Example usage for java.lang Float compare

List of usage examples for java.lang Float compare

Introduction

In this page you can find the example usage for java.lang Float compare.

Prototype

public static int compare(float f1, float f2) 

Source Link

Document

Compares the two specified float values.

Usage

From source file:org.apache.maven.plugin.javadoc.JavadocReportTest.java

/**
 * Test the javadoc resources.//www  .j  a v a2 s .  c  o m
 *
 * @throws Exception if any
 */
public void testJavadocResources() throws Exception {
    File testPom = new File(unit, "resources-test/resources-test-plugin-config.xml");
    JavadocReport mojo = (JavadocReport) lookupMojo("javadoc", testPom);
    mojo.execute();

    File apidocs = new File(getBasedir(), "target/test/unit/resources-test/target/site/apidocs/");

    File app = new File(apidocs, "resources/test/App.html");
    assertTrue(app.exists());
    String content = readFile(app);
    assertTrue(content.contains("<img src=\"doc-files/maven-feather.png\" alt=\"Maven\">"));
    assertTrue(new File(apidocs, "resources/test/doc-files/maven-feather.png").exists());

    File app2 = new File(apidocs, "resources/test2/App2.html");
    assertTrue(app2.exists());
    content = readFile(app2);
    assertTrue(content.contains("<img src=\"doc-files/maven-feather.png\" alt=\"Maven\">"));
    assertFalse(new File(apidocs, "resources/test2/doc-files/maven-feather.png").exists());

    // with excludes
    testPom = new File(unit, "resources-with-excludes-test/resources-with-excludes-test-plugin-config.xml");
    mojo = (JavadocReport) lookupMojo("javadoc", testPom);
    mojo.execute();

    apidocs = new File(getBasedir(), "target/test/unit/resources-with-excludes-test/target/site/apidocs");

    app = new File(apidocs, "resources/test/App.html");
    assertTrue(app.exists());
    content = readFile(app);
    assertTrue(content.contains("<img src=\"doc-files/maven-feather.png\" alt=\"Maven\">"));

    float javadocVersion = (Float) getVariableValueFromObject(mojo, "fJavadocVersion");
    if (Float.compare(1.8f, javadocVersion) == 0) {
        // https://bugs.openjdk.java.net/browse/JDK-8032205
        assertTrue("This bug appeared in JDK8 and was planned to be fixed in JDK9, see JDK-8032205",
                new File(apidocs, "resources/test/doc-files/maven-feather.png").exists());
    } else {
        assertFalse(new File(apidocs, "resources/test/doc-files/maven-feather.png").exists());
    }

    app2 = new File(apidocs, "resources/test2/App2.html");
    assertTrue(app2.exists());
    content = readFile(app2);
    assertTrue(content.contains("<img src=\"doc-files/maven-feather.png\" alt=\"Maven\">"));
    assertTrue(new File(apidocs, "resources/test2/doc-files/maven-feather.png").exists());
}

From source file:com.moviejukebox.tools.OverrideTools.java

public static boolean checkOverwriteFPS(Movie movie, String source) {
    if (skipCheck(movie, OverrideFlag.FPS, source)) {
        // skip the check
        return Boolean.FALSE;
    } else if (Float.compare(movie.getFps(), 60f) == 0) {
        // assume 60 as default value
        return Boolean.TRUE;
    }// ww w  . ja va2s .  c  o m
    return checkOverwrite(movie, OverrideFlag.FPS, source);
}

From source file:pipeline.misc_util.Utils.java

public static void main(String[] args) throws IOException {// findStepsInProfile
    File profileFile = new File(args[0]);
    int columnIndex = Integer.parseInt(args[1]);
    int xColumnIndex = Integer.parseInt(args[2]);
    int nColumns = Integer.parseInt(args[3]);
    float windowLength = Float.parseFloat(args[4]);

    // FIXME Code duplicated in RegisterVideoLabelTimes plugin. Create a parsing class.
    try (Reader r = new BufferedReader(new FileReader(profileFile))) {

        ReaderTokenizer stok = new ReaderTokenizer(r);

        stok.parseNumbers();// w w  w .j a  va  2  s.com
        int currentColumn = 0;
        // Skip column headers
        for (int i = 0; i < nColumns; i++) {
            stok.nextToken();
        }
        stok.nextToken();

        // FloatList profileList=new ArrayFloatList(100000); //Time in seconds
        // FloatList xPositionList=new ArrayFloatList(100000); //Time in seconds

        ArrayList<float[]> readings = new ArrayList<>();

        int currentIndex = 0;
        readings.add(new float[2]);
        while (stok.ttype != ReaderTokenizer.TT_EOF) {

            if (stok.ttype == ReaderTokenizer.TT_NUMBER) {
                float f = (float) stok.nval;
                if (currentColumn == columnIndex) {
                    readings.get(currentIndex)[1] = f;
                    if (f < 0) {
                        Utils.log("Read negative profile", LogLevel.ERROR);
                    }
                } else if (currentColumn == xColumnIndex) {
                    readings.get(currentIndex)[0] = f;
                    if (f < 0) {
                        Utils.log("Read negative profile", LogLevel.ERROR);
                    }
                }
            } else
                throw new RuntimeException(
                        "Unexpected read from detected cell file " + stok.sval + " of type " + stok.ttype);
            stok.nextToken();
            currentColumn++;
            if (currentColumn == nColumns) {
                currentColumn = 0;
                currentIndex++;
                readings.add(new float[2]);
            }
        }

        readings.remove(readings.size() - 1);

        float[][] readingsArray = readings.toArray(new float[][] { { 1, 2 } });

        Arrays.sort(readingsArray, (o1, o2) -> Float.compare(o1[0], o2[0]));

        float[] steps = minMaxSlidingWindow(readingsArray, windowLength);

        for (int i = 0; i < steps.length; i++) {
            System.out.println((readingsArray[i][0] + windowLength * 0.5) + "\t" + steps[i]);
        }
    } catch (FileNotFoundException e) {
        throw new RuntimeException("Could not find output file to read times from", e);
    }
}

From source file:org.shaman.terrain.polygonal.PolygonalMapGenerator.java

private void createBiomes() {
    if (graph == null) {
        return;//from w  w w .  j ava  2s . c o  m
    }

    //assign temperatures
    for (Graph.Corner c : graph.corners) {
        c.temperature = c.elevation;
        c.temperature *= c.temperature;
        c.temperature = 1 - c.temperature;
    }
    assignCenterTemperature();

    //create random rivers
    Random rand = new Random(seed * 3);
    for (Graph.Corner c : graph.corners) {
        c.river = 0;
    }
    float riverProb = 0.2f;
    float riverStartHeight = 0.7f;
    int riverCounter = 0;
    corner: for (Graph.Corner c : graph.corners) {
        if (c.water || c.elevation < riverStartHeight) {
            continue;
        }
        if (rand.nextFloat() > riverProb) {
            continue;
        }
        if (c.river > 0)
            continue;
        for (Graph.Corner c2 : c.adjacent) {
            if (c2.river > 0) {
                continue corner;
            }
            for (Graph.Corner c3 : c2.adjacent) {
                if (c3.river > 0) {
                    continue corner;
                }
            }
        }
        //start new river from here
        Graph.Corner current = c;
        current.river = Math.max(current.river, 1);
        while (!current.ocean && !current.coast) {
            float minH = current.elevation;
            Graph.Corner minC = null;
            for (Graph.Corner c2 : current.adjacent) {
                if (c2.river > 0 && c2.elevation < current.elevation) {
                    minC = c2; //force closing of rivers
                    break;
                }
                if (c2.elevation < minH) {
                    minC = c2;
                    minH = c2.elevation;
                }
            }
            if (minC == null) {
                LOG.warning("river stuck in a local minima without reaching the ocean");
                break;
            }
            minC.river = Math.max(minC.river, current.river + 1);
            current = minC;
        }
        riverCounter++;
    }
    LOG.info("count of created rivers: " + riverCounter);
    showRivers = true;

    //assign moisture
    Queue<Graph.Corner> queue = new ArrayDeque<>();
    for (Graph.Corner q : graph.corners) {
        if ((q.water || q.river > 0) && !q.ocean) {
            q.moisture = q.river > 0 ? Math.min(3.0f, (0.4f * q.river)) : 1;
            queue.add(q);
        } else {
            q.moisture = 0;
        }
    }
    while (!queue.isEmpty()) {
        Graph.Corner q = queue.poll();
        for (Graph.Corner r : q.adjacent) {
            float newMoisture = q.moisture * 0.8f;
            if (newMoisture > r.moisture) {
                r.moisture = newMoisture;
                queue.add(r);
            }
        }
    }
    for (Graph.Corner q : graph.corners) {
        if (q.ocean || q.coast) {
            q.moisture = 1;
        }
    }

    //redistribute moisture
    ArrayList<Graph.Corner> corners = new ArrayList<>();
    for (Graph.Corner q : graph.corners) {
        if (!q.ocean && !q.coast) {
            corners.add(q);
        }
    }
    Collections.sort(corners, new Comparator<Graph.Corner>() {
        @Override
        public int compare(Graph.Corner o1, Graph.Corner o2) {
            return Float.compare(o1.moisture, o2.moisture);
        }
    });
    for (int i = 0; i < corners.size(); i++) {
        corners.get(i).moisture = i / (float) (corners.size() - 1);
    }
    assignCenterMoisture();

    assignBiomes();

    //update mesh
    updateTemperatureGeometry();
    updateMoistureGeometry();
    updateBiomesGeometry();
}

From source file:ml.shifu.shifu.core.dtrain.dt.DTWorker.java

@Override
public DTWorkerParams doCompute(WorkerContext<DTMasterParams, DTWorkerParams> context) {
    if (context.isFirstIteration()) {
        return new DTWorkerParams();
    }//from  ww  w  .  j a v  a 2s. c o m

    DTMasterParams lastMasterResult = context.getLastMasterResult();
    final List<TreeNode> trees = lastMasterResult.getTrees();
    final Map<Integer, TreeNode> todoNodes = lastMasterResult.getTodoNodes();
    if (todoNodes == null) {
        return new DTWorkerParams();
    }

    LOG.info("Start to work: todoNodes size is {}", todoNodes.size());

    Map<Integer, NodeStats> statistics = initTodoNodeStats(todoNodes);

    double trainError = 0d, validationError = 0d;
    double weightedTrainCount = 0d, weightedValidationCount = 0d;
    // renew random seed
    if (this.isGBDT && !this.gbdtSampleWithReplacement && lastMasterResult.isSwitchToNextTree()) {
        this.baggingRandomMap = new HashMap<Integer, Random>();
    }

    long start = System.nanoTime();
    for (Data data : this.trainingData) {
        if (this.isRF) {
            for (TreeNode treeNode : trees) {
                if (treeNode.getNode().getId() == Node.INVALID_INDEX) {
                    continue;
                }

                Node predictNode = predictNodeIndex(treeNode.getNode(), data, true);
                if (predictNode.getPredict() != null) {
                    // only update when not in first node, for treeNode, no predict statistics at that time
                    float weight = data.subsampleWeights[treeNode.getTreeId()];
                    if (Float.compare(weight, 0f) == 0) {
                        // oob data, no need to do weighting
                        validationError += data.significance * loss
                                .computeError((float) (predictNode.getPredict().getPredict()), data.label);
                        weightedValidationCount += data.significance;
                    } else {
                        trainError += weight * data.significance * loss
                                .computeError((float) (predictNode.getPredict().getPredict()), data.label);
                        weightedTrainCount += weight * data.significance;
                    }
                }
            }
        }

        if (this.isGBDT) {
            if (this.isContinuousEnabled && lastMasterResult.isContinuousRunningStart()) {
                recoverGBTData(context, data.output, data.predict, data, false);
                trainError += data.significance * loss.computeError(data.predict, data.label);
                weightedTrainCount += data.significance;
            } else {
                if (isNeedRecoverGBDTPredict) {
                    if (this.recoverTrees == null) {
                        this.recoverTrees = recoverCurrentTrees();
                    }
                    // recover gbdt data for fail over
                    recoverGBTData(context, data.output, data.predict, data, true);
                }
                int currTreeIndex = trees.size() - 1;

                if (lastMasterResult.isSwitchToNextTree()) {
                    if (currTreeIndex >= 1) {
                        Node node = trees.get(currTreeIndex - 1).getNode();
                        Node predictNode = predictNodeIndex(node, data, false);
                        if (predictNode.getPredict() != null) {
                            double predict = predictNode.getPredict().getPredict();
                            // first tree logic, master must set it to first tree even second tree with ROOT is
                            // sending
                            if (context.getLastMasterResult().isFirstTree()) {
                                data.predict = (float) predict;
                            } else {
                                // random drop
                                boolean drop = (this.dropOutRate > 0.0
                                        && dropOutRandom.nextDouble() < this.dropOutRate);
                                if (!drop) {
                                    data.predict += (float) (this.learningRate * predict);
                                }
                            }
                            data.output = -1f * loss.computeGradient(data.predict, data.label);
                        }
                        // if not sampling with replacement in gbdt, renew bagging sample rate in next tree
                        if (!this.gbdtSampleWithReplacement) {
                            Random random = null;
                            int classValue = (int) (data.label + 0.01f);
                            if (this.isStratifiedSampling) {
                                random = baggingRandomMap.get(classValue);
                                if (random == null) {
                                    random = DTrainUtils.generateRandomBySampleSeed(
                                            modelConfig.getTrain().getBaggingSampleSeed(),
                                            CommonConstants.NOT_CONFIGURED_BAGGING_SEED);
                                    baggingRandomMap.put(classValue, random);
                                }
                            } else {
                                random = baggingRandomMap.get(0);
                                if (random == null) {
                                    random = DTrainUtils.generateRandomBySampleSeed(
                                            modelConfig.getTrain().getBaggingSampleSeed(),
                                            CommonConstants.NOT_CONFIGURED_BAGGING_SEED);
                                    baggingRandomMap.put(0, random);
                                }
                            }
                            if (random.nextDouble() <= modelConfig.getTrain().getBaggingSampleRate()) {
                                data.subsampleWeights[currTreeIndex % data.subsampleWeights.length] = 1f;
                            } else {
                                data.subsampleWeights[currTreeIndex % data.subsampleWeights.length] = 0f;
                            }
                        }
                    }
                }

                if (context.getLastMasterResult().isFirstTree() && !lastMasterResult.isSwitchToNextTree()) {
                    Node currTree = trees.get(currTreeIndex).getNode();
                    Node predictNode = predictNodeIndex(currTree, data, true);
                    if (predictNode.getPredict() != null) {
                        trainError += data.significance * loss
                                .computeError((float) (predictNode.getPredict().getPredict()), data.label);
                        weightedTrainCount += data.significance;
                    }
                } else {
                    trainError += data.significance * loss.computeError(data.predict, data.label);
                    weightedTrainCount += data.significance;
                }
            }
        }
    }
    LOG.debug("Compute train error time is {}ms", TimeUnit.NANOSECONDS.toMillis(System.nanoTime() - start));

    if (validationData != null) {
        start = System.nanoTime();
        for (Data data : this.validationData) {
            if (this.isRF) {
                for (TreeNode treeNode : trees) {
                    if (treeNode.getNode().getId() == Node.INVALID_INDEX) {
                        continue;
                    }
                    Node predictNode = predictNodeIndex(treeNode.getNode(), data, true);
                    if (predictNode.getPredict() != null) {
                        // only update when not in first node, for treeNode, no predict statistics at that time
                        validationError += data.significance * loss
                                .computeError((float) (predictNode.getPredict().getPredict()), data.label);
                        weightedValidationCount += data.significance;
                    }
                }
            }

            if (this.isGBDT) {
                if (this.isContinuousEnabled && lastMasterResult.isContinuousRunningStart()) {
                    recoverGBTData(context, data.output, data.predict, data, false);
                    validationError += data.significance * loss.computeError(data.predict, data.label);
                    weightedValidationCount += data.significance;
                } else {
                    if (isNeedRecoverGBDTPredict) {
                        if (this.recoverTrees == null) {
                            this.recoverTrees = recoverCurrentTrees();
                        }
                        // recover gbdt data for fail over
                        recoverGBTData(context, data.output, data.predict, data, true);
                    }
                    int currTreeIndex = trees.size() - 1;
                    if (lastMasterResult.isSwitchToNextTree()) {
                        if (currTreeIndex >= 1) {
                            Node node = trees.get(currTreeIndex - 1).getNode();
                            Node predictNode = predictNodeIndex(node, data, false);
                            if (predictNode.getPredict() != null) {
                                double predict = predictNode.getPredict().getPredict();
                                if (context.getLastMasterResult().isFirstTree()) {
                                    data.predict = (float) predict;
                                } else {
                                    data.predict += (float) (this.learningRate * predict);
                                }
                                data.output = -1f * loss.computeGradient(data.predict, data.label);
                            }
                        }
                    }
                    if (context.getLastMasterResult().isFirstTree() && !lastMasterResult.isSwitchToNextTree()) {
                        Node predictNode = predictNodeIndex(trees.get(currTreeIndex).getNode(), data, true);
                        if (predictNode.getPredict() != null) {
                            validationError += data.significance * loss
                                    .computeError((float) (predictNode.getPredict().getPredict()), data.label);
                            weightedValidationCount += data.significance;
                        }
                    } else {
                        validationError += data.significance * loss.computeError(data.predict, data.label);
                        weightedValidationCount += data.significance;
                    }
                }
            }
        }
        LOG.debug("Compute val error time is {}ms", TimeUnit.NANOSECONDS.toMillis(System.nanoTime() - start));
    }

    if (this.isGBDT) {
        // reset trees to null to save memory
        this.recoverTrees = null;
        if (this.isNeedRecoverGBDTPredict) {
            // no need recover again
            this.isNeedRecoverGBDTPredict = false;
        }
    }

    start = System.nanoTime();
    CompletionService<Map<Integer, NodeStats>> completionService = new ExecutorCompletionService<Map<Integer, NodeStats>>(
            this.threadPool);

    int realThreadCount = 0;
    LOG.debug("while todo size {}", todoNodes.size());

    int realRecords = this.trainingData.size();
    int realThreads = this.workerThreadCount > realRecords ? realRecords : this.workerThreadCount;

    int[] trainLows = new int[realThreads];
    int[] trainHighs = new int[realThreads];

    int stepCount = realRecords / realThreads;
    if (realRecords % realThreads != 0) {
        // move step count to append last gap to avoid last thread worse 2*stepCount-1
        stepCount += (realRecords % realThreads) / stepCount;
    }
    for (int i = 0; i < realThreads; i++) {
        trainLows[i] = i * stepCount;
        if (i != realThreads - 1) {
            trainHighs[i] = trainLows[i] + stepCount - 1;
        } else {
            trainHighs[i] = realRecords - 1;
        }
    }

    for (int i = 0; i < realThreads; i++) {
        final Map<Integer, TreeNode> localTodoNodes = new HashMap<Integer, TreeNode>(todoNodes);
        final Map<Integer, NodeStats> localStatistics = initTodoNodeStats(todoNodes);

        final int startIndex = trainLows[i];
        final int endIndex = trainHighs[i];
        LOG.info("Thread {} todo size {} stats size {} start index {} end index {}", i, localTodoNodes.size(),
                localStatistics.size(), startIndex, endIndex);

        if (localTodoNodes.size() == 0) {
            continue;
        }
        realThreadCount += 1;
        completionService.submit(new Callable<Map<Integer, NodeStats>>() {
            @Override
            public Map<Integer, NodeStats> call() throws Exception {
                long start = System.nanoTime();
                List<Integer> nodeIndexes = new ArrayList<Integer>(trees.size());
                for (int j = startIndex; j <= endIndex; j++) {
                    Data data = DTWorker.this.trainingData.get(j);
                    nodeIndexes.clear();
                    if (DTWorker.this.isRF) {
                        for (TreeNode treeNode : trees) {
                            if (treeNode.getNode().getId() == Node.INVALID_INDEX) {
                                nodeIndexes.add(Node.INVALID_INDEX);
                            } else {
                                Node predictNode = predictNodeIndex(treeNode.getNode(), data, false);
                                nodeIndexes.add(predictNode.getId());
                            }
                        }
                    }

                    if (DTWorker.this.isGBDT) {
                        int currTreeIndex = trees.size() - 1;
                        Node predictNode = predictNodeIndex(trees.get(currTreeIndex).getNode(), data, false);
                        // update node index
                        nodeIndexes.add(predictNode.getId());
                    }
                    for (Map.Entry<Integer, TreeNode> entry : localTodoNodes.entrySet()) {
                        // only do statistics on effective data
                        Node todoNode = entry.getValue().getNode();
                        int treeId = entry.getValue().getTreeId();
                        int currPredictIndex = 0;
                        if (DTWorker.this.isRF) {
                            currPredictIndex = nodeIndexes.get(entry.getValue().getTreeId());
                        }
                        if (DTWorker.this.isGBDT) {
                            currPredictIndex = nodeIndexes.get(0);
                        }

                        if (todoNode.getId() == currPredictIndex) {
                            List<Integer> features = entry.getValue().getFeatures();
                            if (features.isEmpty()) {
                                features = getAllValidFeatures();
                            }
                            for (Integer columnNum : features) {
                                double[] featuerStatistic = localStatistics.get(entry.getKey())
                                        .getFeatureStatistics().get(columnNum);
                                float weight = data.subsampleWeights[treeId % data.subsampleWeights.length];
                                if (Float.compare(weight, 0f) != 0) {
                                    // only compute weight is not 0
                                    short binIndex = data.inputs[DTWorker.this.inputIndexMap.get(columnNum)];
                                    DTWorker.this.impurity.featureUpdate(featuerStatistic, binIndex,
                                            data.output, data.significance, weight);
                                }
                            }
                        }
                    }
                }
                LOG.debug("Thread computing stats time is {}ms in thread {}",
                        TimeUnit.NANOSECONDS.toMillis(System.nanoTime() - start),
                        Thread.currentThread().getName());
                return localStatistics;
            }
        });
    }

    int rCnt = 0;
    while (rCnt < realThreadCount) {
        try {
            Map<Integer, NodeStats> currNodeStatsmap = completionService.take().get();
            if (rCnt == 0) {
                statistics = currNodeStatsmap;
            } else {
                for (Entry<Integer, NodeStats> entry : statistics.entrySet()) {
                    NodeStats resultNodeStats = entry.getValue();
                    mergeNodeStats(resultNodeStats, currNodeStatsmap.get(entry.getKey()));
                }
            }
        } catch (ExecutionException e) {
            throw new RuntimeException(e);
        } catch (InterruptedException e) {
            Thread.currentThread().interrupt();
        }
        rCnt += 1;
    }
    LOG.debug("Compute stats time is {}ms", TimeUnit.NANOSECONDS.toMillis(System.nanoTime() - start));

    LOG.info(
            "worker count is {}, error is {}, and stats size is {}. weightedTrainCount {}, weightedValidationCount {}, trainError {}, validationError {}",
            count, trainError, statistics.size(), weightedTrainCount, weightedValidationCount, trainError,
            validationError);
    return new DTWorkerParams(weightedTrainCount, weightedValidationCount, trainError, validationError,
            statistics);
}

From source file:org.apache.hadoop.yarn.client.api.impl.TimelineClientImpl.java

@Override
public TimelinePutResponse putEntities(ApplicationAttemptId appAttemptId, TimelineEntityGroupId groupId,
        TimelineEntity... entities) throws IOException, YarnException {
    if (Float.compare(this.timelineServiceVersion, 1.5f) != 0) {
        throw new YarnException(
                "This API is not supported under current Timeline Service Version: " + timelineServiceVersion);
    }/*from  w  w  w  .  j  av a 2s. c  o  m*/

    return timelineWriter.putEntities(appAttemptId, groupId, entities);
}

From source file:org.apache.hadoop.yarn.client.api.impl.TimelineClientImpl.java

@Override
public void putDomain(ApplicationAttemptId appAttemptId, TimelineDomain domain)
        throws IOException, YarnException {
    if (Float.compare(this.timelineServiceVersion, 1.5f) != 0) {
        throw new YarnException(
                "This API is not supported under current Timeline Service Version: " + timelineServiceVersion);
    }/*  w w w  .j a  v a2 s .  c  om*/
    timelineWriter.putDomain(appAttemptId, domain);
}

From source file:org.ejbca.core.model.ca.caadmin.CVCCA.java

/** Implementation of UpgradableDataHashMap function upgrade. 
 *//*from ww  w . ja v  a 2  s. c o  m*/
public void upgrade() {
    if (Float.compare(LATEST_VERSION, getVersion()) != 0) {
        // New version of the class, upgrade
        log.info("Upgrading CVCCA with version " + getVersion());

        // Put upgrade code here...

        // v1->v2 is only an upgrade in order to upgrade CA token
        // v2->v3 is a upgrade of X509CA that has to be adjusted here two, due to the common heritage
        if (data.get(CRLPERIOD) instanceof Integer) {
            setCRLPeriod(0L);
        }
        if (data.get(CRLISSUEINTERVAL) instanceof Integer) {
            setCRLIssueInterval(0L);
        }
        if (data.get(CRLOVERLAPTIME) instanceof Integer) {
            setCRLOverlapTime(0L);
        }
        if (data.get(DELTACRLPERIOD) instanceof Integer) {
            setDeltaCRLPeriod(0L);
        }

        data.put(VERSION, new Float(LATEST_VERSION));
    }
}

From source file:us.parr.animl.data.DataTable.java

public void sortBy(int colIndex) {
    switch (colTypes[colIndex]) {
    case CATEGORICAL_INT:
    case NUMERICAL_INT:
    case CATEGORICAL_STRING: // strings are encoded as ints
    case TARGET_CATEGORICAL_STRING:
    case TARGET_CATEGORICAL_INT:
    case UNUSED_INT:
    case UNUSED_STRING:
        Collections.sort(rows, (ra, rb) -> {
            return Integer.compare(ra[colIndex], rb[colIndex]);
        });//ww w. j  ava2s .c o m
        break;
    case NUMERICAL_FLOAT:
    case UNUSED_FLOAT:
        Collections.sort(rows, (ra, rb) -> {
            return Float.compare(Float.intBitsToFloat(ra[colIndex]), Float.intBitsToFloat(rb[colIndex]));
        });
        break;
    }
}

From source file:com.waz.zclient.pages.main.drawing.DrawingFragment.java

private boolean isShowingKeyboard() {
    return sketchEditTextView.getVisibility() == View.VISIBLE
            && Float.compare(sketchEditTextView.getAlpha(), TEXT_ALPHA_VISIBLE) == 0
            && KeyboardUtils.isKeyboardVisible(getContext());
}