private List <NEATGene> geneList; //consultor gene list
/// <summary>
/// Creating consultor structure NEAT packet retrived from database and coefficient information from UI
/// </summary>
/// <param name="packet">NEATPacket retrieved from database</param>
/// <param name="deltaThreshold">Delta threshold to set</param>
/// <param name="disjointCoefficient">Disjoint coefficient to set</param>
/// <param name="excessCoefficient">Excess coefficient to set</param>
/// <param name="averageWeightDifferenceCoefficient">Averange weight difference coefficient to set</param>
public NEATConsultor(NEATPacket packet, float deltaThreshold, float disjointCoefficient, float excessCoefficient, float averageWeightDifferenceCoefficient)
{
this.numberOfInputs = packet.node_inputs; //get number of inputs from packet
this.numberOfOutputs = packet.node_outputs; //get number of outputs from packet
//copy thresholdes and coefficients
this.deltaThreshold = deltaThreshold;
this.disjointCoefficient = disjointCoefficient;
this.excessCoefficient = excessCoefficient;
this.averageWeightDifferenceCoefficient = averageWeightDifferenceCoefficient;
int informationSize = NEATGene.GENE_INFORMATION_SIZE; //get number of gene information size
float[] geneInformation = packet.consultor_genome.Split('_').Select(x => float.Parse(x)).ToArray(); //using Linq libary and delimiters, parse and spilt string genome from neat packet into float array
geneList = new List <NEATGene>();
for (int i = 0; i < geneInformation.Length; i += informationSize)
{
NEATGene gene = new NEATGene(innovationNumber, (int)geneInformation[i], (int)geneInformation[i + 1], 1f, true);
geneList.Add(gene);
innovationNumber++;
}
}
/// <summary>
/// Retrieves all neural networks with the given name in JSON markup form
/// </summary>
/// <param name="name">Name of the neural network to retrieve</param>
/// <returns>Returns web information on executed url</returns>
public IEnumerator GetNet(string name)
{
done = false; //set to fasle to wait for web to return
if (fileSaveMode == false)
{
string page = retrievePage; //retrieve page
page +=
"&creature_name=" + name; //create retrieve page url
web = new WWW(page); //run page
yield return(web); //wait for web to execute url
JsonParser(web.text); //parse given web text with JSON parser
done = true; //retrieved is true
}
else
{
if (File.Exists(name + ".txt"))
{
try
{
StreamReader reader = new StreamReader(name + ".txt");
retrieveNet = new NEATPacket[1];
string[] lines = reader.ReadToEnd().Split('\n');
float fitness = float.Parse(lines[0]);
int nodeTotal = int.Parse(lines[1]);
int nodeInputs = int.Parse(lines[2]);
int nodeOutputs = int.Parse(lines[3]);
int geneTotal = int.Parse(lines[4]);
int genomeTotal = int.Parse(lines[5]);
string genome = lines[6];
string consultorGenome = lines[7];
NEATPacket packet = new NEATPacket();
packet.creature_fitness = fitness;
packet.node_total = nodeTotal;
packet.node_inputs = nodeInputs;
packet.node_outputs = nodeOutputs;
packet.gene_total = geneTotal;
packet.genome_total = genomeTotal;
packet.genome = genome;
packet.consultor_genome = consultorGenome;
retrieveNet[0] = packet;
}
catch (Exception error)
{
retrieveNet = null;
}
}
else
{
retrieveNet = null;
}
done = true;
yield return(true);
}
}
