Examples with DoubleValue org.knime.core.data.DoubleValue used on opensource projects

Example 46 with DoubleValue

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

the class PolyRegLearnerNodeModel method getCellFactory.

private CellFactory getCellFactory(final int dependentIndex) {
    final int degree = m_settings.getDegree();
    return new CellFactory() {

        @Override
        public DataCell[] getCells(final DataRow row) {
            double sum = m_betas[0];
            int betaCount = 1;
            double y = 0;
            for (int col = 0; col < row.getNumCells(); col++) {
                if ((col == dependentIndex || m_colSelected[col]) && row.getCell(col).isMissing()) {
                    switch(m_settings.getMissingValueHandling()) {
                        case ignore:
                            return new DataCell[] { DataType.getMissingCell(), DataType.getMissingCell() };
                        case fail:
                            throw new IllegalStateException("Should failed earlier!");
                        default:
                            throw new UnsupportedOperationException("Not supported missing handling strategy: " + m_settings.getMissingValueHandling());
                    }
                }
                if ((col != dependentIndex) && m_colSelected[col]) {
                    final double value = ((DoubleValue) row.getCell(col)).getDoubleValue();
                    double poly = 1;
                    for (int d = 1; d <= degree; d++) {
                        poly *= value;
                        sum += m_betas[betaCount++] * poly;
                    }
                } else if (col == dependentIndex) {
                    y = ((DoubleValue) row.getCell(col)).getDoubleValue();
                }
            }
            double err = Math.abs(sum - y);
            m_squaredError += err * err;
            return new DataCell[] { new DoubleCell(sum), new DoubleCell(err) };
        }

        @Override
        public DataColumnSpec[] getColumnSpecs() {
            DataColumnSpecCreator crea = new DataColumnSpecCreator("PolyReg prediction", DoubleCell.TYPE);
            DataColumnSpec col1 = crea.createSpec();
            crea = new DataColumnSpecCreator("Prediction Error", DoubleCell.TYPE);
            DataColumnSpec col2 = crea.createSpec();
            return new DataColumnSpec[] { col1, col2 };
        }

        @Override
        public void setProgress(final int curRowNr, final int rowCount, final RowKey lastKey, final ExecutionMonitor execMon) {
        // do nothing
        }
    };
}

Example 47 with DoubleValue

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

the class FuzzyBasisFunctionPredictorRow method computeActivation.

/**
 * Returns the compute activation of this input vector.
 *
 * @param row input pattern
 * @return membership degree
 */
@Override
public double computeActivation(final DataRow row) {
    assert (m_mem.length == row.getNumCells());
    // sets degree to maximum
    double degree = 1.0;
    // overall cells in the vector
    for (int i = 0; i < m_mem.length; i++) {
        DataCell cell = row.getCell(i);
        if (cell.isMissing()) {
            continue;
        }
        // gets cell at index i
        double value = ((DoubleValue) cell).getDoubleValue();
        // act in current dimension
        double act = m_mem[i].getActivation(value);
        if (i == 0) {
            degree = act;
            continue;
        }
        // calculates the new (minimum) degree using norm index
        degree = Norm.NORMS[m_norm].computeTNorm(degree, act);
        assert (0.0 <= degree && degree <= 1.0);
    }
    // returns membership degree
    return degree;
}

Example 48 with DoubleValue

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

the class MinkowskiDist method calcDistance.

/**
 * Calculates the distance between two data rows based on the
 * Minkowski distance.
 *
 * @param firstDataRow the first data row used to calculate the distance
 * @param secondDataRow the second data row used to calculate the distance
 * @param includedCols the columns to include into the calculation
 *
 * @return the distance of the two rows
 */
public double calcDistance(final DataRow firstDataRow, final DataRow secondDataRow, final int[] includedCols) {
    double sumPowDist = 0;
    for (int i : includedCols) {
        // skip not included cells
        DataCell x = firstDataRow.getCell(i);
        DataCell y = secondDataRow.getCell(i);
        if (!x.isMissing() && x instanceof DoubleValue && !y.isMissing() && y instanceof DoubleValue) {
            DoubleValue clusterValue = (DoubleValue) firstDataRow.getCell(i);
            DoubleValue rowValue = (DoubleValue) secondDataRow.getCell(i);
            double dist = Math.abs(clusterValue.getDoubleValue() - rowValue.getDoubleValue());
            sumPowDist += Math.pow(dist, m_p);
        }
    }
    return Math.pow(sumPowDist, (double) 1 / (double) m_p);
}

Example 49 with DoubleValue

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

the class ClusterNodeModel method findClosestPrototypeFor.

private int findClosestPrototypeFor(final DataRow row, final double[][] clusters) {
    // find closest cluster center
    // closest cluster so far
    int winner = -1;
    // best distance
    double winnerDistance = Double.MAX_VALUE;
    for (int c = 0; c < m_nrOfClusters.getIntValue(); c++) {
        double distance = 0.0;
        int pos = 0;
        for (int i = 0; i < m_dimension; i++) {
            DataCell currentCell = row.getCell(i);
            if (!m_ignoreColumn[i]) {
                if (!currentCell.isMissing()) {
                    assert currentCell.getType().isCompatible(DoubleValue.class);
                    double d = (clusters[c][pos] - ((DoubleValue) (currentCell)).getDoubleValue());
                    if (!Double.isNaN(d)) {
                        distance += d * d;
                    }
                } else {
                    // missing
                    distance += 0.0;
                }
                pos++;
            }
        }
        if (distance < winnerDistance) {
            // found closer cluster
            // make it new winner
            winner = c;
            winnerDistance = distance;
        }
    }
    // for all clusters (find closest one)
    return winner;
}

Example 50 with DoubleValue

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

the class PMMLSimpleSetPredicate method evaluate.

/**
 * {@inheritDoc}
 */
@Override
public Boolean evaluate(final DataRow row, final DataTableSpec spec) {
    cacheSpec(spec);
    assert getPreviousIndex() != -1;
    DataCell cell = row.getCell(getPreviousIndex());
    if (cell.isMissing()) {
        return null;
    }
    if (m_arrayType == PMMLArrayType.STRING) {
        return m_op.evaluate(cell.toString(), m_values);
    } else {
        Double a = ((DoubleValue) cell).getDoubleValue();
        return m_op.evaluate(a, m_doubleValues);
    }
}