Accord.Tests.MachineLearning.KDTreeTest.TraverseTest1 C# (CSharp) Method

        public void TraverseTest1()
        {
            double[][] points =
            {
                new double[] { 2, 3 },
                new double[] { 5, 4 },
                new double[] { 9, 6 },
                new double[] { 4, 7 },
                new double[] { 8, 1 },
                new double[] { 7, 2 },
            };


            // To create a tree from a set of points, we use
            KDTree<int> tree = KDTree.FromData<int>(points);

            double[][] breadth =
            {
                new double[] { 7, 2 },
                new double[] { 5, 4 },
                new double[] { 9, 6 },
                new double[] { 2, 3 },
                new double[] { 4, 7 },
                new double[] { 8, 1 },
            };

            double[][] inOrder =
            {
                new double[] { 2, 3 },
                new double[] { 5, 4 },
                new double[] { 4, 7 },
                new double[] { 7, 2 },
                new double[] { 8, 1 },
                new double[] { 9, 6 },
            };

            double[][] postOrder =
            {
                new double[] { 2, 3 },
                new double[] { 4, 7 },
                new double[] { 5, 4 },
                new double[] { 8, 1 },
                new double[] { 9, 6 },
                new double[] { 7, 2 },
            };

            double[][] preOrder =
            {
                new double[] { 7, 2 },
                new double[] { 5, 4 },
                new double[] { 2, 3 },
                new double[] { 4, 7 },
                new double[] { 9, 6 },
                new double[] { 8, 1 },
            };


            AreEqual(tree, breadth, TreeTraversal.BreadthFirst);
            AreEqual(tree, preOrder, TreeTraversal.PreOrder);
            AreEqual(tree, inOrder, TreeTraversal.InOrder);
            AreEqual(tree, postOrder, TreeTraversal.PostOrder);
        }