Examples with SimplePeakList net.sf.mzmine.datamodel.impl.SimplePeakList used on opensource projects

Example 21 with SimplePeakList

use of net.sf.mzmine.datamodel.impl.SimplePeakList in project mzmine2 by mzmine.

the class GridMassTask method run.

/**
 * @see Runnable#run()
 */
public void run() {
    Format mzFormat = MZmineCore.getConfiguration().getMZFormat();
    Format timeFormat = MZmineCore.getConfiguration().getRTFormat();
    setStatus(TaskStatus.PROCESSING);
    logger.info("Started GRIDMASS v1.0 [Apr-09-2014] on " + dataFile);
    scans = scanSelection.getMatchingScans(dataFile);
    scanNumbers = scanSelection.getMatchingScanNumbers(dataFile);
    totalScans = scans.length;
    // Check if we have any scans
    if (totalScans == 0) {
        setStatus(TaskStatus.ERROR);
        setErrorMessage("No scans match the selected criteria");
        return;
    }
    // Check if the scans are properly ordered by RT
    double prevRT = Double.NEGATIVE_INFINITY;
    for (Scan s : scans) {
        if (s.getRetentionTime() < prevRT) {
            setStatus(TaskStatus.ERROR);
            final String msg = "Retention time of scan #" + s.getScanNumber() + " is smaller then the retention time of the previous scan." + " Please make sure you only use scans with increasing retention times." + " You can restrict the scan numbers in the parameters, or you can use the Crop filter module";
            setErrorMessage(msg);
            return;
        }
        prevRT = s.getRetentionTime();
    }
    // Create new feature list
    newPeakList = new SimplePeakList(dataFile + " " + suffix, dataFile);
    int j;
    // minimumTimeSpan
    Scan scan = scans[0];
    double minRT = scan.getRetentionTime();
    double maxRT = scan.getRetentionTime();
    retentiontime = new double[totalScans];
    int i;
    for (i = 0; i < totalScans; i++) {
        scan = scans[i];
        double irt = scan.getRetentionTime();
        if (irt < minRT)
            minRT = irt;
        if (irt > maxRT)
            maxRT = irt;
        retentiontime[i] = irt;
    }
    rtPerScan = (maxRT - minRT) / i;
    // "tolerable" units in scans
    tolScans = Math.max(2, (int) ((minimumTimeSpan / rtPerScan)));
    maxTolScans = Math.max(2, (int) ((maximumTimeSpan / rtPerScan)));
    // Algorithm to find masses:
    // (1) copy masses:intensity > threshold
    // (2) sort intensities descend
    // (3) Find "spot" for each intensity
    // (3.1) if they have not spot ID assigned
    // (3.1.1) Extend mass in mass and time while > 70% pixels > threshold
    // (3.1.2) If extension > mintime ==> mark all pixels with the spot ID
    // (3.1.3) if extension < mintime ==> mark all pixels with spot ID = -1
    // (4) Group spots within a time-tolerance and mass-tolerance
    logger.info("Getting data points on " + dataFile);
    roi = new Datum[totalScans][];
    ArrayList<Datum> roiAL = new ArrayList<Datum>();
    long passed = 0, nopassed = 0;
    minMasa = Double.MAX_VALUE;
    maxMasa = 0;
    int maxJ = 0;
    boolean[] scanOk = new boolean[totalScans];
    Arrays.fill(scanOk, true);
    logger.info("Smoothing data points on " + dataFile + " (Time min=" + smoothTimeSpan + "; Time m/z=" + smoothTimeMZ + ")");
    IndexedDataPoint[][] data = smoothDataPoints(dataFile, smoothTimeSpan, smoothTimeMZ, 0, smoothMZ, 0, minimumHeight);
    logger.info("Determining intensities (mass sum) per scan on " + dataFile);
    for (i = 0; i < totalScans; i++) {
        if (isCanceled())
            return;
        scan = scans[i];
        // scan.getDataPoints();
        IndexedDataPoint[] mzv = data[i];
        double prev = (mzv.length > 0 ? mzv[0].datapoint.getMZ() : 0);
        double massSum = 0;
        for (j = 0; j < mzv.length; j++) {
            if (mzv[j].datapoint.getIntensity() >= minimumHeight)
                massSum += mzv[j].datapoint.getMZ() - prev;
            prev = mzv[j].datapoint.getMZ();
            if (mzv[j].datapoint.getMZ() < minMasa)
                minMasa = mzv[j].datapoint.getMZ();
            if (mzv[j].datapoint.getMZ() > maxMasa)
                maxMasa = mzv[j].datapoint.getMZ();
        }
        double dm = 100.0 / (maxMasa - minMasa);
        if (i % 30 == 0 && debug > 0) {
            System.out.println("");
            System.out.print("t=" + Math.round(retentiontime[i] * 100) / 100.0 + ": (in %) ");
        }
        if (scanOk[i]) {
            if (!scanOk[i]) {
                // Disable neighbouring scans, how many ?
                for (j = i; j > 0 && retentiontime[j] + additionTimeMaxPeaksPerScan > retentiontime[i]; j--) {
                    scanOk[j] = false;
                }
                for (j = i; j < totalScans && retentiontime[j] - additionTimeMaxPeaksPerScan < retentiontime[i]; j++) {
                    scanOk[j] = false;
                }
            }
            if (debug > 0)
                System.out.print(((int) (massSum * dm)) + (scanOk[i] ? " " : "*** "));
        } else {
            if (debug > 0)
                System.out.print(((int) (massSum * dm)) + (scanOk[i] ? " " : "* "));
        }
        setProcedure(i, totalScans, 1);
    }
    if (debug > 0)
        System.out.println("");
    String[] it = ignoreTimes.trim().split(", ?");
    for (j = 0; j < it.length; j++) {
        String[] itj = it[j].split("-");
        if (itj.length == 2) {
            Double a = Double.parseDouble(itj[0].trim());
            Double b = Double.parseDouble(itj[1].trim());
            for (i = Math.abs(Arrays.binarySearch(retentiontime, a)); i < totalScans && retentiontime[i] <= b; i++) {
                if (retentiontime[i] >= a) {
                    scanOk[i] = false;
                }
            }
        }
    }
    passed = 0;
    nopassed = 0;
    for (i = 0; i < totalScans; i++) {
        if (i % 100 == 0 && isCanceled())
            return;
        if (scanOk[i]) {
            scan = scans[i];
            IndexedDataPoint[] mzv = data[i];
            DataPoint[] mzvOriginal = scan.getDataPoints();
            ArrayList<Datum> dal = new ArrayList<Datum>();
            for (j = 0; j < mzv.length; j++) {
                if (mzv[j].datapoint.getIntensity() >= minimumHeight) {
                    dal.add(new Datum(mzv[j].datapoint, i, mzvOriginal[mzv[j].index]));
                    passed++;
                } else {
                    nopassed++;
                }
            }
            if (j > maxJ)
                maxJ = j;
            roi[i] = dal.toArray(new Datum[0]);
            roiAL.addAll(dal);
        }
        setProcedure(i, totalScans, 2);
    }
    logger.info(passed + " intensities >= " + minimumHeight + " of " + (passed + nopassed) + " (" + Math.round(passed * 10000.0 / (double) (passed + nopassed)) / 100.0 + "%) on " + dataFile);
    // New "probing" algorithm
    // (1) Generate probes all over chromatograms
    // (2) Move each probe to their closest maximum until it cannot find a
    // new maximum
    // (3) assign spot id to each "center" using all points within region
    // (1) Generate probes all over
    double byMZ = Math.max(mzTol * 2, 1e-6);
    int byScan = Math.max(1, tolScans / 4);
    logger.info("Creating Grid of probes on " + dataFile + " every " + mzFormat.format(byMZ) + " m/z and " + byScan + " scans");
    double m;
    int ndata = (int) Math.round((((double) totalScans / (double) byScan) + 1) * ((maxMasa - minMasa + byMZ) / byMZ));
    Probe[] probes = new Probe[ndata];
    int idata = 0;
    for (i = 0; i < totalScans; i += byScan) {
        if (i % 100 == 0 && isCanceled())
            return;
        for (m = minMasa - (i % 2) * byMZ / 2; m <= maxMasa; m += byMZ) {
            probes[idata++] = new Probe(m, i);
        }
        setProcedure(i, totalScans, 3);
    }
    // (2) Move each probe to their closest center
    double mzR = byMZ / 2;
    int scanR = Math.max(byScan - 1, 2);
    logger.info("Finding local maxima for each probe on " + dataFile + " radius: scans=" + scanR + ", m/z=" + mzR);
    int okProbes = 0;
    for (i = 0; i < idata; i++) {
        if (i % 100 == 0 && isCanceled())
            return;
        moveProbeToCenter(probes[i], scanR, mzR);
        if (probes[i].intensityCenter < minimumHeight) {
            probes[i] = null;
        } else {
            okProbes++;
        }
        setProcedure(i, idata, 4);
    }
    if (okProbes > 0) {
        Probe[] pArr = new Probe[okProbes];
        for (okProbes = i = 0; i < idata; i++) {
            if (probes[i] != null) {
                pArr[okProbes++] = probes[i];
            }
        }
        probes = pArr;
        pArr = null;
    }
    // (3) Assign spot id to each "center"
    logger.info("Sorting probes " + dataFile);
    Arrays.sort(probes);
    logger.info("Assigning spot id to local maxima on " + dataFile);
    SpotByProbes sbp = new SpotByProbes();
    ArrayList<SpotByProbes> spots = new ArrayList<SpotByProbes>();
    double mzA = -1;
    int scanA = -1;
    for (i = 0; i < probes.length; i++) {
        if (probes[i] != null && probes[i].intensityCenter >= minimumHeight) {
            if (probes[i].mzCenter != mzA || probes[i].scanCenter != scanA) {
                if (i % 10 == 0 && isCanceled())
                    return;
                if (sbp.size() > 0) {
                    spots.add(sbp);
                    sbp.assignSpotId();
                // System.out.println(sbp.toString());
                }
                sbp = new SpotByProbes();
                mzA = probes[i].mzCenter;
                scanA = probes[i].scanCenter;
            }
            sbp.addProbe(probes[i]);
        }
        setProcedure(i, probes.length, 5);
    }
    if (sbp.size() > 0) {
        spots.add(sbp);
        sbp.assignSpotId();
    // System.out.println(sbp.toString());
    }
    logger.info("Spots:" + spots.size());
    // Assign specific datums to spots to avoid using datums to several
    // spots
    logger.info("Assigning intensities to local maxima on " + dataFile);
    i = 0;
    for (SpotByProbes sx : spots) {
        if (sx.size() > 0) {
            if (i % 100 == 0 && isCanceled())
                return;
            assignSpotIdToDatumsFromScans(sx, scanR, mzR);
        }
        setProcedure(i++, spots.size(), 6);
    }
    // (4) Join Tolerable Centers
    logger.info("Joining tolerable maxima on " + dataFile);
    int criticScans = Math.max(1, tolScans / 2);
    int joins = 0;
    for (i = 0; i < spots.size() - 1; i++) {
        SpotByProbes s1 = spots.get(i);
        if (s1.center != null && s1.size() > 0) {
            if (i % 100 == 0 && isCanceled())
                return;
            for (j = i; j > 0 && j < spots.size() && spots.get(j - 1).center != null && spots.get(j - 1).center.mzCenter + mzTol > s1.center.mzCenter; j--) ;
            for (; j < spots.size(); j++) {
                SpotByProbes s2 = spots.get(j);
                if (i != j && s2.center != null) {
                    if (s2.center.mzCenter - s1.center.mzCenter > mzTol)
                        break;
                    int l = Math.min(Math.abs(s1.minScan - s2.minScan), Math.abs(s1.minScan - s2.maxScan));
                    int r = Math.min(Math.abs(s1.maxScan - s2.minScan), Math.abs(s1.maxScan - s2.maxScan));
                    int d = Math.min(l, r);
                    boolean overlap = !(s2.maxScan < s1.minScan || s2.minScan > s1.maxScan);
                    if ((d <= criticScans || overlap) && (intensityRatio(s1.center.intensityCenter, s2.center.intensityCenter) > intensitySimilarity)) {
                        if (debug > 2)
                            System.out.println("Joining s1 id " + s1.spotId + "=" + mzFormat.format(s1.center.mzCenter) + " mz [" + mzFormat.format(s1.minMZ) + " ~ " + mzFormat.format(s1.maxMZ) + "] time=" + timeFormat.format(retentiontime[s1.center.scanCenter]) + " int=" + s1.center.intensityCenter + " with s2 id " + s2.spotId + "=" + mzFormat.format(s2.center.mzCenter) + " mz [" + mzFormat.format(s2.minMZ) + " ~ " + mzFormat.format(s2.maxMZ) + "] time=" + timeFormat.format(retentiontime[s2.center.scanCenter]) + " int=" + s2.center.intensityCenter);
                        assignSpotIdToDatumsFromSpotId(s1, s2, scanR, mzR);
                        s1.addProbesFromSpot(s2, true);
                        // restart
                        j = i;
                        joins++;
                    }
                // }
                }
            }
        }
        setProcedure(i, spots.size(), 7);
    }
    logger.info("Joins:" + joins);
    // (5) Remove "Large" spanned masses
    logger.info("Removing long and comparable 'masses' on " + dataFile);
    for (i = 0; i < spots.size() - 1; i++) {
        SpotByProbes s1 = spots.get(i);
        if (s1.center != null && s1.size() > 0) {
            if (i % 100 == 0 && isCanceled())
                return;
            int totalScans = s1.maxScan - s1.minScan + 1;
            int lScan = s1.minScan;
            int rScan = s1.maxScan;
            ArrayList<Integer> toRemove = new ArrayList<Integer>();
            toRemove.add(i);
            for (j = i; j > 0 && j < spots.size() && spots.get(j - 1).center != null && spots.get(j - 1).center.mzCenter + mzTol > s1.center.mzCenter; j--) ;
            for (; j < spots.size(); j++) {
                SpotByProbes s2 = spots.get(j);
                if (i != j && s2.center != null) {
                    if (s2.center.mzCenter - s1.center.mzCenter > mzTol)
                        break;
                    if (intensityRatio(s1.center.intensityCenter, s2.center.intensityCenter) > intensitySimilarity) {
                        int dl = Math.min(Math.abs(lScan - s2.minScan), Math.abs(lScan - s2.maxScan));
                        int dr = Math.min(Math.abs(rScan - s2.minScan), Math.abs(rScan - s2.maxScan));
                        int md = Math.min(dl, dr);
                        if (md <= maxTolScans || !(s2.maxScan < lScan || s2.minScan > rScan)) {
                            // distancia tolerable o intersectan
                            totalScans += s2.maxScan - s2.minScan + 1;
                            toRemove.add(j);
                            lScan = Math.min(lScan, s2.minScan);
                            rScan = Math.max(rScan, s2.maxScan);
                        }
                    }
                }
            }
            if (totalScans * rtPerScan > maximumTimeSpan) {
                if (debug > 2)
                    System.out.println("Removing " + toRemove.size() + " masses around " + mzFormat.format(s1.center.mzCenter) + " m/z (" + s1.spotId + "), time " + timeFormat.format(retentiontime[s1.center.scanCenter]) + ", intensity " + s1.center.intensityCenter + ", Total Scans=" + totalScans + " (" + Math.round(totalScans * rtPerScan * 1000.0) / 1000.0 + " min).");
                for (Integer J : toRemove) {
                    // System.out.println("Removing: "+spots.get(J).spotId);
                    spots.get(J).clear();
                }
            }
        }
        setProcedure(i, spots.size(), 8);
    }
    // Build peaks from assigned datums
    logger.info("Building peak rows on " + dataFile + " (tolereance scans=" + tolScans + ")");
    i = 0;
    for (SpotByProbes sx : spots) {
        if (sx.size() > 0 && sx.maxScan - sx.minScan + 1 >= tolScans) {
            if (i % 100 == 0 && isCanceled())
                return;
            sx.buildMaxDatumFromScans(roi, minimumHeight);
            if (sx.getMaxDatumScans() >= tolScans && (sx.getContigousMaxDatumScans() >= tolScans || sx.getContigousToMaxDatumScansRatio() > 0.5)) {
                Chromatogram peak = new Chromatogram(dataFile, scanNumbers);
                if (addMaxDatumFromScans(sx, peak) > 0) {
                    peak.finishChromatogram();
                    if (peak.getArea() > 1e-6) {
                        newPeakID++;
                        SimplePeakListRow newRow = new SimplePeakListRow(newPeakID);
                        newRow.addPeak(dataFile, peak);
                        newRow.setComment(sx.toString(retentiontime));
                        newPeakList.addRow(newRow);
                        if (debug > 0)
                            System.out.println("Peak added id=" + sx.spotId + " " + mzFormat.format(sx.center.mzCenter) + " mz, time=" + timeFormat.format(retentiontime[sx.center.scanCenter]) + ", intensity=" + sx.center.intensityCenter + ", probes=" + sx.size() + ", data scans=" + sx.getMaxDatumScans() + ", cont scans=" + sx.getContigousMaxDatumScans() + ", cont ratio=" + sx.getContigousToMaxDatumScansRatio() + " area = " + peak.getArea());
                        if (debug > 1) {
                            // Peak info:
                            System.out.println(sx.toString());
                            sx.printDebugInfo();
                        }
                    } else {
                        if (debug > 0)
                            System.out.println("Ignored by area ~ 0 id=" + sx.spotId + " " + mzFormat.format(sx.center.mzCenter) + " mz, time=" + timeFormat.format(retentiontime[sx.center.scanCenter]) + ", intensity=" + sx.center.intensityCenter + ", probes=" + sx.size() + ", data scans=" + sx.getMaxDatumScans() + ", cont scans=" + sx.getContigousMaxDatumScans() + ", cont ratio=" + sx.getContigousToMaxDatumScansRatio() + " area = " + peak.getArea());
                    }
                }
            } else {
                if (debug > 0)
                    System.out.println("Ignored by continous criteria: id=" + sx.spotId + " " + mzFormat.format(sx.center.mzCenter) + " mz, time=" + timeFormat.format(retentiontime[sx.center.scanCenter]) + ", intensity=" + sx.center.intensityCenter + ", probes=" + sx.size() + ", data scans=" + sx.getMaxDatumScans() + ", cont scans=" + sx.getContigousMaxDatumScans() + ", cont ratio=" + sx.getContigousToMaxDatumScansRatio());
            }
        } else {
            if (sx.size() > 0) {
                if (debug > 0)
                    System.out.println("Ignored by time range criteria: id=" + sx.spotId + " " + mzFormat.format(sx.center.mzCenter) + " mz, time=" + timeFormat.format(retentiontime[sx.center.scanCenter]) + ", intensity=" + sx.center.intensityCenter + ", probes=" + sx.size() + ", data scans=" + sx.getMaxDatumScans() + ", cont scans=" + sx.getContigousMaxDatumScans() + ", cont ratio=" + sx.getContigousToMaxDatumScansRatio());
            }
        }
        setProcedure(i++, spots.size(), 9);
    }
    logger.info("Peaks on " + dataFile + " = " + newPeakList.getNumberOfRows());
    // Add new peaklist to the project
    project.addPeakList(newPeakList);
    // Add quality parameters to peaks
    QualityParameters.calculateQualityParameters(newPeakList);
    setStatus(TaskStatus.FINISHED);
    logger.info("Finished chromatogram builder (RT) on " + dataFile);
}

Example 22 with SimplePeakList

use of net.sf.mzmine.datamodel.impl.SimplePeakList in project mzmine2 by mzmine.

the class TargetedPeakDetectionModuleTask method run.

public void run() {
    setStatus(TaskStatus.PROCESSING);
    // Calculate total number of scans in all files
    totalScans = dataFile.getNumOfScans(1);
    // Create new feature list
    processedPeakList = new SimplePeakList(dataFile.getName() + " " + suffix, dataFile);
    List<PeakInformation> peaks = this.readFile();
    if (peaks == null || peaks.isEmpty()) {
        setStatus(TaskStatus.ERROR);
        setErrorMessage("Could not read file or the file is empty ");
        return;
    }
    // Fill new feature list with empty rows
    for (int row = 0; row < peaks.size(); row++) {
        PeakListRow newRow = new SimplePeakListRow(ID++);
        processedPeakList.addRow(newRow);
    }
    // Canceled?
    if (isCanceled()) {
        return;
    }
    List<Gap> gaps = new ArrayList<Gap>();
    // gaps if necessary
    for (int row = 0; row < peaks.size(); row++) {
        PeakListRow newRow = processedPeakList.getRow(row);
        // Create a new gap
        Range<Double> mzRange = mzTolerance.getToleranceRange(peaks.get(row).getMZ());
        Range<Double> rtRange = rtTolerance.getToleranceRange(peaks.get(row).getRT());
        newRow.addPeakIdentity(new SimplePeakIdentity(peaks.get(row).getName()), true);
        Gap newGap = new Gap(newRow, dataFile, mzRange, rtRange, intTolerance, noiseLevel);
        gaps.add(newGap);
    }
    // Stop processing this file if there are no gaps
    if (gaps.isEmpty()) {
        processedScans += dataFile.getNumOfScans();
    }
    // Get all scans of this data file
    int[] scanNumbers = dataFile.getScanNumbers(msLevel);
    if (scanNumbers == null) {
        logger.log(Level.WARNING, "Could not read file with the MS level of " + msLevel);
        setStatus(TaskStatus.ERROR);
        return;
    }
    // Process each scan
    for (int scanNumber : scanNumbers) {
        // Canceled?
        if (isCanceled()) {
            return;
        }
        // Get the scan
        Scan scan = dataFile.getScan(scanNumber);
        // Feed this scan to all gaps
        for (Gap gap : gaps) {
            gap.offerNextScan(scan);
        }
        processedScans++;
    }
    // Finalize gaps
    for (Gap gap : gaps) {
        gap.noMoreOffers();
    }
    // Append processed feature list to the project
    project.addPeakList(processedPeakList);
    // Add quality parameters to peaks
    QualityParameters.calculateQualityParameters(processedPeakList);
    // Add task description to peakList
    processedPeakList.addDescriptionOfAppliedTask(new SimplePeakListAppliedMethod("Targeted feature detection ", parameters));
    logger.log(Level.INFO, "Finished targeted feature detection on {0}", this.dataFile);
    setStatus(TaskStatus.FINISHED);
}

Example 23 with SimplePeakList

use of net.sf.mzmine.datamodel.impl.SimplePeakList in project mzmine2 by mzmine.

the class HierarAlignerGCTask method run.

/**
 * @see Runnable#run()
 */
public void run() {
    // Check options validity
    if ((Math.abs(mzWeight) < EPSILON) && (Math.abs(rtWeight) < EPSILON)) {
        setStatus(TaskStatus.ERROR);
        setErrorMessage("Cannot run alignment, all the weight parameters are zero!");
        return;
    }
    setStatus(TaskStatus.PROCESSING);
    logger.info("Running join aligner");
    // TIME STUFF
    long startTime, endTime;
    float ms;
    // 
    if (DEBUG)
        startTime = System.currentTimeMillis();
    // MEMORY STUFF
    Runtime run_time = Runtime.getRuntime();
    Long prevTotal = 0l;
    Long prevFree = run_time.freeMemory();
    if (DEBUG)
        printMemoryUsage(logger, run_time, prevTotal, prevFree, "START TASK...");
    // - third for actual alignment
    for (int i = 0; i < peakLists.length; i++) {
        totalRows += peakLists[i].getNumberOfRows() * 3;
    }
    // Collect all data files
    Vector<RawDataFile> allDataFiles = new Vector<RawDataFile>();
    for (PeakList peakList : peakLists) {
        for (RawDataFile dataFile : peakList.getRawDataFiles()) {
            // Each data file can only have one column in aligned feature list
            if (allDataFiles.contains(dataFile)) {
                setStatus(TaskStatus.ERROR);
                setErrorMessage("Cannot run alignment, because file " + dataFile + " is present in multiple feature lists");
                return;
            }
            allDataFiles.add(dataFile);
        }
    }
    // Create a new aligned feature list
    alignedPeakList = new SimplePeakList(peakListName, allDataFiles.toArray(new RawDataFile[0]));
    if (DEBUG)
        printMemoryUsage(logger, run_time, prevTotal, prevFree, "COMPOUND DETECTED");
    /**
     * Alignment mapping *
     */
    // Iterate source feature lists
    Hashtable<SimpleFeature, Double> rtPeaksBackup = new Hashtable<SimpleFeature, Double>();
    Hashtable<PeakListRow, Object[]> infoRowsBackup = new Hashtable<PeakListRow, Object[]>();
    // Since clustering is now order independent, option removed!
    // Build comparison order
    ArrayList<Integer> orderIds = new ArrayList<Integer>();
    for (int i = 0; i < peakLists.length; ++i) {
        orderIds.add(i);
    }
    Integer[] newIds = orderIds.toArray(new Integer[orderIds.size()]);
    // 
    // TriangularMatrix distances = null;
    DistanceMatrix distancesGNF_Tri = null;
    DistanceMatrix distancesGNF_Tri_Bkp = null;
    int nbPeaks = 0;
    for (int i = 0; i < newIds.length; ++i) {
        PeakList peakList = peakLists[newIds[i]];
        nbPeaks += peakList.getNumberOfRows();
    }
    // If 'Hybrid' or no distance matrix: no need for a matrix
    if (CLUSTERER_TYPE == ClustererType.HYBRID || !saveRAMratherThanCPU_1) {
        // distances = new double[nbPeaks][nbPeaks];
        int nRowCount = nbPeaks;
        distancesGNF_Tri = new DistanceMatrixTriangular1D2D(nRowCount);
    }
    full_rows_list = new ArrayList<>();
    for (int i = 0; i < newIds.length; ++i) {
        PeakList peakList = peakLists[newIds[i]];
        PeakListRow[] allRows = peakList.getRows();
        for (int j = 0; j < allRows.length; ++j) {
            PeakListRow row = allRows[j];
            full_rows_list.add(row);
        }
    }
    RowVsRowDistanceProvider distProvider = new RowVsRowDistanceProvider(project, // rtAdjustementMapping,
    full_rows_list, mzWeight, rtWeight, // rtToleranceAfter,
    maximumScore);
    // If 'Hybrid' or no distance matrix: no need for a matrix
    if (CLUSTERER_TYPE == ClustererType.HYBRID || !saveRAMratherThanCPU_1) {
        for (int x = 0; x < nbPeaks; ++x) {
            for (int y = x; y < nbPeaks; ++y) {
                float dist = (float) distProvider.getRankedDistance(x, y, mzTolerance.getMzTolerance(), rtTolerance.getTolerance(), minScore);
                // if (CLUSTERER_TYPE == ClustererType.CLASSIC_OLD)
                // distances.set(x, y , dist);
                // else
                distancesGNF_Tri.setValue(x, y, dist);
            }
            processedRows++;
            if (DEBUG)
                logger.info("Treating lists: " + (Math.round(100 * processedRows / (double) nbPeaks)) + " %");
        }
    }
    if (DEBUG)
        printMemoryUsage(logger, run_time, prevTotal, prevFree, "DISTANCES COMPUTED");
    // ////
    // Math.abs(row.getBestPeak().getRT() -
    double max_dist = maximumScore;
    // k_row.getBestPeak().getRT()) /
    // ((RangeUtils.rangeLength(rtRange) /
    // 2.0));
    // String newickCluster;
    List<List<Integer>> gnfClusters = null;
    // ////
    boolean do_verbose = true;
    boolean do_cluster = true;
    boolean do_print = (exportDendrogramAsTxt);
    boolean do_data = false;
    org.gnf.clustering.Node[] arNodes = null;
    int nRowCount = full_rows_list.size();
    String[] rowNames = null;
    if (do_print) {
        rowNames = new String[nRowCount];
        for (int i = 0; i < nRowCount; i++) {
            // rowNames[i] = "ID_" + i + "_" +
            // full_rows_list.get(i).getID();
            Feature peak = full_rows_list.get(i).getBestPeak();
            double rt = peak.getRT();
            int end = peak.getDataFile().getName().indexOf(" ");
            String short_fname = peak.getDataFile().getName().substring(0, end);
            rowNames[i] = "@" + rtFormat.format(rt) + "^[" + short_fname + "]";
        }
    }
    String outputPrefix = null;
    if (CLUSTERER_TYPE == ClustererType.CLASSIC) {
        // Pure Hierar!
        outputPrefix = "hierar_0";
        throw new IllegalStateException("'" + ClustererType.CLASSIC.toString() + "' algorithm not yet implemented!");
    } else if (CLUSTERER_TYPE == ClustererType.CACHED) {
        // TODO: ...!
        if (DEBUG_2)
            logger.info(distancesGNF_Tri.toString());
        if (saveRAMratherThanCPU_2) {
            // Requires: distances values will be
            // recomputed on demand during
            // "getValidatedClusters_3()"
            // No duplicate backup storage!
            distancesGNF_Tri_Bkp = null;
        } else {
            // Otherwise, backing up the distance matrix (matrix being
            // deeply changed during "clusterDM()", then no more
            // exploitable)
            distancesGNF_Tri_Bkp = new DistanceMatrixTriangular1D2D(distancesGNF_Tri);
            if (DEBUG)
                printMemoryUsage(logger, run_time, prevTotal, prevFree, "GNF CLUSTERER BACKUP MATRIX");
        }
        if (DEBUG)
            logger.info("Clustering...");
        if (distancesGNF_Tri != null)
            arNodes = org.gnf.clustering.sequentialcache.SequentialCacheClustering.clusterDM(distancesGNF_Tri, linkageStartegyType, null, nRowCount);
        distancesGNF_Tri = null;
        System.gc();
        if (DEBUG)
            printMemoryUsage(logger, run_time, prevTotal, prevFree, "GNF CLUSTERER DONE");
        if (DEBUG_2)
            logger.info(distancesGNF_Tri.toString());
        if (DEBUG_2)
            for (int i = 0; i < arNodes.length; i++) {
                logger.info("Node " + i + ": " + arNodes[i]);
            }
        // TODO: Use usual interfacing ...
        // ClusteringResult<org.gnf.clustering.Node> clust_res = new
        // ClusteringResult<>(
        // Arrays.asList(arNodes), null, 0, null);
        outputPrefix = "hierar_1";
    } else if (CLUSTERER_TYPE == ClustererType.HYBRID) {
        throw new IllegalStateException("'" + ClustererType.HYBRID.toString() + "' algorithm not yet implemented!");
    }
    // Sort Nodes by correlation score (Required in
    // 'getValidatedClusters_3')
    int[] rowOrder = new int[nRowCount];
    if (DEBUG)
        logger.info("Sorting tree nodes...");
    org.gnf.clustering.Utils.NodeSort(arNodes, nRowCount - 2, 0, rowOrder);
    if (do_cluster) {
        gnfClusters = getValidatedClusters_3(arNodes, 0.0f, newIds.length, max_dist, distancesGNF_Tri_Bkp, distProvider);
        // -- Print
        if (DEBUG_2 && do_verbose)
            for (int i = 0; i < gnfClusters.size(); i++) {
                List<Integer> cl = gnfClusters.get(i);
                String str = "";
                for (int j = 0; j < cl.size(); j++) {
                    int r = cl.get(j);
                    str += cl.get(j) + "^(" + full_rows_list.get(r).getID() + ", " + full_rows_list.get(r).getAverageRT() + ")" + " ";
                }
                logger.info(str);
            }
    }
    // File output
    int ext_pos = dendrogramTxtFilename.getAbsolutePath().lastIndexOf(".");
    outputPrefix = dendrogramTxtFilename.getAbsolutePath().substring(0, ext_pos);
    String outGtr = outputPrefix + ".gtr";
    String outCdt = outputPrefix + ".cdt";
    if (DEBUG)
        logger.info("Writing output to file...");
    int nColCount = 1;
    String[] colNames = new String[nColCount];
    colNames[nColCount - 1] = "Id";
    String sep = "\t";
    if (do_print) {
        try {
            float[] arFloats = new float[nRowCount];
            for (int i = 0; i < arFloats.length; i++) {
                arFloats[i] = i / 2.0f;
            }
            DataSource source = (do_data) ? new FloatSource1D(arFloats, nRowCount, nColCount) : null;
            /* org.gnf.clustering.Utils. */
            HierarAlignerGCTask.GenerateCDT(outCdt, source, /* null */
            nRowCount, nColCount, sep, rowNames, colNames, rowOrder);
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
        org.gnf.clustering.Utils.WriteTreeToFile(outGtr, nRowCount - 1, arNodes, true);
        if (DEBUG)
            printMemoryUsage(logger, run_time, prevTotal, prevFree, "GNF CLUSTERER FILES PRINTED");
    }
    // //// Arrange row clustered list with method 0,1,2
    List<List<PeakListRow>> clustersList = new ArrayList<>();
    // Build feature list row clusters
    for (List<Integer> cl : gnfClusters) {
        List<PeakListRow> rows_cluster = new ArrayList<>();
        for (int i = 0; i < cl.size(); i++) {
            rows_cluster.add(full_rows_list.get(cl.get(i)));
        }
        clustersList.add(rows_cluster);
        // 
        processedRows += rows_cluster.size();
    }
    if (DEBUG)
        printMemoryUsage(logger, run_time, prevTotal, prevFree, "GNF CLUSTERER CLUSTER_LIST");
    // Fill alignment table: One row per cluster
    for (List<PeakListRow> cluster : clustersList) {
        if (isCanceled())
            return;
        PeakListRow targetRow = new SimplePeakListRow(newRowID);
        newRowID++;
        alignedPeakList.addRow(targetRow);
        // 
        infoRowsBackup.put(targetRow, new Object[] { new HashMap<RawDataFile, Double[]>(), new HashMap<RawDataFile, PeakIdentity>(), new HashMap<RawDataFile, Double>() });
        for (PeakListRow row : cluster) {
            // Add all non-existing identities from the original row to the
            // aligned row
            // Set the preferred identity
            targetRow.setPreferredPeakIdentity(row.getPreferredPeakIdentity());
            // for (RawDataFile file : row.getRawDataFiles()) {
            for (RawDataFile file : alignedPeakList.getRawDataFiles()) {
                if (Arrays.asList(row.getRawDataFiles()).contains(file)) {
                    Feature originalPeak = row.getPeak(file);
                    if (originalPeak != null) {
                        targetRow.addPeak(file, originalPeak);
                    } else {
                        setStatus(TaskStatus.ERROR);
                        setErrorMessage("Cannot run alignment, no originalPeak");
                        return;
                    }
                }
            }
            // present
            for (PeakIdentity identity : row.getPeakIdentities()) {
                PeakIdentity clonedIdentity = (PeakIdentity) identity.clone();
                if (!PeakUtils.containsIdentity(targetRow, clonedIdentity))
                    targetRow.addPeakIdentity(clonedIdentity, false);
            }
        // processedRows++;
        }
    }
    // of the "targetRow.update()" used down there
    for (SimpleFeature peak : rtPeaksBackup.keySet()) {
        peak.setRT((double) rtPeaksBackup.get(peak));
    }
    /**
     * Post-processing... *
     */
    // Build reference RDFs index: We need an ordered reference here, to be
    // able to parse
    // correctly while reading back stored info
    RawDataFile[] rdf_sorted = alignedPeakList.getRawDataFiles().clone();
    Arrays.sort(rdf_sorted, new RawDataFileSorter(SortingDirection.Ascending));
    // Process
    for (PeakListRow targetRow : infoRowsBackup.keySet()) {
        if (isCanceled())
            return;
        // Refresh averaged RTs...
        ((SimplePeakListRow) targetRow).update();
    }
    // 
    if (DEBUG) {
        endTime = System.currentTimeMillis();
        ms = (endTime - startTime);
        logger.info("## >> Whole JoinAlignerGCTask processing took " + Float.toString(ms) + " ms.");
    }
    // ----------------------------------------------------------------------
    // Add new aligned feature list to the project
    this.project.addPeakList(alignedPeakList);
    if (DEBUG) {
        for (RawDataFile rdf : alignedPeakList.getRawDataFiles()) logger.info("RDF: " + rdf);
    }
    // Add task description to peakList
    alignedPeakList.addDescriptionOfAppliedTask(new SimplePeakListAppliedMethod(HierarAlignerGCTask.TASK_NAME, parameters));
    logger.info("Finished join aligner GC");
    setStatus(TaskStatus.FINISHED);
}

Example 24 with SimplePeakList

use of net.sf.mzmine.datamodel.impl.SimplePeakList in project mzmine2 by mzmine.

the class JoinAlignerTask method run.

/**
 * @see Runnable#run()
 */
@Override
public void run() {
    if ((mzWeight == 0) && (rtWeight == 0)) {
        setStatus(TaskStatus.ERROR);
        setErrorMessage("Cannot run alignment, all the weight parameters are zero");
        return;
    }
    setStatus(TaskStatus.PROCESSING);
    logger.info("Running join aligner");
    // twice, first for score calculation, second for actual alignment.
    for (int i = 0; i < peakLists.length; i++) {
        totalRows += peakLists[i].getNumberOfRows() * 2;
    }
    // Collect all data files
    Vector<RawDataFile> allDataFiles = new Vector<RawDataFile>();
    for (PeakList peakList : peakLists) {
        for (RawDataFile dataFile : peakList.getRawDataFiles()) {
            // Each data file can only have one column in aligned feature list
            if (allDataFiles.contains(dataFile)) {
                setStatus(TaskStatus.ERROR);
                setErrorMessage("Cannot run alignment, because file " + dataFile + " is present in multiple feature lists");
                return;
            }
            allDataFiles.add(dataFile);
        }
    }
    // Create a new aligned feature list
    alignedPeakList = new SimplePeakList(peakListName, allDataFiles.toArray(new RawDataFile[0]));
    // Iterate source feature lists
    for (PeakList peakList : peakLists) {
        // Create a sorted set of scores matching
        TreeSet<RowVsRowScore> scoreSet = new TreeSet<RowVsRowScore>();
        PeakListRow[] allRows = peakList.getRows();
        // Calculate scores for all possible alignments of this row
        for (PeakListRow row : allRows) {
            if (isCanceled())
                return;
            // Calculate limits for a row with which the row can be aligned
            Range<Double> mzRange = mzTolerance.getToleranceRange(row.getAverageMZ());
            Range<Double> rtRange = rtTolerance.getToleranceRange(row.getAverageRT());
            // Get all rows of the aligned peaklist within parameter limits
            PeakListRow[] candidateRows = alignedPeakList.getRowsInsideScanAndMZRange(rtRange, mzRange);
            // Calculate scores and store them
            for (PeakListRow candidate : candidateRows) {
                if (sameChargeRequired) {
                    if (!PeakUtils.compareChargeState(row, candidate))
                        continue;
                }
                if (sameIDRequired) {
                    if (!PeakUtils.compareIdentities(row, candidate))
                        continue;
                }
                if (compareIsotopePattern) {
                    IsotopePattern ip1 = row.getBestIsotopePattern();
                    IsotopePattern ip2 = candidate.getBestIsotopePattern();
                    if ((ip1 != null) && (ip2 != null)) {
                        ParameterSet isotopeParams = parameters.getParameter(JoinAlignerParameters.compareIsotopePattern).getEmbeddedParameters();
                        if (!IsotopePatternScoreCalculator.checkMatch(ip1, ip2, isotopeParams)) {
                            continue;
                        }
                    }
                }
                // compare the similarity of spectra mass lists on MS1 or MS2 level
                if (compareSpectraSimilarity) {
                    DataPoint[] rowDPs = null;
                    DataPoint[] candidateDPs = null;
                    SpectralSimilarity sim = null;
                    // get data points of mass list of the representative scans
                    if (msLevel == 1) {
                        rowDPs = row.getBestPeak().getRepresentativeScan().getMassList(massList).getDataPoints();
                        candidateDPs = candidate.getBestPeak().getRepresentativeScan().getMassList(massList).getDataPoints();
                    }
                    // get data points of mass list of the best fragmentation scans
                    if (msLevel == 2) {
                        if (row.getBestFragmentation() != null && candidate.getBestFragmentation() != null) {
                            rowDPs = row.getBestFragmentation().getMassList(massList).getDataPoints();
                            candidateDPs = candidate.getBestFragmentation().getMassList(massList).getDataPoints();
                        } else
                            continue;
                    }
                    // compare mass list data points of selected scans
                    if (rowDPs != null && candidateDPs != null) {
                        // calculate similarity using SimilarityFunction
                        sim = createSimilarity(rowDPs, candidateDPs);
                        // user set threshold
                        if (sim == null) {
                            continue;
                        }
                    }
                }
                RowVsRowScore score = new RowVsRowScore(row, candidate, RangeUtils.rangeLength(mzRange) / 2.0, mzWeight, RangeUtils.rangeLength(rtRange) / 2.0, rtWeight);
                scoreSet.add(score);
            }
            processedRows++;
        }
        // Create a table of mappings for best scores
        Hashtable<PeakListRow, PeakListRow> alignmentMapping = new Hashtable<PeakListRow, PeakListRow>();
        // Iterate scores by descending order
        Iterator<RowVsRowScore> scoreIterator = scoreSet.iterator();
        while (scoreIterator.hasNext()) {
            RowVsRowScore score = scoreIterator.next();
            // Check if the row is already mapped
            if (alignmentMapping.containsKey(score.getPeakListRow()))
                continue;
            // Check if the aligned row is already filled
            if (alignmentMapping.containsValue(score.getAlignedRow()))
                continue;
            alignmentMapping.put(score.getPeakListRow(), score.getAlignedRow());
        }
        // Align all rows using mapping
        for (PeakListRow row : allRows) {
            PeakListRow targetRow = alignmentMapping.get(row);
            // If we have no mapping for this row, add a new one
            if (targetRow == null) {
                targetRow = new SimplePeakListRow(newRowID);
                newRowID++;
                alignedPeakList.addRow(targetRow);
            }
            // Add all peaks from the original row to the aligned row
            for (RawDataFile file : row.getRawDataFiles()) {
                targetRow.addPeak(file, row.getPeak(file));
            }
            // Add all non-existing identities from the original row to the
            // aligned row
            PeakUtils.copyPeakListRowProperties(row, targetRow);
            processedRows++;
        }
    }
    // Next feature list
    // Add new aligned feature list to the project
    project.addPeakList(alignedPeakList);
    // Add task description to peakList
    alignedPeakList.addDescriptionOfAppliedTask(new SimplePeakListAppliedMethod("Join aligner", parameters));
    logger.info("Finished join aligner");
    setStatus(TaskStatus.FINISHED);
}

Example 25 with SimplePeakList

use of net.sf.mzmine.datamodel.impl.SimplePeakList in project mzmine2 by mzmine.

the class ScoreAligner method align.

/*
   * (non-Javadoc)
   * 
   * @see gcgcaligner.AbstractAligner#align()
   */
public PeakList align() {
    if (// Do the actual alignment if we already do not
    alignment == null) // have the result
    {
        Vector<RawDataFile> allDataFiles = new Vector<RawDataFile>();
        for (PeakList list : this.originalPeakList) {
            allDataFiles.addAll(Arrays.asList(list.getRawDataFiles()));
        }
        peaksTotal = 0;
        for (int i = 0; i < peakList.size(); i++) {
            peaksTotal += peakList.get(i).size();
        }
        alignment = new SimplePeakList(params.getParameter(PathAlignerParameters.peakListName).getValue(), allDataFiles.toArray(new RawDataFile[0]));
        List<AlignmentPath> addedPaths = getAlignmentPaths();
        int ID = 1;
        for (AlignmentPath p : addedPaths) {
            // Convert alignments to original order of files and add them to
            // final
            // Alignment data structure
            PeakListRow row = (PeakListRow) p.convertToAlignmentRow(ID++);
            alignment.addRow(row);
        }
    }
    PeakList curAlignment = alignment;
    return curAlignment;
}