Example usage for org.apache.commons.lang ArrayUtils toPrimitive

Introduction

In this page you can find the example usage for org.apache.commons.lang ArrayUtils toPrimitive.

Prototype

public static boolean[] toPrimitive(Boolean[] array) 

Source Link

Document

Converts an array of object Booleans to primitives.

Usage

From source file:org.cesecore.certificates.certificateprofile.CertificateProfile.java

/**
 * Used for bitmasks that don't fit in an int.
 * E.g. the 5-byte bitmask for Authentication Terminals
 *//*from w  w w.  j a v a2s .c o  m*/
public byte[] getCVCLongAccessRights() {
    if (data.get(CVCLONGACCESSRIGHTS) == null) {
        return null;
    }
    @SuppressWarnings("unchecked")
    List<Byte> rightsList = (List<Byte>) data.get(CVCLONGACCESSRIGHTS);
    return ArrayUtils.toPrimitive(rightsList.toArray(new Byte[0]));
}

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From source file:org.csstudio.opibuilder.converter.model.EdmPointsList.java

/**
 * Returns the integer value.//w w w . j  a v  a 2s .c om
 * @return   Value of EdmInt instance.
 */
public int[] get() {
    return ArrayUtils.toPrimitive(val.toArray(new Integer[0]));
}

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From source file:org.diffkit.diff.conf.DKAutomaticTableComparison.java

/**
 * maps only columns that have same name on both sides. Uses only columns
 * that don't participate in the key for diffIndexes. Uses the diff keys for
 * display/*from   w  w w.  j a  va 2  s  .  c  o m*/
 */
public static DKStandardTableComparison createDefaultTableComparison(DKTableModel lhsModel_,
        DKTableModel rhsModel_, Float numberTolerance_, Map<String, Float> toleranceMap_) {
    DKValidate.notNull(lhsModel_, rhsModel_);
    DKColumnComparison[] map = createDefaultMap(lhsModel_, rhsModel_, numberTolerance_, toleranceMap_);
    List<Integer> diffIndexesValue = new ArrayList<Integer>();
    if (map != null) {
        for (int i = 0; i < map.length; i++) {
            if (!map[i].columnsAreKey())
                diffIndexesValue.add(i);
        }
    }
    int[] diffIndexes = ArrayUtils.toPrimitive(diffIndexesValue.toArray(new Integer[diffIndexesValue.size()]));
    int[][] displayIndexes = new int[2][];
    displayIndexes[DKSide.LEFT_INDEX] = lhsModel_.getKey();
    displayIndexes[DKSide.RIGHT_INDEX] = rhsModel_.getKey();
    return new DKStandardTableComparison(lhsModel_, rhsModel_, DKDiff.Kind.BOTH, map, diffIndexes,
            displayIndexes, Long.MAX_VALUE);
}

---

From source file:org.dkpro.similarity.experiments.sts2013.util.Evaluator.java

@SuppressWarnings("unchecked")
public static void runEvaluationMetric(Mode mode, EvaluationMetric metric, Dataset... datasets)
        throws IOException {
    StringBuilder sb = new StringBuilder();

    // Compute Pearson correlation for the specified datasets
    for (Dataset dataset : datasets) {
        computePearsonCorrelation(mode, dataset);
    }/*from   w ww. ja va  2  s  . c o m*/

    if (metric == PearsonAll) {
        List<Double> concatExp = new ArrayList<Double>();
        List<Double> concatGS = new ArrayList<Double>();

        // Concat the scores
        for (Dataset dataset : datasets) {
            File expScoresFile = new File(
                    OUTPUT_DIR + "/" + mode.toString().toLowerCase() + "/" + dataset.toString() + ".csv");

            List<String> lines = FileUtils.readLines(expScoresFile);

            for (String line : lines) {
                concatExp.add(Double.parseDouble(line));
            }
        }

        // Concat the gold standard
        for (Dataset dataset : datasets) {
            String gsScoresFilePath = GOLDSTANDARD_DIR + "/" + mode.toString().toLowerCase() + "/" + "STS.gs."
                    + dataset.toString() + ".txt";

            PathMatchingResourcePatternResolver r = new PathMatchingResourcePatternResolver();
            Resource res = r.getResource(gsScoresFilePath);
            File gsScoresFile = res.getFile();

            List<String> lines = FileUtils.readLines(gsScoresFile);

            for (String line : lines) {
                concatGS.add(Double.parseDouble(line));
            }
        }

        double[] concatExpArray = ArrayUtils.toPrimitive(concatExp.toArray(new Double[concatExp.size()]));
        double[] concatGSArray = ArrayUtils.toPrimitive(concatGS.toArray(new Double[concatGS.size()]));

        PearsonsCorrelation pearson = new PearsonsCorrelation();
        Double correl = pearson.correlation(concatExpArray, concatGSArray);

        sb.append(correl.toString());
    } else if (metric == PearsonMean) {
        List<Double> scores = new ArrayList<Double>();

        for (Dataset dataset : datasets) {
            File resultFile = new File(
                    OUTPUT_DIR + "/" + mode.toString().toLowerCase() + "/" + dataset.toString() + ".txt");
            double score = Double.parseDouble(FileUtils.readFileToString(resultFile));

            scores.add(score);
        }

        double mean = 0.0;
        for (Double score : scores) {
            mean += score;
        }
        mean = mean / scores.size();

        sb.append(mean);
    } else if (metric == PearsonWeightedMean) {
        List<Double> scores = new ArrayList<Double>();
        List<Integer> weights = new ArrayList<Integer>();

        for (Dataset dataset : datasets) {
            File resultFile = new File(
                    OUTPUT_DIR + "/" + mode.toString().toLowerCase() + "/" + dataset.toString() + ".txt");
            double score = Double.parseDouble(FileUtils.readFileToString(resultFile));

            File scoresFile = new File(
                    OUTPUT_DIR + "/" + mode.toString().toLowerCase() + "/" + dataset.toString() + ".csv");
            int weight = FileUtils.readLines(scoresFile).size();

            scores.add(score);
            weights.add(weight);
        }

        double mean = 0.0;
        int weightsum = 0;
        for (int i = 0; i < scores.size(); i++) {
            Double score = scores.get(i);
            Integer weight = weights.get(i);

            mean += weight * score;
            weightsum += weight;
        }
        mean = mean / weightsum;

        sb.append(mean);
    }

    FileUtils.writeStringToFile(
            new File(OUTPUT_DIR + "/" + mode.toString().toLowerCase() + "/" + metric.toString() + ".txt"),
            sb.toString());
}

---

From source file:org.dkpro.similarity.experiments.sts2013.util.Evaluator.java

@SuppressWarnings("unchecked")
private static void computePearsonCorrelation(Mode mode, Dataset dataset) throws IOException {
    File expScoresFile = new File(
            OUTPUT_DIR + "/" + mode.toString().toLowerCase() + "/" + dataset.toString() + ".csv");

    String gsScoresFilePath = GOLDSTANDARD_DIR + "/" + mode.toString().toLowerCase() + "/" + "STS.gs."
            + dataset.toString() + ".txt";

    PathMatchingResourcePatternResolver r = new PathMatchingResourcePatternResolver();
    Resource res = r.getResource(gsScoresFilePath);
    File gsScoresFile = res.getFile();

    List<Double> expScores = new ArrayList<Double>();
    List<Double> gsScores = new ArrayList<Double>();

    List<String> expLines = FileUtils.readLines(expScoresFile);
    List<String> gsLines = FileUtils.readLines(gsScoresFile);

    for (int i = 0; i < expLines.size(); i++) {
        expScores.add(Double.parseDouble(expLines.get(i)));
        gsScores.add(Double.parseDouble(gsLines.get(i)));
    }/*from www. ja  va 2 s .co m*/

    double[] expArray = ArrayUtils.toPrimitive(expScores.toArray(new Double[expScores.size()]));
    double[] gsArray = ArrayUtils.toPrimitive(gsScores.toArray(new Double[gsScores.size()]));

    PearsonsCorrelation pearson = new PearsonsCorrelation();
    Double correl = pearson.correlation(expArray, gsArray);

    FileUtils.writeStringToFile(
            new File(OUTPUT_DIR + "/" + mode.toString().toLowerCase() + "/" + dataset.toString() + ".txt"),
            correl.toString());
}

---

From source file:org.dkpro.similarity.experiments.sts2013baseline.util.Evaluator.java

public static void runEvaluationMetric(Mode mode, EvaluationMetric metric, Dataset... datasets)
        throws IOException {
    StringBuilder sb = new StringBuilder();

    // Compute Pearson correlation for the specified datasets
    for (Dataset dataset : datasets) {
        computePearsonCorrelation(mode, dataset);
    }//from  ww  w  .  j a v a  2s . co m

    if (metric == PearsonAll) {
        List<Double> concatExp = new ArrayList<Double>();
        List<Double> concatGS = new ArrayList<Double>();

        // Concat the scores
        for (Dataset dataset : datasets) {
            File expScoresFile = new File(
                    OUTPUT_DIR + "/" + mode.toString().toLowerCase() + "/" + dataset.toString() + ".csv");

            List<String> lines = FileUtils.readLines(expScoresFile);

            for (String line : lines) {
                concatExp.add(Double.parseDouble(line));
            }
        }

        // Concat the gold standard
        for (Dataset dataset : datasets) {
            String gsScoresFilePath = GOLDSTANDARD_DIR + "/" + mode.toString().toLowerCase() + "/" + "STS.gs."
                    + dataset.toString() + ".txt";

            PathMatchingResourcePatternResolver r = new PathMatchingResourcePatternResolver();
            Resource res = r.getResource(gsScoresFilePath);
            File gsScoresFile = res.getFile();

            List<String> lines = FileUtils.readLines(gsScoresFile);

            for (String line : lines) {
                concatGS.add(Double.parseDouble(line));
            }
        }

        double[] concatExpArray = ArrayUtils.toPrimitive(concatExp.toArray(new Double[concatExp.size()]));
        double[] concatGSArray = ArrayUtils.toPrimitive(concatGS.toArray(new Double[concatGS.size()]));

        PearsonsCorrelation pearson = new PearsonsCorrelation();
        Double correl = pearson.correlation(concatExpArray, concatGSArray);

        sb.append(correl.toString());
    } else if (metric == PearsonMean) {
        List<Double> scores = new ArrayList<Double>();

        for (Dataset dataset : datasets) {
            File resultFile = new File(
                    OUTPUT_DIR + "/" + mode.toString().toLowerCase() + "/" + dataset.toString() + ".txt");
            double score = Double.parseDouble(FileUtils.readFileToString(resultFile));

            scores.add(score);
        }

        double mean = 0.0;
        for (Double score : scores) {
            mean += score;
        }
        mean = mean / scores.size();

        sb.append(mean);
    }

    FileUtils.writeStringToFile(
            new File(OUTPUT_DIR + "/" + mode.toString().toLowerCase() + "/" + metric.toString() + ".txt"),
            sb.toString());
}

---

From source file:org.dkpro.similarity.experiments.sts2013baseline.util.Evaluator.java

private static void computePearsonCorrelation(Mode mode, Dataset dataset) throws IOException {
    File expScoresFile = new File(
            OUTPUT_DIR + "/" + mode.toString().toLowerCase() + "/" + dataset.toString() + ".csv");

    String gsScoresFilePath = GOLDSTANDARD_DIR + "/" + mode.toString().toLowerCase() + "/" + "STS.gs."
            + dataset.toString() + ".txt";

    PathMatchingResourcePatternResolver r = new PathMatchingResourcePatternResolver();
    Resource res = r.getResource(gsScoresFilePath);
    File gsScoresFile = res.getFile();

    List<Double> expScores = new ArrayList<Double>();
    List<Double> gsScores = new ArrayList<Double>();

    List<String> expLines = FileUtils.readLines(expScoresFile);
    List<String> gsLines = FileUtils.readLines(gsScoresFile);

    for (int i = 0; i < expLines.size(); i++) {
        expScores.add(Double.parseDouble(expLines.get(i)));
        gsScores.add(Double.parseDouble(gsLines.get(i)));
    }// ww w .j  a  v  a  2s  .c o m

    double[] expArray = ArrayUtils.toPrimitive(expScores.toArray(new Double[expScores.size()]));
    double[] gsArray = ArrayUtils.toPrimitive(gsScores.toArray(new Double[gsScores.size()]));

    PearsonsCorrelation pearson = new PearsonsCorrelation();
    Double correl = pearson.correlation(expArray, gsArray);

    FileUtils.writeStringToFile(
            new File(OUTPUT_DIR + "/" + mode.toString().toLowerCase() + "/" + dataset.toString() + ".txt"),
            correl.toString());
}

---

From source file:org.dragonet.net.DragonetSession.java

private synchronized void sendAllACK() {
    if (this.queueACK.isEmpty()) {
        return;// w  w w .  jav a 2  s  .  com
    }
    int[] ackSeqs = ArrayUtils.toPrimitive(this.queueACK.toArray(new Integer[0]));
    Arrays.sort(ackSeqs);
    this.queueACK.clear();
    ByteArrayOutputStream allRecBos = new ByteArrayOutputStream();
    PEBinaryWriter allRecWriter = new PEBinaryWriter(allRecBos);
    try {
        int count = ackSeqs.length;
        int records = 0;
        if (count > 0) {
            int pointer = 1;
            int start = ackSeqs[0];
            int last = ackSeqs[0];
            ByteArrayOutputStream recBos = new ByteArrayOutputStream();
            PEBinaryWriter recWriter;
            while (pointer < count) {
                int current = ackSeqs[pointer++];
                int diff = current - last;
                if (diff == 1) {
                    last = current;
                } else if (diff > 1) { //Forget about duplicated packets (bad queues?)
                    recBos.reset();
                    recWriter = new PEBinaryWriter(recBos);
                    if (start == last) {
                        recWriter.writeByte((byte) 0x01);
                        recWriter.writeTriad(start);
                        start = last = current;
                    } else {
                        recWriter.writeByte((byte) 0x00);
                        recWriter.writeTriad(start);
                        recWriter.writeTriad(last);
                        start = last = current;
                    }
                    records++;
                }
            }
            if (start == last) {
                allRecWriter.writeByte((byte) 0x01);
                allRecWriter.writeTriad(start);
            } else {
                allRecWriter.writeByte((byte) 0x00);
                allRecWriter.writeTriad(start);
                allRecWriter.writeTriad(last);
            }
            records++;
        }
        ByteArrayOutputStream bos = new ByteArrayOutputStream();
        PEBinaryWriter writer = new PEBinaryWriter(bos);
        writer.writeByte((byte) 0xC0);
        writer.writeShort((short) (records & 0xFFFF));
        writer.write(allRecBos.toByteArray());
        this.dServer.getNetworkHandler().send(bos.toByteArray(), this.remoteAddress);
    } catch (IOException e) {
    }
}

---

From source file:org.dragonet.net.DragonetSession.java

private synchronized void sendAllNACK() {
    if (this.queueNACK.isEmpty()) {
        return;/*from   w  w w  . ja  va2  s. co m*/
    }
    int[] ackSeqs = ArrayUtils.toPrimitive(this.queueNACK.toArray(new Integer[0]));
    Arrays.sort(ackSeqs);
    this.queueNACK.clear();
    ByteArrayOutputStream allRecBos = new ByteArrayOutputStream();
    PEBinaryWriter allRecWriter = new PEBinaryWriter(allRecBos);
    try {
        int count = ackSeqs.length;
        int records = 0;
        if (count > 0) {
            int pointer = 1;
            int start = ackSeqs[0];
            int last = ackSeqs[0];
            ByteArrayOutputStream recBos = new ByteArrayOutputStream();
            PEBinaryWriter recWriter;
            while (pointer < count) {
                int current = ackSeqs[pointer++];
                int diff = current - last;
                if (diff == 1) {
                    last = current;
                } else if (diff > 1) { //Forget about duplicated packets (bad queues?)
                    recBos.reset();
                    recWriter = new PEBinaryWriter(recBos);
                    if (start == last) {
                        recWriter.writeByte((byte) 0x01);
                        recWriter.writeTriad(start);
                        start = last = current;
                    } else {
                        recWriter.writeByte((byte) 0x00);
                        recWriter.writeTriad(start);
                        recWriter.writeTriad(last);
                        start = last = current;
                    }
                    records++;
                }
            }
            if (start == last) {
                allRecWriter.writeByte((byte) 0x01);
                allRecWriter.writeTriad(start);
            } else {
                allRecWriter.writeByte((byte) 0x00);
                allRecWriter.writeTriad(start);
                allRecWriter.writeTriad(last);
            }
            records++;
        }
        ByteArrayOutputStream bos = new ByteArrayOutputStream();
        PEBinaryWriter writer = new PEBinaryWriter(bos);
        writer.writeByte((byte) 0xA0);
        writer.writeShort((short) (records & 0xFFFF));
        writer.write(allRecBos.toByteArray());
        this.dServer.getNetworkHandler().send(bos.toByteArray(), this.remoteAddress);
    } catch (IOException e) {
    }
}

---

From source file:org.dragonet.net.DragonetSession.java

/**
 * Process a ACK packet/*from ww w . jav a2s.c  o m*/
 *
 * @param buffer The ACK packet binary array
 */
public void processACKPacket(byte[] buffer) {
    try {
        PEBinaryReader reader = new PEBinaryReader(new ByteArrayInputStream(buffer));
        int count = reader.readShort();
        List<Integer> packets = new ArrayList<>();
        for (int i = 0; i < count && reader.available() > 0; ++i) {
            byte[] tmp = new byte[6];
            if (reader.readByte() == (byte) 0x00) {
                int start = reader.readTriad();
                int end = reader.readTriad();
                if ((end - start) > 4096) {
                    end = start + 4096;
                }
                for (int c = start; c <= end; ++c) {
                    packets.add(c);
                }
            } else {
                packets.add(reader.readTriad());
            }
        }
        int[] seqNums = ArrayUtils.toPrimitive(packets.toArray(new Integer[0]));
        for (int seq : seqNums) {
            if (this.cachedOutgoingPacket.containsKey(seq)) {
                this.cachedOutgoingPacket.remove(seq);
            }
        }
    } catch (IOException e) {
    }
}

---

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