private static void PrintTest(string[] tv, double[] outputArray)
{
var manaCostString = $"Mana Cost: {tv[0].PadLeft(3, ' ')}";
var weights = $"W: {outputArray[0]:0.0000} U: {outputArray[1]:0.0000}, B: {outputArray[2]:0.0000}, R: {outputArray[3]:0.0000}, G: {outputArray[4]:0.0000}";
var text = tv[1];
var prediction = MtgDataLoader.ConvertOutputToCardColors(outputArray).PadLeft(5, ' ');
Console.WriteLine($"{manaCostString} | {text.PadRight(30,' ')} | {prediction.PadRight(5,' ')} | {weights} ");
}
private static void Train(BasicNetwork network)
{
// load all of the cards from the MagicAssistant library
var cards = MtgDataLoader.GetAllCards(@"C:\Users\napol\MagicAssistantWorkspace\magiccards\MagicDB");
// build inputs and ideals
var mtgData = new MtgDataLoader(cards);
var input = mtgData.Inputs;
var ideal = mtgData.Ideals;
// create training data
IMLDataSet trainingSet = new BasicMLDataSet(input, ideal);
// train the neural network
IMLTrain train = new ResilientPropagation(network, trainingSet);
int epoch = 1;
do
{
train.Iteration();
if (epoch % 10 == 0)
{
Console.WriteLine(@"Epoch #" + epoch + @" Error:" + train.Error);
}
epoch++;
// if we're not below 1% after 600 iterations (highly unlikely) just bow out.
if (epoch > 1000)
{
break;
}
} while (train.Error > 0.01);
train.FinishTraining();
Console.WriteLine($"Final Error: {train.Error}");
Console.WriteLine("Writing network to file");
if (System.IO.File.Exists("network.data"))
{
System.IO.File.Delete("network.data");
}
Encog.Util.SerializeObject.Save("network.data", network);
}
private static void TestNetwork(string[][] testValues, BasicNetwork network)
{
// test the neural network
Console.WriteLine(@"Neural Network Test Results:");
foreach (var tv in testValues)
{
IMLData output2 = network.Compute(new BasicMLData(MtgDataLoader.GenerateInputs(tv[0], tv[1])));
double[] outputArray = new double[5];
for (int i = 0; i < 5; i++)
{
outputArray[i] = output2[i];
}
// Shiny pretty console display
PrintTest(tv, outputArray);
}
}
