Java Int2DoubleOpenHashMap.size方法代码示例

import it.unimi.dsi.fastutil.ints.Int2DoubleOpenHashMap; //导入方法依赖的package包/类
private double dot(SparseDoubleVector other) {
  double ret = 0.0;

  Int2DoubleOpenHashMap smallMap = this.hashMap;
  Int2DoubleOpenHashMap largeMap = other.hashMap;

  if (smallMap.size() > largeMap.size()) {
    smallMap = other.hashMap;
    largeMap = this.hashMap;
  }

  ObjectIterator<Int2DoubleMap.Entry> iter = smallMap.int2DoubleEntrySet().fastIterator();

  Int2DoubleMap.Entry entry = null;
  while (iter.hasNext()) {
    entry = iter.next();
    if (largeMap.containsKey(entry.getIntKey())) {
      ret += entry.getDoubleValue() * largeMap.get(entry.getIntKey());
    }
  }
  return ret;
}
 

import it.unimi.dsi.fastutil.ints.Int2DoubleOpenHashMap; //导入方法依赖的package包/类
@Override
public SparseFloatVector newNumberVector(Int2DoubleOpenHashMap dvalues, int maxdim) {
  int[] indexes = new int[dvalues.size()];
  float[] values = new float[dvalues.size()];
  // Import and sort the indexes
  ObjectIterator<Int2DoubleMap.Entry> iter = dvalues.int2DoubleEntrySet().fastIterator();
  for(int i = 0; iter.hasNext(); i++) {
    indexes[i] = iter.next().getIntKey();
  }
  Arrays.sort(indexes);
  // Import the values accordingly
  for(int i = 0; i < dvalues.size(); i++) {
    values[i] = (float) dvalues.get(indexes[i]);
  }
  return new SparseFloatVector(indexes, values, maxdim);
}
 

import it.unimi.dsi.fastutil.ints.Int2DoubleOpenHashMap; //导入方法依赖的package包/类
/**
 * Create a SparseByteVector consisting of double values according to the
 * specified mapping of indices and values.
 *
 * @param values the values to be set as values of the real vector
 * @param dimensionality the dimensionality of this feature vector
 * @throws IllegalArgumentException if the given dimensionality is too small
 *         to cover the given values (i.e., the maximum index of any value not
 *         zero is bigger than the given dimensionality)
 */
public SparseByteVector(Int2DoubleOpenHashMap values, int dimensionality) throws IllegalArgumentException {
  if(values.size() > dimensionality) {
    throw new IllegalArgumentException("values.size() > dimensionality!");
  }

  this.indexes = new int[values.size()];
  this.values = new byte[values.size()];
  // Import and sort the indexes
  {
    ObjectIterator<Int2DoubleMap.Entry> iter = values.int2DoubleEntrySet().fastIterator();
    for(int i = 0; iter.hasNext(); i++) {
      this.indexes[i] = iter.next().getIntKey();
    }
    Arrays.sort(this.indexes);
  }
  // Import the values accordingly
  {
    for(int i = 0; i < values.size(); i++) {
      this.values[i] = (byte) values.get(this.indexes[i]);
    }
  }
  this.dimensionality = dimensionality;
  final int maxdim = getMaxDim();
  if(maxdim > dimensionality) {
    throw new IllegalArgumentException("Given dimensionality " + dimensionality + " is too small w.r.t. the given values (occurring maximum: " + maxdim + ").");
  }
}
 

import it.unimi.dsi.fastutil.ints.Int2DoubleOpenHashMap; //导入方法依赖的package包/类
/**
 * Create a SparseShortVector consisting of double values according to the
 * specified mapping of indices and values.
 *
 * @param values the values to be set as values of the real vector
 * @param dimensionality the dimensionality of this feature vector
 * @throws IllegalArgumentException if the given dimensionality is too small
 *         to cover the given values (i.e., the maximum index of any value not
 *         zero is bigger than the given dimensionality)
 */
public SparseShortVector(Int2DoubleOpenHashMap values, int dimensionality) throws IllegalArgumentException {
  if(values.size() > dimensionality) {
    throw new IllegalArgumentException("values.size() > dimensionality!");
  }

  this.indexes = new int[values.size()];
  this.values = new short[values.size()];
  // Import and sort the indexes
  {
    ObjectIterator<Int2DoubleMap.Entry> iter = values.int2DoubleEntrySet().fastIterator();
    for(int i = 0; iter.hasNext(); i++) {
      this.indexes[i] = iter.next().getIntKey();
    }
    Arrays.sort(this.indexes);
  }
  // Import the values accordingly
  {
    for(int i = 0; i < values.size(); i++) {
      this.values[i] = (short) values.get(this.indexes[i]);
    }
  }
  this.dimensionality = dimensionality;
  final int maxdim = getMaxDim();
  if(maxdim > dimensionality) {
    throw new IllegalArgumentException("Given dimensionality " + dimensionality + " is too small w.r.t. the given values (occurring maximum: " + maxdim + ").");
  }
}
 

import it.unimi.dsi.fastutil.ints.Int2DoubleOpenHashMap; //导入方法依赖的package包/类
/**
 * Create a SparseIntegerVector consisting of double values according to the
 * specified mapping of indices and values.
 *
 * @param values the values to be set as values of the real vector
 * @param dimensionality the dimensionality of this feature vector
 * @throws IllegalArgumentException if the given dimensionality is too small
 *         to cover the given values (i.e., the maximum index of any value not
 *         zero is bigger than the given dimensionality)
 */
public SparseIntegerVector(Int2DoubleOpenHashMap values, int dimensionality) throws IllegalArgumentException {
  if(values.size() > dimensionality) {
    throw new IllegalArgumentException("values.size() > dimensionality!");
  }

  this.indexes = new int[values.size()];
  this.values = new int[values.size()];
  // Import and sort the indexes
  {
    ObjectIterator<Int2DoubleMap.Entry> iter = values.int2DoubleEntrySet().fastIterator();
    for(int i = 0; iter.hasNext(); i++) {
      this.indexes[i] = iter.next().getIntKey();
    }
    Arrays.sort(this.indexes);
  }
  // Import the values accordingly
  {
    for(int i = 0; i < values.size(); i++) {
      this.values[i] = (int) values.get(this.indexes[i]);
    }
  }
  this.dimensionality = dimensionality;
  final int maxdim = getMaxDim();
  if(maxdim > dimensionality) {
    throw new IllegalArgumentException("Given dimensionality " + dimensionality + " is too small w.r.t. the given values (occurring maximum: " + maxdim + ").");
  }
}
 

import it.unimi.dsi.fastutil.ints.Int2DoubleOpenHashMap; //导入方法依赖的package包/类
/**
 * Create a SparseDoubleVector consisting of double values according to the
 * specified mapping of indices and values.
 *
 * @param values the values to be set as values of the real vector
 * @param dimensionality the dimensionality of this feature vector
 * @throws IllegalArgumentException if the given dimensionality is too small
 *         to cover the given values (i.e., the maximum index of any value not
 *         zero is bigger than the given dimensionality)
 */
public SparseDoubleVector(Int2DoubleOpenHashMap values, int dimensionality) throws IllegalArgumentException {
  if(values.size() > dimensionality) {
    throw new IllegalArgumentException("values.size() > dimensionality!");
  }

  this.indexes = new int[values.size()];
  this.values = new double[values.size()];
  // Import and sort the indexes
  {
    ObjectIterator<Int2DoubleMap.Entry> iter = values.int2DoubleEntrySet().fastIterator();
    for(int i = 0; iter.hasNext(); i++) {
      this.indexes[i] = iter.next().getIntKey();
    }
    Arrays.sort(this.indexes);
  }
  // Import the values accordingly
  {
    for(int i = 0; i < values.size(); i++) {
      this.values[i] = values.get(this.indexes[i]);
    }
  }
  this.dimensionality = dimensionality;
  final int maxdim = getMaxDim();
  if(maxdim > dimensionality) {
    throw new IllegalArgumentException("Given dimensionality " + dimensionality + " is too small w.r.t. the given values (occurring maximum: " + maxdim + ").");
  }
}