Examples of sample()

@return a random value. @since 2.2
  • org.apache.commons.math3.distribution.RealDistribution.sample()
    Generate a random value sampled from this distribution. @return a random value.
  • org.apache.commons.math3.distribution.UniformIntegerDistribution.sample()
    {@inheritDoc}
  • org.apache.commons.math3.distribution.UniformRealDistribution.sample()
    {@inheritDoc}
  • org.apache.commons.math3.distribution.WeibullDistribution.sample()
    esus.ox.ac.uk/~clifford/a5/chap1/node5.html"> Inversion Method to generate exponentially distributed random values from uniform deviates.

    @return a random value. @since 2.2
  • org.apache.jmeter.protocol.http.sampler.HTTPSampler.sample()
  • org.apache.jmeter.protocol.http.sampler.HTTPSamplerBase.sample()
    Do a sampling and return its results. @param e Entry to be sampled @return results of the sampling
  • org.apache.jmeter.samplers.Sampler.sample()
    Obtains statistics about the given Entry, and packages the information into a SampleResult. @param e !ToDo (Parameter description) @return !ToDo (Return description)
  • org.apache.mahout.clustering.dirichlet.models.NormalModel.sample()
    TODO: Return a proper sample from the posterior. For now, return an instance with the same parameters @return an NormalModel
  • org.apache.mahout.clustering.lda.LDASampler.sample()
    @param topicDistribution vector of p(topicId) for all topicId < model.numTopics() @param numSamples the number of times to sample (with replacement) from the model @return array of length numSamples, with each entry being a sample from the model. Theremay be repeats
  • org.apache.mahout.knn.LumpyData.sample()
  • org.apache.mahout.math.random.ChineseRestaurant.sample()
  • org.apache.mahout.math.random.MultiNormal.sample()
  • org.apache.mahout.math.stats.Sampler.sample()
  • org.apache.openejb.api.Monitor.sample()
  • plm.hmm.DlmHiddenMarkovModel.sample()
    Sample a trajectory up to time T. Note: this method will add the filter's current input to the initial (and all other) states, so if you set the model input, the offset/input will be added twice to the initial state. @param random @param numSamples @return
  • prefuse.data.parser.TypeInferencer.sample()
    Sample the given text string for the given data column index. @param column the data column index of the sample @param value the text string sample
  • twitter4j.TwitterStream.sample()
    tter.com/Streaming-API-Documentation#sample">Twitter API Wiki / Streaming API Documentation - sample @since Twitter4J 2.0.10
  • vanilla.java.processingengine.testing.Histogram.sample()

    • Examples of org.apache.jmeter.protocol.http.sampler.HTTPSamplerBase.sample()

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                        sampler.setProtocol(HTTPConstants.PROTOCOL_HTTPS);
                        forcedHTTPS = true;
                    }
                }
                sampler.threadStarted(); // Needed for HTTPSampler2
                result = sampler.sample();

                /*
                 * If we're dealing with text data, and if we're spoofing https,
                 * replace all occurences of "https://" with "http://" for the client.
                 * TODO - also check the match string to restrict the changes further?
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    Examples of org.apache.jmeter.samplers.Sampler.sample()

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                controller.setRunningVersion(true);
                ifCont.setRunningVersion(true);
               
                Sampler sampler = null;
                while ((sampler = controller.next()) != null) {
                    sampler.sample(null);
                    assertEquals(order[counter], sampler.getName());
                    counter++;
                }
                assertEquals(counter, 6);
            }
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    Examples of org.apache.jmeter.samplers.Sampler.sample()

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                controller.setRunningVersion(true);
                ifCont.setRunningVersion(true);
               
                Sampler sampler = null;
                while ((sampler = controller.next()) != null) {
                    sampler.sample(null);
                    if (sampler.getName().equals("Sample3")) {
                        ifCont.setCondition("true==false");
                    }
                    assertEquals(order[counter], sampler.getName());
                    counter++;
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    Examples of org.apache.jmeter.samplers.Sampler.sample()

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                ifCont.setRunningVersion(true);
                genericCont.setRunningVersion(true);

                Sampler sampler = null;
                while ((sampler = controller.next()) != null) {
                    sampler.sample(null);
                    if (sampler.getName().equals("Sample3")) {
                        ifCont.setCondition("true==false");
                    }
                    assertEquals(order[counter], sampler.getName());
                    counter++;
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    Examples of org.apache.jmeter.samplers.Sampler.sample()

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            catch (Exception ex)
            {
              ex.printStackTrace();
              running = false;
            }
            SampleResult result = sampler.sample(entry);
            checkAssertions(entry, result);
            notifyListeners(result);
          }
        }
      }
    View Full Code Here

    Examples of org.apache.mahout.clustering.dirichlet.models.NormalModel.sample()

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      @Override
      public Model<Vector>[] sampleFromPosterior(Model<Vector>[] posterior) {
        Model<Vector>[] result = new NormalModel[posterior.length];
        for (int i = 0; i < posterior.length; i++) {
          NormalModel m = (NormalModel) posterior[i];
          result[i] = m.sample();
        }
        return result;
      }
    }
    View Full Code Here

    Examples of org.apache.mahout.clustering.lda.LDASampler.sample()

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        for(int i = 0; i < numTopicsPerDoc; i++) {
          int topic = random.nextInt(topicVector.size());
          topicVector.set(topic, topicVector.get(topic) + 1);
        }
        for(int docId = 0; docId < numDocs; docId++) {
          for(int sample : modelSampler.sample(topicVector, numSamples)) {
            corpus.set(docId, sample, corpus.get(docId, sample) + 1);
          }
        }
        return corpus;
      }
    View Full Code Here

    Examples of org.apache.mahout.knn.LumpyData.sample()

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              continue;
            }
            final Matrix data = new DenseMatrix(dataSize + querySize, d);
            final LumpyData clusters = new LumpyData(d, 0.05, 10);
            for (MatrixSlice row : data) {
              row.vector().assign(clusters.sample());
            }

            Matrix q = data.viewPart(0, querySize, 0, d);
            Matrix m = data.viewPart(querySize, dataSize, 0, d);
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    Examples of org.apache.mahout.math.random.ChineseRestaurant.sample()

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                    double millis = Math.floor((t - now) * 1000);
                    double nanos = Math.rint((t - now) * 1e9 - millis * 1e6);
                    Thread.sleep((long) millis, (int) nanos);
                }

                String topic = "topic-" + topicSampler.sample();
                String message = "m-" + (++messageId);
                client.sendMessage(topic, message);
                recorder.message(topic);
                log.debug("Sent {} / {}", topic, message);
                if ((messageId % 10000) == 0) {
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    Examples of org.apache.mahout.math.random.MultiNormal.sample()

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    public abstract class AbstractSearchTest {
      protected static Matrix randomData() {
        Matrix data = new DenseMatrix(1000, 20);
        MultiNormal gen = new MultiNormal(20);
        for (MatrixSlice slice : data) {
          slice.vector().assign(gen.sample());
        }
        return data;
      }

      public abstract Iterable<MatrixSlice> testData();
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