Java Long2DoubleOpenHashMap.size方法代码示例

import it.unimi.dsi.fastutil.longs.Long2DoubleOpenHashMap; //导入方法依赖的package包/类
private final Long2DoubleOpenHashMap verifyCandidates(final Vector v, Long2DoubleOpenHashMap accumulator) {
  Long2DoubleOpenHashMap matches = new Long2DoubleOpenHashMap();
  for (Long2DoubleMap.Entry e : accumulator.long2DoubleEntrySet()) {
    final long candidateID = e.getLongKey();
    if (Double.compare(e.getDoubleValue() + ps.get(candidateID), theta) < 0) // A[y] = dot(x, y'')
      continue; // l2 pruning
    Vector residual = residuals.get(candidateID);
    assert (residual != null);
    final double ds1 = e.getDoubleValue()
        + Math.min(v.maxValue() * residual.sumValues(), residual.maxValue() * v.sumValues());
    if (Double.compare(ds1, theta) < 0)
      continue; // dpscore, eq. (5)
    final double sz2 = e.getDoubleValue() + Math.min(v.maxValue() * residual.size(), residual.maxValue() * v.size());
    if (Double.compare(sz2, theta) < 0)
      continue; // dpscore, eq. (9)

    final long deltaT = v.timestamp() - candidateID;
    double score = e.getDoubleValue() + Vector.similarity(v, residual); // dot(x, y) = A[y] + dot(x, y')
    score *= forgettingFactor(lambda, deltaT); // apply forgetting factor
    numSimilarities++;
    if (Double.compare(score, theta) >= 0) // final check
      matches.put(candidateID, score);
  }
  numMatches += matches.size();
  return matches;
}
 

import it.unimi.dsi.fastutil.longs.Long2DoubleOpenHashMap; //导入方法依赖的package包/类
private final Long2DoubleOpenHashMap verifyCandidates(final Vector v, Long2DoubleOpenHashMap accumulator) {
  Long2DoubleOpenHashMap matches = new Long2DoubleOpenHashMap();
  for (Long2DoubleMap.Entry e : accumulator.long2DoubleEntrySet()) {
    final long candidateID = e.getLongKey();
    if (Double.compare(e.getDoubleValue() + ps.get(candidateID), theta) < 0) // A[y] = dot(x, y'')
      continue; // l2 pruning
    final Vector residual = residuals.get(candidateID);
    assert (residual != null);
    final double ds1 = e.getDoubleValue()
        + Math.min(v.maxValue() * residual.sumValues(), residual.maxValue() * v.sumValues());
    if (Double.compare(ds1, theta) < 0)
      continue; // dpscore, eq. (5)
    final double sz2 = e.getDoubleValue() + Math.min(v.maxValue() * residual.size(), residual.maxValue() * v.size());
    if (Double.compare(sz2, theta) < 0)
      continue; // dpscore, eq. (9)

    final long deltaT = v.timestamp() - candidateID;
    double score = e.getDoubleValue() + Vector.similarity(v, residual); // dot(x, y) = A[y] + dot(x, y')
    score *= forgettingFactor(lambda, deltaT); // apply forgetting factor
    numSimilarities++;
    if (Double.compare(score, theta) >= 0) // final check
      matches.put(candidateID, score);
  }
  numMatches += matches.size();
  return matches;
}
 

import it.unimi.dsi.fastutil.longs.Long2DoubleOpenHashMap; //导入方法依赖的package包/类
private Long2DoubleOpenHashMap verifyCandidates(final Vector v, Long2DoubleOpenHashMap accumulator) {
  Long2DoubleOpenHashMap matches = new Long2DoubleOpenHashMap();
  for (Long2DoubleMap.Entry e : accumulator.long2DoubleEntrySet()) {
    long candidateID = e.getLongKey();
    Vector candidateResidual = residuals.get(candidateID);
    assert (candidateResidual != null);
    double score = e.getDoubleValue() + Vector.similarity(v, candidateResidual); // A[y] + dot(y',x)
    long deltaT = v.timestamp() - candidateID;
    score *= Commons.forgettingFactor(lambda, deltaT); // apply forgetting factor
    numSimilarities++;
    if (Double.compare(score, theta) >= 0) // final check
      matches.put(candidateID, score);
  }
  numMatches += matches.size();
  return matches;
}
 

import it.unimi.dsi.fastutil.longs.Long2DoubleOpenHashMap; //导入方法依赖的package包/类
@Override
protected double doProcessRow(ServerSparseDoubleLongKeyRow row) {
  long entireSize = row.getEndCol() - row.getStartCol();

  double qSum = 0.0;
  Long2DoubleOpenHashMap data = row.getIndex2ValueMap();
  for (Map.Entry<Long, Double> entry: data.long2DoubleEntrySet()) {
    qSum += Math.pow(entry.getValue(), 2);
  }
  qSum += Math.pow(data.defaultReturnValue(), 2) * (entireSize - data.size());
  return qSum;
}
 

import it.unimi.dsi.fastutil.longs.Long2DoubleOpenHashMap; //导入方法依赖的package包/类
@Override
protected double doProcessRow(ServerSparseDoubleLongKeyRow row) {
  long entireSize = row.getEndCol() - row.getStartCol();

  Long2DoubleOpenHashMap data = row.getData();
  double asum = 0.0;
  for (Map.Entry<Long, Double> entry: data.long2DoubleEntrySet()) {
    asum += entry.getValue();
  }
  asum += data.defaultReturnValue() * (entireSize - data.size());
  return asum;
}
 

import it.unimi.dsi.fastutil.longs.Long2DoubleOpenHashMap; //导入方法依赖的package包/类
@Override
protected double doProcessRow(ServerSparseDoubleLongKeyRow row) {
  long entireSize = row.getEndCol() - row.getStartCol();

  Long2DoubleOpenHashMap data = row.getData();
  double asum = 0.0;
  for (Map.Entry<Long, Double> entry: data.long2DoubleEntrySet()) {
    asum += Math.abs(entry.getValue());
  }
  asum += Math.abs(data.defaultReturnValue()) * (entireSize - data.size());
  return asum;
}
 

import it.unimi.dsi.fastutil.longs.Long2DoubleOpenHashMap; //导入方法依赖的package包/类
private final Long2DoubleOpenHashMap generateCandidates(final Vector v, final boolean addToIndex) {
  final Long2DoubleOpenHashMap accumulator = new Long2DoubleOpenHashMap(size);
  for (Entry e : v.int2DoubleEntrySet()) {
    final int dimension = e.getIntKey();
    final double queryWeight = e.getDoubleValue();
    PostingList list;
    if ((list = idx.get(dimension)) != null) {
      for (PostingEntry pe : list) {
        numPostingEntries++;
        final long targetID = pe.getID();
        final double targetWeight = pe.getWeight();
        final double additionalSimilarity = queryWeight * targetWeight;
        accumulator.addTo(targetID, additionalSimilarity);
      }
    }
    if (addToIndex) {
      if (list == null) {
        list = new PostingList();
        idx.put(dimension, list);
      }
      list.add(v.timestamp(), queryWeight);
      size++;
    }
  }
  numCandidates += accumulator.size();
  return accumulator;
}
 

import it.unimi.dsi.fastutil.longs.Long2DoubleOpenHashMap; //导入方法依赖的package包/类
private final Long2DoubleOpenHashMap verifyCandidates(final Vector v, Long2DoubleOpenHashMap accumulator) {
  numSimilarities = numCandidates;
  // add forgetting factor e^(-lambda*delta_T) and filter candidates < theta
  for (Iterator<Long2DoubleMap.Entry> it = accumulator.long2DoubleEntrySet().iterator(); it.hasNext();) {
    Long2DoubleMap.Entry e = it.next();
    final long deltaT = v.timestamp() - e.getLongKey();
    e.setValue(e.getDoubleValue() * forgettingFactor(lambda, deltaT));
    if (Doubles.compare(e.getDoubleValue(), theta) < 0)
      it.remove();
  }
  numMatches += accumulator.size();
  return accumulator;
}
 

import it.unimi.dsi.fastutil.longs.Long2DoubleOpenHashMap; //导入方法依赖的package包/类
private final Long2DoubleOpenHashMap generateCandidates(final Vector v) {
  final Long2DoubleOpenHashMap accumulator = new Long2DoubleOpenHashMap();
  double l2remscore = 1, // rs4
  rst = 1, squaredQueryPrefixMagnitude = 1;

  for (BidirectionalIterator<Entry> vecIter = v.int2DoubleEntrySet().fastIterator(v.int2DoubleEntrySet().last()); vecIter
      .hasPrevious();) { // iterate over v in reverse order
    final Entry e = vecIter.previous();
    final int dimension = e.getIntKey();
    final double queryWeight = e.getDoubleValue(); // x_j
    final double rscore = l2remscore;
    squaredQueryPrefixMagnitude -= queryWeight * queryWeight;

    L2APPostingList list;
    if ((list = idx.get(dimension)) != null) {
      for (L2APPostingEntry pe : list) {
        numPostingEntries++;
        final long targetID = pe.id(); // y
        if (accumulator.containsKey(targetID) || Double.compare(rscore, theta) >= 0) {
          final double targetWeight = pe.weight(); // y_j
          final double additionalSimilarity = queryWeight * targetWeight; // x_j * y_j
          accumulator.addTo(targetID, additionalSimilarity); // A[y] += x_j * y_j
          final double l2bound = accumulator.get(targetID) + FastMath.sqrt(squaredQueryPrefixMagnitude)
              * pe.magnitude(); // A[y] + ||x'_j|| * ||y'_j||
          if (Double.compare(l2bound, theta) < 0)
            accumulator.remove(targetID); // prune this candidate (early verification)
        }
      }
      rst -= queryWeight * queryWeight; // rs_t -= x_j^2
      l2remscore = FastMath.sqrt(rst); // rs_4 = sqrt(rs_t)
    }
  }
  numCandidates += accumulator.size();
  return accumulator;
}
 

import it.unimi.dsi.fastutil.longs.Long2DoubleOpenHashMap; //导入方法依赖的package包/类
private final Long2DoubleOpenHashMap generateCandidates(final Vector v) {
  final Long2DoubleOpenHashMap accumulator = new Long2DoubleOpenHashMap();
  double remscore = Vector.similarity(v, maxVectorInIndex); // rs3, enhanced remscore bound
  double l2remscore = 1, // rs4
  rst = 1, squaredQueryPrefixMagnitude = 1;

  for (BidirectionalIterator<Entry> vecIter = v.int2DoubleEntrySet().fastIterator(v.int2DoubleEntrySet().last()); vecIter
      .hasPrevious();) { // iterate over v in reverse order
    final Entry e = vecIter.previous();
    final int dimension = e.getIntKey();
    final double queryWeight = e.getDoubleValue(); // x_j
    final double rscore = Math.min(remscore, l2remscore);
    squaredQueryPrefixMagnitude -= queryWeight * queryWeight;

    L2APPostingList list;
    if ((list = idx.get(dimension)) != null) {
      for (L2APPostingEntry pe : list) {
        numPostingEntries++;
        final long targetID = pe.id(); // y
        if (accumulator.containsKey(targetID) || Double.compare(rscore, theta) >= 0) {
          final double targetWeight = pe.weight(); // y_j
          final double additionalSimilarity = queryWeight * targetWeight; // x_j * y_j
          accumulator.addTo(targetID, additionalSimilarity); // A[y] += x_j * y_j
          final double l2bound = accumulator.get(targetID) + FastMath.sqrt(squaredQueryPrefixMagnitude)
              * pe.magnitude(); // A[y] + ||x'_j|| * ||y'_j||
          if (Double.compare(l2bound, theta) < 0)
            accumulator.remove(targetID); // prune this candidate (early verification)
        }
      }
      remscore -= queryWeight * maxVectorInIndex.get(dimension); // rs_3 -= x_j * \hat{c_w}
      rst -= queryWeight * queryWeight; // rs_t -= x_j^2
      l2remscore = FastMath.sqrt(rst); // rs_4 = sqrt(rs_t)
    }
  }
  numCandidates += accumulator.size();
  return accumulator;
}
 

import it.unimi.dsi.fastutil.longs.Long2DoubleOpenHashMap; //导入方法依赖的package包/类
private Long2DoubleOpenHashMap generateCandidates(final Vector v) {
  Long2DoubleOpenHashMap accumulator = new Long2DoubleOpenHashMap();
  double remscore = Vector.similarity(v, maxVector);

  /* candidate generation */
  for (BidirectionalIterator<Entry> it = v.int2DoubleEntrySet().fastIterator(v.int2DoubleEntrySet().last()); it
      .hasPrevious();) { // iterate over v in reverse order
    Entry e = it.previous();
    int dimension = e.getIntKey();
    double queryWeight = e.getDoubleValue(); // x_j

    PostingList list;
    if ((list = idx.get(dimension)) != null) {
      for (PostingEntry pe : list) {
        numPostingEntries++;
        final long targetID = pe.getID(); // y
        if (accumulator.containsKey(targetID) || Double.compare(remscore, theta) >= 0) {
          final double targetWeight = pe.getWeight(); // y_j
          final double additionalSimilarity = queryWeight * targetWeight; // x_j * y_j
          accumulator.addTo(targetID, additionalSimilarity); // A[y] += x_j * y_j
        }
      }
    }
    remscore -= queryWeight * maxVector.get(dimension);
  }
  numCandidates += accumulator.size();
  return accumulator;
}