public NetCacheEntry(string name, string tag, double fitness, NeuralNet.Net net)
{
this.name = name;
this.tag = tag;
this.fitness = fitness;
this.net = net;
}
public void exportNeuralNet(Net n, string filePath)
{
var lines = new List<string>();
lines.Add(n.numInput.ToString() + ' ' + n.numHidden.ToString() + ' ' + n.numOutput.ToString());
foreach (var lw in n.inpToHiddenWeight)
{
string line = "";
foreach (var weight in lw)
{
line = line + String.Format("{0:#,0.000}", weight) + ' ';
}
lines.Add(line.TrimEnd(' '));
}
foreach (var lw in n.hidToOutputWeight)
{
string line = "";
foreach (var weight in lw)
{
line = line + String.Format("{0:#,0.000}", weight) + ' ';
}
lines.Add(line.TrimEnd(' '));
}
System.IO.File.WriteAllLines(filePath, lines);
}
public Net loadNeuralNet(string filePath)
{
try
{
using (StreamReader sr = new StreamReader(filePath))
{
String line = sr.ReadToEnd();
var words = line.Split('\n');
var nums = words.First().Split(' ').Select(Int32.Parse).ToList();
var neuralNet = new Net(nums[0], nums[1], nums[2]);
for (int i = 1; i < 1 + nums[1]; i++)
{
var weights = words[i].Split(' ').Select(Double.Parse).ToList();
neuralNet.inpToHiddenWeight.Add(weights);
}
for (int i = nums[1] + 1; i < 1 + nums[1] + nums[2]; i++)
{
var weights = words[i].Split(' ').Select(Double.Parse).ToList();
neuralNet.hidToOutputWeight.Add(weights);
}
return neuralNet;
}
}
catch (Exception e)
{
Console.WriteLine("The file could not be read:");
Console.WriteLine(e.Message);
return null;
}
}
public void TransplantNet(NeuralNet.Net net)
{
this.Net = (FeedForward)net;
// Net fitness is based on amount consumed.
Net.FitnessEvaluator = n => (double)stats.Consumed;
}
