Examples of Sampler

cloudtrace.instrument.Sampler
Extremely simple callback to determine the frequency that an action should be performed. @see Trace.wrapAll
com.google.monitoring.runtime.instrumentation.Sampler
org.apache.accumulo.cloudtrace.instrument.Sampler
Extremely simple callback to determine the frequency that an action should be performed. @see Trace#wrapAll
org.apache.accumulo.trace.instrument.Sampler
Extremely simple callback to determine the frequency that an action should be performed. @see Trace#wrapAll
org.apache.jmeter.samplers.Sampler
Classes which are able to generate information about an entry should implement this interface. @author $Author: mstover1 $ @created $Date: 2002/02/16 03:21:42 $ @version $Revision: 1.18 $
org.apache.lucene.facet.sampling.Sampler
Sampling definition for facets accumulation
The Sampler uses TAKMI style counting to provide a 'best guess' top-K result set of the facets accumulated.
Note: Sampling accumulation (Accumulation over a sampled-set of the results), does not guarantee accurate values for {@link FacetResult#getNumValidDescendants()}. @lucene.experimental
org.apache.mahout.math.stats.Sampler
Discrete distribution sampler: Samples from a given discrete distribution: you provide a source of randomness and a Vector (cardinality N) which describes a distribution over [0,N), and calls to sample() sample from 0 to N using this distribution
org.cspoker.ai.bots.bot.gametree.search.expander.sampling.Sampler
ptolemy.domains.de.lib.Sampler
Output the most recent input token when the trigger port receives a token. If no token has been received on the input port when a token is received on the trigger port, then the value of the initialValue parameter is produced. If, however, the initialValue parameter contains no value, then no output is produced. The inputs can be of any token type, but the output port is constrained to be of a type at least that of the input port and the initialValue parameter (if it has a value).
Both the input port and the output port are multiports. Generally, their widths should match. Otherwise, if the width of the input is greater than the width of the output, the extra input tokens will not appear on any output, although they will be consumed from the input port. If the width of the output is greater than that of the input, then the last few channels of the output will never emit tokens.
Note: If the width of the input changes during execution, then the most recent inputs are forgotten, as if the execution of the model were starting over.
This actor is similar to the Inhibit actor in that it modifies a stream of events based on the presence or absence of events from another input. This actor reacts to the presence of the other event, whereas Inhibit reacts to the absence of it.
This actor is different from the Register actor in that the input tokens are consumed from the input ports before the outputs are generated. @author Jie Liu, Edward A. Lee, Steve Neuendorffer, Elaine Cheong @version $Id: Sampler.java,v 1.46 2005/07/08 19:58:15 cxh Exp $ @since Ptolemy II 0.3 @Pt.ProposedRating Yellow (eal) @Pt.AcceptedRating Yellow (eal) @see ptolemy.domains.de.lib.Inhibit @see ptolemy.domains.de.lib.Register

Examples of org.apache.jmeter.samplers.Sampler

        if (bshInterpreter == null) {
            log.error("BeanShell not found");
            return;
        }
        JMeterContext jmctx = JMeterContextService.getContext();
        Sampler sam = jmctx.getCurrentSampler();
        try {
            // Add variables for access to context and variables
            bshInterpreter.set("sampler", sam);//$NON-NLS-1$
            processFileOrScript(bshInterpreter);
        } catch (JMeterException e) {

View Full Code Here

Examples of org.apache.lucene.facet.sampling.Sampler

    sampleParams.setSamplingThreshold(100);
    sampleParams.setOversampleFactor(1.0d);
    if (random().nextBoolean()) {
      sampleParams.setSampleFixer(new TakmiSampleFixer(indexReader, taxoReader, fsp));
    }
    final Sampler sampler = new RandomSampler(sampleParams, random());
    
    TaxonomyFacetsAccumulator[] accumulators = new TaxonomyFacetsAccumulator[] {
      new TaxonomyFacetsAccumulator(fsp, indexReader, taxoReader),
      new OldFacetsAccumulator(fsp, indexReader, taxoReader),
      new SamplingAccumulator(sampler, fsp, indexReader, taxoReader),

View Full Code Here

Examples of org.apache.mahout.math.stats.Sampler


  public LDASampler(Matrix model, Random random) {
    this.random = random;
    samplers = new Sampler[model.numRows()];
    for(int i = 0; i < samplers.length; i++) {
      samplers[i] = new Sampler(random, model.viewRow(i));
    }
  }

View Full Code Here

Examples of org.cspoker.ai.bots.bot.gametree.search.expander.sampling.Sampler

      configPersist.setContinuousLearning(true);
      configPersist.setModelCreationTreshold(8000);
      configPersist.setContinueAfterCreation(false);
      configPersist.setSolveConceptDrift(false);
      
      Sampler s = new BucketSampler(0.01);
//      Sampler s = new StochasticUniversalSampler(9);
//      Sampler s = new RouletteWheelSampler(9);
//      Sampler s = new RandomSampler(9);
      
      return new BotFactory[] {

View Full Code Here

Examples of ptolemy.domains.de.lib.Sampler

        FIR fir = new FIR(this, "fir");
        fir.taps.setExpression("{0.7, 0.3}");


        Quantizer quan = new Quantizer(this, "Quantizer");
        Average accumulator = new Average(this, "accumulator");
        Sampler sampler = new Sampler(this, "sampler");
        Clock clk = new Clock(this, "ADClock");
        clk.offsets.setExpression("{0.0}");
        clk.period.setToken(new DoubleToken(1.0));
        clk.values.setExpression("{true}");

View Full Code Here

0 1 2 3 4 5

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.