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Example 31 with RawDataFile

use of net.sf.mzmine.datamodel.RawDataFile in project mzmine2 by mzmine.

the class MultiRawDataLearnerTask method run.

/**
 * @see Runnable#run()
 */
@Override
public void run() {
    setStatus(TaskStatus.PROCESSING);
    logger.info("Running learner task on " + peakList);
    // Create a new results peakList which is added at the end
    resultPeakList = new SimplePeakList(peakList + " " + suffix, peakList.getRawDataFiles());
    /**
     * - A PeakList is a list of Features (peak in retention time dimension with accurate m/z)<br>
     * ---- contains one or multiple RawDataFiles <br>
     * ---- access mean retention time, mean m/z, maximum intensity, ...<br>
     * - A RawDataFile holds a full chromatographic run with all ms scans<br>
     * ---- Each Scan and the underlying raw data can be accessed <br>
     * ---- Scans can be filtered by MS level, polarity, ...<br>
     */
    // get all rows and sort by m/z
    PeakListRow[] rows = peakList.getRows();
    Arrays.sort(rows, new PeakListRowSorter(SortingProperty.MZ, SortingDirection.Ascending));
    // number of rawFiles is 1 prior to peaklist alignment
    RawDataFile[] rawFiles = peakList.getRawDataFiles();
    boolean isAlignedPeakList = rawFiles.length > 1;
    totalRows = rows.length;
    // loop through all rows
    for (PeakListRow row : rows) {
        // loop through all raw data files
        for (RawDataFile raw : rawFiles) {
            // check for cancelled state and stop
            if (isCanceled())
                return;
            // current peak
            Feature peak = row.getPeak(raw);
            // check for peak in row for specific raw file
            if (peak != null) {
                double mz = peak.getMZ();
                double intensity = peak.getHeight();
                double rt = peak.getRT();
            // do stuff
            // ...
            }
        }
        // Update completion rate
        processedRows++;
    }
    // add to project
    addResultToProject();
    logger.info("Finished on " + peakList);
    setStatus(TaskStatus.FINISHED);
}
Also used : PeakListRow(net.sf.mzmine.datamodel.PeakListRow) RawDataFile(net.sf.mzmine.datamodel.RawDataFile) SimplePeakList(net.sf.mzmine.datamodel.impl.SimplePeakList) Feature(net.sf.mzmine.datamodel.Feature) PeakListRowSorter(net.sf.mzmine.util.PeakListRowSorter)

Example 32 with RawDataFile

use of net.sf.mzmine.datamodel.RawDataFile in project mzmine2 by mzmine.

the class HeatMapTask method groupingDataset.

private double[][] groupingDataset(UserParameter<?, ?> selectedParameter, String referenceGroup) {
    // Collect all data files
    Vector<RawDataFile> allDataFiles = new Vector<RawDataFile>();
    DescriptiveStatistics meanControlStats = new DescriptiveStatistics();
    DescriptiveStatistics meanGroupStats = new DescriptiveStatistics();
    allDataFiles.addAll(Arrays.asList(peakList.getRawDataFiles()));
    // Determine the reference group and non reference group (the rest of
    // the samples) for raw data files
    List<RawDataFile> referenceDataFiles = new ArrayList<RawDataFile>();
    List<RawDataFile> nonReferenceDataFiles = new ArrayList<RawDataFile>();
    List<String> groups = new ArrayList<String>();
    for (RawDataFile rawDataFile : allDataFiles) {
        Object paramValue = project.getParameterValue(selectedParameter, rawDataFile);
        if (!groups.contains(String.valueOf(paramValue))) {
            groups.add(String.valueOf(paramValue));
        }
        if (String.valueOf(paramValue).equals(referenceGroup)) {
            referenceDataFiles.add(rawDataFile);
        } else {
            nonReferenceDataFiles.add(rawDataFile);
        }
    }
    int numRows = 0;
    for (int row = 0; row < peakList.getNumberOfRows(); row++) {
        if (!onlyIdentified || (onlyIdentified && peakList.getRow(row).getPeakIdentities().length > 0)) {
            numRows++;
        }
    }
    // Create a new aligned feature list with all the samples if the reference
    // group has to be shown or with only
    // the non reference group if not.
    double[][] dataMatrix = new double[groups.size() - 1][numRows];
    pValueMatrix = new String[groups.size() - 1][numRows];
    // data files that should be in the heat map
    List<RawDataFile> shownDataFiles = nonReferenceDataFiles;
    for (int row = 0, rowIndex = 0; row < peakList.getNumberOfRows(); row++) {
        PeakListRow rowPeak = peakList.getRow(row);
        if (!onlyIdentified || (onlyIdentified && rowPeak.getPeakIdentities().length > 0)) {
            // Average area or height of the reference group
            meanControlStats.clear();
            for (int column = 0; column < referenceDataFiles.size(); column++) {
                if (rowPeak.getPeak(referenceDataFiles.get(column)) != null) {
                    if (area) {
                        meanControlStats.addValue(rowPeak.getPeak(referenceDataFiles.get(column)).getArea());
                    } else {
                        meanControlStats.addValue(rowPeak.getPeak(referenceDataFiles.get(column)).getHeight());
                    }
                }
            }
            // Divide the area or height of each peak by the average of the
            // area or height of the reference peaks in each row
            int columnIndex = 0;
            for (int column = 0; column < groups.size(); column++) {
                String group = groups.get(column);
                meanGroupStats.clear();
                if (!group.equals(referenceGroup)) {
                    for (int dataColumn = 0; dataColumn < shownDataFiles.size(); dataColumn++) {
                        Object paramValue = project.getParameterValue(selectedParameter, shownDataFiles.get(dataColumn));
                        if (rowPeak.getPeak(shownDataFiles.get(dataColumn)) != null && String.valueOf(paramValue).equals(group)) {
                            Feature peak = rowPeak.getPeak(shownDataFiles.get(dataColumn));
                            if (!Double.isInfinite(peak.getArea()) && !Double.isNaN(peak.getArea())) {
                                if (area) {
                                    meanGroupStats.addValue(peak.getArea());
                                } else {
                                    meanGroupStats.addValue(peak.getHeight());
                                }
                            }
                        }
                    }
                    double value = meanGroupStats.getMean() / meanControlStats.getMean();
                    if (meanGroupStats.getN() > 1 && meanControlStats.getN() > 1) {
                        pValueMatrix[columnIndex][rowIndex] = this.getPvalue(meanGroupStats, meanControlStats);
                    } else {
                        pValueMatrix[columnIndex][rowIndex] = "";
                    }
                    if (log) {
                        value = Math.log(value);
                    }
                    dataMatrix[columnIndex++][rowIndex] = value;
                }
            }
            rowIndex++;
        }
    }
    // deviation of each column
    if (scale) {
        scale(dataMatrix);
    }
    // Create two arrays: row and column names
    rowNames = new String[dataMatrix[0].length];
    colNames = new String[groups.size() - 1];
    int columnIndex = 0;
    for (String group : groups) {
        if (!group.equals(referenceGroup)) {
            colNames[columnIndex++] = group;
        }
    }
    for (int row = 0, rowIndex = 0; row < peakList.getNumberOfRows(); row++) {
        if (!onlyIdentified || (onlyIdentified && peakList.getRow(row).getPeakIdentities().length > 0)) {
            if (peakList.getRow(row).getPeakIdentities() != null && peakList.getRow(row).getPeakIdentities().length > 0) {
                rowNames[rowIndex++] = peakList.getRow(row).getPreferredPeakIdentity().getName();
            } else {
                rowNames[rowIndex++] = "Unknown";
            }
        }
    }
    return dataMatrix;
}
Also used : DescriptiveStatistics(org.apache.commons.math.stat.descriptive.DescriptiveStatistics) ArrayList(java.util.ArrayList) Feature(net.sf.mzmine.datamodel.Feature) PeakListRow(net.sf.mzmine.datamodel.PeakListRow) RawDataFile(net.sf.mzmine.datamodel.RawDataFile) Vector(java.util.Vector)

Example 33 with RawDataFile

use of net.sf.mzmine.datamodel.RawDataFile in project mzmine2 by mzmine.

the class SammonsDataset method run.

@Override
public void run() {
    setStatus(TaskStatus.PROCESSING);
    if (selectedRows.length == 0) {
        this.status = TaskStatus.ERROR;
        errorMessage = "No peaks selected for Sammons plot";
        return;
    }
    if (selectedRawDataFiles.length == 0) {
        this.status = TaskStatus.ERROR;
        errorMessage = "No raw data files selected for Sammons plot";
        return;
    }
    logger.info("Computing projection plot");
    // Generate matrix of raw data (input to Sammon's projection)
    boolean useArea = false;
    if (parameters.getParameter(ProjectionPlotParameters.peakMeasurementType).getValue() == PeakMeasurementType.AREA)
        useArea = true;
    double[][] rawData = new double[selectedRawDataFiles.length][selectedRows.length];
    for (int rowIndex = 0; rowIndex < selectedRows.length; rowIndex++) {
        PeakListRow peakListRow = selectedRows[rowIndex];
        for (int fileIndex = 0; fileIndex < selectedRawDataFiles.length; fileIndex++) {
            RawDataFile rawDataFile = selectedRawDataFiles[fileIndex];
            Feature p = peakListRow.getPeak(rawDataFile);
            if (p != null) {
                if (useArea)
                    rawData[fileIndex][rowIndex] = p.getArea();
                else
                    rawData[fileIndex][rowIndex] = p.getHeight();
            }
        }
    }
    int numComponents = xAxisDimension;
    if (yAxisDimension > numComponents)
        numComponents = yAxisDimension;
    // Scale data and do Sammon's mapping
    Preprocess.scaleToUnityVariance(rawData);
    Sammons sammonsProj = new Sammons(rawData);
    projectionStatus = sammonsProj.getProjectionStatus();
    sammonsProj.iterate(100);
    if (status == TaskStatus.CANCELED)
        return;
    double[][] result = sammonsProj.getState();
    if (status == TaskStatus.CANCELED)
        return;
    component1Coords = result[xAxisDimension - 1];
    component2Coords = result[yAxisDimension - 1];
    ProjectionPlotWindow newFrame = new ProjectionPlotWindow(peakList, this, parameters);
    newFrame.setVisible(true);
    setStatus(TaskStatus.FINISHED);
    logger.info("Finished computing projection plot.");
}
Also used : PeakListRow(net.sf.mzmine.datamodel.PeakListRow) RawDataFile(net.sf.mzmine.datamodel.RawDataFile) Sammons(jmprojection.Sammons) Feature(net.sf.mzmine.datamodel.Feature)

Example 34 with RawDataFile

use of net.sf.mzmine.datamodel.RawDataFile in project mzmine2 by mzmine.

the class PeakLearnerTask method run.

/**
 * @see Runnable#run()
 */
@Override
public void run() {
    setStatus(TaskStatus.PROCESSING);
    logger.info("Running learner task on " + peakList);
    // Create a new results peakList which is added at the end
    resultPeakList = new SimplePeakList(peakList + " " + suffix, peakList.getRawDataFiles());
    /**
     * - A PeakList is a list of Features (peak in retention time dimension with accurate m/z)<br>
     * ---- contains one or multiple RawDataFiles <br>
     * ---- access mean retention time, mean m/z, maximum intensity, ...<br>
     * - A RawDataFile holds a full chromatographic run with all ms scans<br>
     * ---- Each Scan and the underlying raw data can be accessed <br>
     * ---- Scans can be filtered by MS level, polarity, ...<br>
     */
    // is the data provided by peaklist enough for this task or
    // do you want to work on one raw data file or on all files?
    RawDataFile dataFile = peakList.getRawDataFile(0);
    // get all peaks of a raw data file
    // Sort peaks by ascending mz
    Feature[] sortedPeaks = peakList.getPeaks(dataFile);
    Arrays.sort(sortedPeaks, new PeakSorter(SortingProperty.MZ, SortingDirection.Ascending));
    // Loop through all peaks
    totalPeaks = sortedPeaks.length;
    for (int i = 0; i < totalPeaks; i++) {
        // check for cancelled state and stop
        if (isCanceled())
            return;
        // current peak
        Feature aPeak = sortedPeaks[i];
        // do stuff
        // ...
        // add row to result feature list
        PeakListRow row = peakList.getPeakRow(aPeak);
        row = copyPeakRow(row);
        resultPeakList.addRow(row);
        // Update completion rate
        processedPeaks++;
    }
    // add to project
    addResultToProject();
    logger.info("Finished on " + peakList);
    setStatus(TaskStatus.FINISHED);
}
Also used : SimplePeakListRow(net.sf.mzmine.datamodel.impl.SimplePeakListRow) PeakListRow(net.sf.mzmine.datamodel.PeakListRow) RawDataFile(net.sf.mzmine.datamodel.RawDataFile) PeakSorter(net.sf.mzmine.util.PeakSorter) SimplePeakList(net.sf.mzmine.datamodel.impl.SimplePeakList) SimpleFeature(net.sf.mzmine.datamodel.impl.SimpleFeature) Feature(net.sf.mzmine.datamodel.Feature)

Example 35 with RawDataFile

use of net.sf.mzmine.datamodel.RawDataFile in project mzmine2 by mzmine.

the class ManualPeakPickerModule method runManualDetection.

public static ExitCode runManualDetection(RawDataFile[] dataFiles, PeakListRow peakListRow, PeakList peakList, PeakListTable table) {
    Range<Double> mzRange = null, rtRange = null;
    // Check the peaks for selected data files
    for (RawDataFile dataFile : dataFiles) {
        Feature peak = peakListRow.getPeak(dataFile);
        if (peak == null)
            continue;
        if ((mzRange == null) || (rtRange == null)) {
            mzRange = peak.getRawDataPointsMZRange();
            rtRange = peak.getRawDataPointsRTRange();
        } else {
            mzRange = mzRange.span(peak.getRawDataPointsMZRange());
            rtRange = rtRange.span(peak.getRawDataPointsRTRange());
        }
    }
    // If none of the data files had a peak, check the whole row
    if (mzRange == null) {
        for (Feature peak : peakListRow.getPeaks()) {
            if (peak == null)
                continue;
            if ((mzRange == null) || (rtRange == null)) {
                mzRange = peak.getRawDataPointsMZRange();
                rtRange = peak.getRawDataPointsRTRange();
            } else {
                mzRange = mzRange.span(peak.getRawDataPointsMZRange());
                rtRange = rtRange.span(peak.getRawDataPointsRTRange());
            }
        }
    }
    ManualPickerParameters parameters = new ManualPickerParameters();
    if (mzRange != null) {
        parameters.getParameter(ManualPickerParameters.retentionTimeRange).setValue(rtRange);
        parameters.getParameter(ManualPickerParameters.mzRange).setValue(mzRange);
    }
    ExitCode exitCode = parameters.showSetupDialog(MZmineCore.getDesktop().getMainWindow(), true);
    if (exitCode != ExitCode.OK)
        return exitCode;
    ManualPickerTask task = new ManualPickerTask(MZmineCore.getProjectManager().getCurrentProject(), peakListRow, dataFiles, parameters, peakList, table);
    MZmineCore.getTaskController().addTask(task);
    return exitCode;
}
Also used : RawDataFile(net.sf.mzmine.datamodel.RawDataFile) ExitCode(net.sf.mzmine.util.ExitCode) Feature(net.sf.mzmine.datamodel.Feature)

Aggregations

RawDataFile (net.sf.mzmine.datamodel.RawDataFile)185 Feature (net.sf.mzmine.datamodel.Feature)59 PeakListRow (net.sf.mzmine.datamodel.PeakListRow)52 DataPoint (net.sf.mzmine.datamodel.DataPoint)51 Scan (net.sf.mzmine.datamodel.Scan)40 ArrayList (java.util.ArrayList)33 PeakList (net.sf.mzmine.datamodel.PeakList)33 Nonnull (javax.annotation.Nonnull)24 SimpleDataPoint (net.sf.mzmine.datamodel.impl.SimpleDataPoint)24 SimplePeakList (net.sf.mzmine.datamodel.impl.SimplePeakList)24 SimplePeakListRow (net.sf.mzmine.datamodel.impl.SimplePeakListRow)22 Task (net.sf.mzmine.taskcontrol.Task)20 SimplePeakListAppliedMethod (net.sf.mzmine.datamodel.impl.SimplePeakListAppliedMethod)19 SimpleFeature (net.sf.mzmine.datamodel.impl.SimpleFeature)17 IOException (java.io.IOException)14 ParameterSet (net.sf.mzmine.parameters.ParameterSet)14 File (java.io.File)13 MassList (net.sf.mzmine.datamodel.MassList)13 PeakListAppliedMethod (net.sf.mzmine.datamodel.PeakList.PeakListAppliedMethod)13 TreeMap (java.util.TreeMap)10