public void GetData()
{
bikeStationsDic = new Dictionary <Network, List <BikeStation> >();
BikeAPIManager bikeApiManager = new BikeAPIManager();
networks = bikeApiManager.GetAllCities().Result;
int totalNetworks = networks.Count();
int i = 1;
foreach (Network network in networks)
{
List <BikeStation> bikeStations = bikeApiManager.GetCityBikeStations(network).Result;
bikeStationsDic.Add(network, bikeStations);
log.Info($"GetData() Processing {i++}/{totalNetworks}: {network.Name}");
}
}
/// <summary>
/// Runs each Neural Network of the population through the fitness function and assigns the fitnesses.
/// Overloaded for running on multiple threads. default is unthreaded.
/// </summary>
public void Run()
{
Dictionary <int, double> fitnesses = new Dictionary <int, double>();
double totalfitness = 0;
if (threaded)
{
Thread thread1 = new Thread(() =>
{
for (int i = 0; i < Networks.Count / 4; i++)
{
NeuralNetwork NN = Networks.ElementAt(i);
double fitness = run(NN);
totalfitness += fitness;
lock (fitnesses)
{
fitnesses.Add(i, fitness);
}
//Console.WriteLine(i + " -> " + fitness);
}
});
Thread thread2 = new Thread(() =>
{
for (int i = Networks.Count / 4; i < Networks.Count / 2; i++)
{
NeuralNetwork NN = Networks.ElementAt(i);
double fitness = run(NN);
totalfitness += fitness;
lock (fitnesses)
{
fitnesses.Add(i, fitness);
}
//Console.WriteLine(i + " -> " + fitness);
}
});
Thread thread3 = new Thread(() =>
{
for (int i = Networks.Count / 2; i < 3 * Networks.Count / 4; i++)
{
NeuralNetwork NN = Networks.ElementAt(i);
double fitness = run(NN);
totalfitness += fitness;
lock (fitnesses)
{
fitnesses.Add(i, fitness);
}
//Console.WriteLine(i + " -> " + fitness);
}
});
Thread thread4 = new Thread(() =>
{
for (int i = 3 * Networks.Count / 4; i < Networks.Count; i++)
{
NeuralNetwork NN = Networks.ElementAt(i);
double fitness = run(NN);
totalfitness += fitness;
lock (fitnesses)
{
fitnesses.Add(i, fitness);
}
//Console.WriteLine(i + " -> " + fitness);
}
});
thread1.Start();
thread2.Start();
thread3.Start();
thread4.Start();
thread1.Join();
thread2.Join();
thread3.Join();
thread4.Join();
}
else
{
int count = 0;
foreach (NeuralNetwork NN in Networks)
{
double fitness = run(NN);
totalfitness += fitness;
fitnesses.Add(count, fitness);
//Console.WriteLine(count + " -> " + fitness);
count++;
}
}
AvgPopFitness = totalfitness / Networks.Count;
BestNetwork = null;
for (int i = 0; i < Networks.Count(); i++)
{
fitnesses.TryGetValue(i, out double fitness);
if (BestNetwork == null || fitness > BestNetwork.Fitness)
{
BestNetwork = Networks.ElementAt(i);
}
Networks.ElementAt(i).Fitness = fitness;
}
//Console.WriteLine("Run: " + isConsistent());
}