Example usage for java.lang System nanoTime

List of usage examples for java.lang System nanoTime

Introduction

In this page you can find the example usage for java.lang System nanoTime.

Prototype

@HotSpotIntrinsicCandidate
public static native long nanoTime();

Source Link

Document

Returns the current value of the running Java Virtual Machine's high-resolution time source, in nanoseconds.

Usage

From source file:com.noelios.restlet.ext.oauth.MemoryOAuthProvider.java

@Override
public void generateAccessToken(OAuthAccessor accessor) {
    // generate oauth_token and oauth_secret
    final String consumer_key = (String) accessor.consumer.getProperty("name");

    // generate token and secret based on consumer_key
    // for now use md5 of name + current time as token
    final String token_data = consumer_key + System.nanoTime();
    final String token = DigestUtils.md5Hex(token_data);

    // first remove the accessor from cache
    this.tokens.remove(accessor);

    accessor.requestToken = null;/*  w  w  w .  j a v  a 2s .c o m*/
    accessor.accessToken = token;

    Context.getCurrentLogger().fine("Adding access token " + accessor);

    // update token in local cache
    this.tokens.add(accessor);
}

From source file:com.linkedin.bowser.tool.REPL.java

public void execute(String line, PrintStream out) throws QueryFormatException {
    if (StringUtils.isEmpty(line))
        return;//w  ww  . java 2  s.c  o m

    ANTLRStringStream input = new ANTLRStringStream(line);
    NQLLexer lexer = new NQLLexer(input);
    CommonTokenStream tokens = new CommonTokenStream(lexer);
    NQLParser parser = new NQLParser(tokens);
    NQLParser.repl_return repl;

    long startTime = System.nanoTime();
    try {
        repl = parser.repl();
    } catch (RecognitionException e) {
        String errorHeader = parser.getErrorHeader(e);
        String errorMessage = parser.getErrorMessage(e, parser.getTokenNames());
        throw new QueryFormatException(errorHeader + " " + errorMessage, e.line, e.charPositionInLine,
                e.token.getText());
    }

    CommonTree t = (CommonTree) repl.getTree();
    long parseTime = System.nanoTime() - startTime;

    if (_verbose) {
        log.debug("parse:");
        log.debug("  " + t.toStringTree());
    }

    // Walk Resulting Tree
    CommonTreeNodeStream nodes = new CommonTreeNodeStream(t);
    NQLQueryBuilder builder = new NQLQueryBuilder(nodes);
    builder.setSymbolMap(_symbolMap);
    builder.setPool(_pool);

    try {
        String result = builder.repl();
        if (result != null)
            out.println(result);
    } catch (RecognitionException e) {
        String errorHeader = parser.getErrorHeader(e);
        String errorMessage = parser.getErrorMessage(e, parser.getTokenNames());
        throw new QueryFormatException(errorHeader + " " + errorMessage, e.line, e.charPositionInLine,
                e.token.getText());
    } finally {
        long evalTime = System.nanoTime() - startTime + parseTime;
        out.println(String.format("parse: %.2f ms, eval: %.2f ms", (float) parseTime / 1000000,
                (float) evalTime / 1000000));

    }
}

From source file:com.springsource.insight.plugin.apache.http.hc4.HttpPlaceholderRequestTest.java

@Test
public void testOnExistingValue() {
    HttpRequest req = new HttpGet("http://localhost");
    assertSame(req, HttpPlaceholderRequest.resolveHttpRequest("hello", req, Long.valueOf(System.nanoTime())));
}

From source file:CollectionTest.java

public void start() {
    startTime = System.nanoTime();
    stopped = false;
}

From source file:com.jkoolcloud.jesl.net.syslogd.JsonSyslogServerEventHandler.java

@Override
public void event(Object session, SyslogServerIF syslogServer, SocketAddress socketAddress,
        SyslogServerEventIF event) {/*from   w w  w . ja  v  a2  s .  c  o  m*/
    long now = System.nanoTime();
    long offset = lastEvent == 0 ? 0 : (System.nanoTime() - lastEvent) / 1000;
    lastEvent = now;

    Date date = (event.getDate() == null ? new Date() : event.getDate());
    String timestamp = fmt.print(date.getTime());

    String facility = SyslogTNT4JEventHandler.getFacilityString(event.getFacility());
    String level = SyslogUtility.getLevelString(event.getLevel());
    String host = event.getHost();
    if (!(event instanceof StructuredSyslogServerEvent)) {
        this.stream.println("{\"offset.usec\":" + offset + ", \"host\":\"" + host + "\", \"facility\":\""
                + facility + "\", \"timestamp\":\"" + timestamp + "\", \"level\":\"" + level + "\", \"msg\":\""
                + StringEscapeUtils.escapeJson(event.getMessage()) + "\"}");
    } else {
        StructuredSyslogServerEvent sevent = (StructuredSyslogServerEvent) event;
        StructuredSyslogMessage sm = sevent.getStructuredMessage();
        Map<?, ?> arttrs = sm.getStructuredData();
        this.stream.println("{\"offset.usec\":" + offset + ", \"host\":\"" + host + "\", \"facility\":\""
                + facility + "\", \"timestamp\":\"" + timestamp + "\", \"level\":\"" + level + "\", \"appl\":\""
                + sevent.getApplicationName() + "\", \"mid\":\""
                + (sm.getMessageId() != null ? sm.getMessageId() : "") + "\", \"pid\":"
                + (sevent.getProcessId() != null && sevent.getProcessId().isEmpty() ? 0 : sevent.getProcessId())
                + ", \"map.size\":" + ((arttrs != null) ? arttrs.size() : 0) + ", \"msg\":\""
                + StringEscapeUtils.escapeJson(event.getMessage()) + "\"}");
    }
}

From source file:ispok.bo.Visitor.java

public void setPassword(String password) {
    this.saltHash = hashProvider.computeHash(System.nanoTime() + "");
    this.passwordHash = hashProvider.computeHash(password + saltHash);
}

From source file:eu.amidst.core.inference.MPEInferenceExperiments_Deliv2.java

/**
 * The class constructor./*ww  w.  j ava  2 s  .  c  o  m*/
 * @param args Array of options: "filename variable a b N useVMP" if variable is continuous or "filename variable w N useVMP" for discrete
 */
public static void main(String[] args) throws Exception { // args: seedNetwork numberGaussians numberDiscrete seedAlgorithms

    int seedNetwork = 234235;
    int numberOfGaussians = 100;
    int numberOfMultinomials = 100;

    int seed = 125634;

    int parallelSamples = 100;
    int samplingMethodSize = 10000;

    int repetitions = 10;

    int numberOfIterations = 200;

    if (args.length != 8) {
        if (Main.VERBOSE)
            System.out.println("Invalid number of parameters. Using default values");
    } else {
        try {
            seedNetwork = Integer.parseInt(args[0]);
            numberOfGaussians = Integer.parseInt(args[1]);
            numberOfMultinomials = Integer.parseInt(args[2]);

            seed = Integer.parseInt(args[3]);

            parallelSamples = Integer.parseInt(args[4]);
            samplingMethodSize = Integer.parseInt(args[5]);

            repetitions = Integer.parseInt(args[6]);

            numberOfIterations = Integer.parseInt(args[7]);

        } catch (NumberFormatException ex) {
            if (Main.VERBOSE)
                System.out.println(
                        "Invalid parameters. Provide integers: seedNetwork numberGaussians numberDiscrete seedAlgorithms parallelSamples sampleSize repetitions");
            if (Main.VERBOSE)
                System.out.println("Using default parameters");
            if (Main.VERBOSE)
                System.out.println(ex.toString());
            System.exit(20);
        }
    }
    int numberOfLinks = (int) 1.3 * (numberOfGaussians + numberOfMultinomials);

    BayesianNetworkGenerator.setSeed(seedNetwork);
    BayesianNetworkGenerator.setNumberOfGaussianVars(numberOfGaussians);
    BayesianNetworkGenerator.setNumberOfMultinomialVars(numberOfMultinomials, 2);
    BayesianNetworkGenerator.setNumberOfLinks(numberOfLinks);

    String filename = "./networks/simulated/RandomBN_" + Integer.toString(numberOfMultinomials) + "D_"
            + Integer.toString(numberOfGaussians) + "C_" + Integer.toString(seedNetwork) + "_Seed.bn";
    //BayesianNetworkGenerator.generateBNtoFile(numberOfMultinomials,2,numberOfGaussians,numberOfLinks,seedNetwork,filename);
    BayesianNetwork bn = BayesianNetworkGenerator.generateBayesianNetwork();

    //if (Main.VERBOSE) System.out.println(bn.getDAG());
    //if (Main.VERBOSE) System.out.println(bn.toString());

    MPEInference mpeInference = new MPEInference();
    mpeInference.setModel(bn);
    mpeInference.setParallelMode(true);

    //if (Main.VERBOSE) System.out.println("CausalOrder: " + Arrays.toString(Utils.getCausalOrder(mpeInference.getOriginalModel().getDAG()).stream().map(Variable::getName).toArray()));
    List<Variable> modelVariables = Utils.getTopologicalOrder(bn.getDAG());
    if (Main.VERBOSE)
        System.out.println();

    // Including evidence:
    //double observedVariablesRate = 0.00;
    //Assignment evidence = randomEvidence(seed, observedVariablesRate, bn);
    //mpeInference.setEvidence(evidence);

    mpeInference.setNumberOfIterations(numberOfIterations);

    mpeInference.setSampleSize(parallelSamples);
    mpeInference.setSeed(seed);

    double[] SA_All_prob = new double[repetitions];
    double[] SA_Some_prob = new double[repetitions];
    double[] HC_All_prob = new double[repetitions];
    double[] HC_Some_prob = new double[repetitions];
    double[] sampling_prob = new double[repetitions];

    double[] SA_All_time = new double[repetitions];
    double[] SA_Some_time = new double[repetitions];
    double[] HC_All_time = new double[repetitions];
    double[] HC_Some_time = new double[repetitions];
    double[] sampling_time = new double[repetitions];

    long timeStart;
    long timeStop;
    double execTime;

    Assignment bestMpeEstimate = new HashMapAssignment(bn.getNumberOfVars());
    double bestMpeEstimateLogProb = -100000;
    int bestMpeEstimateMethod = -5;

    mpeInference.setParallelMode(true);

    final double bestProbability = -171.81983739975342;
    //        BEST MPE ESTIMATE FOUND:
    //        {DiscreteVar0 = 0, DiscreteVar1 = 0, DiscreteVar2 = 1, DiscreteVar3 = 0, DiscreteVar4 = 0, DiscreteVar5 = 0, DiscreteVar6 = 0, DiscreteVar7 = 0, DiscreteVar8 = 0, DiscreteVar9 = 0, DiscreteVar10 = 0, DiscreteVar11 = 1, DiscreteVar12 = 1, DiscreteVar13 = 1, DiscreteVar14 = 0, DiscreteVar15 = 0, DiscreteVar16 = 0, DiscreteVar17 = 1, DiscreteVar18 = 1, DiscreteVar19 = 0, DiscreteVar20 = 0, DiscreteVar21 = 0, DiscreteVar22 = 1, DiscreteVar23 = 1, DiscreteVar24 = 0, DiscreteVar25 = 0, DiscreteVar26 = 0, DiscreteVar27 = 0, DiscreteVar28 = 1, DiscreteVar29 = 1, DiscreteVar30 = 0, DiscreteVar31 = 0, DiscreteVar32 = 1, DiscreteVar33 = 1, DiscreteVar34 = 0, DiscreteVar35 = 1, DiscreteVar36 = 0, DiscreteVar37 = 0, DiscreteVar38 = 0, DiscreteVar39 = 0, DiscreteVar40 = 0, DiscreteVar41 = 1, DiscreteVar42 = 1, DiscreteVar43 = 1, DiscreteVar44 = 0, DiscreteVar45 = 1, DiscreteVar46 = 1, DiscreteVar47 = 0, DiscreteVar48 = 1, DiscreteVar49 = 1, DiscreteVar50 = 0, DiscreteVar51 = 0, DiscreteVar52 = 0, DiscreteVar53 = 1, DiscreteVar54 = 0, DiscreteVar55 = 1, DiscreteVar56 = 1, DiscreteVar57 = 0, DiscreteVar58 = 1, DiscreteVar59 = 0, DiscreteVar60 = 0, DiscreteVar61 = 1, DiscreteVar62 = 0, DiscreteVar63 = 0, DiscreteVar64 = 0, DiscreteVar65 = 1, DiscreteVar66 = 1, DiscreteVar67 = 1, DiscreteVar68 = 1, DiscreteVar69 = 1, DiscreteVar70 = 1, DiscreteVar71 = 0, DiscreteVar72 = 0, DiscreteVar73 = 0, DiscreteVar74 = 0, DiscreteVar75 = 1, DiscreteVar76 = 0, DiscreteVar77 = 1, DiscreteVar78 = 1, DiscreteVar79 = 0, DiscreteVar80 = 1, DiscreteVar81 = 1, DiscreteVar82 = 1, DiscreteVar83 = 0, DiscreteVar84 = 1, DiscreteVar85 = 1, DiscreteVar86 = 1, DiscreteVar87 = 1, DiscreteVar88 = 0, DiscreteVar89 = 0, DiscreteVar90 = 1, DiscreteVar91 = 0, DiscreteVar92 = 0, DiscreteVar93 = 0, DiscreteVar94 = 0, DiscreteVar95 = 0, DiscreteVar96 = 0, DiscreteVar97 = 1, DiscreteVar98 = 1, DiscreteVar99 = 1, GaussianVar0 = -4,551, GaussianVar1 = 14,731, GaussianVar2 = -1,108, GaussianVar3 = -6,564, GaussianVar4 = -2,415, GaussianVar5 = 10,265, GaussianVar6 = 6,058, GaussianVar7 = 6,367, GaussianVar8 = 26,731, GaussianVar9 = 0,807, GaussianVar10 = -19,410, GaussianVar11 = 18,070, GaussianVar12 = -14,177, GaussianVar13 = 7,765, GaussianVar14 = 3,596, GaussianVar15 = -7,757, GaussianVar16 = -1,705, GaussianVar17 = -5,476, GaussianVar18 = -17,932, GaussianVar19 = 22,843, GaussianVar20 = -9,860, GaussianVar21 = 3,844, GaussianVar22 = 8,262, GaussianVar23 = -9,080, GaussianVar24 = 1,750, GaussianVar25 = 11,532, GaussianVar26 = 0,700, GaussianVar27 = 12,206, GaussianVar28 = 8,532, GaussianVar29 = -40,395, GaussianVar30 = 19,981, GaussianVar31 = -30,713, GaussianVar32 = 0,476, GaussianVar33 = -12,406, GaussianVar34 = 4,942, GaussianVar35 = -0,245, GaussianVar36 = -176,861, GaussianVar37 = 8,474, GaussianVar38 = -8,849, GaussianVar39 = -3,844, GaussianVar40 = -8,495, GaussianVar41 = 4,664, GaussianVar42 = -4,730, GaussianVar43 = 4,063, GaussianVar44 = -1,631, GaussianVar45 = -103,340, GaussianVar46 = -1,598, GaussianVar47 = -11,460, GaussianVar48 = 14,123, GaussianVar49 = -0,135, GaussianVar50 = 1,487, GaussianVar51 = -4,859, GaussianVar52 = 0,370, GaussianVar53 = -10,038, GaussianVar54 = 18,145, GaussianVar55 = 225,324, GaussianVar56 = 1,059, GaussianVar57 = -1,170, GaussianVar58 = 83,480, GaussianVar59 = 7,375, GaussianVar60 = 5,091, GaussianVar61 = 61,381, GaussianVar62 = 42,955, GaussianVar63 = -712,533, GaussianVar64 = 21,460, GaussianVar65 = -19,337, GaussianVar66 = 213,903, GaussianVar67 = -10,197, GaussianVar68 = -65,619, GaussianVar69 = 41,045, GaussianVar70 = 133,452, GaussianVar71 = -1,997, GaussianVar72 = 17,485, GaussianVar73 = -40,691, GaussianVar74 = -16,378, GaussianVar75 = -72,550, GaussianVar76 = -1,761, GaussianVar77 = 12,647, GaussianVar78 = -31,531, GaussianVar79 = -41,444, GaussianVar80 = -14,190, GaussianVar81 = 17,387, GaussianVar82 = -12,333, GaussianVar83 = -57,795, GaussianVar84 = -20,386, GaussianVar85 = 49,735, GaussianVar86 = 14,593, GaussianVar87 = -168,778, GaussianVar88 = -6,157, GaussianVar89 = 82,897, GaussianVar90 = -30,018, GaussianVar91 = -2,366, GaussianVar92 = -12,753, GaussianVar93 = -141,490, GaussianVar94 = 17,844, GaussianVar95 = 99,703, GaussianVar96 = -37,859, GaussianVar97 = 123,045, GaussianVar98 = -4,054, GaussianVar99 = 3,024}
    //        with method:2
    //        and log probability: -171.81983739975342

    for (int k = 0; k < repetitions; k++) {

        mpeInference.setSampleSize(parallelSamples);

        /***********************************************
         *        SIMULATED ANNEALING
         ************************************************/

        // MPE INFERENCE WITH SIMULATED ANNEALING, ALL VARIABLES
        //if (Main.VERBOSE) System.out.println();
        timeStart = System.nanoTime();
        mpeInference.runInference(MPEInference.SearchAlgorithm.SA_GLOBAL);

        //mpeEstimate = mpeInference.getEstimate();
        //if (Main.VERBOSE) System.out.println("MPE estimate (SA.All): " + mpeEstimate.outputString(modelVariables));   //toString(modelVariables)
        //if (Main.VERBOSE) System.out.println("with probability: " + Math.exp(mpeInference.getLogProbabilityOfEstimate()) + ", logProb: " + mpeInference.getLogProbabilityOfEstimate());
        timeStop = System.nanoTime();
        execTime = (double) (timeStop - timeStart) / 1000000000.0;
        //if (Main.VERBOSE) System.out.println("computed in: " + Double.toString(execTime) + " seconds");
        //if (Main.VERBOSE) System.out.println(.toString(mapInference.getOriginalModel().getStaticVariables().iterator().));
        //if (Main.VERBOSE) System.out.println();
        SA_All_prob[k] = mpeInference.getLogProbabilityOfEstimate();
        SA_All_time[k] = execTime;

        if (mpeInference.getLogProbabilityOfEstimate() > bestMpeEstimateLogProb) {
            bestMpeEstimate = mpeInference.getEstimate();
            bestMpeEstimateLogProb = mpeInference.getLogProbabilityOfEstimate();
            bestMpeEstimateMethod = 1;
        }

        // MPE INFERENCE WITH SIMULATED ANNEALING, SOME VARIABLES AT EACH TIME
        timeStart = System.nanoTime();
        mpeInference.runInference(MPEInference.SearchAlgorithm.SA_LOCAL);

        //mpeEstimate = mpeInference.getEstimate();
        //if (Main.VERBOSE) System.out.println("MPE estimate  (SA.Some): " + mpeEstimate.outputString(modelVariables));   //toString(modelVariables)
        //if (Main.VERBOSE) System.out.println("with probability: "+ Math.exp(mpeInference.getLogProbabilityOfEstimate()) + ", logProb: " + mpeInference.getLogProbabilityOfEstimate());
        timeStop = System.nanoTime();
        execTime = (double) (timeStop - timeStart) / 1000000000.0;
        //if (Main.VERBOSE) System.out.println("computed in: " + Double.toString(execTime) + " seconds");
        //if (Main.VERBOSE) System.out.println(.toString(mapInference.getOriginalModel().getStaticVariables().iterator().));
        //if (Main.VERBOSE) System.out.println();
        SA_Some_prob[k] = mpeInference.getLogProbabilityOfEstimate();
        SA_Some_time[k] = execTime;

        if (mpeInference.getLogProbabilityOfEstimate() > bestMpeEstimateLogProb) {
            bestMpeEstimate = mpeInference.getEstimate();
            bestMpeEstimateLogProb = mpeInference.getLogProbabilityOfEstimate();
            bestMpeEstimateMethod = 0;
        }

        /***********************************************
         *        HILL CLIMBING
         ************************************************/

        // MPE INFERENCE WITH HILL CLIMBING, ALL VARIABLES
        timeStart = System.nanoTime();
        mpeInference.runInference(MPEInference.SearchAlgorithm.HC_GLOBAL);

        //mpeEstimate = mpeInference.getEstimate();
        //modelVariables = mpeInference.getOriginalModel().getVariables().getListOfVariables();
        //if (Main.VERBOSE) System.out.println("MPE estimate (HC.All): " + mpeEstimate.outputString(modelVariables));
        //if (Main.VERBOSE) System.out.println("with probability: " + Math.exp(mpeInference.getLogProbabilityOfEstimate()) + ", logProb: " + mpeInference.getLogProbabilityOfEstimate());
        timeStop = System.nanoTime();
        execTime = (double) (timeStop - timeStart) / 1000000000.0;
        //if (Main.VERBOSE) System.out.println("computed in: " + Double.toString(execTime) + " seconds");
        //if (Main.VERBOSE) System.out.println();
        HC_All_prob[k] = mpeInference.getLogProbabilityOfEstimate();
        HC_All_time[k] = execTime;

        if (mpeInference.getLogProbabilityOfEstimate() > bestMpeEstimateLogProb) {
            bestMpeEstimate = mpeInference.getEstimate();
            bestMpeEstimateLogProb = mpeInference.getLogProbabilityOfEstimate();
            bestMpeEstimateMethod = 3;
        }

        //  MPE INFERENCE WITH HILL CLIMBING, ONE VARIABLE AT EACH TIME
        timeStart = System.nanoTime();
        mpeInference.runInference(MPEInference.SearchAlgorithm.HC_LOCAL);

        //mpeEstimate = mpeInference.getEstimate();
        //if (Main.VERBOSE) System.out.println("MPE estimate  (HC.Some): " + mpeEstimate.outputString(modelVariables));   //toString(modelVariables)
        //if (Main.VERBOSE) System.out.println("with probability: " + Math.exp(mpeInference.getLogProbabilityOfEstimate()) + ", logProb: " + mpeInference.getLogProbabilityOfEstimate());
        timeStop = System.nanoTime();
        execTime = (double) (timeStop - timeStart) / 1000000000.0;
        //if (Main.VERBOSE) System.out.println("computed in: " + Double.toString(execTime) + " seconds");
        //if (Main.VERBOSE) System.out.println();
        HC_Some_prob[k] = mpeInference.getLogProbabilityOfEstimate();
        HC_Some_time[k] = execTime;

        if (mpeInference.getLogProbabilityOfEstimate() > bestMpeEstimateLogProb) {
            bestMpeEstimate = mpeInference.getEstimate();
            bestMpeEstimateLogProb = mpeInference.getLogProbabilityOfEstimate();
            bestMpeEstimateMethod = 2;
        }

        /***********************************************
         *        SAMPLING AND DETERMINISTIC
         ************************************************/

        // MPE INFERENCE WITH SIMULATION AND PICKING MAX

        mpeInference.setSampleSize(samplingMethodSize);

        timeStart = System.nanoTime();
        mpeInference.runInference(MPEInference.SearchAlgorithm.SAMPLING);

        //mpeEstimate = mpeInference.getEstimate();
        //modelVariables = mpeInference.getOriginalModel().getVariables().getListOfVariables();
        //if (Main.VERBOSE) System.out.println("MPE estimate (SAMPLING): " + mpeEstimate.outputString(modelVariables));
        //if (Main.VERBOSE) System.out.println("with probability: " + Math.exp(mpeInference.getLogProbabilityOfEstimate()) + ", logProb: " + mpeInference.getLogProbabilityOfEstimate());
        timeStop = System.nanoTime();
        execTime = (double) (timeStop - timeStart) / 1000000000.0;
        //if (Main.VERBOSE) System.out.println("computed in: " + Double.toString(execTime) + " seconds");
        //if (Main.VERBOSE) System.out.println();
        sampling_prob[k] = mpeInference.getLogProbabilityOfEstimate();
        sampling_time[k] = execTime;

        if (mpeInference.getLogProbabilityOfEstimate() > bestMpeEstimateLogProb) {
            bestMpeEstimate = mpeInference.getEstimate();
            bestMpeEstimateLogProb = mpeInference.getLogProbabilityOfEstimate();
            bestMpeEstimateMethod = -1;
        }
    }

    double determ_prob = 0;
    double determ_time = 0;

    //        if(bn.getNumberOfVars()<=50) {
    //
    //            // MPE INFERENCE, DETERMINISTIC
    //            timeStart = System.nanoTime();
    //            mpeInference.runInference(-2);
    //
    //            //mpeEstimate = mpeInference.getEstimate();
    //            //modelVariables = mpeInference.getOriginalModel().getVariables().getListOfVariables();
    //            //if (Main.VERBOSE) System.out.println("MPE estimate (DETERM.): " + mpeEstimate.outputString(modelVariables));
    //            //if (Main.VERBOSE) System.out.println("with probability: " + Math.exp(mpeInference.getLogProbabilityOfEstimate()) + ", logProb: " + mpeInference.getLogProbabilityOfEstimate());
    //            timeStop = System.nanoTime();
    //            execTime = (double) (timeStop - timeStart) / 1000000000.0;
    //            //if (Main.VERBOSE) System.out.println("computed in: " + Double.toString(execTime) + " seconds");
    //            //if (Main.VERBOSE) System.out.println();
    //            determ_prob = mpeInference.getLogProbabilityOfEstimate();
    //            determ_time = execTime;
    //
    //        }
    //        else {
    //            if (Main.VERBOSE) System.out.println("Too many variables for deterministic method");
    //        }

    /***********************************************
     *        DISPLAY OF RESULTS
     ************************************************/

    if (Main.VERBOSE)
        System.out.println("*** RESULTS ***");

    //        if (Main.VERBOSE) System.out.println("SA_All log-probabilities");
    //        if (Main.VERBOSE) System.out.println(Arrays.toString(SA_All_prob));
    //        if (Main.VERBOSE) System.out.println("SA_Some log-probabilities");
    //        if (Main.VERBOSE) System.out.println(Arrays.toString(SA_Some_prob));
    //        if (Main.VERBOSE) System.out.println("HC_All log-probabilities");
    //        if (Main.VERBOSE) System.out.println(Arrays.toString(HC_All_prob));
    //        if (Main.VERBOSE) System.out.println("HC_Some log-probabilities");
    //        if (Main.VERBOSE) System.out.println(Arrays.toString(HC_Some_prob));
    //        if (Main.VERBOSE) System.out.println("Sampling log-probabilities");
    //        if (Main.VERBOSE) System.out.println(Arrays.toString(sampling_prob));
    //        if(bn.getNumberOfVars()<=50) {
    //            if (Main.VERBOSE) System.out.println("Deterministic log-probability");
    //            if (Main.VERBOSE) System.out.println(Double.toString(determ_prob));
    //        }

    if (Main.VERBOSE)
        System.out.println("SA_All RMS probabilities");
    if (Main.VERBOSE)
        System.out.println(Double.toString(Math.sqrt(Arrays.stream(SA_All_prob)
                .map(value -> Math.pow(value - bestProbability, 2)).average().getAsDouble())));
    if (Main.VERBOSE)
        System.out.println("SA_Some RMS probabilities");
    if (Main.VERBOSE)
        System.out.println(Double.toString(Math.sqrt(Arrays.stream(SA_Some_prob)
                .map(value -> Math.pow(value - bestProbability, 2)).average().getAsDouble())));
    if (Main.VERBOSE)
        System.out.println("HC_All RMS probabilities");
    if (Main.VERBOSE)
        System.out.println(Double.toString(Math.sqrt(Arrays.stream(HC_All_prob)
                .map(value -> Math.pow(value - bestProbability, 2)).average().getAsDouble())));
    if (Main.VERBOSE)
        System.out.println("HC_Some RMS probabilities");
    if (Main.VERBOSE)
        System.out.println(Double.toString(Math.sqrt(Arrays.stream(HC_Some_prob)
                .map(value -> Math.pow(value - bestProbability, 2)).average().getAsDouble())));
    if (Main.VERBOSE)
        System.out.println("Sampling RMS probabilities");
    if (Main.VERBOSE)
        System.out.println(Double.toString(Math.sqrt(Arrays.stream(sampling_prob)
                .map(value -> Math.pow(value - bestProbability, 2)).average().getAsDouble())));
    if (Main.VERBOSE)
        System.out.println();

    if (Main.VERBOSE)
        System.out.println("SA_All times");
    //if (Main.VERBOSE) System.out.println(Arrays.toString(SA_All_time));
    if (Main.VERBOSE)
        System.out.println("Mean time: " + Double.toString(Arrays.stream(SA_All_time).average().getAsDouble()));
    if (Main.VERBOSE)
        System.out.println("SA_Some times");
    //if (Main.VERBOSE) System.out.println(Arrays.toString(SA_Some_time));
    if (Main.VERBOSE)
        System.out
                .println("Mean time: " + Double.toString(Arrays.stream(SA_Some_time).average().getAsDouble()));
    if (Main.VERBOSE)
        System.out.println("HC_All times");
    //if (Main.VERBOSE) System.out.println(Arrays.toString(HC_All_time));
    if (Main.VERBOSE)
        System.out.println("Mean time: " + Double.toString(Arrays.stream(HC_All_time).average().getAsDouble()));
    if (Main.VERBOSE)
        System.out.println("HC_Some times");
    //if (Main.VERBOSE) System.out.println(Arrays.toString(HC_Some_time));
    if (Main.VERBOSE)
        System.out
                .println("Mean time: " + Double.toString(Arrays.stream(HC_Some_time).average().getAsDouble()));
    if (Main.VERBOSE)
        System.out.println("Sampling times");
    //if (Main.VERBOSE) System.out.println(Arrays.toString(sampling_time));
    if (Main.VERBOSE)
        System.out
                .println("Mean time: " + Double.toString(Arrays.stream(sampling_time).average().getAsDouble()));
    if (Main.VERBOSE)
        System.out.println();
    //        if(bn.getNumberOfVars()<=50) {
    //            if (Main.VERBOSE) System.out.println("Deterministic time");
    //            if (Main.VERBOSE) System.out.println(Double.toString(determ_time));
    //        }

    if (Main.VERBOSE)
        System.out.println("BEST MPE ESTIMATE FOUND:");
    if (Main.VERBOSE)
        System.out.println(bestMpeEstimate.outputString(Utils.getTopologicalOrder(bn.getDAG())));
    if (Main.VERBOSE)
        System.out.println("with method:" + bestMpeEstimateMethod);
    if (Main.VERBOSE)
        System.out.println("and log probability: " + bestMpeEstimateLogProb);
}

From source file:de.acosix.alfresco.utility.common.web.scripts.ExtensibleDeclarativeWebScript.java

/**
 *
 * {@inheritDoc}/* w ww .j  a  v  a 2  s .  c om*/
 */
@Override
protected void executeScript(final ScriptContent location, final Map<String, Object> model) {
    final boolean debug = logger.isDebugEnabled();
    long start = 0L;
    if (debug) {
        start = System.nanoTime();
    }

    final Container container = this.getContainer();
    final ScriptProcessor scriptProcessor = container.getScriptProcessorRegistry().getScriptProcessor(location);
    scriptProcessor.executeScript(location, model);

    if (container instanceof HandlesExtensibility) {
        // main difference from AbstractWebScript handling: we take care of web script format during lookup

        // AbstractWebScript instance variable is not accessible so use the description from which it was initialised
        final String basePath = this.getDescription().getId();

        final FormatRegistry formatRegistry = container.getFormatRegistry();
        String generalizedMimetype = this.scriptLookupMimetype.get();
        while (generalizedMimetype != null) {
            final String format = formatRegistry.getFormat(null, generalizedMimetype);
            if (format != null) {
                final String expectedPath = basePath + "." + format;
                this.executeExtendingScripts(model, expectedPath);
            }

            generalizedMimetype = formatRegistry.generalizeMimetype(generalizedMimetype);
        }

        this.executeExtendingScripts(model, basePath);
    }
}

From source file:com.pva.QueryGeneratorImpl.java

public void addToTimeSeriesQueue(TimeSeries timeSeries) {
    long startTime = 0L;
    timeSeriesSendCount.incrementAndGet();
    // we're gonna let Redis do the serialization..
    LOGGER.debug(String.format("Adding to queue: %s", timeSeries));
    startTime = System.nanoTime();
    timeSeriesQueue.add(timeSeries);/*w  ww. j  a  va  2s .  c o  m*/
    LOGGER.debug(String.format("Time to add to queue: %s",
            DurationFormatUtils.formatDurationHMS((System.nanoTime() - startTime) / 1000000)));
}

From source file:eu.planets_project.pp.plato.services.characterisation.fits.FitsIntegration.java

public String characterise(File input) throws PlatoServiceException {
    CommandExecutor cmdExecutor = new CommandExecutor();
    cmdExecutor.setWorkingDirectory(FITS_HOME);
    String scriptExt;/*from w  w  w . j  a v a 2  s . com*/
    if ("Linux".equalsIgnoreCase(System.getProperty("os.name"))) {
        scriptExt = "./fits.sh";
    } else {
        scriptExt = "cmd /c %FITS_HOME%/fits";
    }
    File output = new File(OS.getTmpPath() + "fits" + System.nanoTime() + ".out");
    try {
        String commandLine = FITS_COMMAND.replace("%FITS_EXEC%", scriptExt)
                .replace("%INPUT%", input.getAbsolutePath()).replace("%OUTPUT%", output.getAbsolutePath());

        try {
            int exitcode = cmdExecutor.runCommand(commandLine);
            if (exitcode != 0) {
                String cmdError = cmdExecutor.getCommandError();
                throw new PlatoServiceException(
                        "FITS characterisation for file: " + input + " failed: " + cmdError);
            }
            if (!output.exists()) {
                throw new PlatoServiceException(
                        "FITS characterisation for file: " + input + " failed: no output was written.");
            }

            return new String(FileUtils.getBytesFromFile(output));
        } catch (PlatoServiceException e) {
            throw e;
        } catch (Throwable t) {
            throw new PlatoServiceException(
                    "FITS characterisation for file: " + input + " failed: " + t.getMessage(), t);
        }
    } finally {
        output.delete();
    }
}