public List <GraphNode> GetNearestNeighbours(List <float[]> input)
{
// Assign each point in the input data to the nearest node in
// the graph. Return the list of the nearest node instances, and
// the list of distances.
List <GraphNode> nodes = new List <GraphNode>();
List <double> distances = new List <double>();
foreach (float[] pos in input)
{
NNResult nnresult = this.g.GetNearestNodes(pos);
nodes.Add(nnresult.nearestNeighbour0);
distances.Add(nnresult.distance0);
}
return(nodes);
}
public NNResult GetNearestNodes(float[] sample)
{
DataTable dt = GetDataTable();
double[,] results = NearestNeighbour.GetTwoNearestNeighbours(metric, numThreads, this.insertNodeCount, dt.NumDimensions, sample, dt.GetData());
int first_index = (int)results[0, 1];
int second_index = (int)results[1, 1];
NNResult nnresult = new NNResult();
nnresult.nearestNeighbour0 = (GraphNode)dt.GetDataObject(first_index);
nnresult.distance0 = results[0, 0];
nnresult.index0 = first_index;
nnresult.nearestNeightbour1 = (GraphNode)dt.GetDataObject(second_index);
nnresult.distance1 = results[1, 0];
nnresult.index1 = second_index;
return(nnresult);
}
public void train(List <float[]> input)
{
checkInput(input);
if (this.graph.GetNodeCount() == 0)
{
// if missing, generate two initial nodes at random
// assuming that the input data has zero mean and unit variance,
// choose the random position according to a gaussian distribution
// with zero mean and unit variance
//InitialiseGraph();
GraphNode g1 = graph.AddNode(input[0], tlen);
GraphNode g2 = graph.AddNode(input[1], tlen);
//graph.addEdge(g1, g2);
}
foreach (float[] sample in input)
{
this.tlen++;
// step 2 - find the nearest nodes
// dists are the squared distances of sample from the 2 nn
NNResult nnresult = this.graph.GetNearestNodes(sample);
GraphNode n0 = nnresult.nearestNeighbour0;
GraphNode n1 = nnresult.nearestNeightbour1;
// step 3 increase age of the emanating edges
foreach (GraphEdge e in n0.getEdges())
{
e.incAge();
}
double n0CumError = getCumError(n0);
if (this.metric == 1)
{
n0CumError += Math.Sqrt(nnresult.distance0); // do the sqrt here instead of the nn call
}
//n0CumError += nnresult.distance0; // Fritzke says add the SQUARED distance ......do the sqrt here instead of the nn call
else
{
n0CumError += Math.Abs(nnresult.distance0); // cosine
}
setCumError(n0, n0CumError);
// step 5 - move nearest node and neighbours
this.moveNode(n0, sample, this.eps_b);
List <GraphNode> neighbours = n0.getNeighbours();
foreach (GraphNode n in neighbours)
{
moveNode(n, sample, this.eps_n);
}
// step 6 update n0<->n1 edge
if (neighbours.Contains(n1))
{
// should only be one edge
List <GraphEdge> edges = n0.getEdges(n1);
edges[0].Age = 0;
}
else
{
"Adding edge {0} id0: {1} id1: {2} ".Cout(this.tlen, nnresult.index0, nnresult.index1);
this.graph.addEdge(n0, n1);
}
// step 7
this.removeOldEdges(n0.getEdges());
// step 8 - add a new node each lambda steps
if (this.tlen % this.lambda == 0 && graph.GetNodeCount() < this.max_nodes)
{
foreach (GraphNode zn in this.graph.getNodes())
{
float[] pos = this.graph.GetNodePosition(zn);
double cumError = zn.getCumError(tlen, this.d);
//Console.WriteLine("{4} [{0},{1},{2}] {3}", pos[0], pos[1], pos[2], cumError, tlen);
}
//if (tlen > 2000)
// Console.WriteLine("stop");
this.insertNewNode();
}
if (this.tlen % 10000 == 1)
{
Console.WriteLine("Number of Nodes: {0}, Number of edges: {1}", this.graph.GetNodeCount(), this.graph.GetEdgeCount());
}
// step 9 - no step 9
}
"tlen:{0} insert_node_count: {1} removed_node_count: {2}".Cout(this.tlen, this.graph.InsertNodeCount, this.graph.RemovedNodeCount);
Console.WriteLine("Number of Nodes: {0}, Number of edges: {1}", this.graph.GetNodeCount(), this.graph.GetEdgeCount());
}
