TemporalNetworksTest.ExampleData.GetTestNetwork C# (CSharp) Method

        public static TemporalNetwork GetTestNetwork()
        {
            TemporalNetwork temporal_net = new TemporalNetwork();

            // Add edges according to two paths
            temporal_net.AddTemporalEdge(1, "c", "e");
            temporal_net.AddTemporalEdge(2, "e", "f");

            temporal_net.AddTemporalEdge(3, "a", "e");
            temporal_net.AddTemporalEdge(4, "e", "g");

            temporal_net.AddTemporalEdge(5, "c", "e");
            temporal_net.AddTemporalEdge(6, "e", "f");

            temporal_net.AddTemporalEdge(7, "a", "e");
            temporal_net.AddTemporalEdge(8, "e", "g");

            temporal_net.AddTemporalEdge(9, "c", "e");
            temporal_net.AddTemporalEdge(10, "e", "f");
            // Note that the next added edge additionally continues a two-path e -> f -> e
            temporal_net.AddTemporalEdge(11, "f", "e");
            temporal_net.AddTemporalEdge(12, "e", "b");

            // An additional edge that should be filtered during preprocessing ...
            temporal_net.AddTemporalEdge(13, "e", "b");

            // And one case where we have multiple edges in a single time step
            temporal_net.AddTemporalEdge(14, "g", "e");
            temporal_net.AddTemporalEdge(14, "c", "e");
            temporal_net.AddTemporalEdge(15, "e", "f");

            temporal_net.AddTemporalEdge(16, "b", "e");
            temporal_net.AddTemporalEdge(17, "e", "g");

            temporal_net.AddTemporalEdge(18, "c", "e");
            temporal_net.AddTemporalEdge(19, "e", "f");

            temporal_net.AddTemporalEdge(20, "c", "e");
            temporal_net.AddTemporalEdge(21, "e", "f");

            return temporal_net;
        }

        public void GetUncorrelatedBetweennessPrefMatrixTest()
        {
            TemporalNetwork          temp_net   = ExampleData.GetTestNetwork();
            Dictionary <string, int> index_pred = null;
            Dictionary <string, int> index_succ = null;

            double[,] actual = null;
            actual           = BetweennessPref.GetUncorrelatedBetweennessPrefMatrix(temp_net, "e", out index_pred, out index_succ);

            Assert.IsNotNull(index_pred);
            Assert.IsNotNull(index_succ);
            Assert.IsNotNull(actual);

            // Check whether all entries in the normalized betweenness preference matrix returned match the expected values
            Assert.AreEqual(actual[index_pred["a"], index_succ["b"]], (2d / 11d) * (1d / 10d));
            Assert.AreEqual(actual[index_pred["b"], index_succ["b"]], (1d / 11d) * (1d / 10d));
            Assert.AreEqual(actual[index_pred["c"], index_succ["b"]], (6d / 11d) * (1d / 10d));
            Assert.AreEqual(actual[index_pred["f"], index_succ["b"]], (1d / 11d) * (1d / 10d));
            Assert.AreEqual(actual[index_pred["g"], index_succ["b"]], (1d / 11d) * (1d / 10d));

            Assert.AreEqual(actual[index_pred["a"], index_succ["f"]], (2d / 11d) * (6d / 10d));
            Assert.AreEqual(actual[index_pred["b"], index_succ["f"]], (1d / 11d) * (6d / 10d));
            Assert.AreEqual(actual[index_pred["c"], index_succ["f"]], (6d / 11d) * (6d / 10d));
            Assert.AreEqual(actual[index_pred["f"], index_succ["f"]], (1d / 11d) * (6d / 10d));
            Assert.AreEqual(actual[index_pred["g"], index_succ["f"]], (1d / 11d) * (6d / 10d));

            Assert.AreEqual(actual[index_pred["a"], index_succ["g"]], (2d / 11d) * (3d / 10d));
            Assert.AreEqual(actual[index_pred["b"], index_succ["g"]], (1d / 11d) * (3d / 10d));
            Assert.AreEqual(actual[index_pred["c"], index_succ["g"]], (6d / 11d) * (3d / 10d));
            Assert.AreEqual(actual[index_pred["f"], index_succ["g"]], (1d / 11d) * (3d / 10d));
            Assert.AreEqual(actual[index_pred["g"], index_succ["g"]], (1d / 11d) * (3d / 10d));
        }