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

Example 1 with SimplePeakIdentity

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

the class FormulaPredictionPeakListTask method run.

/**
 * @see java.lang.Runnable#run()
 */
@Override
public void run() {
    setStatus(TaskStatus.PROCESSING);
    totalRows = peakList.getNumberOfRows();
    for (PeakListRow row : peakList.getRows()) {
        if (row.getPeakIdentities().length > 0) {
            continue;
        }
        this.searchedMass = (row.getAverageMZ() - ionType.getAddedMass()) * charge;
        message = "Formula prediction for " + MZmineCore.getConfiguration().getMZFormat().format(searchedMass);
        massRange = mzTolerance.getToleranceRange(searchedMass);
        IChemObjectBuilder builder = SilentChemObjectBuilder.getInstance();
        generator = new MolecularFormulaGenerator(builder, massRange.lowerEndpoint(), massRange.upperEndpoint(), elementCounts);
        IMolecularFormula cdkFormula;
        // create a map to store ResultFormula and relative mass deviation for sorting
        Map<Double, String> possibleFormulas = new TreeMap<>();
        while ((cdkFormula = generator.getNextFormula()) != null) {
            if (isCanceled())
                return;
            // Mass is ok, so test other constraints
            if (checkConstraints(cdkFormula, row) == true) {
                String formula = MolecularFormulaManipulator.getString(cdkFormula);
                // calc rel mass deviation
                Double relMassDev = ((searchedMass - (FormulaUtils.calculateExactMass(formula))) / searchedMass) * 1000000;
                // write to map
                possibleFormulas.put(relMassDev, formula);
            }
        }
        if (isCanceled())
            return;
        // create a map to store ResultFormula and relative mass deviation for sorting
        Map<Double, String> possibleFormulasSorted = new TreeMap<>((Comparator<Double>) (o1, o2) -> Double.compare(Math.abs(o1), Math.abs(o2)));
        possibleFormulasSorted.putAll(possibleFormulas);
        // Add the new formula entry top results
        int ctr = 0;
        for (Map.Entry<Double, String> entry : possibleFormulasSorted.entrySet()) {
            if (ctr < maxBestFormulasPerPeak) {
                SimplePeakIdentity newIdentity = new SimplePeakIdentity(entry.getValue(), entry.getValue(), this.getClass().getName(), null, null);
                row.addPeakIdentity(newIdentity, false);
                ctr++;
            }
        }
        if (isCanceled())
            return;
        finishedRows++;
    }
    if (isCanceled())
        return;
    logger.finest("Finished formula search for all the peaks");
    setStatus(TaskStatus.FINISHED);
}

Example 2 with SimplePeakIdentity

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

the class LipidSearchTask method searchModifications.

private void searchModifications(PeakListRow rows, double lipidIonMass, LipidIdentity lipid, double[] lipidModificationMasses, Range<Double> mzTolModification) {
    for (int j = 0; j < lipidModificationMasses.length; j++) {
        if (mzTolModification.contains(lipidIonMass + (lipidModificationMasses[j]))) {
            // Calc relativ mass deviation
            double relMassDev = ((lipidIonMass + (lipidModificationMasses[j]) - rows.getAverageMZ()) / (lipidIonMass + lipidModificationMasses[j])) * 1000000;
            // Add row identity
            rows.addPeakIdentity(new SimplePeakIdentity(lipid + " " + lipidModification[j]), false);
            rows.setComment("Ionization: " + ionizationType.getAdduct() + " " + lipidModification[j] + ", Δ " + NumberFormat.getInstance().format(relMassDev) + " ppm");
            logger.info("Found modified lipid: " + lipid.getName() + " " + lipidModification[j] + ", Δ " + NumberFormat.getInstance().format(relMassDev) + " ppm");
            // Notify the GUI about the change in the project
            MZmineCore.getProjectManager().getCurrentProject().notifyObjectChanged(rows, false);
        }
    }
}

Example 3 with SimplePeakIdentity

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

the class CustomDBSearchTask method processOneLine.

private void processOneLine(String[] values) {
    int numOfColumns = Math.min(fieldOrder.length, values.length);
    String lineID = null, lineName = null, lineFormula = null;
    double lineMZ = 0, lineRT = 0;
    for (int i = 0; i < numOfColumns; i++) {
        if (fieldOrder[i] == FieldItem.FIELD_ID)
            lineID = values[i];
        if (fieldOrder[i] == FieldItem.FIELD_NAME)
            lineName = values[i];
        if (fieldOrder[i] == FieldItem.FIELD_FORMULA)
            lineFormula = values[i];
        if (fieldOrder[i] == FieldItem.FIELD_MZ)
            lineMZ = Double.parseDouble(values[i]);
        if (fieldOrder[i] == FieldItem.FIELD_RT)
            lineRT = Double.parseDouble(values[i]);
    }
    SimplePeakIdentity newIdentity = new SimplePeakIdentity(lineName, lineFormula, dataBaseFile.getName(), lineID, null);
    for (PeakListRow peakRow : peakList.getRows()) {
        Range<Double> mzRange = mzTolerance.getToleranceRange(peakRow.getAverageMZ());
        Range<Double> rtRange = rtTolerance.getToleranceRange(peakRow.getAverageRT());
        boolean mzMatches = (lineMZ == 0d) || mzRange.contains(lineMZ);
        boolean rtMatches = (lineRT == 0d) || rtRange.contains(lineRT);
        if (mzMatches && rtMatches) {
            logger.finest("Found compound " + lineName + " (m/z " + lineMZ + ", RT " + lineRT + ")");
            // add new identity to the row
            peakRow.addPeakIdentity(newIdentity, false);
            // Notify the GUI about the change in the project
            MZmineCore.getProjectManager().getCurrentProject().notifyObjectChanged(peakRow, false);
        }
    }
}

Example 4 with SimplePeakIdentity

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

the class CameraSearchTask method addPseudoSpectraIdentities.

/**
 * Add pseudo-spectra identities.
 *
 * @param peaks peaks to annotate with identities.
 * @param spectraExp the pseudo-spectra ids vector.
 * @param isotopeExp the isotopes vector.
 */
private void addPseudoSpectraIdentities(final Feature[] peaks, final int[] spectra, final String[] isotopes, final String[] adducts) {
    // Add identities for each peak.
    int peakIndex = 0;
    for (final Feature peak : peaks) {
        // Create pseudo-spectrum identity
        final SimplePeakIdentity identity = new SimplePeakIdentity("Pseudo-spectrum #" + String.format("%03d", spectra[peakIndex]));
        identity.setPropertyValue(PeakIdentity.PROPERTY_METHOD, "Bioconductor CAMERA");
        // Add isotope info, if any.
        if (isotopes != null) {
            final String isotope = isotopes[peakIndex].trim();
            if (isotope.length() > 0) {
                // Parse the isotope pattern.
                final Matcher matcher = ISOTOPE_PATTERN.matcher(isotope);
                if (matcher.matches()) {
                    // identity.setPropertyValue("Isotope", matcher.group(1));
                    identity.setPropertyValue("Isotope", isotope);
                } else {
                    LOG.warning("Irregular isotope value: " + isotope);
                }
            }
        }
        if (adducts != null) {
            final String adduct = adducts[peakIndex].trim();
            if (adduct.length() > 0)
                identity.setPropertyValue("Adduct", adduct);
        }
        // Add identity to peak's row.
        PeakListRow row = peakList.getPeakRow(peak);
        for (PeakIdentity peakIdentity : row.getPeakIdentities()) row.removePeakIdentity(peakIdentity);
        peakList.getPeakRow(peak).addPeakIdentity(identity, true);
        peakIndex++;
    }
}

Example 5 with SimplePeakIdentity

use of net.sf.mzmine.datamodel.impl.SimplePeakIdentity 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);
}