@ScheduledMethod(start = 1, interval = 1)
 public void endRun() {
   ISchedule schedule = RunState.getInstance().getScheduleRegistry().getModelSchedule();
   double tickCount = schedule.getTickCount();
   if (tickCount >= endAt) {
     schedule.executeEndActions();
     RunEnvironment.getInstance().endRun();
   }
   RunInfo runInfo = RunState.getInstance().getRunInfo();
   if (runInfo.getRunNumber() > runCount) {}
 }
/** @author ersantasan */
@SuppressWarnings({"unused", "unchecked", "rawtypes"})
public class User {
  private ContinuousSpace<Object> space;
  private Grid<Object> grid;
  private boolean isActiveUser; // true if User is a Zealot, false if Good Samaritan
  private boolean hasGeneralInterest; /*true if User follows Administrator career
										 false if he follows Project Leader career*/
  private Article articleToEdit;
  private static List<Article> goodArticles = new ArrayList<Article>();
  private DijkstraDistance<User, RepastEdge<Object>> dijkDistAlg;

  double averageConnectionsOfNetwork = 0;
  private boolean isDone = false; // for good samaritans to stop after first iteration
  private Random randGen = new Random();
  private static double exclusionNumber = -98765432.1;
  private static int NonAggrSamplingQueficient = 50;

  // parameters
  Parameters params = RunEnvironment.getInstance().getParameters();
  final int neighbourDimensions = (Integer) params.getValue("neighbourhood_dimensions");
  final double goodArticleMultiplier = (Double) params.getValue("good_article_multiplier");
  final int goodArticleConnectionCount = (Integer) params.getValue("good_article_connection_count");
  final int endAt = (Integer) params.getValue("run_length"); // Run length parameter for batch mode
  final int runCount =
      (Integer)
          params.getValue("run_count"); // Run count of whole simulation parameter for batch mode

  public User(
      ContinuousSpace<Object> space,
      Grid<Object> grid,
      boolean isActiveUser,
      boolean hasGeneralInterest) {
    this.space = space;
    this.grid = grid;
    this.hasGeneralInterest = hasGeneralInterest;
    this.isActiveUser = isActiveUser;

    User.goodArticles.clear();
  }

  @ScheduledMethod(start = 1, interval = 1)
  public void step() {

    // create colNetwork in hosting context
    Context<Object> context = ContextUtils.getContext(this);
    Network<Object> colNet = (Network<Object>) context.getProjection("collaboration_network");
    Network<Object> userNet = (Network<Object>) context.getProjection("user_network");
    Network<Object> articleNet = (Network<Object>) context.getProjection("article_network");

    if (!isDone) {
      /*
       * Neighbourhood Connection Algorithm
       */
      // get the grid location of this User
      GridPoint pt = grid.getLocation(this);

      // use the GridCellNgh class to create GridCells for
      // the surrounding neighbourhood
      if (pt != null) { // TODO Why NULL?
        GridCellNgh<Article> nghCreator =
            new GridCellNgh<Article>(
                grid, pt, Article.class, neighbourDimensions, neighbourDimensions);
        List<GridCell<Article>> gridCells = nghCreator.getNeighborhood(false);
        SimUtilities.shuffle(gridCells, RandomHelper.getUniform());

        // if an agent exist in the surrounding environment, add an edge with it.
        for (GridCell<Article> cell : gridCells) {
          if (cell.size() > 0) {
            List<Article> cellUsers = new ArrayList<Article>((Collection<Article>) cell.items());
            articleToEdit = cellUsers.get((RandomHelper.nextIntFromTo(0, cellUsers.size() - 1)));
            if (context != null && colNet != null && cellUsers != null && articleToEdit != null) {
              if (!isActiveUser) { // Good Samaritan - one and only one connection
                if (colNet.getDegree(articleToEdit) <= 0 // if neighbour is unconnected
                    && colNet.getDegree(this) <= 0) { // if our agent is unconnected)
                  colNet.addEdge(this, articleToEdit);
                  this.isDone =
                      true; // this good samaritan is no longer counted in operating agents
                }
              } else if (!hasGeneralInterest) { // Project Leader zealot (active user),
                colNet.addEdge(this, articleToEdit); // connects neighbours in every step

                for (Object coopUser : colNet.getAdjacent(articleToEdit)) {
                  if (coopUser != null && !userNet.containsEdge(userNet.getEdge(this, coopUser))) {
                    userNet.addEdge(this, coopUser);
                  }
                }
                for (Object relatedArticle : colNet.getAdjacent(this)) {
                  if (relatedArticle != null
                      && !articleNet.containsEdge(userNet.getEdge(articleToEdit, relatedArticle))) {
                    articleNet.addEdge(articleToEdit, relatedArticle);
                  }
                }
              }

              // For active agent connection algorithm we need to update good article array if found
              if (colNet.getDegree(articleToEdit)
                      > (goodArticleMultiplier * colNet.getDegree() / colNet.size())
                  && colNet.getDegree(articleToEdit) > goodArticleConnectionCount
                  && !articleToEdit.isGood) {
                articleToEdit.isGood = true;
                goodArticles.add(articleToEdit);
              }
            }
            break;
          }
        }
      }

      /*
       * Active Agent Connection Algorithm
       */
      if (isActiveUser
          && hasGeneralInterest
          && goodArticles.size() > 0) { // if in administrator career path
        articleToEdit = goodArticles.get(RandomHelper.nextIntFromTo(0, goodArticles.size() - 1));
        colNet.addEdge(this, articleToEdit); // TODO reduce goodArticles by one?

        for (Object coopUser : colNet.getAdjacent(articleToEdit)) {
          if (coopUser != null && !userNet.containsEdge(userNet.getEdge(this, coopUser))) {
            userNet.addEdge(this, coopUser);
          }
        }
        for (Object relatedArticle : colNet.getAdjacent(this)) {
          if (relatedArticle != null
              && !articleNet.containsEdge(userNet.getEdge(articleToEdit, relatedArticle))) {
            articleNet.addEdge(articleToEdit, relatedArticle);
          }
        }
        goodArticles.remove(0);
      }

      this.endRun();
    }
  }

  public int getAffiliationEdgeCountOfUser() {
    Context<Object> context = ContextUtils.getContext(this);
    Network<Object> colNet = (Network<Object>) context.getProjection("collaboration_network");
    return colNet.getDegree(this);
  }

  public int getUserEdgeCount() {
    Context<Object> context = ContextUtils.getContext(this);
    Network<Object> colNet = (Network<Object>) context.getProjection("user_network");
    return colNet.getDegree(this);
  }

  public double getUserNeighbourAverageEdgeCount() {
    int tempInt = 0;
    double sumOfNeigbourDegrees = 0.0;
    Context<Object> context = ContextUtils.getContext(this);
    Network<Object> colNet = (Network<Object>) context.getProjection("user_network");
    for (Object neighbourObject : colNet.getSuccessors(this)) {
      if (neighbourObject instanceof User) {
        sumOfNeigbourDegrees += colNet.getDegree(neighbourObject);
        tempInt++;
      }
    }
    double averageNeighbourDegree = 0.0;
    if (tempInt != 0) {
      averageNeighbourDegree = sumOfNeigbourDegrees / tempInt;
    }
    return averageNeighbourDegree;
  }

  public double getClusteringCoefficientOfUser() {
    if (this.hashCode() % NonAggrSamplingQueficient
        == 9) { // only calculate clustering coefficient for 1/20 of the agents
      Context<Object> context = ContextUtils.getContext(this);
      ContextJungNetwork jungNet = (ContextJungNetwork) context.getProjection("user_network");
      Map<Object, Double> clusterCoeffMap =
          repast.simphony.jung.statistics.RepastJungGraphStatistics.clusteringCoefficients(
              jungNet.getGraph());
      return clusterCoeffMap.get(this);
    } else {
      return exclusionNumber;
    }
  }

  public double getPathlengthOfUser() {
    if (this.hashCode() % NonAggrSamplingQueficient
        == 9) { // only calculate clustering coefficient for 1/20 of the agents
      List<User> userList = new ArrayList<User>();
      Context<Object> context = ContextUtils.getContext(this);
      Network<Object> colNet = (Network<Object>) context.getProjection("user_network");
      ContextJungNetwork jungNet = (ContextJungNetwork) context.getProjection("user_network");
      for (Object tempNode : colNet.getNodes()) {
        if (tempNode instanceof User) {
          userList.add((User) tempNode);
        }
      }
      dijkDistAlg = new DijkstraDistance<User, RepastEdge<Object>>(jungNet.getGraph());
      Number dist = dijkDistAlg.getDistance(this, userList.get(randGen.nextInt(userList.size())));
      if (dist != null) {
        return dist.doubleValue();
      } else {
        return exclusionNumber;
      }
    } else {
      return exclusionNumber;
    }
  }

  @ScheduledMethod(start = 1, interval = 1)
  public void endRun() {
    ISchedule schedule = RunState.getInstance().getScheduleRegistry().getModelSchedule();
    double tickCount = schedule.getTickCount();
    if (tickCount >= endAt) {
      schedule.executeEndActions();
      RunEnvironment.getInstance().endRun();
    }
    RunInfo runInfo = RunState.getInstance().getRunInfo();
    if (runInfo.getRunNumber() > runCount) {}
  }
}
示例#3
0
 public double getTime() {
   double time = (RunEnvironment.getInstance().getCurrentSchedule().getTickCount());
   return time;
 }
示例#4
0
 public static double getMinute() {
   double tick = (RunEnvironment.getInstance().getCurrentSchedule().getTickCount());
   minute = (tick % 60);
   return minute;
 }