本文整理了Java中edu.uci.ics.jung.graph.Graph.getNeighbors()方法的一些代码示例，展示了Graph.getNeighbors()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Graph.getNeighbors()方法的具体详情如下：
包路径：edu.uci.ics.jung.graph.Graph
类名称：Graph
方法名：getNeighbors

Graph.getNeighbors介绍

暂无

代码示例

代码示例来源：origin: geogebra/geogebra

/**
 * @see edu.uci.ics.jung.graph.Hypergraph#getNeighbors(java.lang.Object)
 */
@Override
public synchronized Collection<V> getNeighbors(V vertex) {
  return delegate.getNeighbors(vertex);
}

代码示例来源：origin: geogebra/geogebra

/**
 * @see edu.uci.ics.jung.graph.Hypergraph#getNeighbors(java.lang.Object)
 */
@Override
public Collection<V> getNeighbors(V vertex) {
  return delegate.getNeighbors(vertex);
}

代码示例来源：origin: net.sf.jung/jung-api

/**
 * @see edu.uci.ics.jung.graph.Hypergraph#getNeighbors(java.lang.Object)
 */
public synchronized Collection<V> getNeighbors(V vertex) {
  return delegate.getNeighbors(vertex);
}

代码示例来源：origin: net.sf.jung/jung-api

/**
 * @see edu.uci.ics.jung.graph.Hypergraph#getNeighbors(java.lang.Object)
 */
public Collection<V> getNeighbors(V vertex) {
  return delegate.getNeighbors(vertex);
}

代码示例来源：origin: geogebra/geogebra

/**
 * @see edu.uci.ics.jung.graph.Hypergraph#getNeighbors(java.lang.Object)
 */
@Override
public Collection<V> getNeighbors(V vertex) {
  return delegate.getNeighbors(vertex);
}

代码示例来源：origin: net.sf.jung/jung-api

/**
 * @see edu.uci.ics.jung.graph.Hypergraph#getNeighbors(java.lang.Object)
 */
public Collection<V> getNeighbors(V vertex) {
  return delegate.getNeighbors(vertex);
}

代码示例来源：origin: net.sourceforge.jadex/jadex-tools-comanalyzer

/**
 * Returns the neighbor vertices of a given vertex.
 * @param vertex The vertex.
 * @return The collection of neighbors.
 */
public Collection getNeighbors(Object vertex)
{
  return delegate.getNeighbors(vertex);
}

代码示例来源：origin: net.sf.jung/jung-visualization

public Collection<V> getNeighbors(V vertex) {
  return graph.getNeighbors(vertex);
}
public V getOpposite(V vertex, E edge) {

代码示例来源：origin: stackoverflow.com

public int countReachable(int root, boolean[] visited, boolean[] ignored, Graph graph) {
  if (ignored[root]) {
    return 0;
  }

  Stack<Integer> stack = new Stack<>();
  stack.push(root);

  int count = 0;
  while (stack.empty() == false) {
    int node = stack.pop();
    if (visited[node] == false) {
      count++;
      visited[node] = true;
      for (int neighbor : graph.getNeighbors(node)) {
        if (visited[neighbor] == false) {
          stack.push(neighbor);
        }
      }
    }
  }
  if (count * 2 >= graph.numNodes()) {
    return markAndCountAncestors(root, visited, ignored, graph);
  } else {
    return markSuccessors(root, visited, ignored, graph);
  }
}

代码示例来源：origin: org.opendaylight.controller.thirdparty/net.sf.jung2

/**
 * Burt's measure of the effective size of a vertex's network.  Essentially, the
 * number of neighbors minus the average degree of those in <code>v</code>'s neighbor set,
 * not counting ties to <code>v</code>.  Formally: 
 * <pre>
 * effectiveSize(v) = v.degree() - (sum_{u in N(v)} sum_{w in N(u), w !=u,v} p(v,w)*m(u,w))
 * </pre>
 * where 
 * <ul>
 * <li/><code>N(a) = a.getNeighbors()</code>
 * <li/><code>p(v,w) =</code> normalized mutual edge weight of v and w
 * <li/><code>m(u,w)</code> = maximum-scaled mutual edge weight of u and w
 * </ul>
 * @see #normalizedMutualEdgeWeight(Object, Object)
 * @see #maxScaledMutualEdgeWeight(Object, Object) 
 */
public double effectiveSize(V v)
{
  double result = g.degree(v);
  for(V u : g.getNeighbors(v)) {
    for(V w : g.getNeighbors(u)) {
      if (w != v && w != u)
        result -= normalizedMutualEdgeWeight(v,w) * 
             maxScaledMutualEdgeWeight(u,w);
    }
  }
  return result;
}

代码示例来源：origin: org.opendaylight.controller.thirdparty/net.sf.jung2

for (V w : g.getNeighbors(v1)) {

代码示例来源：origin: net.sf.jung/jung-samples

public Stroke apply(V v)
    {
      if (highlight)
      {
        if (pi.isPicked(v))
          return heavy;
        else
        {
          for(V w : graph.getNeighbors(v)) {
//                    for (Iterator iter = graph.getNeighbors(v)v.getNeighbors().iterator(); iter.hasNext(); )
//                    {
//                        Vertex w = (Vertex)iter.next();
            if (pi.isPicked(w))
              return medium;
          }
          return light;
        }
      }
      else
        return light; 
    }

代码示例来源：origin: org.opendaylight.controller.thirdparty/net.sf.jung2

/**
 * The aggregate constraint on <code>v</code>.  Based on Burt's equation 2.7.  
 * Formally:
 * <pre>
 * aggregateConstraint(v) = sum_{w in N(v)} localConstraint(v,w) * O(w)
 * </pre>
 * where
 * <ul>
 * <li/><code>N(v) = v.getNeighbors()</code>
 * <li/><code>O(w) = organizationalMeasure(w)</code>
 * </ul>
 */
public double aggregateConstraint(V v)
{
  double result = 0;
  for (V w : g.getNeighbors(v)) {
    result += localConstraint(v, w) * organizationalMeasure(g, w);
  }
  return result;
}

代码示例来源：origin: geogebra/geogebra

/**
 * The aggregate constraint on <code>v</code>. Based on Burt's equation 2.7.
 * Formally:
 * 
 * <pre>
 * aggregateConstraint(v) = sum_{w in N(v)} localConstraint(v,w) * O(w)
 * </pre>
 * 
 * where
 * <ul>
 * <li/><code>N(v) = v.getNeighbors()</code>
 * <li/><code>O(w) = organizationalMeasure(w)</code>
 * </ul>
 */
public double aggregateConstraint(V v) {
  double result = 0;
  for (V w : g.getNeighbors(v)) {
    result += localConstraint(v, w) * organizationalMeasure(g, w);
  }
  return result;
}

代码示例来源：origin: net.sf.jung/jung-algorithms

/**
 * The aggregate constraint on <code>v</code>.  Based on Burt's equation 2.7.  
 * Formally:
 * <pre>
 * aggregateConstraint(v) = sum_{w in N(v)} localConstraint(v,w) * O(w)
 * </pre>
 * where
 * <ul>
 * <li><code>N(v) = v.getNeighbors()</code>
 * <li><code>O(w) = organizationalMeasure(w)</code>
 * </ul>
 * 
 * @param v the vertex whose properties are being measured
 * @return the aggregate constraint on v
 */
public double aggregateConstraint(V v)
{
  double result = 0;
  for (V w : g.getNeighbors(v)) {
    result += localConstraint(v, w) * organizationalMeasure(g, w);
  }
  return result;
}

代码示例来源：origin: org.opendaylight.controller.thirdparty/net.sf.jung2

/**
 * Returns the proportion of <code>v1</code>'s network time and energy invested
 * in the relationship with <code>v2</code>.  Formally:
 * <pre>
 * normalizedMutualEdgeWeight(a,b) = mutual_weight(a,b) / (sum_c mutual_weight(a,c))
 * </pre>
 * Returns 0 if either numerator or denominator = 0, or if <code>v1 == v2</code>.
 * @see #mutualWeight(Object, Object)
 */
protected double normalizedMutualEdgeWeight(V v1, V v2)
{
  if (v1 == v2)
    return 0;
  
  double numerator = mutualWeight(v1, v2);
  
  if (numerator == 0)
    return 0;
  
  double denominator = 0;
  for (V v : g.getNeighbors(v1)) {
    denominator += mutualWeight(v1, v);
  }
  if (denominator == 0)
    return 0;
  
  return numerator / denominator;
}

代码示例来源：origin: net.sf.jung/jung-algorithms

for (V v : g.getNeighbors(v1)) {
  denominator += mutualWeight(v1, v);

代码示例来源：origin: org.opendaylight.controller.thirdparty/net.sf.jung2

/**
 * Returns the local constraint on <code>v</code> from a lack of primary holes 
 * around its neighbor <code>v2</code>.
 * Based on Burt's equation 2.4.  Formally:
 * <pre>
 * localConstraint(v1, v2) = ( p(v1,v2) + ( sum_{w in N(v)} p(v1,w) * p(w, v2) ) )^2
 * </pre>
 * where 
 * <ul>
 * <li/><code>N(v) = v.getNeighbors()</code>
 * <li/><code>p(v,w) =</code> normalized mutual edge weight of v and w
 * </ul>
 * @see #normalizedMutualEdgeWeight(Object, Object)
 */
public double localConstraint(V v1, V v2) 
{
  double nmew_vw = normalizedMutualEdgeWeight(v1, v2);
  double inner_result = 0;
  for (V w : g.getNeighbors(v1)) {
    inner_result += normalizedMutualEdgeWeight(v1,w) * 
      normalizedMutualEdgeWeight(w,v2);
  }
  return (nmew_vw + inner_result) * (nmew_vw + inner_result);
}

代码示例来源：origin: geogebra/geogebra

/**
 * Returns the local constraint on <code>v</code> from a lack of primary
 * holes around its neighbor <code>v2</code>. Based on Burt's equation 2.4.
 * Formally:
 * 
 * <pre>
 * localConstraint(v1, v2) = ( p(v1,v2) + ( sum_{w in N(v)} p(v1,w) * p(w, v2) ) )^2
 * </pre>
 * 
 * where
 * <ul>
 * <li/><code>N(v) = v.getNeighbors()</code>
 * <li/><code>p(v,w) =</code> normalized mutual edge weight of v and w
 * </ul>
 * 
 * @see #normalizedMutualEdgeWeight(Object, Object)
 */
public double localConstraint(V v1, V v2) {
  double nmew_vw = normalizedMutualEdgeWeight(v1, v2);
  double inner_result = 0;
  for (V w : g.getNeighbors(v1)) {
    inner_result += normalizedMutualEdgeWeight(v1, w)
        * normalizedMutualEdgeWeight(w, v2);
  }
  return (nmew_vw + inner_result) * (nmew_vw + inner_result);
}

代码示例来源：origin: net.sf.jung/jung-algorithms

/**
 * Returns the local constraint on <code>v1</code> from a lack of primary holes 
 * around its neighbor <code>v2</code>.
 * Based on Burt's equation 2.4.  Formally:
 * <pre>
 * localConstraint(v1, v2) = ( p(v1,v2) + ( sum_{w in N(v)} p(v1,w) * p(w, v2) ) )^2
 * </pre>
 * where 
 * <ul>
 * <li><code>N(v) = v.getNeighbors()</code>
 * <li><code>p(v,w) =</code> normalized mutual edge weight of v and w
 * </ul>
 * @param v1 the first vertex whose local constraint is desired
 * @param v2 the second vertex whose local constraint is desired
 * @return the local constraint on (v1, v2)
 * @see #normalizedMutualEdgeWeight(Object, Object)
 */
public double localConstraint(V v1, V v2) 
{
  double nmew_vw = normalizedMutualEdgeWeight(v1, v2);
  double inner_result = 0;
  for (V w : g.getNeighbors(v1)) {
    inner_result += normalizedMutualEdgeWeight(v1,w) * 
      normalizedMutualEdgeWeight(w,v2);
  }
  return (nmew_vw + inner_result) * (nmew_vw + inner_result);
}