Package org.apache.mahout.math

Examples of org.apache.mahout.math.Vector.clone()

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        int itemIDIndex = e.index();
        numberOfSimilarItemsUsed.setQuick(itemIDIndex, numberOfSimilarItemsUsed.getQuick(itemIDIndex) + 1);
      }

      if (denominators == null) {
        denominators = simColumn.clone();
      } else {
        denominators.assign(simColumn, Functions.PLUS_ABS);
      }

      if (numerators == null) {
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      } else {
        denominators.assign(simColumn, Functions.PLUS_ABS);
      }

      if (numerators == null) {
        numerators = simColumn.clone();
        if (prefValue != BOOLEAN_PREF_VALUE) {
          numerators.assign(Functions.MULT, prefValue);
        }
      } else {
        if (prefValue != BOOLEAN_PREF_VALUE) {
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      if (r.nextBoolean() || numRows == nonNullRows) {
        m.assignRow(numRows == nonNullRows ? i : c, v);
      } else {
        Vector other = m.viewRow(r.nextInt(numRows));
        if (other != null && other.getLengthSquared() > 0) {
          m.assignRow(c, other.clone());
        }
      }
      //n += m.getRow(c).getLengthSquared();
    }
    return m;
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    initData(1, 0.25, measure);
    Canopy cluster = new Canopy(new DenseVector(new double[] {0, 0}), 19, measure);
    clusters.add(cluster);
    List<VectorWritable> points = Lists.newArrayList();
    Vector delta = new DenseVector(new double[] {0, Double.MIN_NORMAL});
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    representativePoints.put(cluster.getId(), points);
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    Canopy cluster = new Canopy(new DenseVector(new double[] {0, 0}), 19, measure);
    clusters.add(cluster);
    List<VectorWritable> points = Lists.newArrayList();
    Vector delta = new DenseVector(new double[] {0, Double.MIN_NORMAL});
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    representativePoints.put(cluster.getId(), points);
    CDbwEvaluator evaluator = new CDbwEvaluator(representativePoints, clusters, measure);
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    clusters.add(cluster);
    List<VectorWritable> points = Lists.newArrayList();
    Vector delta = new DenseVector(new double[] {0, Double.MIN_NORMAL});
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    representativePoints.put(cluster.getId(), points);
    CDbwEvaluator evaluator = new CDbwEvaluator(representativePoints, clusters, measure);
    System.out.println("CDbw = " + evaluator.getCDbw());
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    List<VectorWritable> points = Lists.newArrayList();
    Vector delta = new DenseVector(new double[] {0, Double.MIN_NORMAL});
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    representativePoints.put(cluster.getId(), points);
    CDbwEvaluator evaluator = new CDbwEvaluator(representativePoints, clusters, measure);
    System.out.println("CDbw = " + evaluator.getCDbw());
    System.out.println("Intra-cluster density = " + evaluator.intraClusterDensity());
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    Vector delta = new DenseVector(new double[] {0, Double.MIN_NORMAL});
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    points.add(new VectorWritable(delta.clone()));
    representativePoints.put(cluster.getId(), points);
    CDbwEvaluator evaluator = new CDbwEvaluator(representativePoints, clusters, measure);
    System.out.println("CDbw = " + evaluator.getCDbw());
    System.out.println("Intra-cluster density = " + evaluator.intraClusterDensity());
    System.out.println("Inter-cluster density = " + evaluator.interClusterDensity());
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        int itemIDIndex = usedItemsIterator.next().index();
        numberOfSimilarItemsUsed.setQuick(itemIDIndex, numberOfSimilarItemsUsed.getQuick(itemIDIndex) + 1);
      }

      numerators = numerators == null
          ? prefValue == BOOLEAN_PREF_VALUE ? simColumn.clone() : simColumn.times(prefValue)
          : numerators.plus(prefValue == BOOLEAN_PREF_VALUE ? simColumn : simColumn.times(prefValue));

      simColumn.assign(ABSOLUTE_VALUES);
      denominators = denominators == null ? simColumn : denominators.plus(simColumn);
    }
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      String clusterId = clusterIdBuilder.toString();
      clusterId = clusterId.substring(0, clusterId.lastIndexOf('-'));
      Text cluster = new Text(clusterId);
      Writable point;
      if (debugOutput) {
        point = new VectorWritable(featureVector.clone());
      } else {
        point = new Text(item.toString());
      }
      context.write(cluster, point);
    }
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