float x_pos, y_pos;
x_pos = Random.Range(-GM_.Instance.config.city_limits_x, GM_.Instance.config.city_limits_x);
y_pos = Random.Range(-GM_.Instance.config.city_limits_z, GM_.Instance.config.city_limits_z);
new_peak.centre_position = new Vector2(x_pos, y_pos);
peaks.Add(new_peak); //save the peak
}
}
static void Main(string[] args)
{
/*IEnumerable<string> lines = File.ReadAllLines("order-details.csv");
* var query =
* from line in lines
* let row = line.Split(",")
* let fourthColumn = row[3]
* select int.Parse(fourthColumn);
* Console.WriteLine(query.Sum());
* var max = query.Max();
* Console.WriteLine(max);
*
* //scriviamo in un file
* File.WriteAllText("max.text", max.ToString());*/
for (int i = 0; i < args.Length; i++)
{
Console.WriteLine(args[i].ToUpper());
}
// var firstCustomer = new Customer();
Customer firstCustomer = new Customer("Francesco", "Bacci", "*****@*****.**");
firstCustomer.Login();
Customer secondCustomer = new Customer("Mario", "Rossi", "*****@*****.**");
secondCustomer.Login();
Customer.SaySomething();
//class Article
Article article = new Article("Face mask", 12.44);
article.List();
article.Retrieve(0);
article.Destroy(0);
Console.WriteLine(article.Description); // GET
article.Description = "Notebook"; // SET
Console.WriteLine($"{article.Description} price is : {article.Price}");
// class OrderHeader
OrderHeader orderHeader = new OrderHeader(20, DateTime.Now);
orderHeader.List();
orderHeader.Retrieve(0);
orderHeader.Destroy(0);
Console.WriteLine($"Date: {orderHeader.Date}, UserID: {orderHeader.UserId}");
//mountain #8
Peaks.FirstColumn(";", "Monte Falco, 1658, Parco Foreste Casentinesi ; Monte Falterona, 1654, Parco Foreste Casentinesi; Monte Fumaiolo, 1407, Appennino Tosco Emiliano");
/* Console.WriteLine(args[0]);
* Console.WriteLine(args[1]);
* Console.WriteLine("Enter your name:");
* string tuoNome = Console.ReadLine();
* Console.WriteLine($"Il tuo nome è {tuoNome.ToUpper()}!"); */
/* public static void Main(string[] args){
*
* var prices = new List<Article>{};
*
* Article article1 = new Article(45.56, "felpa");
* Article article2 = new Article(52.55, "jeans");
*
* prices.Add(article1);
* prices.Add(article2);
*
* Console.WriteLine(prices[1].Description);
*
* var total = prices.Aggregate(0.00, (acc , val) => acc + val.Price);
* Console.WriteLine(total);
* }
*
* class Article
* {
* public double Price {get;} = 52.12;
* public string Description = "Description example";
*
* public Article(double price, string description)
* {
* this.Price = price;
* this.Description = description;
* }*/
// issue 8 millestone 1------------------------------------------------------------------------
// we can create new customers
// Create a new users or a list of users.....
// Create a new users or a list of users.....
Customer User1 = new Customer("user1", "surname1", "*****@*****.**"); // Create a new customers;
Customer User2 = new Customer("user2", "surname2", "*****@*****.**");
Customers insert = new Customers(); // Create a new List of customers
insert.AddCustomer(User1);
insert.AddCustomer(User2); //With this method we can add users in a list of users
//Now we can create a new Article and add to a list of articles
Article scarpe = new Article("scarpe blu", 55.2); // Article take description, stock and price as arguments
Article felpa = new Article("felpa bianca", 88.1);
Article maglia = new Article("maglia nera", 24.9);
Articles CreateList = new Articles(); //Set an istance to create a list of article
CreateList.addToListOfArticles(scarpe);
CreateList.addToListOfArticles(felpa); //Add article to articles
CreateList.addToListOfArticles(maglia);
CreateList.List(); //Add a method to diplay all articles add
//millestone 2------------------------------
//we can search for an article by its description, and we can print its price
//we can add the searched article to the Cart
Console.WriteLine(CreateList.search("felpa binca").Price); //search an article and print his price
//Add article
var myarticle = CreateList.search("felpa bianca");
Cart Cart = new Cart(myarticle, User1, 20);
// Milestone 3 -----------------------------
//We can add multiple article to the cart
Cart newCart1 = new Cart(scarpe, User1, 10);
Cart newCart2 = new Cart(maglia, User2, 20); //Create a new istance of a cart
newCart1.addMultiplyArticle(scarpe); //Add multiply article to cart
newCart1.addMultiplyArticle(maglia);
newCart1.Total(); //Calculate the total from the cart1
}
/// <summary>
/// run clustering, Rescue PSMs, update idpDB
/// </summary>
private void RescuePSMsByClustering()
{
DateTime startTime = DateTime.Now;
reportProgressDelegate reportProgress = new reportProgressDelegate(setProgress);
reportStatusDelegate reportStatus = new reportStatusDelegate(setStatus);
string database = session.Connection.GetDataSource();
logFile = Path.ChangeExtension(database, ".log.txt");
string config = string.Format("Parameters:\r\n" +
"PrecursorMZTol: {0} \r\n" +
"FragmentMZTol: {1} \r\n" +
"Similarity Threshold >= {2} \r\n" +
"Rank <= {3} \r\n" +
"Cluster Size >= {4} \r\n" +
"Search Scores: {5}{6}{7};{8}{9}{10};{11}{12}{13} \r\n\r\n",
precursorMzTolerance,
fragmentMzTolerance,
similarityThreshold,
maxRank,
minClusterSize,
searchScore1Name, searchScore1Order, searchScore1Threshold,
searchScore2Name, searchScore2Order, searchScore2Threshold,
searchScore3Name, searchScore3Order, searchScore3Threshold);
reportStatus(config);
//if (writeLog)
// File.WriteAllText(logFile, config);
/*
* back up original idpDB
*/
if (backupDB)
{
string dbBackupFile = Path.ChangeExtension(database, ".backup.idpDB");
reportStatus(string.Format("Backing up idpDB to {0} ... ", dbBackupFile));
reportProgress(-1, "Backing up idpDB");
File.Copy(database, dbBackupFile, true);
reportStatus(reportSecondsElapsed((DateTime.Now - startTime).TotalSeconds));
}
//reportStatus("Dropping filters... \r\n");
// basicDataFilter.DropFilters(session); //// this will drop all filtered tables and rename unfiltered tables
//basicDataFilter.ApplyBasicFilters(session);
reportStatus("Querying spectra...");
reportProgress(-1, "Querying spectra...");
IList<object[]> queryRows;
lock (session)
//// SQL query to retrieve spectrum info for unfiltered psm, filter query results by rank1 search score
// queryRows = session.CreateSQLQuery(@"SELECT s.Id, source.Name, NativeID, PrecursorMZ
// FROM Spectrum s
// JOIN SpectrumSource source ON s.Source = source.Id
// JOIN UnfilteredPeptideSpectrumMatch psm ON s.Id = psm.Spectrum AND psm.Rank = 1
// JOIN PeptideSpectrumMatchScore psmScore ON psm.Id = psmScore.PsmId
// JOIN PeptideSpectrumMatchScoreName scoreName ON psmScore.ScoreNameId=scoreName.Id
// WHERE (scoreName.Name = " + "'" + searchScore1Name + "'" + " AND psmScore.Value " + searchScore1Order + searchScore1Threshold.ToString() + ") OR (scoreName.Name = " + "'" + searchScore2Name + "'" + " AND psmScore.Value " + searchScore2Order + searchScore2Threshold.ToString() + ") OR (scoreName.Name = " + "'" + searchScore3Name + "'" + " AND psmScore.Value " + searchScore3Order + searchScore3Threshold.ToString() + ")" +
// " GROUP BY s.Id"
// ).List<object[]>();
//// SQL query to retrieve spectrum info for unfiltered psm that map to identified peptide, filter by search score
queryRows = session.CreateSQLQuery(@"SELECT s.Id, source.Name, NativeID, PrecursorMZ
FROM UnfilteredSpectrum s
JOIN SpectrumSource source ON s.Source = source.Id
JOIN UnfilteredPeptideSpectrumMatch psm ON s.Id = psm.Spectrum
JOIN Peptide p ON p.Id = psm.Peptide
JOIN PeptideSpectrumMatchScore psmScore ON psm.Id = psmScore.PsmId
JOIN PeptideSpectrumMatchScoreName scoreName ON psmScore.ScoreNameId=scoreName.Id
WHERE (scoreName.Name = " + "'" + searchScore1Name + "'" + " AND psmScore.Value " + searchScore1Order + searchScore1Threshold.ToString() + ") OR (scoreName.Name = " + "'" + searchScore2Name + "'" + " AND psmScore.Value " + searchScore2Order + searchScore2Threshold.ToString() + ") OR (scoreName.Name = " + "'" + searchScore3Name + "'" + " AND psmScore.Value " + searchScore3Order + searchScore3Threshold.ToString() + ")" +
" GROUP BY s.Id"
).List<object[]>();
var foundSpectraList = session.CreateSQLQuery(@"SELECT distinct spectrum FROM PeptideSpectrumMatch").List<object>();
var foundSpectra = new HashSet<long>();
{
long tempLong;
foreach (var item in foundSpectraList)
if (long.TryParse(item.ToString(), out tempLong))
foundSpectra.Add(tempLong);
}
var spectrumRows = queryRows.Select(o => new SpectrumRow(o)).OrderBy(o => o.SourceName).ToList();
////converted IOrderedEnumerable to List, the former one may end up with multiple enumeration, each invokes constructor, resulting a fresh set of object
/*
* extract peaks for each spectrum, spectrumRows was sorted by SourceName
*/
string currentSourceName = null;
string currentSourcePath = null;
msdata.MSData msd = null;
int spectrumRowsCount = spectrumRows.Count();
//Set<long> processedSpectrumIDs = new Set<long>();
reportStatus(reportSecondsElapsed((DateTime.Now - startTime).TotalSeconds));
reportStatus(string.Format("Extracting peaks for {0} spectra ... ", spectrumRowsCount));
lock (owner)
for (int i = 0; i < spectrumRowsCount; ++i)
{
if (_bgWorkerClustering.CancellationPending)
{
_bgWorkerCancelled = true;
return;
}
var row = spectrumRows.ElementAt(i);
reportProgress((int)(((double)(i + 1) / (double)spectrumRowsCount) * 100), string.Format("Extracting peaks ({0}/{1}) from {2}", i + 1, spectrumRowsCount, row.SourceName));
//if (processedSpectrumIDs.Contains(row.SpectrumId))
// break;
if (row.SourceName != currentSourceName)
{
currentSourceName = row.SourceName;
currentSourcePath = IDPickerForm.LocateSpectrumSource(currentSourceName, session.Connection.GetDataSource());
if (msd != null)
msd.Dispose();
msd = new pwiz.CLI.msdata.MSDataFile(currentSourcePath);
SpectrumListFactory.wrap(msd, "threshold count 100 most-intense"); //only keep the top 100 peaks
//SpectrumListFactory.wrap(msd, "threshold bpi-relative .5 most-intense"); //keep all peaks that are at least 50% of the intensity of the base peak
//SpectrumListFactory.wrap(msd, "threshold tic-cutoff .95 most-intense"); //keep all peaks that count for 95% TIC
//threshold <count|count-after-ties|absolute|bpi-relative|tic-relative|tic-cutoff> <threshold> <most-intense|least-intense> [int_set(MS levels)]
}
var spectrumList = msd.run.spectrumList;
var pwizSpectrum = spectrumList.spectrum(spectrumList.find(row.SpectrumNativeID), true); //may create indexoutofrange error if no spectrum nativeID
row.OriginalMZs = pwizSpectrum.getMZArray().data; //getMZArray().data returns IList<double>
row.OriginalIntensities = pwizSpectrum.getIntensityArray().data;
//processedSpectrumIDs.Add(row.SpectrumId);
}
/*
* re-sort spectrumRows by precursorMZ
* walk through each spectrum. compare similarity to all other spectra within the precursorMZTolerance
* (e.g. compare 1 to 2,3,4, then 2 to 3,4,5, then 3 to 4,5 etc),
* if above similarityThreshold, add link edge to BOTH spectra
* merge all connected spectra to a cluster
*/
reportStatus(reportSecondsElapsed((DateTime.Now - startTime).TotalSeconds));
reportStatus("Computing similarities... ");
var spectrumRowsOrderByPrecursorMZ = (from randomVar in spectrumRows orderby randomVar.PrecursorMZ select randomVar).ToList();
LinkMap linkMap = new LinkMap(); //// spectrum Id as key, directly linked spectra as value
double similarityScore = 0;
lock (owner)
for (int i = 0; i < spectrumRowsCount; ++i)
{
if (_bgWorkerClustering.CancellationPending)
{
_bgWorkerCancelled = true;
return;
}
var row = spectrumRowsOrderByPrecursorMZ.ElementAt(i);
reportProgress((int)(((double)(i + 1) / (double)spectrumRowsCount) * 100), "Computing similarities");
for (int j = i + 1; j < spectrumRowsCount; ++j)
{
var nextRow = spectrumRowsOrderByPrecursorMZ.ElementAt(j);
if (Math.Abs(row.PrecursorMZ - nextRow.PrecursorMZ) > precursorMzTolerance)
{
break;
}
else
{
////compare pairwise similarity, link spectra passing threshold to both spectrum
Peaks rowPeakList = new Peaks(row.OriginalMZs, row.OriginalIntensities);
Peaks nextRowPeakList = new Peaks(nextRow.OriginalMZs, nextRow.OriginalIntensities);
//// converting peak intensities to sqrt here is 5-fold slower than doing this in DotProductCompareTo function
//Peaks rowPeakList = new Peaks(row.OriginalMZs, row.OriginalIntensities.Select(o => Math.Sqrt(o)).ToList());
//Peaks nextRowPeakList = new Peaks(nextRow.OriginalMZs, nextRow.OriginalIntensities.Select(o => Math.Sqrt(o)).ToList());
similarityScore = ClusteringAnalysis.DotProductCompareTo(rowPeakList, nextRowPeakList, fragmentMzTolerance);
//reportStatus("similarity between " + row.SpectrumNativeID + " and " + nextRow.SpectrumNativeID + " is " + similarityScore.ToString() + "\r\n");
if (similarityScore >= similarityThreshold)
{
linkMap[(long)row.SpectrumId].Add((long)nextRow.SpectrumId);
linkMap[(long)nextRow.SpectrumId].Add((long)row.SpectrumId); //// if a -> b, then b -> a
}
}
}
}
reportStatus(reportSecondsElapsed((DateTime.Now - startTime).TotalSeconds));
reportStatus("Clustering spectra... ");
reportProgress(-1, "Clustering spectra");
linkMap.GetMergedLinkList();
reportStatus(reportSecondsElapsed((DateTime.Now - startTime).TotalSeconds));
//// print clustered spectra
//foreach (var cluster in linkMap.MergedLinkList)
//{
// reportStatus("Number of spectra in cluster: " + cluster.Count().ToString() + "\r\n");
// foreach (var sID in cluster)
// {
// var nativeID = (from o in spectrumRows where o.SpectrumId == sID select o.SpectrumNativeID).First();
// reportStatus(nativeID.ToString() + "\t");
// }
// reportStatus("\r\n");
//}
////free some memory
queryRows.Clear();
queryRows = null;
msd.Dispose();
msd = null;
spectrumRows.Clear();
spectrumRows = null;
spectrumRowsOrderByPrecursorMZ.Clear();
spectrumRowsOrderByPrecursorMZ = null;
/*
* Go through each cluster, rescue PSMs if spectra in the same cluster were identified as the same peptide (id)
*/
List<Set<long>> clusterSetList = (from o in linkMap.MergedLinkList where o.Count >= minClusterSize select o).ToList(); //// each element in the list is a set of clustered spectrum Ids, select sets with at least minClusterSize element
int clusterSetListCount = clusterSetList.Count();
var allSpectrumIDs = (from o in clusterSetList from j in o select j).ToList();
reportStatus(string.Format("Number of clusters: {0} \r\n", clusterSetListCount));
reportStatus(string.Format("Number of spectra clustered: {0}/{1} ({2:0.0%}) \r\n", allSpectrumIDs.Count, spectrumRowsCount, (double)allSpectrumIDs.Count / spectrumRowsCount));
IList<object> identPSMQueryRows;
lock (session)
identPSMQueryRows = session.CreateSQLQuery(@"SELECT psm.Id FROM PeptideSpectrumMatch psm").List<object>();
var identPSMIdSet = new Set<long>(identPSMQueryRows.Select(o => (long)o));
reportStatus(string.Format("Number of PSMs identified: {0} \r\n", identPSMIdSet.Count));
//// create a temp table to store clustered spectrum IDs
session.CreateSQLQuery(@"DROP TABLE IF EXISTS TempSpecIds;
CREATE TEMP TABLE TempSpecIds (Id INTEGER PRIMARY KEY)
").ExecuteUpdate();
var insertTempSpecIdscmd = session.Connection.CreateCommand();
insertTempSpecIdscmd.CommandText = "INSERT INTO TempSpecIds VALUES (?)";
var insertTempSpecIdsParameters = new List<System.Data.IDbDataParameter>();
for (int i = 0; i < 1; ++i)
{
insertTempSpecIdsParameters.Add(insertTempSpecIdscmd.CreateParameter());
insertTempSpecIdscmd.Parameters.Add(insertTempSpecIdsParameters[i]);
}
insertTempSpecIdscmd.Prepare();
foreach (var id in allSpectrumIDs)
{
insertTempSpecIdsParameters[0].Value = id;
insertTempSpecIdscmd.ExecuteNonQuery();
}
IList<object> allPsmIdQueryRows;
lock (session)
//// SQL query to retrieve all psm id for clustered spectra with score above a threshold
allPsmIdQueryRows = session.CreateSQLQuery(@"SELECT GROUP_CONCAT(psm.Id)
FROM TempSpecIds
JOIN UnfilteredPeptideSpectrumMatch psm ON TempSpecIds.Id = psm.Spectrum
JOIN PeptideSpectrumMatchScore psmScore ON psm.Id = psmScore.PsmId
JOIN PeptideSpectrumMatchScoreName scoreName ON psmScore.ScoreNameId=scoreName.Id
WHERE psm.Rank <= " + maxRank.ToString() + " AND ((scoreName.Name = " + "'" + searchScore1Name + "'" + " AND psmScore.Value " + searchScore1Order + searchScore1Threshold.ToString() + ") OR (scoreName.Name = " + "'" + searchScore2Name + "'" + " AND psmScore.Value " + searchScore2Order + searchScore2Threshold.ToString() + ") OR (scoreName.Name = " + "'" + searchScore3Name + "'" + " AND psmScore.Value " + searchScore3Order + searchScore3Threshold.ToString() + "))" +
" GROUP BY TempSpecIds.Id, psm.Charge"
).List<object>();
var allPsmIdsRows = allPsmIdQueryRows.Select(o => new PsmIdRow(o)).ToList();
Set<long> allPsmIds = new Set<long>();
foreach (var row in allPsmIdsRows)
{
allPsmIds.Union(row.PsmIds);
}
session.CreateSQLQuery(@"DROP TABLE IF EXISTS TempSpecIds").ExecuteUpdate();
reportStatus("Querying PSMs...");
reportProgress(-1, "Querying PSMs");
IList<object[]> allClusterQueryRows;
//// create a temp table to store psm IDs
session.CreateSQLQuery(@"DROP TABLE IF EXISTS TempPsmIds;
CREATE TEMP TABLE TempPsmIds (Id INTEGER PRIMARY KEY)
").ExecuteUpdate();
var cmd = session.Connection.CreateCommand();
cmd.CommandText = "INSERT INTO TempPsmIds VALUES (?)";
var parameters = new List<System.Data.IDbDataParameter>();
for (int i = 0; i < 1; ++i)
{
parameters.Add(cmd.CreateParameter());
cmd.Parameters.Add(parameters[i]);
}
cmd.Prepare();
foreach (var id in allPsmIds)
{
parameters[0].Value = id;
cmd.ExecuteNonQuery();
}
//// qurey string for revison 286, no DecoySequence in Peptide table
// string queryCmd = @"SELECT psm.Id as psmId, s.Id, source.Name, s.NativeID, psm.Rank, psm.Charge, psmScore.Value, IFNULL(GROUP_CONCAT(DISTINCT pm.Offset || ':' || mod.MonoMassDelta),''),
// (SELECT SUBSTR(pro.Sequence, pi.Offset+1, pi.Length)
// FROM PeptideInstance pi
// JOIN ProteinData pro ON pi.Protein=pro.Id
// WHERE pi.Protein=pro.Id AND
// pi.Id=(SELECT MIN(pi2.Id)
// FROM PeptideInstance pi2
// WHERE psm.Peptide=pi2.Peptide))
// FROM TempIDs tempIDs
// JOIN Spectrum s ON s.Id = tempIDs.Id
// JOIN SpectrumSource source ON s.Source = source.Id
// JOIN PeptideSpectrumMatch psm ON s.Id = psm.Spectrum
// LEFT JOIN PeptideModification pm ON psm.Id = pm.PeptideSpectrumMatch
// LEFT JOIN Modification mod ON pm.Modification = mod.Id
// JOIN PeptideSpectrumMatchScore psmScore ON psm.Id = psmScore.PsmId
// JOIN PeptideSpectrumMatchScoreName scoreName ON psmScore.ScoreNameId=scoreName.Id
// WHERE scoreName.Name = " + "'" + searchScoreName + "'" + " AND psm.Rank <= 5" +
// " GROUP BY psm.Id";
//AND s.Id IN ( " + String.Join(",", allSpectrumIDs.Select(o => o.ToString()).ToArray()) + " ) " +
//// query string for revison 288, added DecoySequence in Peptide table
// string queryCmd = @"SELECT psm.Id as psmId, s.Id, source.Name, s.NativeID, psm.Rank, psm.Charge, psmScore.Value, IFNULL(GROUP_CONCAT(DISTINCT pm.Offset || ':' || mod.MonoMassDelta),''),
// (SELECT IFNULL(SUBSTR(pro.Sequence, pi.Offset+1, pi.Length), (SELECT DecoySequence FROM Peptide p WHERE p.Id = pi.Peptide))
// FROM PeptideInstance pi
// LEFT JOIN ProteinData pro ON pi.Protein=pro.Id
// WHERE pi.Id=(SELECT pi2.Id FROM PeptideInstance pi2 WHERE pi2.Peptide=psm.Peptide LIMIT 1))
// FROM TempIDs tempIDs
// JOIN Spectrum s ON s.Id = tempIDs.Id
// JOIN SpectrumSource source ON s.Source = source.Id
// JOIN PeptideSpectrumMatch psm ON s.Id = psm.Spectrum
// LEFT JOIN PeptideModification pm ON psm.Id = pm.PeptideSpectrumMatch
// LEFT JOIN Modification mod ON pm.Modification = mod.Id
// JOIN PeptideSpectrumMatchScore psmScore ON psm.Id = psmScore.PsmId
// JOIN PeptideSpectrumMatchScoreName scoreName ON psmScore.ScoreNameId=scoreName.Id
// WHERE scoreName.Name = " + "'" + searchScoreName + "'" + " AND psm.Rank <= 5" +
// " GROUP BY psm.Id";
////query string for revision 291, retrive by PSM Ids
// string queryCmd = @"SELECT psm.Id as psmId, psm.Peptide,s.Id, source.Name, s.NativeID, psm.Charge, IFNULL(GROUP_CONCAT(DISTINCT pm.Offset || ':' || mod.MonoMassDelta),''),
// (SELECT IFNULL(SUBSTR(pd.Sequence, pi.Offset+1, pi.Length), (SELECT DecoySequence FROM UnfilteredPeptide p WHERE p.Id = pi.Peptide))),
// GROUP_CONCAT(pro.Accession),psm.QValue, psm.Rank, psmScore.Value, analysis.Id
// FROM TempPsmIds tempPsmIds
// JOIN UnfilteredPeptideSpectrumMatch psm ON psm.Id = tempPsmIds.Id
// JOIN Analysis analysis ON psm.Analysis = analysis.Id
// JOIN Spectrum s ON s.Id = psm.Spectrum
// JOIN SpectrumSource source ON s.Source = source.Id
// JOIN UnfilteredPeptideInstance pi ON psm.Peptide = pi.Peptide
// JOIN UnfilteredProtein pro ON pi.Protein = pro.Id
// LEFT JOIN ProteinData pd ON pi.Protein=pd.Id
// LEFT JOIN PeptideModification pm ON psm.Id = pm.PeptideSpectrumMatch
// LEFT JOIN Modification mod ON pm.Modification = mod.Id
// LEFT JOIN PeptideSpectrumMatchScore psmScore ON psm.Id = psmScore.PsmId
// LEFT JOIN PeptideSpectrumMatchScoreName scoreName ON psmScore.ScoreNameId=scoreName.Id
// WHERE scoreName.Name = " + "'" + searchScore1Name + "'" +
// " GROUP BY psm.Id";
// query for r291, fix no seq for some peptides shared by target and decoy proteins, query seq for target and decoy proteins separately then union
string queryCmd = @"SELECT psm.Id as psmId, psm.Peptide,s.Id, source.Name, s.NativeID, psm.Charge,
IFNULL(GROUP_CONCAT(DISTINCT pm.Offset || ':' || mod.MonoMassDelta),''),
IFNULL(IFNULL(SUBSTR(pd.Sequence, pi.Offset+1, pi.Length),(SELECT DecoySequence FROM UnfilteredPeptide p WHERE p.Id = pi.Peptide)),
(SELECT SUBSTR(pd.Sequence, pi.Offset+1, pi.Length)
FROM UnfilteredPeptideInstance pi
JOIN UnfilteredProtein pro ON pi.Protein = pro.Id AND pro.IsDecoy = 0
LEFT JOIN ProteinData pd ON pi.Protein=pd.Id
WHERE psm.Peptide = pi.Peptide
UNION
SELECT p.DecoySequence
FROM UnfilteredPeptide p
JOIN UnfilteredPeptideInstance pi ON p.Id = pi.Peptide
JOIN UnfilteredProtein pro ON pi.Protein = pro.Id AND pro.IsDecoy = 1
WHERE psm.Peptide = pi.Peptide AND p.DecoySequence is not null)),
GROUP_CONCAT(pro.Accession),
psm.QValue, psm.Rank, psmScore.Value, psm.Analysis
FROM TempPsmIds tempPsmIds
JOIN UnfilteredPeptideSpectrumMatch psm ON psm.Id = tempPsmIds.Id
JOIN UnfilteredSpectrum s ON s.Id = psm.Spectrum
JOIN SpectrumSource source ON s.Source = source.Id
JOIN UnfilteredPeptideInstance pi ON psm.Peptide = pi.Peptide
JOIN UnfilteredProtein pro ON pi.Protein = pro.Id
LEFT JOIN ProteinData pd ON pi.Protein=pd.Id
LEFT JOIN PeptideModification pm ON psm.Id = pm.PeptideSpectrumMatch
LEFT JOIN Modification mod ON pm.Modification = mod.Id
LEFT JOIN PeptideSpectrumMatchScore psmScore ON psm.Id = psmScore.PsmId
LEFT JOIN PeptideSpectrumMatchScoreName scoreName ON psmScore.ScoreNameId=scoreName.Id
WHERE scoreName.Name in ( " + "'" + searchScore1Name + "','" + searchScore2Name + "','" + searchScore3Name + "')" +
" GROUP BY psm.Id";
lock (session)
allClusterQueryRows = session.CreateSQLQuery(queryCmd).List<object[]>();
var allClusterSpectrumRows = allClusterQueryRows.Select(o => new ClusterSpectrumRow(o)).ToList();
session.CreateSQLQuery(@"DROP TABLE IF EXISTS TempPsmIds").ExecuteUpdate();
reportStatus(reportSecondsElapsed((DateTime.Now - startTime).TotalSeconds));
reportStatus(string.Format("Number of PSMs retrieved: {0} \r\n", allClusterSpectrumRows.Count));
reportStatus("Rescuing PSMs... ");
if (writeLog)
{
string logHeader = string.Join("\t", new string[] { "SourceName", "NativeID", "Charge", "RescuedSequence", "Protein", "ScoreName", "SearchScore", "BAScore", "QValue", "Rank", "Rank1Sequence", "Rank1Protein", "Rank1SearchScore", "Rank1BAScore", "Rank1Qvalue", "\r\n" });
File.WriteAllText(logFile, logHeader);
}
Dictionary<long, UpdateValues> updateDict = new Dictionary<long, UpdateValues>(); ////key: Id in unfiltered psm table, value: reassigned Qvalue and reassinged Rank
Set<long> rescuedDistinctSpectraIds = new Set<long>();
//// SQL query to retrieve anlaysis Id and search score order in QonvertSettings table
IList<object[]> qonvertSettingsQueryRows;
lock (session)
qonvertSettingsQueryRows = session.CreateSQLQuery("SELECT Id, ScoreInfoByName FROM QonverterSettings").List<object[]>();
var qonvertSettingRows = qonvertSettingsQueryRows.Select(o => new qonvertSettingRows(o)).ToList();
Dictionary<long, string> analysisScoreOrder = new Dictionary<long, string>();
Dictionary<long, string> analysisScoreName = new Dictionary<long, string>();
foreach (var qonvertSettingRow in qonvertSettingRows)
{
analysisScoreOrder.Add(qonvertSettingRow.Id, qonvertSettingRow.ScoreOrder);
analysisScoreName.Add(qonvertSettingRow.Id, qonvertSettingRow.ScoreName);
}
////walk through each cluster to rescue PSMs
for (int i = 0; i < clusterSetListCount; ++i)
{
var clusterSet = clusterSetList.ElementAt(i);
if (_bgWorkerClustering.CancellationPending)
{
_bgWorkerCancelled = true;
return;
}
//reportStatus("Clustering set: " + String.Join(",",clusterSet.Select(j => j.ToString()).ToArray()) + "\r\n");
reportProgress((int)(((double)(i + 1) / (double)clusterSetListCount) * 100), "Rescuing PSMs");
var clusterSpectrumRows = (from o in allClusterSpectrumRows where clusterSet.Contains(o.SpectrumId) select o).ToList();
//Map<long, Set<long>> peptideIdDict = new Map<long, Set<long>>(); //key: peptide id, value: psm ids
//Set<long> unprocessedPSMIds = new Set<long>();
Set<string> unprocessedSpecChargeAnalysisSet = new Set<string>(); //spectrumId.charge.analysis
var pepSeqDict = new PepDictionary(); //key: modified peptide sequence, value: spectrumId.charge.analysis, score
//var peptideIdDict = new PepDictionary(); //key: peptide ID, value: PSM Ids and scores
foreach (var row in clusterSpectrumRows)
{
//peptideIdDict.Add(row.PeptideId,row.PSMId, row.SearchScore);
//peptideIdDict[row.PeptideId].Add(row.PSMId);
pepSeqDict.Add(row.ModifiedSequence, row.SpectrumId, row.Charge, row.Analysis, row.SearchScore, row.PSMId);
//unprocessedPSMIds.Add(row.PSMId);
//unprocessedSpectrumCharge.Add(row.SpectrumId.ToString() + "." + row.Charge.ToString());
unprocessedSpecChargeAnalysisSet.Add(row.SpectrumId.ToString() + "." + row.Charge.ToString() + "." + row.Analysis.ToString());
}
pepSeqDict.ComputeBayesianAverage(analysisScoreOrder); //replace score from sum of search scores to Bayesian Average
var sortedPepSeqDictKeys = from k in pepSeqDict.Keys orderby pepSeqDict[k].FinalScore descending, pepSeqDict[k].PsmIdSpecDict.Count() descending select k; // sort by score, if tied, second sort by # of linked psms
foreach (var pepSeq in sortedPepSeqDictKeys)
{
if (unprocessedSpecChargeAnalysisSet.Count == 0)
break;
if (pepSeqDict[pepSeq].PsmIdSpecDict.Keys.Any(pId => identPSMIdSet.Contains(pId))) ////at least one psm identified as this peptide in this cluster
{
foreach (var psmId in pepSeqDict[pepSeq].PsmIdSpecDict.Keys)
{
var row = (from o in clusterSpectrumRows where o.PSMId == psmId select o).First();
string spec = row.SpectrumId.ToString() + "." + row.Charge.ToString() + "." + row.Analysis.ToString();
if (unprocessedSpecChargeAnalysisSet.Contains(spec))
{
if (identPSMIdSet.Contains(psmId) || foundSpectra.Contains(row.SpectrumId))
{
//// not process ident PSMs
unprocessedSpecChargeAnalysisSet.Remove(spec);
}
else
{
updateDict.Add(psmId, new UpdateValues(-1, 1)); //// update Qvalue = -1, Rank =1
++rescuedPSMsCount;
rescuedDistinctSpectraIds.Add(row.SpectrumId);
unprocessedSpecChargeAnalysisSet.Remove(spec);
if (writeLog)
{
string originalRank1Seq = "";
string originalRank1Protein = "";
string originalRank1Score = "";
string originalRank1BAScore = "";
string originalRank1Qvalue = "";
if (row.Rank != 1)
{
var originalRank1Rows = (from o in clusterSpectrumRows where o.SpectrumId == row.SpectrumId && o.Rank == 1 && o.Charge == row.Charge && o.Analysis == row.Analysis select new { o.ModifiedSequence, o.Protein, o.SearchScore, o.QValue }).ToList(); ////may exist more than one rank1 hits
foreach (var originalRank1Row in originalRank1Rows)
{
originalRank1Seq += originalRank1Row.ModifiedSequence + ";";
originalRank1Protein += originalRank1Row.Protein + ";";
originalRank1Score += originalRank1Row.SearchScore.ToString("0.0000") + ";";
originalRank1BAScore += pepSeqDict.ContainsKey(originalRank1Row.ModifiedSequence) ? pepSeqDict[originalRank1Row.ModifiedSequence].FinalScore.ToString("0.0000") + ";" : "";
originalRank1Qvalue += originalRank1Row.QValue.ToString("0.0000") + ";";
}
}
string logLine = string.Join("\t", new string[] { row.SourceName, row.SpectrumNativeID, row.Charge.ToString(), row.ModifiedSequence, row.Protein, analysisScoreName[row.Analysis], row.SearchScore.ToString("0.0000"), pepSeqDict[pepSeq].FinalScore.ToString("0.0000"), row.QValue.ToString("0.0000"), row.Rank.ToString(), originalRank1Seq, originalRank1Protein, originalRank1Score, originalRank1BAScore, originalRank1Qvalue });
using (StreamWriter sw = File.AppendText(logFile))
{
sw.WriteLine(logLine);
}
}
}
}
}
}
} //// end of foreach (var pepSeq in sortedPepSeqDictKeys)
} //// end of for (int i = 0; i < clusterSetListCount; ++i)
reportStatus(string.Format("{0} seconds elapsed\r\n", (DateTime.Now - startTime).TotalSeconds));
/*
*update unfiltered psm table in idpDB
*/
if (rescuedPSMsCount == 0)
return;
reportStatus("Updating idpDB... ");
session.Transaction.Begin();
//basicDataFilter.DropFilters(session); // tables were dropped before querying
var updateCmd = session.Connection.CreateCommand();
updateCmd.CommandText = "UPDATE UnfilteredPeptideSpectrumMatch SET QValue = ?, Rank = ? WHERE Id = ?";
var updateParameters = new List<System.Data.IDbDataParameter>();
for (int i = 0; i < 3; ++i)
{
updateParameters.Add(updateCmd.CreateParameter());
updateCmd.Parameters.Add(updateParameters[i]);
}
updateCmd.Prepare();
int updateCount = 0;
int allUpdateCount = updateDict.Count;
foreach (KeyValuePair<long, UpdateValues> pair in updateDict)
{
updateParameters[0].Value = pair.Value.ReassignedQvalue; //// Qvalue
updateParameters[1].Value = pair.Value.ReassignedRank; //// Rank
updateParameters[2].Value = pair.Key; //// psm id
updateCmd.ExecuteNonQuery();
reportProgress((int)(((double)(updateCount + 1) / (double)allUpdateCount) * 100), "Updating idpDB");
++updateCount;
}
session.Transaction.Commit();
//basicDataFilter.ApplyBasicFilters(session);
reportStatus(reportSecondsElapsed((DateTime.Now - startTime).TotalSeconds));
reportStatus(string.Format("Rescued {0} PSMs for {1} distinct spectra\r\n", rescuedPSMsCount, rescuedDistinctSpectraIds.Count));
reportProgress(0, "Ready");
/*
* not recompute q values, reload idpDB, implemented in _bgWorkerClustering_RunWorkerCompleted
*/
} //// end of RescuePSMsByClustering
public void AnalyzeSpectrum()
{
try
{
Peaks.Clear();
PlotPoints.Clear();
if (firstAnalyze)
{
SamplePeaks.Clear();
}
var uri = new Uri(PicPath);
var bitmap = new BitmapImage(uri);
int stride = bitmap.PixelWidth * 4;
int size = bitmap.PixelHeight * stride;
byte[] pixels = new byte[size];
bitmap.CopyPixels(pixels, stride, 0);
//make an average values
//1. get sum of each color components
int[] avgpixels = new int[stride];
for (int y = 0; y < bitmap.PixelHeight; y++)
{
for (int x = 0; x < bitmap.PixelWidth; x++)
{
int index = y * stride + 4 * x;
avgpixels[4 * x] += pixels[index];
avgpixels[4 * x + 1] += pixels[index + 1];
avgpixels[4 * x + 2] += pixels[index + 2];
}
}
//2. get an average values - smooth
for (int x = 0; x < bitmap.PixelWidth; x++)
{
int index = bitmap.PixelHeight * stride + 4 * x;
avgpixels[4 * x] /= bitmap.PixelHeight;
avgpixels[4 * x + 1] /= bitmap.PixelHeight;
avgpixels[4 * x + 2] /= bitmap.PixelHeight;
}
//get intensity and make points on plot
for (int x = 0; x < bitmap.PixelWidth; x++)
{
var spec = new AnalyzedSpectrum();
int index = 4 * x;
int red = avgpixels[index];
int green = avgpixels[index + 1];
int blue = avgpixels[index + 2];
spec.PeakPixel = x + 380; //scale to wavelenght
spec.PeakIntensity = Math.Round(Math.Sqrt(0.299 * red * red + 0.587 * green * green + 0.114 * blue * blue), 2); // hsp color model
Peaks.Add(spec);
if (firstAnalyze)
{
SamplePeaks.Add(spec);
}
var _point = new DataPoint(spec.PeakPixel, spec.PeakIntensity);
PlotPoints.Add(_point);
}
firstAnalyze = false;
}
catch (Exception e)
{
MessageBox.Show("You must make a photo of spectrum first!");
}
}
static void Main(string[] args)
{
Peaks.FirstColumn(";", "Monte Falco, 1658, Parco Foreste Casentinesi ; Monte Falterona, 1654, Parco Foreste Casentinesi; Monte Fumaiolo, 1407, Appennino Tosco Emiliano");
}
public Polygon CutPolygon(Polygon P)
{
PointF I, Tmp1, Tmp2;
Vector Nv, D, W;
List <PointF> Q = new List <PointF>();
Peaks.Add(Peaks[0]);
double Dsk, Wsk, t;
// Обход по всем сторонам отсекателя
for (int i = 1; i < Peaks.Count; i++)
{
Nv = GetNormal(Peaks[i - 1], Peaks[i]);
if (VisiblePeak(P.GetPeak(0), Peaks[i], Nv))
{
Q.Add(P.GetPeak(0));
}
// Обход по всем сторонам многоугольника
for (int j = 1; j < P.Count(); j++)
{
Tmp1 = P.GetPeak(j - 1);
Tmp2 = P.GetPeak(j);
// Вектор отрезка
D = new Vector(Tmp2.X - Tmp1.X, Tmp2.Y - Tmp1.Y);
// Угол и с какой он стороны
Dsk = ScalarMultVector(D, Nv);
// Проверка, что отрезок не вырождается в точку и не параллелен
if (Dsk != 0)
{
// Вектор, который соединяет начало отрезка и вершину многоугольника
W = new Vector(Tmp1.X - Peaks[i - 1].X, Tmp1.Y - Peaks[i - 1].Y);
Wsk = ScalarMultVector(W, Nv);
t = -Wsk / Dsk;
if (t >= 0 && t <= 1)
{
I = new PointF((float)(P.GetPeak(j - 1).X + t * D.X), (float)(P.GetPeak(j - 1).Y + t * D.Y));
Q.Add(I);
}
}
if (VisiblePeak(P.GetPeak(j), Peaks[i], Nv))
{
Q.Add(P.GetPeak(j));
}
}
Q.Add(Q[0]);
P.Clear();
P.AddRange(Q);
Q.Clear();
}
return(P);
}
public void SumEnvelopeTo(double[] targetEnvelope)
{
Peaks.SumEnvelopeTo(targetEnvelope);
}
public override void Clear()
{
Peaks.Clear();
Direction = 0;
}
public void DoWork()
{
Stopwatch entire = new Stopwatch();
entire.Start();
for (int xyzxyz = 0; xyzxyz < parameters.peakListFile.Length; xyzxyz++)
{
Stopwatch total = new Stopwatch();
total.Start();
DBConnect db = new DBConnect();
Peaks peakData = new Peaks();
double mol_weight = PeakReader.peakListReader(peakData.mass, peakData.intens, parameters.peakListFile[xyzxyz], parameters.fileType);
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
//long mem = 0;
//mem = GC.GetTotalMemory(false);
// db.Set_Progress(parameters.queryid, 10);///////////prg
CurrentJobs.current[location].progress = "Module 1 of 9: Running Mass tuner.";//prg
Stopwatch timer = new Stopwatch();
execution_time time = new execution_time();
if (parameters.GUI_mass > 0)
{
mol_weight = parameters.GUI_mass;
}
timer.Start();
if (parameters.autotune == 1)
{
//int massCount = peakData.mass.Count;
//double[] massArray = new double[peakData.mass.Count];
//massArray = peakData.mass.ToArray<double>();
// double[] b = new double[massCount * massCount];
//int[] c = new int[massCount * massCount];
WholeProteinMassTunerGPU.GPU_generator(peakData.mass, peakData.intens, ref mol_weight, parameters.MW_tolerance);
}
timer.Stop();
time.tuner_time = timer.Elapsed.ToString();
timer.Reset();
// db.Set_Progress(parameters.queryid, 80);///////////prg
CurrentJobs.current[location].progress = "Module 2 of 9: Filtering DB on molecular weight.";
timer.Start();
// Thread.Sleep(5000);
List <proteins> filter_prot = new List <proteins>();
try
{
filter_prot = MW_Module.Fasta_Reader(mol_weight, parameters.MW_tolerance, parameters.protDB, parameters.filterDB);
}
catch (Exception eez)
{
string asdd = eez.InnerException.ToString();
}
timer.Stop();
time.mw_filter_time = timer.Elapsed.ToString();
timer.Reset();
/////////////////////////////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////////////
CurrentJobs.current[location].progress = "Module 3 of 9: Generating PST's";
timer.Start();
string input = "";
StringBuilder sb = new StringBuilder();
sb.Clear();
List <int> pro_ind = new List <int>();
//for (int i = 0; i < 200000; i++ )
for (int i = 0; i < filter_prot.Count; i++)
{
sb.Append(filter_prot[i].sequence);
pro_ind.Add(filter_prot[i].sequence.Length);
//input += PROT[i].sequence;
}
// PROT = new List<proteins>();
input = sb.ToString();
sb.Clear();
int I_len = input.Length;
if (parameters.denovo_allow == 1)
{
List <tags> estTags = EST_module.findEST(peakData.mass, peakData.intens, parameters.hopThreshhold / 17, parameters.minimum_est_length, parameters.maximum_est_length);
// db.Set_Progress(parameters.queryid, 85);///////////prg
CurrentJobs.current[location].progress = "Module 4 of 9: Filtering on the basis of PST's.";
// filter_prot = EST_module.EST_filter(estTags, filter_prot);
String[] keys = new String[estTags.Count];
for (int est = 0; est < estTags.Count; est++)
{
keys[est] = estTags[est].AA.ToUpper();
}
if (filter_prot.Count > 0)
{
char[] matched_result = Device_search.Execute(keys, input, I_len);
EST_module.GPU_Filter(matched_result, estTags, pro_ind, filter_prot);
matched_result = null;
}
input = "";
keys = null;
pro_ind.Clear();
estTags.Clear();
}
timer.Stop();
time.pst_time = timer.Elapsed.ToString();
timer.Reset();
// db.Set_Progress(parameters.queryid, 90);///////////prg
CurrentJobs.current[location].progress = "Module 5 of 9: Executing PTM module.";
timer.Start();
List <proteins> modified_proteins = new List <proteins>(); // EMPTY LIST
List <proteins> shortlisted_proteins = new List <proteins>();
if (parameters.ptm_allow == 1)
{
PTM_2.PTM_Control_2(filter_prot, parameters.ptm_tolerance, modified_proteins, parameters.ptm_code_var, parameters.ptm_code_fix, shortlisted_proteins, parameters.insilico_frag_type, parameters.HandleIons, peakData.mass, parameters.hopThreshhold, parameters.MW_sweight, parameters.PST_sweight, parameters.Insilico_sweight);
}
//PTM_Module.PTM_Control(filter_prot, parameters.ptm_tolerance, modified_proteins, parameters.ptm_code_var, parameters.ptm_code_fix, shortlisted_proteins);
else
{
shortlisted_proteins = filter_prot;
foreach (proteins kkk in shortlisted_proteins)
{
kkk.ptm_particulars = new List <Sites>();
}
}
if (parameters.ptm_code_fix.Count != 0 && parameters.ptm_code_var.Count != 0)
{
if (shortlisted_proteins.Count > 1)
{
double buffer = 0;
for (int p = 1; p < shortlisted_proteins.Count; p++)
{
buffer = MW_Module.MW_filter(mol_weight, parameters.MW_tolerance, shortlisted_proteins.ElementAt(p).MW, false);
if (buffer == -7)
{
shortlisted_proteins.Remove(shortlisted_proteins.ElementAt(p));
}
else
{
shortlisted_proteins.ElementAt(p).MW_score = buffer;
}
}
}
}
//foreach(pr)
timer.Stop();
time.ptm_time = timer.Elapsed.ToString();
timer.Reset();
// db.Set_Progress(parameters.queryid, 93);///////////prg
CurrentJobs.current[location].progress = "Module 6 of 9: Generating Insilico Fragments.";
//Thread.Sleep(5000);
timer.Start();
//List<Fragment> insilico = new List<Fragment>();
//insilico =
if (parameters.ptm_allow == 0)
{
Insilico_Module.insilico_fragmentation(shortlisted_proteins, parameters.insilico_frag_type, parameters.HandleIons);
}
// db.Set_Progress(parameters.queryid, 95);///////////prg
CurrentJobs.current[location].progress = "Module 7 of 9: Insilico Filteration.";
//INSILICO FIltering of xxx
if (parameters.ptm_allow == 0)
{
Insilico_Module.Insilico_filter(shortlisted_proteins, peakData.mass, parameters.hopThreshhold);
}
//Insilico_Module.Insilico_filter_U(modified_proteins, peakData.mass, parameters.hopThreshhold);
timer.Stop();
time.insilico_time = timer.Elapsed.ToString();
timer.Reset();
// db.Set_Progress(parameters.queryid, 98);///////////prg
CurrentJobs.current[location].progress = "Module 8 of 9: Evaluating Final Scores.";
//Thread.Sleep(5000);
for (int i = 0; i < shortlisted_proteins.Count; i++)
{
shortlisted_proteins[i].set_score(parameters.MW_sweight, parameters.PST_sweight, parameters.Insilico_sweight);
}
//modified_proteins.Sort((x,y)=>y.score.CompareTo(x.score));
shortlisted_proteins.AsParallel().OrderBy(x => x.score);
//List<proteins> SortedList = modified_proteins.OrderByDescending(o => o.score).ToList();
// db.Set_Progress(parameters.queryid, 100);///////////prg
CurrentJobs.current[location].progress = "Module 9 of 9: Storing Results.";
shortlisted_proteins.Sort((x, y) => y.score.CompareTo(x.score));
List <proteins> store_prot = new List <proteins>();
//Console.ReadKey();
for (int store_i = 0; store_i < 30 && store_i < shortlisted_proteins.Count; store_i++)
{
store_prot.Add(shortlisted_proteins[store_i]);
}
//Results final = new Results(parameters.queryid, SortedList);
//Results final = new Results(parameters.queryid, modified_proteins);
Results final = new Results(parameters.queryid, store_prot, time);
total.Stop();
final.times.total_time = total.Elapsed.ToString();
db.store_results(final, parameters.peakListFile[xyzxyz], xyzxyz);
//Send_Results_Link(parameters);
CurrentJobs.current[location].progress = "Done";
}
Send_Results_Link(parameters);
entire.Stop();
String timeForLoop;
timeForLoop = entire.Elapsed.ToString();
//string result_serial = Newtonsoft.Json.JsonConvert.SerializeObject(final);
}
