Package org.apache.mahout.common

Examples of org.apache.mahout.common.TimingStatistics

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      throw new IllegalArgumentException("Unrecognized dataSource type: " + params.get("dataSource"));
    }
    ClassifierContext classifier = new ClassifierContext(algorithm, datastore);
    classifier.initialize();
    ResultAnalyzer resultAnalyzer = new ResultAnalyzer(classifier.getLabels(), params.get("defaultCat"));
    TimingStatistics totalStatistics = new TimingStatistics();
    if (subdirs != null) {
     
      for (File file : subdirs) {
        if (verbose) {
          log.info("--------------");
          log.info("Testing: {}", file);
        }
        TimingStatistics operationStats = new TimingStatistics();
       
        long lineNum = 0;
        for (String line : new FileLineIterable(new File(file.getPath()), Charset.forName(params
            .get("encoding")), false)) {
         
          Map<String,List<String>> document = new NGrams(line, Integer.parseInt(params.get("gramSize")))
              .generateNGrams();
          for (Map.Entry<String,List<String>> stringListEntry : document.entrySet()) {
            String correctLabel = stringListEntry.getKey();
            List<String> strings = stringListEntry.getValue();
            TimingStatistics.Call call = operationStats.newCall();
            TimingStatistics.Call outercall = totalStatistics.newCall();
            ClassifierResult classifiedLabel = classifier.classifyDocument(strings.toArray(new String[strings
                .size()]), params.get("defaultCat"));
            call.end();
            outercall.end();
            boolean correct = resultAnalyzer.addInstance(correctLabel, classifiedLabel);
            if (verbose) {
              // We have one document per line
              log.info("Line Number: {} Line(30): {} Expected Label: {} Classified Label: {} Correct: {}",
                new Object[] {lineNum, line.length() > 30 ? line.substring(0, 30) : line, correctLabel,
                              classifiedLabel.getLabel(), correct,});
            }
            // log.info("{} {}", correctLabel, classifiedLabel);
           
          }
          lineNum++;
        }
        /*
         * log.info("{}\t{}\t{}/{}", new Object[] {correctLabel,
         * resultAnalyzer.getConfusionMatrix().getAccuracy(correctLabel),
         * resultAnalyzer.getConfusionMatrix().getCorrect(correctLabel),
         * resultAnalyzer.getConfusionMatrix().getTotal(correctLabel)});
         */
        log.info("Classified instances from {}", file.getName());
        if (verbose) {
          log.info("Performance stats {}", operationStats.toString());
        }
      }
     
    }
    if (verbose) {
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    }
    implStats.set(implId, info.split("\t"));
  }
 
  public void createBenchmark() {
    TimingStatistics stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        vectors[0][i] = new DenseVector(randomVectors.get(i));
        call.end();
      }
    }
    printStats(stats, "Create (copy)", "DenseVector");
   
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        vectors[1][i] = new RandomAccessSparseVector(randomVectors.get(i));
        call.end();
      }
    }
    printStats(stats, "Create (copy)", "RandSparseVector");
   
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        vectors[2][i] = new SequentialAccessSparseVector(randomVectors.get(i));
        call.end();
      }
    }
    printStats(stats, "Create (copy)", "SeqSparseVector");
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    }
    call.end();
  }

  public void incrementalCreateBenchmark() {
    TimingStatistics stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        vectors[0][i] = new DenseVector(cardinality);
        buildVectorIncrementally(stats, i, vectors[0][i], false);
      }
    }
    printStats(stats, "Create (incrementally)", "DenseVector");

    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        vectors[1][i] = new RandomAccessSparseVector(cardinality);
        buildVectorIncrementally(stats, i, vectors[1][i], false);
      }
    }
    printStats(stats, "Create (incrementally)", "RandSparseVector");

    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        vectors[2][i] = new SequentialAccessSparseVector(cardinality);
        buildVectorIncrementally(stats, i, vectors[2][i], false);
      }
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    }
    printStats(stats, "Create (incrementally)", "SeqSparseVector");
  }
 
  public void cloneBenchmark() {
    TimingStatistics stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        vectors[0][i] = vectors[0][i].clone();
        call.end();
      }
    }
    printStats(stats, "Clone", "DenseVector");
   
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        vectors[1][i] = vectors[1][i].clone();
        call.end();
      }
    }
    printStats(stats, "Clone", "RandSparseVector");
   
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        vectors[2][i] = vectors[2][i].clone();
        call.end();
      }
    }
    printStats(stats, "Clone", "SeqSparseVector");
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  }
 
  public void dotBenchmark() {
    double result = 0;
    TimingStatistics stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        result += vectors[0][i].dot(vectors[0][(i + 1) % numVectors]);
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, "DotProduct", "DenseVector", "sum = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        result += vectors[1][i].dot(vectors[1][(i + 1) % numVectors]);
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, "DotProduct", "RandSparseVector", "sum = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        result += vectors[2][i].dot(vectors[2][(i + 1) % numVectors]);
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, "DotProduct", "SeqSparseVector", "sum = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        result += vectors[0][i].dot(vectors[1][(i + 1) % numVectors]);
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, "DotProduct", "Dense.fn(Rand)", "sum = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        result += vectors[0][i].dot(vectors[2][(i + 1) % numVectors]);
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, "DotProduct", "Dense.fn(Seq)", "sum = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        result += vectors[1][i].dot(vectors[0][(i + 1) % numVectors]);
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, "DotProduct", "Rand.fn(Dense)", "sum = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        result += vectors[1][i].dot(vectors[2][(i + 1) % numVectors]);
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, "DotProduct", "Rand.fn(Seq)", "sum = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        result += vectors[2][i].dot(vectors[0][(i + 1) % numVectors]);
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, "DotProduct", "Seq.fn(Dense)", "sum = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        result += vectors[2][i].dot(vectors[1][(i + 1) % numVectors]);
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
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  }
 
  public void distanceMeasureBenchmark(DistanceMeasure measure) {
    double result = 0;
    TimingStatistics stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[0][i], vectors[0][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "DenseVector", "minDistance = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[1][i], vectors[1][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "RandSparseVector", "minDistance = " + result
                                                                                + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[2][i], vectors[2][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "SeqSparseVector", "minDistance = " + result
                                                                                    + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[0][i], vectors[1][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "Dense.fn(Rand)", "minDistance = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[0][i], vectors[2][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "Dense.fn(Seq)", "minDistance = " + result
                                                                                + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[1][i], vectors[0][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "Rand.fn(Dense)", "minDistance = " + result
                                                                                    + ' ');
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[1][i], vectors[2][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "Rand.fn(Seq)", "minDistance = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[2][i], vectors[0][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "Seq.fn(Dense)", "minDistance = " + result
                                                                                + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[2][i], vectors[1][u]);
          if (distance < minDistance) {
            minDistance = distance;
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      throw new IllegalArgumentException("Unrecognized dataSource type: " + params.get("dataSource"));
    }
    ClassifierContext classifier = new ClassifierContext(algorithm, datastore);
    classifier.initialize();
    ResultAnalyzer resultAnalyzer = new ResultAnalyzer(classifier.getLabels(), params.get("defaultCat"));
    TimingStatistics totalStatistics = new TimingStatistics();
    if (subdirs != null) {
     
      for (File file : subdirs) {
        if (verbose) {
          log.info("--------------");
          log.info("Testing: {}", file);
        }
        TimingStatistics operationStats = new TimingStatistics();
       
        long lineNum = 0;
        for (String line : new FileLineIterable(new File(file.getPath()), Charset.forName(params
            .get("encoding")), false)) {
         
          Map<String,List<String>> document = new NGrams(line, Integer.parseInt(params.get("gramSize")))
              .generateNGrams();
          for (Map.Entry<String,List<String>> stringListEntry : document.entrySet()) {
            String correctLabel = stringListEntry.getKey();
            List<String> strings = stringListEntry.getValue();
            TimingStatistics.Call call = operationStats.newCall();
            TimingStatistics.Call outercall = totalStatistics.newCall();
            ClassifierResult classifiedLabel = classifier.classifyDocument(strings.toArray(new String[strings
                .size()]), params.get("defaultCat"));
            call.end();
            outercall.end();
            boolean correct = resultAnalyzer.addInstance(correctLabel, classifiedLabel);
            if (verbose) {
              // We have one document per line
              log.info("Line Number: {} Line(30): {} Expected Label: {} Classified Label: {} Correct: {}",
                new Object[] {lineNum, line.length() > 30 ? line.substring(0, 30) : line, correctLabel,
                              classifiedLabel.getLabel(), correct,});
            }
            // log.info("{} {}", correctLabel, classifiedLabel);
           
          }
          lineNum++;
        }
        ConfusionMatrix matrix = resultAnalyzer.getConfusionMatrix();
        log.info("{}", matrix);
        BayesClassifierDriver.confusionMatrixSeqFileExport(params, matrix);

        log.info("ConfusionMatrix: {}", matrix.toString());
          
        log.info("Classified instances from {}", file.getName());
        if (verbose) {
          log.info("Performance stats {}", operationStats.toString());
        }
      }
     
    }
    if (verbose) {
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  }
 
  public void distanceMeasureBenchmark(DistanceMeasure measure) {
    double result = 0;
    TimingStatistics stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[0][i], vectors[0][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "DenseVector", "minDistance = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[1][i], vectors[1][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "RandSparseVector", "minDistance = " + result
                                                                                + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[2][i], vectors[2][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "SeqSparseVector", "minDistance = " + result
                                                                                    + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[0][i], vectors[1][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "Dense.fn(Rand)", "minDistance = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[0][i], vectors[2][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "Dense.fn(Seq)", "minDistance = " + result
                                                                                + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[1][i], vectors[0][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "Rand.fn(Dense)", "minDistance = " + result
                                                                                    + ' ');
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[1][i], vectors[2][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "Rand.fn(Seq)", "minDistance = " + result + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[2][i], vectors[0][u]);
          if (distance < minDistance) {
            minDistance = distance;
          }
        }
        result += minDistance;
        call.end();
      }
    }
    // print result to prevent hotspot from eliminating deadcode
    printStats(stats, measure.getClass().getName(), "Seq.fn(Dense)", "minDistance = " + result
                                                                                + ' ');
    result = 0;
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        double minDistance = Double.MAX_VALUE;
        for (int u = 0; u < opsPerUnit; u++) {
          double distance = measure.distance(vectors[2][i], vectors[1][u]);
          if (distance < minDistance) {
            minDistance = distance;
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    }
    implStats.set(implId, TAB_PATTERN.split(info));
  }
 
  public void createBenchmark() {
    TimingStatistics stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        vectors[0][i] = new DenseVector(randomVectors.get(i));
        call.end();
      }
    }
    printStats(stats, "Create (copy)", "DenseVector");
   
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        vectors[1][i] = new RandomAccessSparseVector(randomVectors.get(i));
        call.end();
      }
    }
    printStats(stats, "Create (copy)", "RandSparseVector");
   
    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        TimingStatistics.Call call = stats.newCall();
        vectors[2][i] = new SequentialAccessSparseVector(randomVectors.get(i));
        call.end();
      }
    }
    printStats(stats, "Create (copy)", "SeqSparseVector");
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    }
    call.end();
  }

  public void incrementalCreateBenchmark() {
    TimingStatistics stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        vectors[0][i] = new DenseVector(cardinality);
        buildVectorIncrementally(stats, i, vectors[0][i], false);
      }
    }
    printStats(stats, "Create (incrementally)", "DenseVector");

    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        vectors[1][i] = new RandomAccessSparseVector(cardinality);
        buildVectorIncrementally(stats, i, vectors[1][i], false);
      }
    }
    printStats(stats, "Create (incrementally)", "RandSparseVector");

    stats = new TimingStatistics();
    for (int l = 0; l < loop; l++) {
      for (int i = 0; i < numVectors; i++) {
        vectors[2][i] = new SequentialAccessSparseVector(cardinality);
        buildVectorIncrementally(stats, i, vectors[2][i], false);
      }
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