Examples with PMMLPortObject org.knime.core.node.port.pmml.PMMLPortObject used on opensource projects

Example 66 with PMMLPortObject

use of org.knime.core.node.port.pmml.PMMLPortObject in project knime-core by knime.

the class MLPPredictorNodeModel method createStreamableOperator.

/**
 * {@inheritDoc}
 */
@Override
public StreamableOperator createStreamableOperator(final PartitionInfo partitionInfo, final PortObjectSpec[] inSpecs) throws InvalidSettingsException {
    return new StreamableOperator() {

        @Override
        public void runFinal(final PortInput[] inputs, final PortOutput[] outputs, final ExecutionContext exec) throws Exception {
            PMMLPortObject pmmlPortObject = (PMMLPortObject) ((PortObjectInput) inputs[0]).getPortObject();
            ColumnRearranger colre = createColumnRearranger(pmmlPortObject, (DataTableSpec) inSpecs[1]);
            StreamableFunction func = colre.createStreamableFunction(1, 0);
            func.runFinal(inputs, outputs, exec);
        }
    };
}

Example 67 with PMMLPortObject

use of org.knime.core.node.port.pmml.PMMLPortObject in project knime-core by knime.

the class ClusterNodeModel method execute.

/**
 * Generate new clustering based on InputDataTable and specified number of
 * clusters. Currently the objective function only looks for cluster centers
 * that are extremely similar to the first n patterns...
 *
 * {@inheritDoc}
 */
@Override
protected PortObject[] execute(final PortObject[] data, final ExecutionContext exec) throws Exception {
    // FIXME actually do something useful with missing values!
    BufferedDataTable inData = (BufferedDataTable) data[0];
    DataTableSpec spec = inData.getDataTableSpec();
    // get dimension of feature space
    m_dimension = inData.getDataTableSpec().getNumColumns();
    HashMap<RowKey, Set<RowKey>> mapping = new HashMap<RowKey, Set<RowKey>>();
    addExcludeColumnsToIgnoreList(spec);
    double[][] clusters = initializeClusters(inData);
    // also keep counts of how many patterns fall in a specific cluster
    int[] clusterCoverage = new int[m_nrOfClusters.getIntValue()];
    // --------- create clusters --------------
    // reserve space for cluster center updates (do batch update!)
    double[][] delta = new double[m_nrOfClusters.getIntValue()][];
    for (int c = 0; c < m_nrOfClusters.getIntValue(); c++) {
        delta[c] = new double[m_dimension - m_nrIgnoredColumns];
    }
    // main loop - until clusters stop changing or maxNrIterations reached
    int currentIteration = 0;
    boolean finished = false;
    while ((!finished) && (currentIteration < m_nrMaxIterations.getIntValue())) {
        exec.checkCanceled();
        exec.setProgress((double) currentIteration / (double) m_nrMaxIterations.getIntValue(), "Iteration " + currentIteration);
        // initialize counts and cluster-deltas
        for (int c = 0; c < m_nrOfClusters.getIntValue(); c++) {
            clusterCoverage[c] = 0;
            delta[c] = new double[m_dimension - m_nrIgnoredColumns];
            int deltaPos = 0;
            for (int i = 0; i < m_dimension; i++) {
                if (!m_ignoreColumn[i]) {
                    delta[c][deltaPos++] = 0.0;
                }
            }
        }
        // assume that we are done (i.e. clusters have stopped changing)
        finished = true;
        // first training example
        RowIterator rowIt = inData.iterator();
        while (rowIt.hasNext()) {
            DataRow currentRow = rowIt.next();
            int winner = findClosestPrototypeFor(currentRow, clusters);
            if (winner >= 0) {
                // update winning cluster centers delta
                int deltaPos = 0;
                for (int i = 0; i < m_dimension; i++) {
                    DataCell currentCell = currentRow.getCell(i);
                    if (!m_ignoreColumn[i]) {
                        if (!currentCell.isMissing()) {
                            delta[winner][deltaPos] += ((DoubleValue) (currentCell)).getDoubleValue();
                        } else {
                            throw new Exception("Missing Values not (yet) allowed in k-Means.");
                        }
                        deltaPos++;
                    }
                }
                clusterCoverage[winner]++;
            } else {
                // let's report this during
                assert (winner >= 0);
                // otherwise just don't reproduce result
                throw new IllegalStateException("No winner found: " + winner);
            }
        }
        // update cluster centers
        finished = updateClusterCenters(clusterCoverage, clusters, delta);
        currentIteration++;
    }
    // while(!finished & nrIt<maxNrIt)
    // create list of feature names
    // index of not-ignored columns
    int k = 0;
    // index of column
    int j = 0;
    String[] featureNames = new String[m_dimension];
    do {
        if (!m_ignoreColumn[j]) {
            featureNames[k] = spec.getColumnSpec(j).getName();
            k++;
        }
        j++;
    } while (j < m_dimension);
    // create output container and also mapping for HiLiteing
    BufferedDataContainer labeledInput = exec.createDataContainer(createAppendedSpec(spec));
    for (DataRow row : inData) {
        int winner = findClosestPrototypeFor(row, clusters);
        DataCell cell = new StringCell(CLUSTER + winner);
        labeledInput.addRowToTable(new AppendedColumnRow(row, cell));
        if (m_enableHilite.getBooleanValue()) {
            RowKey key = new RowKey(CLUSTER + winner);
            if (mapping.get(key) == null) {
                Set<RowKey> set = new HashSet<RowKey>();
                set.add(row.getKey());
                mapping.put(key, set);
            } else {
                mapping.get(key).add(row.getKey());
            }
        }
    }
    labeledInput.close();
    if (m_enableHilite.getBooleanValue()) {
        m_translator.setMapper(new DefaultHiLiteMapper(mapping));
    }
    BufferedDataTable outData = labeledInput.getTable();
    // handle the optional PMML input
    PMMLPortObject inPMMLPort = m_pmmlInEnabled ? (PMMLPortObject) data[1] : null;
    PMMLPortObjectSpec inPMMLSpec = null;
    if (inPMMLPort != null) {
        inPMMLSpec = inPMMLPort.getSpec();
    }
    PMMLPortObjectSpec pmmlOutSpec = createPMMLSpec(inPMMLSpec, spec);
    PMMLPortObject outPMMLPort = new PMMLPortObject(pmmlOutSpec, inPMMLPort, spec);
    Set<String> columns = new LinkedHashSet<String>();
    for (String s : pmmlOutSpec.getLearningFields()) {
        columns.add(s);
    }
    outPMMLPort.addModelTranslater(new PMMLClusterTranslator(ComparisonMeasure.squaredEuclidean, m_nrOfClusters.getIntValue(), clusters, clusterCoverage, columns));
    m_viewData = new ClusterViewData(clusters, clusterCoverage, m_dimension - m_nrIgnoredColumns, featureNames);
    if (m_outputCenters) {
        DataContainer clusterCenterContainer = exec.createDataContainer(createClusterCentersSpec(spec));
        int i = 0;
        for (double[] cluster : clusters) {
            List<DataCell> cells = new ArrayList<>();
            for (double d : cluster) {
                cells.add(new DoubleCell(d));
            }
            clusterCenterContainer.addRowToTable(new DefaultRow(new RowKey(PMMLClusterTranslator.CLUSTER_NAME_PREFIX + i++), cells));
        }
        clusterCenterContainer.close();
        return new PortObject[] { outData, (BufferedDataTable) clusterCenterContainer.getTable(), outPMMLPort };
    } else {
        return new PortObject[] { outData, outPMMLPort };
    }
}

Example 68 with PMMLPortObject

use of org.knime.core.node.port.pmml.PMMLPortObject in project knime-core by knime.

the class DecTreeToImageNodeModel method execute.

/**
 * {@inheritDoc}
 */
@Override
public PortObject[] execute(final PortObject[] inPorts, final ExecutionContext exec) throws CanceledExecutionException, Exception {
    exec.setMessage("Decision Tree To Image: Loading model...");
    PMMLPortObject port = (PMMLPortObject) inPorts[0];
    List<Node> models = port.getPMMLValue().getModels(PMMLModelType.TreeModel);
    if (models.isEmpty()) {
        String msg = "Decision Tree evaluation failed: " + "No tree model found.";
        LOGGER.error(msg);
        throw new RuntimeException(msg);
    }
    PMMLDecisionTreeTranslator trans = new PMMLDecisionTreeTranslator();
    port.initializeModelTranslator(trans);
    m_decTree = trans.getDecisionTree();
    m_decTree.resetColorInformation();
    String colorColumn = null;
    if (null != inPorts[1]) {
        BufferedDataTable inData = (BufferedDataTable) inPorts[1];
        // get column with color information
        for (DataColumnSpec s : inData.getDataTableSpec()) {
            if (s.getColorHandler() != null) {
                colorColumn = s.getName();
                break;
            }
        }
        m_decTree.setColorColumn(colorColumn);
        for (DataRow thisRow : inData) {
            m_decTree.addCoveredColor(thisRow, inData.getDataTableSpec());
        }
    }
    // create PNG via streamed string
    ByteArrayOutputStream os = new ByteArrayOutputStream();
    int width = m_settings.getWidth();
    int height = m_settings.getHeight();
    GraphicsEnvironment env = GraphicsEnvironment.getLocalGraphicsEnvironment();
    BufferedImage image = null;
    if (env.isHeadlessInstance()) {
        image = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB);
    } else {
        // create compatible image for better performance
        GraphicsConfiguration gfxConf = env.getDefaultScreenDevice().getDefaultConfiguration();
        // image = gfxConf.createCompatibleImage(width, height);
        // with binary transparency
        image = gfxConf.createCompatibleImage(width, height, Transparency.BITMASK);
    // with transparency
    // image = gfxConf.createCompatibleImage(width, height,
    // Transparency.TRANSLUCENT);
    }
    Graphics2D g = (Graphics2D) image.getGraphics();
    DecisionTreeNode root = null != getDecisionTree() ? getDecisionTree().getRootNode() : null;
    DecTreeGraphView graph = new DecTreeToImageGraphView(root, colorColumn, m_settings);
    // draw graph
    graph.getView().paint(g);
    // write png
    ImageIO.write(image, "png", os);
    ByteArrayInputStream is = new ByteArrayInputStream(os.toByteArray());
    m_imageContent = new PNGImageContent(is);
    ImagePortObjectSpec outSpec = new ImagePortObjectSpec(PNGImageContent.TYPE);
    // return image object
    PortObject po = new ImagePortObject(m_imageContent, outSpec);
    return new PortObject[] { po };
}

Example 69 with PMMLPortObject

use of org.knime.core.node.port.pmml.PMMLPortObject in project knime-core by knime.

the class NaiveBayesPredictorNodeModel2 method createStreamableOperator.

/**
 * {@inheritDoc}
 */
@Override
public StreamableOperator createStreamableOperator(final PartitionInfo partitionInfo, final PortObjectSpec[] inSpecs) throws InvalidSettingsException {
    return new StreamableOperator() {

        @Override
        public void runFinal(final PortInput[] inputs, final PortOutput[] outputs, final ExecutionContext exec) throws Exception {
            PMMLPortObject pmmlPortObj = (PMMLPortObject) ((PortObjectInput) inputs[MODEL_IN_PORT]).getPortObject();
            DataTableSpec inSpec = (DataTableSpec) inSpecs[DATA_IN_PORT];
            StreamableFunction fct = createColumnRearranger(pmmlPortObj, inSpec).createStreamableFunction(DATA_IN_PORT, 0);
            fct.runFinal(inputs, outputs, exec);
        }
    };
}

Example 70 with PMMLPortObject

use of org.knime.core.node.port.pmml.PMMLPortObject in project knime-core by knime.

the class DataColumnSpecFilterPMMLNodeModel method execute.

/**
 * {@inheritDoc}
 */
@Override
protected PortObject[] execute(final PortObject[] data, final ExecutionContext exec) throws Exception {
    final BufferedDataTable inTable = (BufferedDataTable) data[0];
    final BufferedDataTable outTable = super.execute(new BufferedDataTable[] { inTable }, exec)[0];
    final FilterResult res = getFilterResult(inTable.getSpec());
    final PMMLPortObject pmmlOut = createPMMLOut((PMMLPortObject) data[1], outTable.getSpec(), res);
    return new PortObject[] { outTable, pmmlOut };
}