Пример #1
0
 private List<String> getNames(List<Node> nodes) {
   List<String> names = new ArrayList<String>();
   for (Node node : nodes) {
     names.add(node.getName());
   }
   return names;
 }
Пример #2
0
  public static Graph erdosRenyiGraph(int n, int e) {
    List<Node> nodes = new ArrayList<Node>();
    for (int i = 0; i < n; i++) nodes.add(new GraphNode("X" + i));

    Graph graph = new EdgeListGraph(nodes);

    for (int e0 = 0; e0 < e; e0++) {
      int i1 = RandomUtil.getInstance().nextInt(n);
      int i2 = RandomUtil.getInstance().nextInt(n);

      if (i1 == i2) {
        e0--;
        continue;
      }

      Edge edge = Edges.undirectedEdge(nodes.get(i1), nodes.get(i2));

      if (graph.containsEdge(edge)) {
        e0--;
        continue;
      }

      graph.addEdge(edge);
    }

    return graph;
  }
Пример #3
0
  private Graph structure(Graph mim) {
    List<Node> latents = new ArrayList<Node>();

    for (Node node : mim.getNodes()) {
      if (node.getNodeType() == NodeType.LATENT) {
        latents.add(node);
      }
    }

    return mim.subgraph(latents);
  }
Пример #4
0
  private boolean dConnected(Graph graph, String x, String y, String... z) {
    Node _x = graph.getNode(x);
    Node _y = graph.getNode(y);

    List<Node> _z = new ArrayList<Node>();

    for (String name : z) {
      _z.add(graph.getNode(name));
    }

    return graph.isDConnectedTo(_x, _y, _z);
  }
Пример #5
0
  public void testAlternativeGraphs() {

    //        UniformGraphGenerator gen = new UniformGraphGenerator(UniformGraphGenerator.ANY_DAG);
    //        gen.setNumNodes(100);
    //        gen.setMaxEdges(200);
    //        gen.setMaxDegree(30);
    //        gen.setMaxInDegree(30);
    //        gen.setMaxOutDegree(30);
    ////        gen.setNumIterations(3000000);
    //        gen.setResamplingDegree(10);
    //
    //        gen.generate();
    //
    //        Graph graph = gen.getDag();

    Graph graph = weightedRandomGraph(250, 400);

    List<Integer> degreeCounts = new ArrayList<Integer>();
    Map<Integer, Integer> degreeCount = new HashMap<Integer, Integer>();

    for (Node node : graph.getNodes()) {
      int degree = graph.getNumEdges(node);
      degreeCounts.add(degree);

      if (degreeCount.get(degree) == null) {
        degreeCount.put(degree, 0);
      }

      degreeCount.put(degree, degreeCount.get(degree) + 1);
    }

    Collections.sort(degreeCounts);
    System.out.println(degreeCounts);
    List<Integer> _degrees = new ArrayList<Integer>(degreeCount.keySet());
    Collections.sort(_degrees);

    for (int i : _degrees) {
      int j = degreeCount.get(i);
      //            System.out.println(i + " " + j);
      System.out.println(log(i + 1) + " " + log(j));
    }

    System.out.println("\nCPL = " + characteristicPathLength(graph));

    Graph erGraph = erdosRenyiGraph(200, 200);
    System.out.println("\n ER CPL = " + characteristicPathLength(erGraph));
  }
Пример #6
0
  public static Graph weightedRandomGraph(int n, int e) {
    List<Node> nodes = new ArrayList<Node>();
    for (int i = 0; i < n; i++) nodes.add(new GraphNode("X" + i));

    Graph graph = new EdgeListGraph(nodes);

    for (int e0 = 0; e0 < e; e0++) {
      int i1 = weightedRandom(nodes, graph);
      //            int i2 = RandomUtil.getInstance().nextInt(n);
      int i2 = weightedRandom(nodes, graph);

      if (!(shortestPath(nodes.get(i1), nodes.get(i2), graph) < 9)) {
        e0--;
        continue;
      }

      if (i1 == i2) {
        e0--;
        continue;
      }

      Edge edge = Edges.undirectedEdge(nodes.get(i1), nodes.get(i2));

      if (graph.containsEdge(edge)) {
        e0--;
        continue;
      }

      graph.addEdge(edge);
    }

    for (Edge edge : graph.getEdges()) {
      Node n1 = edge.getNode1();
      Node n2 = edge.getNode2();

      if (!graph.isAncestorOf(n2, n1)) {
        graph.removeEdge(edge);
        graph.addDirectedEdge(n1, n2);
      } else {
        graph.removeEdge(edge);
        graph.addDirectedEdge(n2, n1);
      }
    }

    return graph;
  }
Пример #7
0
  /** Tests to see if d separation facts are symmetric. */
  public void testDSeparation2() {
    EdgeListGraphSingleConnections graph =
        new EdgeListGraphSingleConnections(
            new Dag(GraphUtils.randomGraph(7, 0, 14, 30, 15, 15, true)));

    List<Node> nodes = graph.getNodes();

    int depth = -1;

    for (int i = 0; i < nodes.size(); i++) {
      for (int j = i; j < nodes.size(); j++) {
        Node x = nodes.get(i);
        Node y = nodes.get(j);

        List<Node> theRest = new ArrayList<Node>(nodes);
        //                theRest.remove(x);
        //                theRest.remove(y);

        DepthChoiceGenerator gen = new DepthChoiceGenerator(theRest.size(), depth);
        int[] choice;

        while ((choice = gen.next()) != null) {
          List<Node> z = new LinkedList<Node>();

          for (int k = 0; k < choice.length; k++) {
            z.add(theRest.get(choice[k]));
          }

          boolean dConnectedTo = graph.isDConnectedTo(x, y, z);
          boolean dConnectedTo1 = graph.isDConnectedTo(y, x, z);

          if (dConnectedTo != dConnectedTo1) {
            System.out.println(x + " d connected to " + y + " given " + z);
            System.out.println(graph);
            System.out.println("dconnectedto = " + dConnectedTo);
            System.out.println("dconnecteto1 = " + dConnectedTo1);
            fail();
          }
        }
      }
    }
  }
Пример #8
0
  /** Get all nodes that are connected to Y by an undirected edge and not adjacent to X. */
  private static List<Node> getTNeighbors(Node x, Node y, Graph graph) {
    List<Edge> yEdges = graph.getEdges(y);
    List<Node> tNeighbors = new ArrayList<Node>();

    for (Edge edge : yEdges) {
      if (!Edges.isUndirectedEdge(edge)) {
        continue;
      }

      Node z = edge.getDistalNode(y);

      if (graph.isAdjacentTo(z, x)) {
        continue;
      }

      tNeighbors.add(z);
    }

    return tNeighbors;
  }
Пример #9
0
  /**
   * Find all nodes that are connected to Y by an undirected edge that are adjacent to X (that is,
   * by undirected or directed edge).
   */
  private static List<Node> getNaYX(Node x, Node y, Graph graph) {
    List<Edge> yEdges = graph.getEdges(y);
    List<Node> nayx = new ArrayList<Node>();

    for (Edge edge : yEdges) {
      if (!Edges.isUndirectedEdge(edge)) {
        continue;
      }

      Node z = edge.getDistalNode(y);

      if (!graph.isAdjacentTo(z, x)) {
        continue;
      }

      nayx.add(z);
    }

    return nayx;
  }
Пример #10
0
  /** Tests to see if d separation facts are symmetric. */
  public void testDSeparation() {
    EdgeListGraphSingleConnections graph =
        new EdgeListGraphSingleConnections(
            new Dag(GraphUtils.randomGraph(7, 0, 7, 30, 15, 15, true)));
    System.out.println(graph);

    List<Node> nodes = graph.getNodes();

    int depth = -1;

    for (int i = 0; i < nodes.size(); i++) {
      for (int j = i + 1; j < nodes.size(); j++) {
        Node x = nodes.get(i);
        Node y = nodes.get(j);

        List<Node> theRest = new ArrayList<Node>(nodes);
        theRest.remove(x);
        theRest.remove(y);

        DepthChoiceGenerator gen = new DepthChoiceGenerator(theRest.size(), depth);
        int[] choice;

        while ((choice = gen.next()) != null) {
          List<Node> z = new LinkedList<Node>();

          for (int k = 0; k < choice.length; k++) {
            z.add(theRest.get(choice[k]));
          }

          if (graph.isDSeparatedFrom(x, y, z) != graph.isDSeparatedFrom(y, x, z)) {
            fail(
                SearchLogUtils.independenceFact(x, y, z)
                    + " should have same d-sep result as "
                    + SearchLogUtils.independenceFact(y, x, z));
          }
        }
      }
    }
  }
Пример #11
0
  public void rtest3() {
    Node x = new GraphNode("X");
    Node y = new GraphNode("Y");
    Node z = new GraphNode("Z");
    Node w = new GraphNode("W");

    List<Node> nodes = new ArrayList<Node>();
    nodes.add(x);
    nodes.add(y);
    nodes.add(z);
    nodes.add(w);

    Graph g = new EdgeListGraph(nodes);
    g.addDirectedEdge(x, y);
    g.addDirectedEdge(x, z);
    g.addDirectedEdge(y, w);
    g.addDirectedEdge(z, w);

    Graph maxGraph = null;
    double maxPValue = -1.0;
    ICovarianceMatrix maxLatentCov = null;

    Graph mim = DataGraphUtils.randomMim(g, 8, 0, 0, 0, true);
    //        Graph mim = DataGraphUtils.randomSingleFactorModel(5, 5, 8, 0, 0, 0);
    Graph mimStructure = structure(mim);
    SemPm pm = new SemPm(mim);

    System.out.println("\n\nTrue graph:");
    System.out.println(mimStructure);

    SemImInitializationParams params = new SemImInitializationParams();
    params.setCoefRange(0.5, 1.5);

    SemIm im = new SemIm(pm, params);

    int N = 1000;

    DataSet data = im.simulateData(N, false);

    CovarianceMatrix cov = new CovarianceMatrix(data);

    for (int i = 0; i < 1; i++) {

      ICovarianceMatrix _cov = DataUtils.reorderColumns(cov);
      List<List<Node>> partition;

      FindOneFactorClusters fofc = new FindOneFactorClusters(_cov, TestType.TETRAD_WISHART, .001);
      fofc.search();
      partition = fofc.getClusters();
      System.out.println(partition);

      List<String> latentVarList = reidentifyVariables(mim, data, partition, 2);

      Mimbuild2 mimbuild = new Mimbuild2();

      mimbuild.setAlpha(0.001);
      //            mimbuild.setMinimumSize(5);

      // To test knowledge.
      //            Knowledge knowledge = new Knowledge2();
      //            knowledge.setEdgeForbidden("L.Y", "L.W", true);
      //            knowledge.setEdgeRequired("L.Y", "L.Z", true);
      //            mimbuild.setKnowledge(knowledge);

      Graph mimbuildStructure = mimbuild.search(partition, latentVarList, _cov);

      double pValue = mimbuild.getpValue();
      System.out.println(mimbuildStructure);
      System.out.println("P = " + pValue);
      System.out.println("Latent Cov = " + mimbuild.getLatentsCov());

      if (pValue > maxPValue) {
        maxPValue = pValue;
        maxGraph = new EdgeListGraph(mimbuildStructure);
        maxLatentCov = mimbuild.getLatentsCov();
      }
    }

    System.out.println("\n\nTrue graph:");
    System.out.println(mimStructure);
    System.out.println("\nBest graph:");
    System.out.println(maxGraph);
    System.out.println("P = " + maxPValue);
    System.out.println("Latent Cov = " + maxLatentCov);
    System.out.println();
  }