Example usage for weka.core Instance toDoubleArray

Introduction

In this page you can find the example usage for weka.core Instance toDoubleArray.

Prototype

public double[] toDoubleArray();

Source Link

Document

Returns the values of each attribute as an array of doubles.

Usage

From source file:SpectralClusterer.java

License:Open Source License

/**
 * Classifies an instance w.r.t. the partitions found. It applies a naive
 * min-distance algorithm.//ww  w .  j  a  v a2s .  com
 * 
 * @param instance
 *            the instance to classify
 * @return the cluster that contains the nearest point to the instance
 */
public int clusterInstance(Instance instance) throws java.lang.Exception {
    DoubleMatrix1D u = DoubleFactory1D.dense.make(instance.toDoubleArray());
    double min_dist = Double.POSITIVE_INFINITY;
    int c = -1;
    for (int i = 0; i < v.rows(); i++) {
        double dist = distnorm2(u, v.viewRow(i));
        if (dist < min_dist) {
            c = cluster[i];
            min_dist = dist;
        }
    }
    return c;
}

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From source file:MPCKMeans.java

License:Open Source License

/** lookup the instance in the checksum hash, assuming transductive clustering
 * @param instance instance to be looked up
 * @return the index of the cluster to which the instance was assigned, -1 if the instance has not bee clustered
 *//* w  w w  .j a v  a2s .  co m*/
protected int lookupInstanceCluster(Instance instance) throws Exception {
    int classIdx = instance.classIndex();
    double checksum = 0;

    // need to normalize using original metric, since cluster data is normalized similarly
    if (m_metric.doesNormalizeData()) {
        if (m_Trainable == TRAINING_INTERNAL) {
            m_metric.resetMetric();
        }
        m_metric.normalizeInstanceWeighted(instance);
    }

    double[] values1 = instance.toDoubleArray();
    for (int i = 0; i < values1.length; i++) {
        if (i != classIdx) {
            checksum += m_checksumCoeffs[i] * values1[i];
        }
    }

    Object list = m_checksumHash.get(new Double((float) checksum));
    if (list != null) {
        // go through the list of instances with the same checksum and find the one that is equivalent
        ArrayList checksumList = (ArrayList) list;
        for (int i = 0; i < checksumList.size(); i++) {
            int instanceIdx = ((Integer) checksumList.get(i)).intValue();
            Instance listInstance = m_Instances.instance(instanceIdx);
            double[] values2 = listInstance.toDoubleArray();
            boolean equal = true;
            for (int j = 0; j < values1.length && equal == true; j++) {
                if (j != classIdx) {
                    if ((float) values1[j] != (float) values2[j]) {
                        equal = false;
                    }
                }
            }
            if (equal == true) {
                return m_ClusterAssignments[instanceIdx];
            }
        }
    }
    return -1;
}

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From source file:MPCKMeans.java

License:Open Source License

/** Sets training instances */
public void setInstances(Instances instances) {
    m_Instances = instances;/* ww  w .  j av  a2s  .  c  om*/

    // create the checksum coefficients
    m_checksumCoeffs = new double[instances.numAttributes()];
    for (int i = 0; i < m_checksumCoeffs.length; i++) {
        m_checksumCoeffs[i] = m_RandomNumberGenerator.nextDouble();
    }

    // hash the instance checksums
    m_checksumHash = new HashMap(instances.numInstances());
    int classIdx = instances.classIndex();
    for (int i = 0; i < instances.numInstances(); i++) {
        Instance instance = instances.instance(i);
        double[] values = instance.toDoubleArray();
        double checksum = 0;

        for (int j = 0; j < values.length; j++) {
            if (j != classIdx) {
                checksum += m_checksumCoeffs[j] * values[j];
            }
        }

        // take care of chaining
        Object list = m_checksumHash.get(new Double((float) checksum));
        ArrayList idxList = null;
        if (list == null) {
            idxList = new ArrayList();
            m_checksumHash.put(new Double((float) checksum), idxList);
        } else { // chaining
            idxList = (ArrayList) list;
        }
        idxList.add(new Integer(i));
    }
}

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From source file:adams.data.instances.AbstractInstanceGenerator.java

License:Open Source License

/**
 * For adding IDs, notes, additional fields to the data.
 *
 * @param data   the input data//from  ww w. j  av  a2s.c  o  m
 * @param inst   the generated instance
 * @return      the processed instance
 */
protected Instance postProcessOutput(T data, Instance inst) {
    Instance result;
    double[] values;
    int index;
    Report report;

    values = inst.toDoubleArray();
    report = data.getReport();

    if (m_AddDatabaseID) {
        index = m_OutputHeader.attribute(ArffUtils.getDBIDName()).index();
        values[index] = report.getDatabaseID();
    }

    result = new DenseInstance(1.0, values);
    result.setDataset(m_OutputHeader);

    return result;
}

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From source file:adams.flow.transformer.WekaInstanceBuffer.java

License:Open Source License

/**
 * Executes the flow item.// w  w w  . j a  v a 2s  .  c o m
 *
 * @return      null if everything is fine, otherwise error message
 */
@Override
protected String doExecute() {
    String result;
    Instance[] insts;
    Instance inst;
    double[] values;
    int i;
    int n;
    boolean updated;

    result = null;

    if (m_Operation == Operation.INSTANCE_TO_INSTANCES) {
        if (m_InputToken.getPayload() instanceof Instance) {
            insts = new Instance[] { (Instance) m_InputToken.getPayload() };
        } else {
            insts = (Instance[]) m_InputToken.getPayload();
        }

        for (n = 0; n < insts.length; n++) {
            inst = insts[n];

            if ((m_Buffer != null) && m_CheckHeader) {
                if (!m_Buffer.equalHeaders(inst.dataset())) {
                    getLogger().info("Header changed, resetting buffer");
                    m_Buffer = null;
                }
            }

            // buffer instance
            if (m_Buffer == null)
                m_Buffer = new Instances(inst.dataset(), 0);

            // we need to make sure that string and relational values are in our
            // buffer header and update the current Instance accordingly before
            // buffering it
            values = inst.toDoubleArray();
            updated = false;
            for (i = 0; i < values.length; i++) {
                if (inst.isMissing(i))
                    continue;
                if (inst.attribute(i).isString()) {
                    values[i] = m_Buffer.attribute(i).addStringValue(inst.stringValue(i));
                    updated = true;
                } else if (inst.attribute(i).isRelationValued()) {
                    values[i] = m_Buffer.attribute(i).addRelation(inst.relationalValue(i));
                    updated = true;
                }
            }

            if (updated) {
                if (inst instanceof SparseInstance) {
                    inst = new SparseInstance(inst.weight(), values);
                } else if (inst instanceof BinarySparseInstance) {
                    inst = new BinarySparseInstance(inst.weight(), values);
                } else {
                    if (!(inst instanceof DenseInstance)) {
                        getLogger().severe("Unhandled instance class (" + inst.getClass().getName() + "), "
                                + "defaulting to " + DenseInstance.class.getName());
                    }
                    inst = new DenseInstance(inst.weight(), values);
                }
            } else {
                inst = (Instance) inst.copy();
            }

            m_Buffer.add(inst);
        }

        if (m_Buffer.numInstances() % m_Interval == 0) {
            m_OutputToken = new Token(m_Buffer);
            if (m_ClearBuffer)
                m_Buffer = null;
        }
    } else if (m_Operation == Operation.INSTANCES_TO_INSTANCE) {
        m_Buffer = (Instances) m_InputToken.getPayload();
        m_Iterator = m_Buffer.iterator();
    } else {
        throw new IllegalStateException("Unhandled operation: " + m_Operation);
    }

    return result;
}

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From source file:adams.flow.transformer.WekaInstancesAppend.java

License:Open Source License

/**
 * Executes the flow item./*from  ww  w  .j  a  v  a  2  s . c o  m*/
 *
 * @return      null if everything is fine, otherwise error message
 */
@Override
protected String doExecute() {
    String result;
    String[] filesStr;
    File[] files;
    int i;
    int n;
    Instances[] inst;
    Instances full;
    String msg;
    StringBuilder relation;
    double[] values;

    result = null;

    // get filenames
    files = null;
    inst = null;
    if (m_InputToken.getPayload() instanceof String[]) {
        filesStr = (String[]) m_InputToken.getPayload();
        files = new File[filesStr.length];
        for (i = 0; i < filesStr.length; i++)
            files[i] = new PlaceholderFile(filesStr[i]);
    } else if (m_InputToken.getPayload() instanceof File[]) {
        files = (File[]) m_InputToken.getPayload();
    } else if (m_InputToken.getPayload() instanceof Instances[]) {
        inst = (Instances[]) m_InputToken.getPayload();
    } else {
        throw new IllegalStateException("Unhandled input type: " + m_InputToken.getPayload().getClass());
    }

    // load data?
    if (files != null) {
        inst = new Instances[files.length];
        for (i = 0; i < files.length; i++) {
            try {
                inst[i] = DataSource.read(files[i].getAbsolutePath());
            } catch (Exception e) {
                result = handleException("Failed to load dataset: " + files[i], e);
                break;
            }
        }
    }

    // test compatibility
    if (result == null) {
        for (i = 0; i < inst.length - 1; i++) {
            for (n = i + 1; n < inst.length; n++) {
                if ((msg = inst[i].equalHeadersMsg(inst[n])) != null) {
                    result = "Dataset #" + (i + 1) + " and #" + (n + 1) + " are not compatible:\n" + msg;
                    break;
                }
            }
            if (result != null)
                break;
        }
    }

    // append
    if (result == null) {
        full = new Instances(inst[0]);
        relation = new StringBuilder(inst[0].relationName());
        for (i = 1; i < inst.length; i++) {
            relation.append("+" + inst[i].relationName());
            for (Instance row : inst[i]) {
                values = row.toDoubleArray();
                for (n = 0; n < values.length; n++) {
                    if (row.attribute(n).isString())
                        values[n] = full.attribute(n).addStringValue(row.stringValue(n));
                    else if (row.attribute(n).isRelationValued())
                        values[n] = full.attribute(n).addRelation(row.relationalValue(n));
                }
                if (row instanceof SparseInstance)
                    row = new SparseInstance(row.weight(), values);
                else
                    row = new DenseInstance(row.weight(), values);
                full.add(row);
            }
        }
        full.setRelationName(relation.toString());
        m_OutputToken = new Token(full);
    }

    return result;
}

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From source file:CEP.CEPListener.java

Instances SetDuration(Instances in) throws InterruptedException {
    Instances out = HeaderManager.GetEmptyStructure();
    for (Instance inst : in) {

        double time = inst.toDoubleArray()[5];
        if (time > 20) {
            inst.setValue(5, time - windowSize);
            out.add(inst);//from ww w  .ja  va  2 s  .  c  om
        }
    }
    return out;

}

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From source file:cezeri.utils.FactoryInstance.java

public static double[][] getData(Instances m) {
    double[][] ret = new double[m.numInstances()][m.numAttributes()];
    for (int i = 0; i < m.numInstances(); i++) {
        Instance ins = m.instance(i);
        ret[i] = ins.toDoubleArray();
    }//from  w  w  w  .  j  av a2  s . co m
    return ret;
}

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From source file:cezeri.utils.FactoryInstance.java

public static CMatrix toMatrix(Instances m) {
    double[][] ret = new double[m.numInstances()][m.numAttributes()];
    for (int i = 0; i < m.numInstances(); i++) {
        Instance ins = m.instance(i);
        ret[i] = ins.toDoubleArray();
    }// ww  w. java2 s . c o  m
    return CMatrix.getInstance(ret);
}

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From source file:cezeri.utils.FactoryInstance.java

public static CMatrix fromInstances(Instances m) {
    double[][] ret = new double[m.numInstances()][m.numAttributes()];
    for (int i = 0; i < m.numInstances(); i++) {
        Instance ins = m.instance(i);
        ret[i] = ins.toDoubleArray();
    }//from  ww  w .ja  v a  2  s .  c om
    return CMatrix.getInstance(ret);
}

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