public void CountPairs(int[] arr, int expectedResult)
{
var sut = new PairCounter();
var result = sut.CountPairs(arr);
result.Should().Be(expectedResult);
}
void Start()
{
comparer = new CardComparer(CardComparerCallback);
InitCards();
remainingPairs.Value = cards.Length / 2;
pairCounter = new PairCounter(remainingPairs, OnGameOver);
}
public void Test(int[] dimensions, int bestSoFar, int targetCases)
{
int features = dimensions.Length;
string[][] sources = new string[features][];
for (int i = 0; i < features; i++)
{
string featureName = "ABCDEFGHIJKLMNOPQRSTUVWXYZ".Substring(i, 1);
int n = dimensions[i];
sources[i] = new string[n];
for (int j = 0; j < n; j++)
{
sources[i][j] = featureName + j.ToString();
}
}
ICombiningStrategy strategy = new PairwiseStrategy();
PairCounter pairs = new PairCounter();
int cases = 0;
foreach (NUnit.Framework.Internal.TestCaseParameters parms in strategy.GetTestCases(sources))
{
for (int i = 1; i < features; i++)
{
for (int j = 0; j < i; j++)
{
string a = parms.Arguments[i] as string;
string b = parms.Arguments[j] as string;
pairs[a + b] = null;
}
}
++cases;
}
int expectedPairs = 0;
for (int i = 1; i < features; i++)
{
for (int j = 0; j < i; j++)
{
expectedPairs += dimensions[i] * dimensions[j];
}
}
Assert.That(pairs.Count, Is.EqualTo(expectedPairs), "Number of pairs is incorrect");
Assert.That(cases, Is.AtMost(bestSoFar), "Regression: Number of test cases exceeded target previously reached");
#if DEBUG
//Assert.That(cases, Is.AtMost(targetCases), "Number of test cases exceeded target");
#endif
}
public static OSResult guessOS(string[] foundServices)
{
OSResult result;
// Initialize objects
NeuralNetwork.Network net = new NeuralNetwork.Network();
// Load in data to memory
if (!File.Exists(Path.Combine(Environment.ExpandEnvironmentVariables("%userprofile%"), "Documents", "Gerbil", "memstore", "OSServiceTraining.ini")))
{
return(new OSResult("ERROR", 0.0f));
}
string[] trainingData = File.ReadAllLines(Path.Combine(Environment.ExpandEnvironmentVariables("%userprofile%"), "Documents", "Gerbil", "memstore", "OSServiceTraining.ini"));
// Calculate weights
PairCounter pc = new PairCounter();
foreach (string i in trainingData)
{
string sName = i.Split('=')[0];
string fOS = i.Split('=')[1];
pc.Add(new Pair(sName, fOS));
}
Dictionary <Pair, float> connectionWeights = getPercentagesFromPair(pc.getResults());
// TODO: Train network
foreach (KeyValuePair <Pair, float> i in connectionWeights)
{
net.addInput(i.Key.item1);
net.addOutput(i.Key.item2, i.Key.item1 + "Connector", i.Value, i.Key.item1);
}
// Feed data into tranined neural network
foreach (string i in foundServices)
{
try
{
net.fireInput(i);
}
catch (NeuralNetwork.NodeNotFoundException e)
{
// Serive does not exist, since we are not in training mode, ignore.
}
catch
{
// A serious engine error occured. Throw fatal error.
throw new FatalEngineException();
}
}
// Get outputs
Dictionary <string, float> results = net.getResults();
string resultName = "Unknown";
float resultCertainty = 0.0f;
float maxCertainty = 0.0f;
// Find most likely answer
foreach (KeyValuePair <string, float> i in results)
{
if (i.Value > resultCertainty)
{
resultName = i.Key;
resultCertainty = i.Value;
maxCertainty += i.Value;
}
}
resultCertainty = resultCertainty / maxCertainty;
result = new OSResult(resultName, resultCertainty);
return(result);
}
public void TestFixtureSetUp()
{
pairsTested = new PairCounter();
}
public void OneTimeSetUp()
{
pairsTested = new PairCounter();
}
