public void Calculate_SameResultTwice()
{
var net = new Core.Network(new int[] { 1, 5, 1 });
var input = new double[] { 1 };
var result = net.Calculate(input);
var result2 = net.Calculate(input);
Assert.AreEqual<double>(result.First(), result2.First());
}
public void Train_ChangesWeight()
{
var net = new Core.Network(new int[] { 1, 1, 1 });
var input = new double[] { 1 };
var result = net.Calculate(input).ToArray();
var increased = result.Select(r => r + 1).ToArray();
net.Train(result, increased);
var result2 = net.Calculate(input).ToList();
Assert.AreNotEqual<double>(result.First(), result2.First());
}
public void Train_FindApproximateValue()
{
var net = new Core.Network(new int[] { 1, 1 });
var input = new double[] { 1 };
double expected = 0.72;
double tolerance = 0.01;
double delta = 0;
double watchdog = 1000;
do
{
var result = net.Calculate(input);
net.Train(result, new double[] { expected });
delta = Math.Abs(result[0] - expected);
if (watchdog-- <= 0)
Assert.Fail();
} while (delta >= tolerance);
}
public void Train_SimpleProblem()
{
var net = new Core.Network(new int[] { 3, 2, 2 });
double tolerance = 0.001;
double delta = 0;
double watchdog = 5000;
Random rand = new Random();
do
{
double result1 = (double)rand.Next(0, 2);
double result2 = (double)rand.Next(0, 2);
double[] input = new double[] { result2, rand.NextDouble(), result1 };
var data = net.Calculate(input);
net.Train(input, new double[] { result1, result2 });
delta = Math.Abs(data[0] - result1) + Math.Abs(data[1] - result2);
if (watchdog-- <= 0)
Assert.Fail();
} while (delta >= tolerance);
}
public void SetUp()
{
this.network = new Core.Network(6, 9, 3);
}
