Example usage for org.apache.commons.lang ArrayUtils toObject

Introduction

In this page you can find the example usage for org.apache.commons.lang ArrayUtils toObject.

Prototype

public static Boolean[] toObject(boolean[] array) 

Source Link

Document

Converts an array of primitive booleans to objects.

Usage

From source file:org.apereo.portal.tools.dbloader.DataXmlHandler.java

protected final void doInsert() {
    if (this.rowData.size() == 0) {
        this.logger
                .warn("Found a row with no data for table " + this.currentTable + ", the row will be ignored");
        return;//from w  w w  . j av a  2s . c om
    }

    final Map<String, Integer> columnInfo = this.tableColumnInfo.get(this.currentTable);

    final StringBuilder columns = new StringBuilder();
    final StringBuilder parameters = new StringBuilder();
    final Object[] values = new Object[this.rowData.size()];
    final int[] types = new int[this.rowData.size()];

    int index = 0;
    for (final Iterator<Entry<String, String>> rowIterator = this.rowData.entrySet().iterator(); rowIterator
            .hasNext();) {
        final Entry<String, String> row = rowIterator.next();
        final String columnName = row.getKey();
        columns.append(columnName);
        parameters.append("?");

        values[index] = row.getValue();
        types[index] = columnInfo.get(columnName);

        if (rowIterator.hasNext()) {
            columns.append(", ");
            parameters.append(", ");
        }

        index++;
    }

    final String sql = "INSERT INTO " + this.currentTable + " (" + columns + ") VALUES (" + parameters + ")";
    if (this.logger.isInfoEnabled()) {
        this.logger.info(sql + "\t" + Arrays.asList(values) + "\t" + Arrays.asList(ArrayUtils.toObject(types)));
    }

    this.transactionOperations.execute(new TransactionCallbackWithoutResult() {
        @Override
        protected void doInTransactionWithoutResult(TransactionStatus status) {
            jdbcOperations.update(sql, values, types);
        }
    });
}

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From source file:org.broadinstitute.gatk.tools.walkers.variantrecalibration.VariantDataManager.java

public void normalizeData() {
    boolean foundZeroVarianceAnnotation = false;
    for (int iii = 0; iii < meanVector.length; iii++) {
        final double theMean = mean(iii, true);
        final double theSTD = standardDeviation(theMean, iii, true);
        logger.info(annotationKeys.get(iii)
                + String.format(": \t mean = %.2f\t standard deviation = %.2f", theMean, theSTD));
        if (Double.isNaN(theMean)) {
            throw new UserException.BadInput("Values for " + annotationKeys.get(iii)
                    + " annotation not detected for ANY training variant in the input callset. VariantAnnotator may be used to add these annotations.");
        }/*from  w  w  w  .j a v a2  s.  c o  m*/

        foundZeroVarianceAnnotation = foundZeroVarianceAnnotation || (theSTD < 1E-5);
        meanVector[iii] = theMean;
        varianceVector[iii] = theSTD;
        for (final VariantDatum datum : data) {
            // Transform each data point via: (x - mean) / standard deviation
            datum.annotations[iii] = (datum.isNull[iii] ? 0.1 * Utils.getRandomGenerator().nextGaussian()
                    : (datum.annotations[iii] - theMean) / theSTD);
        }
    }
    if (foundZeroVarianceAnnotation) {
        throw new UserException.BadInput(
                "Found annotations with zero variance. They must be excluded before proceeding.");
    }

    // trim data by standard deviation threshold and mark failing data for exclusion later
    for (final VariantDatum datum : data) {
        boolean remove = false;
        for (final double val : datum.annotations) {
            remove = remove || (Math.abs(val) > VRAC.STD_THRESHOLD);
        }
        datum.failingSTDThreshold = remove;
    }

    // re-order the data by increasing standard deviation so that the results don't depend on the order things were specified on the command line
    // standard deviation over the training points is used as a simple proxy for information content, perhaps there is a better thing to use here
    final List<Integer> theOrder = calculateSortOrder(meanVector);
    annotationKeys = reorderList(annotationKeys, theOrder);
    varianceVector = ArrayUtils.toPrimitive(reorderArray(ArrayUtils.toObject(varianceVector), theOrder));
    meanVector = ArrayUtils.toPrimitive(reorderArray(ArrayUtils.toObject(meanVector), theOrder));
    for (final VariantDatum datum : data) {
        datum.annotations = ArrayUtils
                .toPrimitive(reorderArray(ArrayUtils.toObject(datum.annotations), theOrder));
        datum.isNull = ArrayUtils.toPrimitive(reorderArray(ArrayUtils.toObject(datum.isNull), theOrder));
    }
    logger.info("Annotations are now ordered by their information content: " + annotationKeys.toString());
}

---

From source file:org.broadinstitute.sting.gatk.walkers.variantrecalibration.VariantDataManager.java

public void normalizeData() {
    boolean foundZeroVarianceAnnotation = false;
    for (int iii = 0; iii < meanVector.length; iii++) {
        final double theMean = mean(iii, true);
        final double theSTD = standardDeviation(theMean, iii, true);
        logger.info(annotationKeys.get(iii)
                + String.format(": \t mean = %.2f\t standard deviation = %.2f", theMean, theSTD));
        if (Double.isNaN(theMean)) {
            throw new UserException.BadInput("Values for " + annotationKeys.get(iii)
                    + " annotation not detected for ANY training variant in the input callset. VariantAnnotator may be used to add these annotations. See "
                    + HelpConstants.forumPost("discussion/49/using-variant-annotator"));
        }/*  w  ww.  ja v a  2 s. c  o m*/

        foundZeroVarianceAnnotation = foundZeroVarianceAnnotation || (theSTD < 1E-5);
        meanVector[iii] = theMean;
        varianceVector[iii] = theSTD;
        for (final VariantDatum datum : data) {
            // Transform each data point via: (x - mean) / standard deviation
            datum.annotations[iii] = (datum.isNull[iii]
                    ? 0.1 * GenomeAnalysisEngine.getRandomGenerator().nextGaussian()
                    : (datum.annotations[iii] - theMean) / theSTD);
        }
    }
    if (foundZeroVarianceAnnotation) {
        throw new UserException.BadInput(
                "Found annotations with zero variance. They must be excluded before proceeding.");
    }

    // trim data by standard deviation threshold and mark failing data for exclusion later
    for (final VariantDatum datum : data) {
        boolean remove = false;
        for (final double val : datum.annotations) {
            remove = remove || (Math.abs(val) > VRAC.STD_THRESHOLD);
        }
        datum.failingSTDThreshold = remove;
    }

    // re-order the data by increasing standard deviation so that the results don't depend on the order things were specified on the command line
    // standard deviation over the training points is used as a simple proxy for information content, perhaps there is a better thing to use here
    final List<Integer> theOrder = calculateSortOrder(meanVector);
    annotationKeys = reorderList(annotationKeys, theOrder);
    varianceVector = ArrayUtils.toPrimitive(reorderArray(ArrayUtils.toObject(varianceVector), theOrder));
    meanVector = ArrayUtils.toPrimitive(reorderArray(ArrayUtils.toObject(meanVector), theOrder));
    for (final VariantDatum datum : data) {
        datum.annotations = ArrayUtils
                .toPrimitive(reorderArray(ArrayUtils.toObject(datum.annotations), theOrder));
        datum.isNull = ArrayUtils.toPrimitive(reorderArray(ArrayUtils.toObject(datum.isNull), theOrder));
    }
    logger.info("Annotations are now ordered by their information content: " + annotationKeys.toString());
}

---

From source file:org.carbondata.core.reader.sortindex.CarbonDictionarySortIndexReaderImplTest.java

/**
 * Test to read the data from dictionary sort index file
 *
 * @throws Exception//from   w  ww .  j ava  2  s  .  c o  m
 */
@Test
public void read() throws Exception {
    deleteStorePath();
    CarbonTableIdentifier carbonTableIdentifier = new CarbonTableIdentifier("testSchema", "carbon");
    CarbonDictionarySortIndexWriter dictionarySortIndexWriter = new CarbonDictionarySortIndexWriterImpl(
            carbonTableIdentifier, "Name", hdfsStorePath);
    List<int[]> expectedData = prepareExpectedData();

    List<Integer> sortIndex = Arrays.asList(ArrayUtils.toObject(expectedData.get(0)));
    List<Integer> invertedSortIndex = Arrays.asList(ArrayUtils.toObject(expectedData.get(1)));
    dictionarySortIndexWriter.writeSortIndex(sortIndex);
    dictionarySortIndexWriter.writeInvertedSortIndex(invertedSortIndex);
    dictionarySortIndexWriter.close();
    CarbonDictionarySortIndexReader dictionarySortIndexReader = new CarbonDictionarySortIndexReaderImpl(
            carbonTableIdentifier, "Name", hdfsStorePath);
    List<Integer> actualSortIndex = dictionarySortIndexReader.readSortIndex();
    List<Integer> actualInvertedSortIndex = dictionarySortIndexReader.readInvertedSortIndex();
    for (int i = 0; i < actualSortIndex.size(); i++) {
        Assert.assertEquals(sortIndex.get(i), actualSortIndex.get(i));
        Assert.assertEquals(invertedSortIndex.get(i), actualInvertedSortIndex.get(i));
    }

}

---

From source file:org.carbondata.core.writer.sortindex.CarbonDictionarySortIndexWriterImplTest.java

/**
 * s//from w  w w.j a  v  a2  s.c o m
 * Method to test the write of sortIndex file.
 *
 * @throws Exception
 */
@Test
public void write() throws Exception {
    String storePath = hdfsStorePath;
    CarbonTableIdentifier carbonTableIdentifier = new CarbonTableIdentifier("testSchema", "carbon");
    CarbonDictionarySortIndexWriter dictionarySortIndexWriter = new CarbonDictionarySortIndexWriterImpl(
            carbonTableIdentifier, "Name", storePath);
    List<int[]> indexList = prepareExpectedData();
    List<Integer> sortIndex = Arrays.asList(ArrayUtils.toObject(indexList.get(0)));
    List<Integer> invertedSortIndex = Arrays.asList(ArrayUtils.toObject(indexList.get(1)));
    dictionarySortIndexWriter.writeSortIndex(sortIndex);
    dictionarySortIndexWriter.writeInvertedSortIndex(invertedSortIndex);
    dictionarySortIndexWriter.close();
    CarbonDictionarySortIndexReader carbonDictionarySortIndexReader = new CarbonDictionarySortIndexReaderImpl(
            carbonTableIdentifier, "Name", storePath);
    List<Integer> actualSortIndex = carbonDictionarySortIndexReader.readSortIndex();
    List<Integer> actualInvertedSortIndex = carbonDictionarySortIndexReader.readInvertedSortIndex();
    for (int i = 0; i < actualSortIndex.size(); i++) {
        Assert.assertEquals(sortIndex.get(i), actualSortIndex.get(i));
        Assert.assertEquals(invertedSortIndex.get(i), actualInvertedSortIndex.get(i));
    }

}

---

From source file:org.cesecore.certificates.certificateprofile.CertificateProfile.java

public void setCVCLongAccessRights(byte[] access) {
    if (access == null) {
        data.put(CVCLONGACCESSRIGHTS, null);
    } else {/* w  ww  . j  a v a  2s. co  m*/
        // Convert to List<Byte> since byte[] doesn't work with database protection
        data.put(CVCLONGACCESSRIGHTS, new ArrayList<Byte>(Arrays.asList(ArrayUtils.toObject(access))));
    }
}

---

From source file:org.codice.ddf.admin.core.impl.AdminConsoleService.java

private Object sanitizeUIConfiguration(String pid, String configEntryKey, Object configEntryValue) {
    if (UI_CONFIG_PID.equals(pid)
            && ("color".equalsIgnoreCase(configEntryKey) || "background".equalsIgnoreCase(configEntryKey))
            && (Arrays.stream(ArrayUtils.toObject(String.valueOf(configEntryValue).toCharArray())).parallel()
                    .anyMatch(ILLEGAL_CHARACTER_SET::contains))) {
        throw loggedException(
                "Invalid UI Configuration: The color and background properties must only contain a color value");
    }// w ww  .j a  v a 2s  . c  om
    return configEntryValue;
}

---

From source file:org.dawnsci.plotting.tools.powderlines.PowderLineTool.java

@Override
public void createControl(Composite parent) {
    this.composite = new Composite(parent, SWT.NONE);
    composite.setLayout(new FillLayout());

    // Add a SashForm to show both the table and the domain specific pane
    sashForm = new SashForm(composite, SWT.VERTICAL);

    // Create the table of lines
    tableCompo = new Composite(sashForm, SWT.NONE);
    lineTableViewer = new TableViewer(tableCompo,
            SWT.FULL_SELECTION | SWT.SINGLE | SWT.H_SCROLL | SWT.V_SCROLL | SWT.BORDER);
    createColumns(lineTableViewer);//w w w .  j  a va2 s.c  o m

    lineTableViewer.getTable().setLinesVisible(true);
    lineTableViewer.getTable().setHeaderVisible(true);
    // Create the Actions
    createActions();

    // define the content and the provider
    lineTableViewer.setContentProvider(new IStructuredContentProvider() {

        @Override
        public void inputChanged(Viewer viewer, Object oldInput, Object newInput) {
            // TODO Auto-generated method stub
        }

        @Override
        public void dispose() {
            // TODO Auto-generated method stub

        }

        @Override
        public Object[] getElements(Object inputElement) {
            return ArrayUtils.toObject(((DoubleDataset) inputElement).getData());
        }
    });

    lineTableViewer.setInput(model.getLines());

    // The domain specific part of the interface
    domainCompo = new Composite(sashForm, SWT.NONE);
    eosCompo = new EoSComposite(domainCompo, SWT.NONE);
    // maximize the table until told otherwise
    sashForm.setMaximizedControl(tableCompo);

    activate();

    super.createControl(parent);
}

---

From source file:org.dkpro.tc.evaluation.measures.regression.SpearmanCorrelation.java

public static Map<String, Double> calculate(Id2Outcome id2Outcome) {
    Map<String, Double> results = new HashMap<String, Double>();

    Double[] goldstandard = ArrayUtils.toObject(id2Outcome.getGoldValues());
    Double[] prediction = ArrayUtils.toObject(id2Outcome.getPredictions());
    results.put(SpearmanCorrelation.class.getSimpleName(), SpearmansRankCorrelation
            .computeCorrelation(Arrays.asList(goldstandard), Arrays.asList(prediction)));
    return results;
}

---

From source file:org.dkpro.tc.ml.report.util.ScatterplotRenderer.java

private double getMin(double[] values) {
    return Collections.min(Arrays.asList(ArrayUtils.toObject(values)));
}

---

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