Examples with Normalizer2 org.knime.base.data.normalize.Normalizer2 used on opensource projects

Example 1 with Normalizer2

use of org.knime.base.data.normalize.Normalizer2 in project knime-core by knime.

the class Normalizer3NodeModel method calculate.

/**
 * New normalized {@link org.knime.core.data.DataTable} is created depending on the mode.
 */
/**
 * @param inData The input data.
 * @param exec For BufferedDataTable creation and progress.
 * @return the result of the calculation
 * @throws Exception If the node calculation fails for any reason.
 */
protected CalculationResult calculate(final PortObject[] inData, final ExecutionContext exec) throws Exception {
    BufferedDataTable inTable = (BufferedDataTable) inData[0];
    DataTableSpec inSpec = inTable.getSpec();
    // extract selected numeric columns
    String[] includedColumns = getIncludedComlumns(inSpec);
    Normalizer2 ntable = new Normalizer2(inTable, includedColumns);
    long rowcount = inTable.size();
    ExecutionContext prepareExec = exec.createSubExecutionContext(0.3);
    AffineTransTable outTable;
    boolean fixDomainBounds = false;
    switch(m_config.getMode()) {
        case MINMAX:
            fixDomainBounds = true;
            outTable = ntable.doMinMaxNorm(m_config.getMax(), m_config.getMin(), prepareExec);
            break;
        case Z_SCORE:
            outTable = ntable.doZScoreNorm(prepareExec);
            break;
        case DECIMALSCALING:
            outTable = ntable.doDecimalScaling(prepareExec);
            break;
        default:
            throw new InvalidSettingsException("No mode set");
    }
    if (outTable.getErrorMessage() != null) {
        // something went wrong, report and throw an exception
        throw new Exception(outTable.getErrorMessage());
    }
    if (ntable.getErrorMessage() != null) {
        // something went wrong during initialization, report.
        setWarningMessage(ntable.getErrorMessage());
    }
    DataTableSpec modelSpec = FilterColumnTable.createFilterTableSpec(inSpec, includedColumns);
    AffineTransConfiguration configuration = outTable.getConfiguration();
    DataTableSpec spec = outTable.getDataTableSpec();
    // the same transformation, which is not guaranteed to snap to min/max)
    if (fixDomainBounds) {
        DataColumnSpec[] newColSpecs = new DataColumnSpec[spec.getNumColumns()];
        for (int i = 0; i < newColSpecs.length; i++) {
            newColSpecs[i] = spec.getColumnSpec(i);
        }
        for (int i = 0; i < includedColumns.length; i++) {
            int index = spec.findColumnIndex(includedColumns[i]);
            DataColumnSpecCreator creator = new DataColumnSpecCreator(newColSpecs[index]);
            DataColumnDomainCreator domCreator = new DataColumnDomainCreator(newColSpecs[index].getDomain());
            domCreator.setLowerBound(new DoubleCell(m_config.getMin()));
            domCreator.setUpperBound(new DoubleCell(m_config.getMax()));
            creator.setDomain(domCreator.createDomain());
            newColSpecs[index] = creator.createSpec();
        }
        spec = new DataTableSpec(spec.getName(), newColSpecs);
    }
    ExecutionMonitor normExec = exec.createSubProgress(.7);
    BufferedDataContainer container = exec.createDataContainer(spec);
    long count = 1;
    for (DataRow row : outTable) {
        normExec.checkCanceled();
        normExec.setProgress(count / (double) rowcount, "Normalizing row no. " + count + " of " + rowcount + " (\"" + row.getKey() + "\")");
        container.addRowToTable(row);
        count++;
    }
    container.close();
    return new CalculationResult(container.getTable(), modelSpec, configuration);
}

Example 2 with Normalizer2

use of org.knime.base.data.normalize.Normalizer2 in project knime-core by knime.

the class Normalizer2NodeModel method calculate.

/**
 * New normalized {@link org.knime.core.data.DataTable} is created depending
 * on the mode.
 */
/**
 * @param inData The input data.
 * @param exec For BufferedDataTable creation and progress.
 * @return the result of the calculation
 * @throws Exception If the node calculation fails for any reason.
 */
protected CalculationResult calculate(final PortObject[] inData, final ExecutionContext exec) throws Exception {
    BufferedDataTable inTable = (BufferedDataTable) inData[0];
    DataTableSpec inSpec = inTable.getSpec();
    // extract selected numeric columns
    updateNumericColumnSelection(inSpec);
    Normalizer2 ntable = new Normalizer2(inTable, m_columns);
    long rowcount = inTable.size();
    ExecutionContext prepareExec = exec.createSubExecutionContext(0.3);
    AffineTransTable outTable;
    boolean fixDomainBounds = false;
    switch(m_mode) {
        case NONORM_MODE:
            return new CalculationResult(inTable, new DataTableSpec(), new AffineTransConfiguration());
        case MINMAX_MODE:
            fixDomainBounds = true;
            outTable = ntable.doMinMaxNorm(m_max, m_min, prepareExec);
            break;
        case ZSCORE_MODE:
            outTable = ntable.doZScoreNorm(prepareExec);
            break;
        case DECIMALSCALING_MODE:
            outTable = ntable.doDecimalScaling(prepareExec);
            break;
        default:
            throw new Exception("No mode set");
    }
    if (outTable.getErrorMessage() != null) {
        // something went wrong, report and throw an exception
        throw new Exception(outTable.getErrorMessage());
    }
    if (ntable.getErrorMessage() != null) {
        // something went wrong during initialization, report.
        setWarningMessage(ntable.getErrorMessage());
    }
    DataTableSpec modelSpec = FilterColumnTable.createFilterTableSpec(inSpec, m_columns);
    AffineTransConfiguration configuration = outTable.getConfiguration();
    DataTableSpec spec = outTable.getDataTableSpec();
    // the same transformation, which is not guaranteed to snap to min/max)
    if (fixDomainBounds) {
        DataColumnSpec[] newColSpecs = new DataColumnSpec[spec.getNumColumns()];
        for (int i = 0; i < newColSpecs.length; i++) {
            newColSpecs[i] = spec.getColumnSpec(i);
        }
        for (int i = 0; i < m_columns.length; i++) {
            int index = spec.findColumnIndex(m_columns[i]);
            DataColumnSpecCreator creator = new DataColumnSpecCreator(newColSpecs[index]);
            DataColumnDomainCreator domCreator = new DataColumnDomainCreator(newColSpecs[index].getDomain());
            domCreator.setLowerBound(new DoubleCell(m_min));
            domCreator.setUpperBound(new DoubleCell(m_max));
            creator.setDomain(domCreator.createDomain());
            newColSpecs[index] = creator.createSpec();
        }
        spec = new DataTableSpec(spec.getName(), newColSpecs);
    }
    ExecutionMonitor normExec = exec.createSubProgress(.7);
    BufferedDataContainer container = exec.createDataContainer(spec);
    long count = 1;
    for (DataRow row : outTable) {
        normExec.checkCanceled();
        normExec.setProgress(count / (double) rowcount, "Normalizing row no. " + count + " of " + rowcount + " (\"" + row.getKey() + "\")");
        container.addRowToTable(row);
        count++;
    }
    container.close();
    return new CalculationResult(container.getTable(), modelSpec, configuration);
}