private static (decimal Swing, string Party) GenerateSwing(DateTime forecastDate, DateTime electionDay)
{
string party = new Random().Next() % 2 == 0 ? "Republican" : "Democratic";
decimal swing = Guassian.Next(0, ((decimal)(electionDay - forecastDate).Days / 90) + 1);
return(swing, party);
}
public override int Run(string[] remainingArguments)
{
InitializeArgumentsFromConfinIfItIsNecessary();
var inputs = _dataLoader.LoadCoordinates(_fileName);
var normalizedInputs = inputs.Select(_matrixHelpers.Normalize).ToList();
var maxInputOne = normalizedInputs.Select(x => x.At(0, 0)).Max();
var maxInputTwo = normalizedInputs.Select(x => x.At(0, 1)).Max();
var network = new SOMNet(maxInputOne, maxInputTwo, inputs.Count);
var rmax = 4;
//var neighborhoodFunction = new Guassian();
var neighborhoodFunction = new Guassian();
var teacher = new Teacher(network, neighborhoodFunction, rmax);
teacher.Learn(normalizedInputs);
var order = new List <int>();
foreach (var input in inputs)
{
order.Add(network.GetIndexOfTheMostMatchesNeuron(input));
}
var saver = new DataSaver();
saver.SaveWeights(network);
saver.SaveNormalizedInputs(normalizedInputs);
saver.SaveOrder(order);
if (shouldVisual)
{
var orderlinesses = inputs.Select((x, i) => new Orderliness(order[i], x)).ToList();
var bm = _visualizer.Visualize(orderlinesses);
bm.Save(ConfigurationManager.AppSettings["Visualization"]);
}
return(0);
}
static int Main(string[] args)
{
var nf = new Guassian();
for (var i = 0; i < 2; i++)
{
Console.WriteLine("Wartość guassaina przy i = {0} to {1}", i, nf.GiveValue(i, 1));
}
// locate any commands in the assembly (or use an IoC container, or whatever source)
var commands = GetCommands();
// then run them.
return(ConsoleCommandDispatcher.DispatchCommand(commands, args, Console.Out));
}
private float GenerateGuassianMatrix(uint oct, uint layer)
{
float sigma = (float)(1.6 * pow(2, oct + ((float)layer / (float)(layers - 3))));//layers-3 to make sure the continues of the Guassian pyrimid
uint n = 0; float normalizing = 0;
for (int j = 0; j < guassMatrixSize.y; j++)
{
for (int i = 0; i < guassMatrixSize.x; i++)
{
Guassian[n] = GuassianFunction(sigma, j, i); normalizing += Guassian[n]; n++;
}
}
for (int i = 0; i < Guassian.Length; i++)
{
Guassian[i] = Guassian[i] / normalizing;
} //normalization
Guassian.SetData(Guassian);
return(sigma);
}//Generate Guassian Matrix Method End
private static (decimal Result, decimal Weight) GetGuassian(Poll poll, string candidateName, DateTime date)
{
PollResult result = poll.Results.FirstOrDefault(c => c.Candidate == candidateName);
if (result != null)
{
decimal mean = result.Percent;
decimal stdDev = ((decimal)(date - poll.Date).Days / 60) + 1;
decimal pct = Guassian.Next(mean, stdDev);
int denominator = (date - poll.Date).Days;
if (denominator == 0)
{
denominator = 1;
}
var weight = (decimal)System.Math.Sqrt(1.0 / denominator);
return(pct * weight, weight);
}
return(0.0M, 0.0M);
}
