Examples with PeakListAppliedMethod net.sf.mzmine.datamodel.PeakList.PeakListAppliedMethod used on opensource projects

Example 6 with PeakListAppliedMethod

use of net.sf.mzmine.datamodel.PeakList.PeakListAppliedMethod in project mzmine2 by mzmine.

the class ShapeModelerTask method run.

public void run() {
    setStatus(TaskStatus.PROCESSING);
    Class<?> shapeModelClass = shapeModelerType.getModelClass();
    Constructor<?> shapeModelConstruct;
    shapeModelConstruct = shapeModelClass.getConstructors()[0];
    // Get data file information
    RawDataFile dataFile = originalPeakList.getRawDataFile(0);
    // Create new feature list
    newPeakList = new SimplePeakList(originalPeakList + " " + suffix, dataFile);
    totalRows = originalPeakList.getNumberOfRows();
    int[] scanNumbers;
    double[] retentionTimes, intensities;
    SimplePeakListRow newRow;
    for (PeakListRow row : originalPeakList.getRows()) {
        if (isCanceled())
            return;
        newRow = new SimplePeakListRow(newPeakID);
        try {
            for (Feature peak : row.getPeaks()) {
                // Load the intensities into array
                dataFile = peak.getDataFile();
                scanNumbers = peak.getScanNumbers();
                retentionTimes = new double[scanNumbers.length];
                for (int i = 0; i < scanNumbers.length; i++) retentionTimes[i] = dataFile.getScan(scanNumbers[i]).getRetentionTime();
                intensities = new double[scanNumbers.length];
                for (int i = 0; i < scanNumbers.length; i++) {
                    DataPoint dp = peak.getDataPoint(scanNumbers[i]);
                    if (dp != null)
                        intensities[i] = dp.getIntensity();
                    else
                        intensities[i] = 0;
                }
                Feature shapePeak = (Feature) shapeModelConstruct.newInstance(peak, scanNumbers, intensities, retentionTimes, resolution);
                newRow.addPeak(shapePeak.getDataFile(), shapePeak);
            }
        } catch (Exception e) {
            String message = "Error trying to make an instance of shape model class " + shapeModelClass;
            MZmineCore.getDesktop().displayErrorMessage(MZmineCore.getDesktop().getMainWindow(), message);
            logger.severe(message);
            return;
        }
        newPeakList.addRow(newRow);
        newPeakID++;
        processedRows++;
    }
    // Add new peaklist to the project
    project.addPeakList(newPeakList);
    // Add quality parameters to peaks
    QualityParameters.calculateQualityParameters(newPeakList);
    // Remove the original peaklist if requested
    if (removeOriginal)
        project.removePeakList(originalPeakList);
    // Load previous applied methods
    for (PeakListAppliedMethod proc : originalPeakList.getAppliedMethods()) {
        newPeakList.addDescriptionOfAppliedTask(proc);
    }
    // Add task description to peakList
    newPeakList.addDescriptionOfAppliedTask(new SimplePeakListAppliedMethod("Peaks shaped by " + shapeModelerType + " function", parameters));
    logger.finest("Finished peak shape modeler " + processedRows + " rows processed");
    setStatus(TaskStatus.FINISHED);
}

Example 7 with PeakListAppliedMethod

use of net.sf.mzmine.datamodel.PeakList.PeakListAppliedMethod in project mzmine2 by mzmine.

the class PeakExtenderTask method run.

/**
 * @see Runnable#run()
 */
public void run() {
    setStatus(TaskStatus.PROCESSING);
    logger.info("Running peak extender on " + peakList);
    // We assume source peakList contains one datafile
    RawDataFile dataFile = peakList.getRawDataFile(0);
    // Create a new deisotoped peakList
    extendedPeakList = new SimplePeakList(peakList + " " + suffix, peakList.getRawDataFiles());
    // Sort peaks by descending height
    Feature[] sortedPeaks = peakList.getPeaks(dataFile);
    Arrays.sort(sortedPeaks, new PeakSorter(SortingProperty.Height, SortingDirection.Descending));
    // Loop through all peaks
    totalPeaks = sortedPeaks.length;
    Feature oldPeak;
    for (int ind = 0; ind < totalPeaks; ind++) {
        if (isCanceled())
            return;
        oldPeak = sortedPeaks[ind];
        if (oldPeak.getHeight() >= minimumHeight) {
            Feature newPeak = this.getExtendedPeak(oldPeak);
            // Get previous pekaListRow
            PeakListRow oldRow = peakList.getPeakRow(oldPeak);
            // keep old ID
            int oldID = oldRow.getID();
            SimplePeakListRow newRow = new SimplePeakListRow(oldID);
            PeakUtils.copyPeakListRowProperties(oldRow, newRow);
            newRow.addPeak(dataFile, newPeak);
            extendedPeakList.addRow(newRow);
        }
        // Update completion rate
        processedPeaks++;
    }
    // Add new peakList to the project
    project.addPeakList(extendedPeakList);
    // Add quality parameters to peaks
    QualityParameters.calculateQualityParameters(extendedPeakList);
    // Load previous applied methods
    for (PeakListAppliedMethod proc : peakList.getAppliedMethods()) {
        extendedPeakList.addDescriptionOfAppliedTask(proc);
    }
    // Add task description to peakList
    extendedPeakList.addDescriptionOfAppliedTask(new SimplePeakListAppliedMethod("Peak extender", parameters));
    // Remove the original peakList if requested
    if (removeOriginal)
        project.removePeakList(peakList);
    logger.info("Finished peak extender on " + peakList);
    setStatus(TaskStatus.FINISHED);
}

Example 8 with PeakListAppliedMethod

use of net.sf.mzmine.datamodel.PeakList.PeakListAppliedMethod in project mzmine2 by mzmine.

the class NeutralLossFilterTask method addResultToProject.

/**
 * Add feature list to project, delete old if requested, add description to result
 */
public void addResultToProject() {
    // Add new peakList to the project
    project.addPeakList(resultPeakList);
    // Load previous applied methods
    for (PeakListAppliedMethod proc : peakList.getAppliedMethods()) {
        resultPeakList.addDescriptionOfAppliedTask(proc);
    }
    // Add task description to peakList
    resultPeakList.addDescriptionOfAppliedTask(new SimplePeakListAppliedMethod("NeutralLossFilter", parameters));
}

Example 9 with PeakListAppliedMethod

use of net.sf.mzmine.datamodel.PeakList.PeakListAppliedMethod in project mzmine2 by mzmine.

the class PeakComparisonRowFilterTask method filterPeakListRows.

/**
 * Filter the feature list rows by comparing peaks within a row.
 *
 * @param peakList feature list to filter.
 * @return a new feature list with rows of the original feature list that pass the filtering.
 */
private PeakList filterPeakListRows(final PeakList peakList) {
    // Create new feature list.
    final PeakList newPeakList = new SimplePeakList(peakList.getName() + ' ' + parameters.getParameter(PeakComparisonRowFilterParameters.SUFFIX).getValue(), peakList.getRawDataFiles());
    // Copy previous applied methods.
    for (final PeakListAppliedMethod method : peakList.getAppliedMethods()) {
        newPeakList.addDescriptionOfAppliedTask(method);
    }
    // Add task description to peakList.
    newPeakList.addDescriptionOfAppliedTask(new SimplePeakListAppliedMethod(getTaskDescription(), parameters));
    // Get parameters.
    final boolean evalutateFoldChange = parameters.getParameter(PeakComparisonRowFilterParameters.FOLD_CHANGE).getValue();
    final boolean evalutatePPMdiff = parameters.getParameter(PeakComparisonRowFilterParameters.MZ_PPM_DIFF).getValue();
    final boolean evalutateRTdiff = parameters.getParameter(PeakComparisonRowFilterParameters.RT_DIFF).getValue();
    final int columnIndex1 = parameters.getParameter(PeakComparisonRowFilterParameters.COLUMN_INDEX_1).getValue();
    final int columnIndex2 = parameters.getParameter(PeakComparisonRowFilterParameters.COLUMN_INDEX_2).getValue();
    final Range<Double> foldChangeRange = parameters.getParameter(PeakComparisonRowFilterParameters.FOLD_CHANGE).getEmbeddedParameter().getValue();
    final Range<Double> ppmDiffRange = parameters.getParameter(PeakComparisonRowFilterParameters.FOLD_CHANGE).getEmbeddedParameter().getValue();
    final Range<Double> rtDiffRange = parameters.getParameter(PeakComparisonRowFilterParameters.FOLD_CHANGE).getEmbeddedParameter().getValue();
    // Setup variables
    final PeakListRow[] rows = peakList.getRows();
    RawDataFile rawDataFile1;
    RawDataFile rawDataFile2;
    Feature peak1;
    Feature peak2;
    totalRows = rows.length;
    final RawDataFile[] rawDataFiles = peakList.getRawDataFiles();
    boolean allCriteriaMatched = true;
    // doesn't exist.
    if (columnIndex1 > rawDataFiles.length) {
        setErrorMessage("Column 1 set too large.");
        setStatus(TaskStatus.ERROR);
        return null;
    }
    if (columnIndex2 > rawDataFiles.length) {
        setErrorMessage("Column 2 set too large.");
        setStatus(TaskStatus.ERROR);
        return null;
    }
    // Loop over the rows & filter
    for (processedRows = 0; !isCanceled() && processedRows < totalRows; processedRows++) {
        if (isCanceled())
            return null;
        allCriteriaMatched = true;
        // Default value in case of null peak
        double peak1Area = 1.0;
        double peak2Area = 1.0;
        double peak1MZ = -1.0;
        double peak2MZ = -1.0;
        double peak1RT = -1.0;
        double peak2RT = -1.0;
        double foldChange = 0.0;
        double ppmDiff = 0.0;
        double rtDiff = 0.0;
        final PeakListRow row = rows[processedRows];
        rawDataFile1 = rawDataFiles[columnIndex1];
        rawDataFile2 = rawDataFiles[columnIndex2];
        peak1 = row.getPeak(rawDataFile1);
        peak2 = row.getPeak(rawDataFile2);
        if (peak1 != null) {
            peak1Area = peak1.getArea();
            peak1MZ = peak1.getMZ();
            peak1RT = peak1.getRT();
        }
        if (peak2 != null) {
            peak2Area = peak2.getArea();
            peak2MZ = peak2.getMZ();
            peak2RT = peak2.getRT();
        }
        // Fold change criteria checking.
        if (evalutateFoldChange) {
            foldChange = Math.log(peak1Area / peak2Area) / Math.log(2);
            if (!foldChangeRange.contains(foldChange))
                allCriteriaMatched = false;
            // PPM difference evaluation
            if (evalutatePPMdiff) {
                ppmDiff = (peak1MZ - peak2MZ) / peak1MZ * 1E6;
                if (!ppmDiffRange.contains(ppmDiff))
                    allCriteriaMatched = false;
            }
            // RT difference evaluation
            if (evalutateRTdiff) {
                rtDiff = peak1RT - peak2RT;
                if (!rtDiffRange.contains(rtDiff))
                    allCriteriaMatched = false;
            }
        }
        // Good row?
        if (allCriteriaMatched)
            newPeakList.addRow(copyPeakRow(row));
    }
    return newPeakList;
}

Example 10 with PeakListAppliedMethod

use of net.sf.mzmine.datamodel.PeakList.PeakListAppliedMethod in project mzmine2 by mzmine.

the class DuplicateFilterTask method filterDuplicatePeakListRows.

/**
 * Filter our duplicate feature list rows.
 *
 * @param origPeakList the original feature list.
 * @param suffix the suffix to apply to the new feature list name.
 * @param mzTolerance m/z tolerance.
 * @param rtTolerance RT tolerance.
 * @param requireSameId must duplicate peaks have the same identities?
 * @return the filtered feature list.
 */
private PeakList filterDuplicatePeakListRows(final PeakList origPeakList, final String suffix, final MZTolerance mzTolerance, final RTTolerance rtTolerance, final boolean requireSameId, FilterMode mode) {
    final PeakListRow[] peakListRows = origPeakList.getRows();
    final int rowCount = peakListRows.length;
    RawDataFile[] rawFiles = origPeakList.getRawDataFiles();
    // Create the new feature list.
    final PeakList newPeakList = new SimplePeakList(origPeakList + " " + suffix, origPeakList.getRawDataFiles());
    // sort rows
    if (mode.equals(FilterMode.OLD_AVERAGE))
        Arrays.sort(peakListRows, new PeakListRowSorter(SortingProperty.Area, SortingDirection.Descending));
    else
        Arrays.sort(peakListRows, new PeakListRowSorter(SortingProperty.ID, SortingDirection.Ascending));
    // filter by average mz and rt
    boolean filterByAvgRTMZ = !mode.equals(FilterMode.SINGLE_FEATURE);
    // Loop through all feature list rows
    processedRows = 0;
    int n = 0;
    totalRows = rowCount;
    for (int firstRowIndex = 0; !isCanceled() && firstRowIndex < rowCount; firstRowIndex++) {
        final PeakListRow mainRow = peakListRows[firstRowIndex];
        if (mainRow != null) {
            // copy first row
            PeakListRow firstRow = copyRow(mainRow);
            for (int secondRowIndex = firstRowIndex + 1; !isCanceled() && secondRowIndex < rowCount; secondRowIndex++) {
                final PeakListRow secondRow = peakListRows[secondRowIndex];
                if (secondRow != null) {
                    // Compare identifications
                    final boolean sameID = !requireSameId || PeakUtils.compareIdentities(firstRow, secondRow);
                    boolean sameMZRT = // average or single feature
                    filterByAvgRTMZ ? checkSameAverageRTMZ(firstRow, secondRow, mzTolerance, rtTolerance) : checkSameSingleFeatureRTMZ(rawFiles, firstRow, secondRow, mzTolerance, rtTolerance);
                    // Duplicate peaks?
                    if (sameID && sameMZRT) {
                        // create consensus row in new filter
                        if (!mode.equals(FilterMode.OLD_AVERAGE)) {
                            // copy all detected features of row2 into row1
                            // to exchange gap-filled against detected features
                            createConsensusFirstRow(rawFiles, firstRow, secondRow);
                        }
                        // second row deleted
                        n++;
                        peakListRows[secondRowIndex] = null;
                    }
                }
            }
            // add to new list
            newPeakList.addRow(firstRow);
        }
        processedRows++;
    }
    // finalize
    if (!isCanceled()) {
        // Load previous applied methods.
        for (final PeakListAppliedMethod method : origPeakList.getAppliedMethods()) {
            newPeakList.addDescriptionOfAppliedTask(method);
        }
        // Add task description to peakList
        newPeakList.addDescriptionOfAppliedTask(new SimplePeakListAppliedMethod("Duplicate feature list rows filter", parameters));
        LOG.info("Removed " + n + " duplicate rows");
    }
    return newPeakList;
}