/// <summary>
/// Create an array of FastConnection(s) representing the connectivity of the provided INetworkDefinition.
/// </summary>
private static FastConnection[] CreateFastConnectionArray(INetworkDefinition networkDef)
{
// We vary the decode logic depending on the size of the genome. The most CPU intensive aspect of
// decoding is the conversion of the neuron IDs at connection endpoints into neuron indexes. For small
// genomes we simply use the BinarySearch() method on NeuronGeneList for each lookup; Each lookup is
// an operation with O(log n) time complexity. Thus for C connections and N neurons the number of operations
// to perform all lookups is approximately = 2*C*Log(N)
//
// For larger genomes we invest time in building a Dictionary that maps neuron IDs to their indexes, this on the
// basis that the time invested will be more than recovered in time saved performing lookups; The time complexity
// of a dictionary lookup is near constant O(1). Thus number of operations is approximately = O(2*C*1) + the time
// required to build the dictionary which is approximately O(N).
//
// Therefore the choice of lookup type is based on which of these two expressions gives the lowest value.
//
// Binary search. LookupOps = 2 * C * Log2(N) * x
// Dictionary Search. LookupOps = (N * y) + (2 * C * z)
//
// Where x, y and z are constants that adjust for the relative speeds of the lookup and dictionary building operations.
// Note that the actual time required to perform these separate algorithms is actually a far more complex problem, and
// for modern CPUs exact times cannot be calculated because of large memory caches and superscalar architecture that
// makes execution times in a real environment effectively non-deterministic. Thus these calculations are a rough
// guide/heuristic that estimate which algorithm will perform best. The constants can be found experimentally but will
// tend to vary depending on factors such as CPU and memory architecture, .Net framework version and what other tasks the
// CPU is currently doing which may affect our utilisation of memory caches.
// TODO: Experimentally determine reasonably good values for constants x,y and z in some common real world runtime platform.
IConnectionList connectionList = networkDef.ConnectionList;
INodeList nodeList = networkDef.NodeList;
int connectionCount = connectionList.Count;
int nodeCount = nodeList.Count;
FastConnection[] fastConnectionArray = new FastConnection[connectionCount];
if ((2.0 * connectionCount * Math.Log(nodeCount, 2.0)) < ((2.0 * connectionCount) + nodeCount))
{
// Binary search requires items to be sorted.
Debug.Assert(nodeList.IsSorted());
// Loop the connections and lookup the neuron IDs for each connection's end points using a binary search
// on nGeneList. This is probably the quickest approach for small numbers of lookups.
for (int i = 0; i < connectionCount; i++)
{
INetworkConnection conn = connectionList[i];
fastConnectionArray[i]._srcNeuronIdx = nodeList.BinarySearch(conn.SourceNodeId);
fastConnectionArray[i]._tgtNeuronIdx = nodeList.BinarySearch(conn.TargetNodeId);
fastConnectionArray[i]._weight = conn.Weight;
// Check that the correct neuron indexes were found.
Debug.Assert(
nodeList[fastConnectionArray[i]._srcNeuronIdx].Id == conn.SourceNodeId &&
nodeList[fastConnectionArray[i]._tgtNeuronIdx].Id == conn.TargetNodeId);
}
}
else
{
// Build dictionary of neuron indexes keyed on neuron innovation ID.
Dictionary <uint, int> neuronIndexDictionary = new Dictionary <uint, int>(nodeCount);
for (int i = 0; i < nodeCount; i++)
{
// ENHANCEMENT: Check if neuron innovation ID requires further manipulation to make a good hash code.
neuronIndexDictionary.Add(nodeList[i].Id, i);
}
// Loop the connections and lookup the neuron IDs for each connection's end points using neuronIndexDictionary.
// This is probably the quickest approach for large numbers of lookups.
for (int i = 0; i < connectionCount; i++)
{
INetworkConnection conn = connectionList[i];
fastConnectionArray[i]._srcNeuronIdx = neuronIndexDictionary[conn.SourceNodeId];
fastConnectionArray[i]._tgtNeuronIdx = neuronIndexDictionary[conn.TargetNodeId];
fastConnectionArray[i]._weight = conn.Weight;
// Check that the correct neuron indexes were found.
Debug.Assert(
nodeList[fastConnectionArray[i]._srcNeuronIdx].Id == conn.SourceNodeId &&
nodeList[fastConnectionArray[i]._tgtNeuronIdx].Id == conn.TargetNodeId);
}
}
return(fastConnectionArray);
}
