Examples with Graph org.gephi.graph.api.Graph used on opensource projects

Example 16 with Graph

use of org.gephi.graph.api.Graph in project gephi by gephi.

the class DynamicClusteringCoefficient method loop.

@Override
public void loop(GraphView window, Interval interval) {
    Graph graph;
    if (isDirected) {
        graph = graphModel.getDirectedGraph(window);
    } else {
        graph = graphModel.getUndirectedGraph(window);
    }
    TimeRepresentation tr = graphModel.getConfiguration().getTimeRepresentation();
    graph.readLock();
    try {
        clusteringCoefficientStat = new ClusteringCoefficient();
        clusteringCoefficientStat.setDirected(isDirected);
        clusteringCoefficientStat.triangles(graph);
        //Columns
        if (!averageOnly) {
            double[] coefficients = clusteringCoefficientStat.getCoefficientReuslts();
            int i = 0;
            for (Node n : graph.getNodes()) {
                double coef = coefficients[i++];
                switch(tr) {
                    case INTERVAL:
                        n.setAttribute(dynamicCoefficientColumn, coef, new Interval(interval.getLow(), interval.getLow() + tick));
                        break;
                    case TIMESTAMP:
                        n.setAttribute(dynamicCoefficientColumn, coef, interval.getLow());
                        n.setAttribute(dynamicCoefficientColumn, coef, interval.getHigh());
                        break;
                }
                if (cancel) {
                    break;
                }
            }
        }
    } finally {
        graph.readUnlockAll();
    }
    //Average
    double avg = clusteringCoefficientStat.getAverageClusteringCoefficient();
    graphModel.getGraphVisible().setAttribute(DYNAMIC_AVG_CLUSTERING_COEFFICIENT, avg, interval.getLow());
    graphModel.getGraphVisible().setAttribute(DYNAMIC_AVG_CLUSTERING_COEFFICIENT, avg, interval.getHigh());
    averages.put(interval.getLow(), avg);
    averages.put(interval.getHigh(), avg);
}

Example 17 with Graph

use of org.gephi.graph.api.Graph in project gephi by gephi.

the class DynamicDegree method loop.

@Override
public void loop(GraphView window, Interval interval) {
    Graph graph = graphModel.getGraph(window);
    DirectedGraph directedGraph = null;
    if (isDirected) {
        directedGraph = graphModel.getDirectedGraph(window);
    }
    TimeRepresentation tr = graphModel.getConfiguration().getTimeRepresentation();
    long sum = 0;
    for (Node n : graph.getNodes().toArray()) {
        int degree = graph.getDegree(n);
        if (!averageOnly) {
            switch(tr) {
                case INTERVAL:
                    n.setAttribute(dynamicDegreeColumn, degree, new Interval(interval.getLow(), interval.getLow() + tick));
                    break;
                case TIMESTAMP:
                    n.setAttribute(dynamicDegreeColumn, degree, interval.getLow());
                    n.setAttribute(dynamicDegreeColumn, degree, interval.getHigh());
                    break;
            }
            if (isDirected) {
                int indegree = directedGraph.getInDegree(n);
                int outdegree = directedGraph.getOutDegree(n);
                switch(tr) {
                    case INTERVAL:
                        n.setAttribute(dynamicInDegreeColumn, indegree, new Interval(interval.getLow(), interval.getLow() + tick));
                        n.setAttribute(dynamicOutDegreeColumn, outdegree, new Interval(interval.getLow(), interval.getLow() + tick));
                        break;
                    case TIMESTAMP:
                        n.setAttribute(dynamicInDegreeColumn, indegree, interval.getLow());
                        n.setAttribute(dynamicInDegreeColumn, indegree, interval.getHigh());
                        n.setAttribute(dynamicOutDegreeColumn, outdegree, interval.getLow());
                        n.setAttribute(dynamicOutDegreeColumn, outdegree, interval.getHigh());
                        break;
                }
            }
        }
        sum += degree;
        if (cancel) {
            break;
        }
    }
    double avg = sum / (double) graph.getNodeCount();
    averages.put(interval.getLow(), avg);
    averages.put(interval.getHigh(), avg);
    graphModel.getGraphVisible().setAttribute(DYNAMIC_AVGDEGREE, avg, interval.getLow());
    graphModel.getGraphVisible().setAttribute(DYNAMIC_AVGDEGREE, avg, interval.getHigh());
}

Example 18 with Graph

use of org.gephi.graph.api.Graph in project gephi by gephi.

the class DynamicNbNodes method loop.

@Override
public void loop(GraphView window, Interval interval) {
    Graph graph = graphModel.getGraph(window);
    int count = graph.getNodeCount();
    graphModel.getGraphVisible().setAttribute(NB_NODES, count, interval.getLow());
    graphModel.getGraphVisible().setAttribute(NB_NODES, count, interval.getHigh());
    counts.put(interval.getLow(), count);
    counts.put(interval.getHigh(), count);
}

Example 19 with Graph

use of org.gephi.graph.api.Graph in project gephi by gephi.

the class ClusteringCoefficientNGTest method testOneNodeClusteringCoefficient.

@Test
public void testOneNodeClusteringCoefficient() {
    GraphModel graphModel = GraphGenerator.generateCompleteUndirectedGraph(1);
    Graph graph = graphModel.getGraph();
    ClusteringCoefficient cc = new ClusteringCoefficient();
    cc.setDirected(false);
    ArrayWrapper[] network = new ArrayWrapper[1];
    int[] triangles = new int[1];
    double[] nodeClustering = new double[1];
    HashMap<String, Double> results = cc.computeClusteringCoefficient(graph, network, triangles, nodeClustering, false);
    double avClusteringCoefficient = results.get("clusteringCoefficient");
    assertEquals(avClusteringCoefficient, Double.NaN);
}

Example 20 with Graph

use of org.gephi.graph.api.Graph in project gephi by gephi.

the class ClusteringCoefficientNGTest method testTwoConectedNodesClusteringCoefficient.

@Test
public void testTwoConectedNodesClusteringCoefficient() {
    GraphModel graphModel = GraphGenerator.generateCompleteUndirectedGraph(2);
    Graph graph = graphModel.getGraph();
    ClusteringCoefficient cc = new ClusteringCoefficient();
    ArrayWrapper[] network = new ArrayWrapper[2];
    int[] triangles = new int[2];
    double[] nodeClustering = new double[2];
    HashMap<String, Double> results = cc.computeClusteringCoefficient(graph, network, triangles, nodeClustering, false);
    double avClusteringCoefficient = results.get("clusteringCoefficient");
    assertEquals(avClusteringCoefficient, Double.NaN);
}