Examples of run()


Examples of de.jetwick.tw.TweetDetector.run()

        // some users were only mentioned by others ...
        Collection<JTweet> tweets = user.getOwnTweets();
        if (tweets.size() > 0) {
            TweetDetector extractor = new TweetDetector(tweets);
            List<String> tagList = new ArrayList<String>();
            for (Entry<String, Integer> entry : extractor.run().getSortedTerms()) {
                if (entry.getValue() > termMinFrequency)
                    tagList.add(entry.getKey());
            }
            b.field("tag", tagList);
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Examples of de.jetwick.tw.UrlExtractor.run()

                return UrlEntry.createSimpleResult(origUrl);
            }
        };
        JTweet tw = new JTweet(id, "text is not important " + url, new JUser("timetabling")).setRetweetCount(rt);
        extractor.setTweet(tw);
        tw.setUrlEntries(extractor.run().getUrlEntries());       
        return tw;
    }

    @Override
    public Module createModule() {
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Examples of de.jetwick.tw.queue.QueueThread.run()

    @Test
    public void testQueueWhenUserSearch() throws InterruptedException {
        TweetSearchPage page = getInstance(TweetSearchPage.class);

        QueueThread p = page.queueTweets(null, null, "java");
        p.run();
        assertNotNull(sentTweets);

        assertEquals("", qString);
        assertEquals("#java", uString);
    }
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Examples of de.lmu.ifi.dbs.elki.KDDTask.run()

        config.tryInstantiate(LoggingStep.class);
        KDDTask task = config.tryInstantiate(KDDTask.class);
        try {
          config.logUnusedParameters();
          if(config.getErrors().size() == 0) {
            task.run();
          }
          else {
            reportErrors(config);
          }
        }
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Examples of de.lmu.ifi.dbs.elki.algorithm.APRIORI.run()

        oaa.append(bitmeta, new BitVector(bits));
        apriori_db.insert(oaa);
      }
    }
    APRIORI apriori = new APRIORI(minpts);
    AprioriResult aprioriResult = apriori.run(apriori_db);

    // result of apriori
    List<BitSet> frequentItemsets = aprioriResult.getSolution();
    Map<BitSet, Integer> supports = aprioriResult.getSupports();
    if(logger.isDebugging()) {
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Examples of de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByLabelClustering.run()

   * @param expected Expected score
   */
  protected <O> void testFMeasure(Database database, Clustering<?> clustering, double expected) {
    // Run by-label as reference
    ByLabelClustering bylabel = new ByLabelClustering();
    Clustering<Model> rbl = bylabel.run(database);

    double score = PairCountingFMeasure.compareClusterings(clustering, rbl, 1.0);
    if(logger.isVerbose()) {
      logger.verbose(this.getClass().getSimpleName() + " score: " + score + " expect: " + expected);
    }
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Examples of de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByLabelHierarchicalClustering.run()

   * @param expected Expected score
   */
  protected <O> void testFMeasureHierarchical(Database database, Clustering<?> clustering, double expected) {
    // Run by-label as reference
    ByLabelHierarchicalClustering bylabel = new ByLabelHierarchicalClustering();
    Clustering<Model> rbl = bylabel.run(database);

    double score = PairCountingFMeasure.compareClusterings(clustering, rbl, 1.0, false, true);
    if(logger.isVerbose()) {
      logger.verbose(this.getClass().getSimpleName() + " score: " + score + " expect: " + expected);
    }
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Examples of de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.TrivialAllInOne.run()

    Relation<?> rel = db.getRelation(TypeUtil.ANY);
    assertTrue(rel.size() == shoulds);

    // run all-in-one
    TrivialAllInOne allinone = new TrivialAllInOne();
    Clustering<Model> rai = allinone.run(db);

    // run all-in-noise
    TrivialAllNoise allinnoise = new TrivialAllNoise();
    Clustering<Model> ran = allinnoise.run(db);
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Examples of de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.TrivialAllNoise.run()

    TrivialAllInOne allinone = new TrivialAllInOne();
    Clustering<Model> rai = allinone.run(db);

    // run all-in-noise
    TrivialAllNoise allinnoise = new TrivialAllNoise();
    Clustering<Model> ran = allinnoise.run(db);

    // run by-label
    ByLabelClustering bylabel = new ByLabelClustering();
    Clustering<?> rbl = bylabel.run(db);
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Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.fitting.LevenbergMarquardtMethod.run()

    // fit.iterate();
    // double[] ps = fit.getParams();
    // System.out.println("Mean: " + ps[0] + " Stddev: " + ps[1] + " Amp: " +
    // ps[2]+" Chi: "+fit.getChiSq());
    // }
    fit.run();
    // double[] ps = fit.getParams();
    // System.out.println("Result: "+ps[0]+" "+ps[1]+" "+ps[2]+" Chi: "+fit.getChiSq()+" Iter: "+fit.maxruns);
    return fit.getParams();
  }
}
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