Package edu.umd.cloud9.util.map

Examples of edu.umd.cloud9.util.map.HMapII.keySet()

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    assertEquals(doc2.getNumberOfTypes(), doc1.getNumberOfTypes());
    assertEquals(doc2.getNumberOfTopics(), doc1.getNumberOfTopics());
    assertEquals(hmap2.size(), hmap1.size());
    assertEquals(array2.length, array1.length);

    Iterator<Integer> itr = hmap2.keySet().iterator();
    while (itr.hasNext()) {
      int key = itr.next();
      assertEquals(hmap2.get(key), hmap1.get(key));
    }
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      for (int i = 0; i < numberOfTopics; i++) {
        tempGamma[i] = Gamma.digamma(tempGamma[i]);
        updateLogGamma[i] = Math.log(alpha[i]);
      }

      itr = content.keySet().iterator();
      while (itr.hasNext()) {
        int termID = itr.next();
        // acquire the corresponding beta vector for this term
        if (logPhiTable.containsKey(termID)) {
          // reuse existing object
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          // output.collect(outputKey, outputValue);
          // totalAlphaSufficientStatistics[i] = 0;
          // }
        }

        itr = content.keySet().iterator();
        while (itr.hasNext()) {
          int termID = itr.next();
          if (termID < Settings.TOP_WORDS_FOR_CACHING) {
            if (totalPhi.containsKey(termID)) {
              logPhi = logPhiTable.get(termID);
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          }
        }
      }
    } else {
      if (learning) {
        itr = content.keySet().iterator();
        while (itr.hasNext()) {
          int termID = itr.next();
          // only get the phi's of current document
          logPhi = logPhiTable.get(termID);
          for (int i = 0; i < numberOfTopics; i++) {
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    }

    output.writeInt(-1);

    output.writeInt(docLengths.size());
    for(int docid: docLengths.keySet()) {
      output.writeInt(docid);
      output.writeInt(docLengths.get(docid));
    }

    output.close();
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