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Example 41 with DataRow

use of org.knime.core.data.DataRow in project knime-core by knime.

the class DateShiftConfigure method getColumnbasedCellFactory.

/**
 * @param spec the  output column spec
 * @param col1Idx the column index of the numerical column to add
 * @param g the time field to modify (as defined by calendar constants)
 * @param conf the configuration object
 * @param col2Idx the time column
 * @return the cell factory
 */
public static SingleCellFactory getColumnbasedCellFactory(final DataColumnSpec spec, final int col1Idx, final int col2Idx, final int g, final DateShiftConfigure conf) {
    return new SingleCellFactory(spec) {

        /**
         * Value for the new column is based on the values of two column of the row (first and second date column),
         * the selected granularity, and the fraction digits for rounding.
         *
         * @param row the current row
         * @return the difference between the two date values with the given granularity and rounding
         */
        @Override
        public DataCell getCell(final DataRow row) {
            final int value;
            DataCell cell2 = row.getCell(col2Idx);
            if (cell2.isMissing()) {
                return DataType.getMissingCell();
            }
            String typeofshift = conf.gettypeofshift().getStringValue();
            if (typeofshift.equals(DateShiftNodeDialog.CFG_COLUMN_SHIFT)) {
                DataCell cell1 = row.getCell(col1Idx);
                if ((cell1.isMissing())) {
                    return DataType.getMissingCell();
                }
                value = ((IntValue) cell1).getIntValue();
            } else {
                value = conf.getvalueofshift().getIntValue();
            }
            Calendar c = ((DateAndTimeValue) cell2).getUTCCalendarClone();
            c.add(g, value);
            return new DateAndTimeCell(c.getTimeInMillis(), conf.getHasDate().getBooleanValue(), conf.getHasTime().getBooleanValue(), conf.getHasMiliSeconds().getBooleanValue());
        }
    };
}
Also used : DateAndTimeValue(org.knime.core.data.date.DateAndTimeValue) Calendar(java.util.Calendar) SettingsModelCalendar(org.knime.timeseries.util.SettingsModelCalendar) DataCell(org.knime.core.data.DataCell) DateAndTimeCell(org.knime.core.data.date.DateAndTimeCell) SettingsModelString(org.knime.core.node.defaultnodesettings.SettingsModelString) SingleCellFactory(org.knime.core.data.container.SingleCellFactory) DataRow(org.knime.core.data.DataRow)

Example 42 with DataRow

use of org.knime.core.data.DataRow in project knime-core by knime.

the class StatisticsTable method calculateAllMoments.

/**
 * Calculates <b>all the statistical moments in one pass </b>. After the
 * call of this operation, the statistical moments can be obtained very fast
 * from all the other methods.
 *
 * @param rowCount Row count of table for progress, may be NaN if unknown.
 * @param exec object to check with if user canceled the operation
 * @throws CanceledExecutionException if user canceled
 * @throws IllegalArgumentException if rowCount argument < 0
 */
protected void calculateAllMoments(final double rowCount, final ExecutionMonitor exec) throws CanceledExecutionException {
    if (rowCount < 0.0) {
        throw new IllegalArgumentException("rowCount argument must not < 0: " + rowCount);
    }
    DataTableSpec origSpec = m_table.getDataTableSpec();
    int numOfCols = origSpec.getNumColumns();
    // the number of non-missing cells in each column
    int[] validCount = new int[numOfCols];
    double[] sumsquare = new double[numOfCols];
    final DataValueComparator[] comp = new DataValueComparator[numOfCols];
    for (int i = 0; i < numOfCols; i++) {
        sumsquare[i] = 0.0;
        validCount[i] = 0;
        comp[i] = origSpec.getColumnSpec(i).getType().getComparator();
        assert comp[i] != null;
    }
    int nrRows = 0;
    for (RowIterator rowIt = m_table.iterator(); rowIt.hasNext(); nrRows++) {
        DataRow row = rowIt.next();
        if (exec != null) {
            double prog = Double.isNaN(rowCount) ? 0.0 : nrRows / rowCount;
            exec.setProgress(prog, "Calculating statistics, processing row " + (nrRows + 1) + " (\"" + row.getKey() + "\")");
            // throws exception if user canceled
            exec.checkCanceled();
        }
        for (int c = 0; c < numOfCols; c++) {
            final DataCell cell = row.getCell(c);
            if (!(cell.isMissing())) {
                // keep the min and max for each column
                if ((m_minValues[c] == null) || (comp[c].compare(cell, m_minValues[c]) < 0)) {
                    m_minValues[c] = cell;
                }
                if ((m_maxValues[c] == null) || (comp[c].compare(m_maxValues[c], cell) < 0)) {
                    m_maxValues[c] = cell;
                }
                // for double columns we calc the sum (for the mean calc)
                DataType type = origSpec.getColumnSpec(c).getType();
                if (type.isCompatible(DoubleValue.class)) {
                    double d = ((DoubleValue) cell).getDoubleValue();
                    if (Double.isNaN(m_sum[c])) {
                        m_sum[c] = d;
                    } else {
                        m_sum[c] += d;
                    }
                    sumsquare[c] += d * d;
                    validCount[c]++;
                }
            } else {
                m_missingValueCnt[c]++;
            }
        }
        calculateMomentInSubClass(row);
    }
    m_nrRows = nrRows;
    for (int j = 0; j < numOfCols; j++) {
        // missing values
        if (validCount[j] == 0 || m_minValues[j] == null) {
            DataCell mc = DataType.getMissingCell();
            m_minValues[j] = mc;
            m_maxValues[j] = mc;
            m_meanValues[j] = Double.NaN;
            m_varianceValues[j] = Double.NaN;
        } else {
            m_meanValues[j] = m_sum[j] / validCount[j];
            if (validCount[j] > 1) {
                m_varianceValues[j] = (sumsquare[j] - ((m_sum[j] * m_sum[j]) / validCount[j])) / (validCount[j] - 1);
            } else {
                m_varianceValues[j] = 0.0;
            }
            // round-off errors resulting in negative variance values
            if (m_varianceValues[j] < 0.0 && m_varianceValues[j] > -1.0E8) {
                m_varianceValues[j] = 0.0;
            }
            assert m_varianceValues[j] >= 0.0 : "Variance cannot be negative (column \"" + origSpec.getColumnSpec(j).getName() + "\": " + m_varianceValues[j];
        }
    }
    // compute resulting table spec
    int nrCols = m_table.getDataTableSpec().getNumColumns();
    DataColumnSpec[] cSpec = new DataColumnSpec[nrCols];
    for (int c = 0; c < nrCols; c++) {
        DataColumnSpec s = m_table.getDataTableSpec().getColumnSpec(c);
        // we create domains with our bounds.
        Set<DataCell> values = (s.getDomain() == null ? null : s.getDomain().getValues());
        DataColumnDomain newDomain = new DataColumnDomainCreator(values, (m_minValues[c] == null || m_minValues[c].isMissing()) ? null : m_minValues[c], (m_maxValues[c] == null || m_maxValues[c].isMissing()) ? null : m_maxValues[c]).createDomain();
        DataColumnSpecCreator creator = new DataColumnSpecCreator(s);
        creator.setDomain(newDomain);
        cSpec[c] = creator.createSpec();
    }
    m_tSpec = new DataTableSpec(cSpec);
}
Also used : DataTableSpec(org.knime.core.data.DataTableSpec) DataColumnSpecCreator(org.knime.core.data.DataColumnSpecCreator) DataColumnDomainCreator(org.knime.core.data.DataColumnDomainCreator) DataValueComparator(org.knime.core.data.DataValueComparator) DataRow(org.knime.core.data.DataRow) DataColumnSpec(org.knime.core.data.DataColumnSpec) DataColumnDomain(org.knime.core.data.DataColumnDomain) DoubleValue(org.knime.core.data.DoubleValue) RowIterator(org.knime.core.data.RowIterator) DataCell(org.knime.core.data.DataCell) DataType(org.knime.core.data.DataType)

Example 43 with DataRow

use of org.knime.core.data.DataRow in project knime-core by knime.

the class InMemoryIterator method next.

/**
 * {@inheritDoc}
 */
@Override
public DataRow next() {
    if (m_nextRow == null) {
        if (getNextMatch() == null) {
            throw new NoSuchElementException("No more rows");
        }
    }
    DataRow row;
    if (m_inverted) {
        row = new JoinedRow(m_nextRow[1], m_nextRow[0]);
    } else {
        row = new JoinedRow(m_nextRow[0], m_nextRow[1]);
    }
    m_nextRow = null;
    return row;
}
Also used : JoinedRow(org.knime.core.data.def.JoinedRow) DataRow(org.knime.core.data.DataRow) NoSuchElementException(java.util.NoSuchElementException)

Example 44 with DataRow

use of org.knime.core.data.DataRow in project knime-core by knime.

the class JoinedTableRowIterator method next.

/**
 * {@inheritDoc}
 */
@Override
public DataRow next() {
    if (m_leftIt.hasNext()) {
        final DataRow left = m_leftIt.next();
        final RowKey leftID = left.getKey();
        assert (!leftID.equals(m_lastRightID));
        DataRow right;
        RowKey rightID;
        boolean cont = true;
        do {
            right = null;
            rightID = null;
            if (!m_rightIt.hasNext() && initNewRightIterator()) {
                break;
            }
            right = nextRight();
            rightID = right.getKey();
            boolean madeWholeLoop = (m_lastRightID == null && !m_rightIt.hasNext()) || rightID.equals(m_lastRightID);
            cont = !madeWholeLoop && !rightID.equals(leftID);
            if (cont) {
                if (!m_hasSkippedRight) {
                    if (!m_table.isPrintedErrorOnSorting()) {
                        LOGGER.warn("Either both tables don't have all rows in " + "common or they are sorted differently.");
                        LOGGER.warn("(Iteration may have quadratic complexity " + "to ensure that all matching rows are " + "found.");
                        LOGGER.warn("I'll suppress further warnings.");
                        m_table.setPrintedErrorOnSorting(true);
                    }
                    m_hasSkippedRight = true;
                }
            }
        } while (cont);
        // no matching right row found
        if (!leftID.equals(rightID)) {
            right = getRightMissing(leftID);
        } else {
            m_lastRightID = rightID;
            assert (rightID.equals(leftID));
            m_rightSet.set(m_rightItCounter);
        }
        if (!m_leftIt.hasNext()) {
            // (according to the bit set m_rightSet)
            if (m_hasSkippedRight) {
                initNewRightIterator();
            }
            m_lastRightID = null;
            m_nextRightRow = findNextRightRow();
        }
        return new JoinedRow(left, right);
    } else {
        // in a perfect world, you don't come here...
        DataRow maybeNext = findNextRightRow();
        DataRow left = getLeftMissing(m_nextRightRow.getKey());
        DataRow merged = new JoinedRow(left, m_nextRightRow);
        m_nextRightRow = maybeNext;
        return merged;
    }
}
Also used : RowKey(org.knime.core.data.RowKey) JoinedRow(org.knime.core.data.def.JoinedRow) DataRow(org.knime.core.data.DataRow)

Example 45 with DataRow

use of org.knime.core.data.DataRow in project knime-core by knime.

the class ReadPNGFromURLNodeModel method createColumnRearranger.

private ColumnRearranger createColumnRearranger(final DataTableSpec in, final AtomicLong failCounter) throws InvalidSettingsException {
    String colName = m_config.getUrlColName();
    if (colName == null) {
        // throws ISE
        m_config.guessDefaults(in);
        colName = m_config.getUrlColName();
        setWarningMessage("Auto-configuration: Guessing column \"" + colName + "\" to contain locations");
    }
    final int colIndex = in.findColumnIndex(colName);
    if (colIndex < 0) {
        throw new InvalidSettingsException("No such column in input: " + colName);
    }
    DataColumnSpec colSpec = in.getColumnSpec(colIndex);
    if (!colSpec.getType().isCompatible(StringValue.class)) {
        throw new InvalidSettingsException("Selected column \"" + colName + "\" is not string-compatible");
    }
    final String newColName = m_config.getNewColumnName();
    DataColumnSpecCreator colSpecCreator;
    if (newColName != null) {
        String newName = DataTableSpec.getUniqueColumnName(in, newColName);
        colSpecCreator = new DataColumnSpecCreator(newName, PNGImageContent.TYPE);
    } else {
        colSpecCreator = new DataColumnSpecCreator(colSpec);
        colSpecCreator.setType(PNGImageContent.TYPE);
        colSpecCreator.removeAllHandlers();
        colSpecCreator.setDomain(null);
    }
    DataColumnSpec outColumnSpec = colSpecCreator.createSpec();
    ColumnRearranger rearranger = new ColumnRearranger(in);
    CellFactory fac = new SingleCellFactory(outColumnSpec) {

        @Override
        public DataCell getCell(final DataRow row) {
            DataCell cell = row.getCell(colIndex);
            if (cell.isMissing()) {
                return DataType.getMissingCell();
            } else {
                String url = ((StringValue) cell).getStringValue();
                try {
                    return toPNGCell(url);
                } catch (Exception e) {
                    if (m_config.isFailOnInvalid()) {
                        if (e instanceof RuntimeException) {
                            throw (RuntimeException) e;
                        } else {
                            throw new RuntimeException(e.getMessage(), e);
                        }
                    } else {
                        String message = "Failed to read png content from " + "\"" + url + "\": " + e.getMessage();
                        LOGGER.warn(message, e);
                        failCounter.incrementAndGet();
                        return DataType.getMissingCell();
                    }
                }
            }
        }
    };
    if (newColName == null) {
        rearranger.replace(fac, colIndex);
    } else {
        rearranger.append(fac);
    }
    return rearranger;
}
Also used : DataColumnSpecCreator(org.knime.core.data.DataColumnSpecCreator) DataRow(org.knime.core.data.DataRow) InvalidSettingsException(org.knime.core.node.InvalidSettingsException) CanceledExecutionException(org.knime.core.node.CanceledExecutionException) IOException(java.io.IOException) DataColumnSpec(org.knime.core.data.DataColumnSpec) ColumnRearranger(org.knime.core.data.container.ColumnRearranger) InvalidSettingsException(org.knime.core.node.InvalidSettingsException) DataCell(org.knime.core.data.DataCell) StringValue(org.knime.core.data.StringValue) SingleCellFactory(org.knime.core.data.container.SingleCellFactory) CellFactory(org.knime.core.data.container.CellFactory) SingleCellFactory(org.knime.core.data.container.SingleCellFactory)

Aggregations

DataRow (org.knime.core.data.DataRow)482 DataCell (org.knime.core.data.DataCell)268 DataTableSpec (org.knime.core.data.DataTableSpec)159 BufferedDataTable (org.knime.core.node.BufferedDataTable)125 DataColumnSpec (org.knime.core.data.DataColumnSpec)109 RowKey (org.knime.core.data.RowKey)88 DefaultRow (org.knime.core.data.def.DefaultRow)88 BufferedDataContainer (org.knime.core.node.BufferedDataContainer)80 InvalidSettingsException (org.knime.core.node.InvalidSettingsException)76 ColumnRearranger (org.knime.core.data.container.ColumnRearranger)73 DoubleValue (org.knime.core.data.DoubleValue)72 ArrayList (java.util.ArrayList)65 DataColumnSpecCreator (org.knime.core.data.DataColumnSpecCreator)65 RowIterator (org.knime.core.data.RowIterator)62 DataType (org.knime.core.data.DataType)61 DoubleCell (org.knime.core.data.def.DoubleCell)57 StringCell (org.knime.core.data.def.StringCell)53 SingleCellFactory (org.knime.core.data.container.SingleCellFactory)48 ExecutionMonitor (org.knime.core.node.ExecutionMonitor)44 CanceledExecutionException (org.knime.core.node.CanceledExecutionException)43