Examples with StringCell org.knime.core.data.def.StringCell used on opensource projects

Example 16 with StringCell

use of org.knime.core.data.def.StringCell in project knime-core by knime.

the class TreeEnsembleClassificationPredictorCellFactory2 method getCells.

/**
 * {@inheritDoc}
 */
@Override
public DataCell[] getCells(final DataRow row) {
    TreeEnsembleModelPortObject modelObject = m_predictor.getModelObject();
    TreeEnsemblePredictorConfiguration cfg = m_predictor.getConfiguration();
    final TreeEnsembleModel ensembleModel = modelObject.getEnsembleModel();
    int size = 1;
    final boolean appendConfidence = cfg.isAppendPredictionConfidence();
    if (appendConfidence) {
        size += 1;
    }
    final boolean appendClassConfidences = cfg.isAppendClassConfidences();
    if (appendClassConfidences) {
        size += m_targetValueMap.size();
    }
    final boolean appendModelCount = cfg.isAppendModelCount();
    if (appendModelCount) {
        size += 1;
    }
    final boolean hasOutOfBagFilter = m_predictor.hasOutOfBagFilter();
    DataCell[] result = new DataCell[size];
    DataRow filterRow = new FilterColumnRow(row, m_learnColumnInRealDataIndices);
    PredictorRecord record = ensembleModel.createPredictorRecord(filterRow, m_learnSpec);
    if (record == null) {
        // missing value
        Arrays.fill(result, DataType.getMissingCell());
        return result;
    }
    OccurrenceCounter<String> counter = new OccurrenceCounter<String>();
    final int nrModels = ensembleModel.getNrModels();
    TreeTargetNominalColumnMetaData targetMeta = (TreeTargetNominalColumnMetaData) ensembleModel.getMetaData().getTargetMetaData();
    final double[] classProbabilities = new double[targetMeta.getValues().length];
    int nrValidModels = 0;
    for (int i = 0; i < nrModels; i++) {
        if (hasOutOfBagFilter && m_predictor.isRowPartOfTrainingData(row.getKey(), i)) {
        // ignore, row was used to train the model
        } else {
            TreeModelClassification m = ensembleModel.getTreeModelClassification(i);
            TreeNodeClassification match = m.findMatchingNode(record);
            String majorityClassName = match.getMajorityClassName();
            final float[] nodeClassProbs = match.getTargetDistribution();
            double instancesInNode = 0;
            for (int c = 0; c < nodeClassProbs.length; c++) {
                instancesInNode += nodeClassProbs[c];
            }
            for (int c = 0; c < classProbabilities.length; c++) {
                classProbabilities[c] += nodeClassProbs[c] / instancesInNode;
            }
            counter.add(majorityClassName);
            nrValidModels += 1;
        }
    }
    String bestValue = counter.getMostFrequent();
    int index = 0;
    if (bestValue == null) {
        assert nrValidModels == 0;
        Arrays.fill(result, DataType.getMissingCell());
        index = size - 1;
    } else {
        // result[index++] = m_targetValueMap.get(bestValue);
        int indexBest = -1;
        double probBest = -1;
        for (int c = 0; c < classProbabilities.length; c++) {
            double prob = classProbabilities[c];
            if (prob > probBest) {
                probBest = prob;
                indexBest = c;
            }
        }
        result[index++] = new StringCell(targetMeta.getValues()[indexBest].getNominalValue());
        if (appendConfidence) {
            // final int freqValue = counter.getFrequency(bestValue);
            // result[index++] = new DoubleCell(freqValue / (double)nrValidModels);
            result[index++] = new DoubleCell(probBest);
        }
        if (appendClassConfidences) {
            for (NominalValueRepresentation nomVal : targetMeta.getValues()) {
                double prob = classProbabilities[nomVal.getAssignedInteger()] / nrValidModels;
                result[index++] = new DoubleCell(prob);
            }
        }
    }
    if (appendModelCount) {
        result[index++] = new IntCell(nrValidModels);
    }
    return result;
}

Example 17 with StringCell

use of org.knime.core.data.def.StringCell in project knime-core by knime.

the class RuleEngineNodeModel method createRearranger.

private ColumnRearranger createRearranger(final DataTableSpec inSpec, final List<Rule> rules) throws InvalidSettingsException {
    ColumnRearranger crea = new ColumnRearranger(inSpec);
    String newColName = DataTableSpec.getUniqueColumnName(inSpec, m_settings.getNewColName());
    final int defaultLabelColumnIndex;
    if (m_settings.getDefaultLabelIsColumn()) {
        if (m_settings.getDefaultLabel().length() < 3) {
            throw new InvalidSettingsException("Default label is not a column reference");
        }
        if (!m_settings.getDefaultLabel().startsWith("$") || !m_settings.getDefaultLabel().endsWith("$")) {
            throw new InvalidSettingsException("Column references in default label must be enclosed in $");
        }
        String colRef = m_settings.getDefaultLabel().substring(1, m_settings.getDefaultLabel().length() - 1);
        defaultLabelColumnIndex = inSpec.findColumnIndex(colRef);
        if (defaultLabelColumnIndex == -1) {
            throw new InvalidSettingsException("Column '" + m_settings.getDefaultLabel() + "' for default label does not exist in input table");
        }
    } else {
        defaultLabelColumnIndex = -1;
    }
    // determine output type
    List<DataType> types = new ArrayList<DataType>();
    // add outcome column types
    for (Rule r : rules) {
        if (r.getOutcome() instanceof ColumnReference) {
            types.add(((ColumnReference) r.getOutcome()).spec.getType());
        } else if (r.getOutcome() instanceof Double) {
            types.add(DoubleCell.TYPE);
        } else if (r.getOutcome() instanceof Integer) {
            types.add(IntCell.TYPE);
        } else if (r.getOutcome().toString().length() > 0) {
            types.add(StringCell.TYPE);
        }
    }
    if (defaultLabelColumnIndex >= 0) {
        types.add(inSpec.getColumnSpec(defaultLabelColumnIndex).getType());
    } else if (m_settings.getDefaultLabel().length() > 0) {
        try {
            Integer.parseInt(m_settings.getDefaultLabel());
            types.add(IntCell.TYPE);
        } catch (NumberFormatException ex) {
            try {
                Double.parseDouble(m_settings.getDefaultLabel());
                types.add(DoubleCell.TYPE);
            } catch (NumberFormatException ex1) {
                types.add(StringCell.TYPE);
            }
        }
    }
    final DataType outType;
    if (types.size() > 0) {
        DataType temp = types.get(0);
        for (int i = 1; i < types.size(); i++) {
            temp = DataType.getCommonSuperType(temp, types.get(i));
        }
        if ((temp.getValueClasses().size() == 1) && temp.getValueClasses().contains(DataValue.class)) {
            // a non-native type, we replace it with string
            temp = StringCell.TYPE;
        }
        outType = temp;
    } else {
        outType = StringCell.TYPE;
    }
    DataColumnSpec cs = new DataColumnSpecCreator(newColName, outType).createSpec();
    crea.append(new SingleCellFactory(cs) {

        @Override
        public DataCell getCell(final DataRow row) {
            for (Rule r : rules) {
                if (r.matches(row)) {
                    Object outcome = r.getOutcome();
                    if (outcome instanceof ColumnReference) {
                        DataCell cell = row.getCell(((ColumnReference) outcome).index);
                        if (outType.equals(StringCell.TYPE) && !cell.isMissing() && !cell.getType().equals(StringCell.TYPE)) {
                            return new StringCell(cell.toString());
                        } else {
                            return cell;
                        }
                    } else if (outType.equals(IntCell.TYPE)) {
                        return new IntCell((Integer) outcome);
                    } else if (outType.equals(DoubleCell.TYPE)) {
                        return new DoubleCell((Double) outcome);
                    } else {
                        return new StringCell(outcome.toString());
                    }
                }
            }
            if (defaultLabelColumnIndex >= 0) {
                DataCell cell = row.getCell(defaultLabelColumnIndex);
                if (outType.equals(StringCell.TYPE) && !cell.getType().equals(StringCell.TYPE)) {
                    return new StringCell(cell.toString());
                } else {
                    return cell;
                }
            } else if (m_settings.getDefaultLabel().length() > 0) {
                String l = m_settings.getDefaultLabel();
                if (outType.equals(StringCell.TYPE)) {
                    return new StringCell(l);
                }
                try {
                    int i = Integer.parseInt(l);
                    return new IntCell(i);
                } catch (NumberFormatException ex) {
                    try {
                        double d = Double.parseDouble(l);
                        return new DoubleCell(d);
                    } catch (NumberFormatException ex1) {
                        return new StringCell(l);
                    }
                }
            } else {
                return DataType.getMissingCell();
            }
        }
    });
    return crea;
}

Example 18 with StringCell

use of org.knime.core.data.def.StringCell in project knime-core by knime.

the class LogisticRegressionContent method createTablePortObject.

/**
 * Creates a BufferedDataTable with the
 * @param exec The execution context
 * @return a port object
 */
public BufferedDataTable createTablePortObject(final ExecutionContext exec) {
    DataTableSpec tableOutSpec = new DataTableSpec("Coefficients and Statistics", new String[] { "Logit", "Variable", "Coeff.", "Std. Err.", "z-score", "P>|z|" }, new DataType[] { StringCell.TYPE, StringCell.TYPE, DoubleCell.TYPE, DoubleCell.TYPE, DoubleCell.TYPE, DoubleCell.TYPE });
    BufferedDataContainer dc = exec.createDataContainer(tableOutSpec);
    List<DataCell> logits = this.getLogits();
    List<String> parameters = this.getParameters();
    int c = 0;
    for (DataCell logit : logits) {
        Map<String, Double> coefficients = this.getCoefficients(logit);
        Map<String, Double> stdErrs = this.getStandardErrors(logit);
        Map<String, Double> zScores = this.getZScores(logit);
        Map<String, Double> pValues = this.getPValues(logit);
        for (String parameter : parameters) {
            List<DataCell> cells = new ArrayList<DataCell>();
            cells.add(new StringCell(logit.toString()));
            cells.add(new StringCell(parameter));
            cells.add(new DoubleCell(coefficients.get(parameter)));
            cells.add(new DoubleCell(stdErrs.get(parameter)));
            cells.add(new DoubleCell(zScores.get(parameter)));
            cells.add(new DoubleCell(pValues.get(parameter)));
            c++;
            dc.addRowToTable(new DefaultRow("Row" + c, cells));
        }
        List<DataCell> cells = new ArrayList<DataCell>();
        cells.add(new StringCell(logit.toString()));
        cells.add(new StringCell("Constant"));
        cells.add(new DoubleCell(this.getIntercept(logit)));
        cells.add(new DoubleCell(this.getInterceptStdErr(logit)));
        cells.add(new DoubleCell(this.getInterceptZScore(logit)));
        cells.add(new DoubleCell(this.getInterceptPValue(logit)));
        c++;
        dc.addRowToTable(new DefaultRow("Row" + c, cells));
    }
    dc.close();
    return dc.getTable();
}

Example 19 with StringCell

use of org.knime.core.data.def.StringCell in project knime-core by knime.

the class LogisticRegressionContent method createTablePortObject.

/**
 * Creates a BufferedDataTable with the
 * @param exec The execution context
 * @return a port object
 */
public BufferedDataTable createTablePortObject(final ExecutionContext exec) {
    DataTableSpec tableOutSpec = new DataTableSpec("Coefficients and Statistics", new String[] { "Logit", "Variable", "Coeff.", "Std. Err.", "z-score", "P>|z|" }, new DataType[] { StringCell.TYPE, StringCell.TYPE, DoubleCell.TYPE, DoubleCell.TYPE, DoubleCell.TYPE, DoubleCell.TYPE });
    BufferedDataContainer dc = exec.createDataContainer(tableOutSpec);
    List<DataCell> logits = this.getLogits();
    List<String> parameters = this.getParameters();
    int c = 0;
    for (DataCell logit : logits) {
        Map<String, Double> coefficients = this.getCoefficients(logit);
        Map<String, Double> stdErrs = this.getStandardErrors(logit);
        Map<String, Double> zScores = this.getZScores(logit);
        Map<String, Double> pValues = this.getPValues(logit);
        for (String parameter : parameters) {
            List<DataCell> cells = new ArrayList<DataCell>();
            cells.add(new StringCell(logit.toString()));
            cells.add(new StringCell(parameter));
            cells.add(new DoubleCell(coefficients.get(parameter)));
            cells.add(new DoubleCell(stdErrs.get(parameter)));
            cells.add(new DoubleCell(zScores.get(parameter)));
            cells.add(new DoubleCell(pValues.get(parameter)));
            c++;
            dc.addRowToTable(new DefaultRow("Row" + c, cells));
        }
        List<DataCell> cells = new ArrayList<DataCell>();
        cells.add(new StringCell(logit.toString()));
        cells.add(new StringCell("Constant"));
        cells.add(new DoubleCell(this.getIntercept(logit)));
        cells.add(new DoubleCell(this.getInterceptStdErr(logit)));
        cells.add(new DoubleCell(this.getInterceptZScore(logit)));
        cells.add(new DoubleCell(this.getInterceptPValue(logit)));
        c++;
        dc.addRowToTable(new DefaultRow("Row" + c, cells));
    }
    dc.close();
    return dc.getTable();
}

Example 20 with StringCell

use of org.knime.core.data.def.StringCell in project knime-core by knime.

the class AbstractTreeEnsembleModel method createLearnAttributeRow.

public DataRow createLearnAttributeRow(final DataRow learnRow, final DataTableSpec learnSpec) {
    final TreeType type = getType();
    final DataCell c = learnRow.getCell(0);
    final int nrAttributes = getMetaData().getNrAttributes();
    switch(type) {
        case Ordinary:
            return learnRow;
        case BitVector:
            if (c.isMissing()) {
                return null;
            }
            BitVectorValue bv = (BitVectorValue) c;
            final long length = bv.length();
            if (length != nrAttributes) {
                // TODO indicate error message
                return null;
            }
            DataCell trueCell = new StringCell("1");
            DataCell falseCell = new StringCell("0");
            DataCell[] cells = new DataCell[nrAttributes];
            for (int i = 0; i < nrAttributes; i++) {
                cells[i] = bv.get(i) ? trueCell : falseCell;
            }
            return new DefaultRow(learnRow.getKey(), cells);
        case ByteVector:
            if (c.isMissing()) {
                return null;
            }
            ByteVectorValue byteVector = (ByteVectorValue) c;
            final long bvLength = byteVector.length();
            if (bvLength != nrAttributes) {
                return null;
            }
            DataCell[] bvCells = new DataCell[nrAttributes];
            for (int i = 0; i < nrAttributes; i++) {
                bvCells[i] = new IntCell(byteVector.get(i));
            }
            return new DefaultRow(learnRow.getKey(), bvCells);
        case DoubleVector:
            if (c.isMissing()) {
                return null;
            }
            DoubleVectorValue doubleVector = (DoubleVectorValue) c;
            final int dvLength = doubleVector.getLength();
            if (dvLength != nrAttributes) {
                return null;
            }
            DataCell[] dvCells = new DataCell[nrAttributes];
            for (int i = 0; i < nrAttributes; i++) {
                dvCells[i] = new DoubleCell(doubleVector.getValue(i));
            }
            return new DefaultRow(learnRow.getKey(), dvCells);
        default:
            throw new IllegalStateException("Type unknown (not implemented): " + type);
    }
}