public void AddOverflowEdgeTest()
{
MarkovChain <int> chains = new MarkovChain <int>(4);
chains.AddEdge(0, 4, 0.2);
chains.AddEdge(5, 6, 0.7);
chains.AddEdge(7, 9, 0.1);
Assert.That(0.2, Is.EqualTo(chains[0, 4]));
Assert.That(0.1, Is.EqualTo(chains[7, 9]));
}
public void GetOutgoingVerticesTest()
{
MarkovChain <int> chains = new MarkovChain <int>(4);
chains.AddEdge(0, 4, 0.2);
chains.AddEdge(5, 6, 0.7);
chains.AddEdge(0, 5, 0.2);
Assert.That(chains.GetOutgoingVertices(0), Is.EquivalentTo(new List <int> {
4, 5
}));
}
public void GetRateTest()
{
MarkovChain <int> chains = new MarkovChain <int>(4);
chains.AddEdge(0, 4, 0.2);
chains.AddEdge(5, 6, 0.7);
chains.AddEdge(7, 9, 0.1);
Assert.That(0.2, Is.EqualTo(chains.GetRate(0, 4)));
Assert.That(0.1, Is.EqualTo(chains.GetRate(7, 9)));
Assert.That(0, Is.EqualTo(chains.GetRate(10, 11)));
}
public void GetAllVerticesTest()
{
MarkovChain <int> chains = new MarkovChain <int>(4);
chains.AddEdge(0, 4, 0.2);
chains.AddEdge(5, 6, 0.7);
chains.AddEdge(7, 9, 0.1);
CollectionAssert.AreEquivalent(new List <int> {
0, 4, 5, 6, 7, 9
}, chains.GetAllVertices());
}
public void GetAllEdgesTest()
{
MarkovChain <int> chains = new MarkovChain <int>(7);
chains.AddEdge(0, 1, 0.2);
chains.AddEdge(0, 2, 0.7);
chains.AddEdge(3, 2, 0.2);
chains.AddEdge(4, 5, 0.2);
CollectionAssert.AreEquivalent(new List <Tuple <int, double, int> > {
new Tuple <int, double, int>(0, 0.2, 1), new Tuple <int, double, int>(0, 0.7, 2), new Tuple <int, double, int>(3, 0.2, 2), new Tuple <int, double, int>(4, 0.2, 5)
}, chains.GetAllEdges());
}
public void AddEdgeTest()
{
MarkovChain <int> chains = new MarkovChain <int>(4);
chains.AddEdge(0, 3, 0.2);
chains[7, 10] = 0.7;
Assert.That(0.2, Is.EqualTo(chains[0, 3]));
Assert.That(0.7, Is.EqualTo(chains[7, 10]));
}
public void GetComponentsTest()
{
MarkovChain <int> chains = new MarkovChain <int>(7);
chains.AddEdge(0, 1, 0.2);
chains.AddEdge(0, 2, 0.7);
chains.AddEdge(3, 2, 0.2);
chains.AddEdge(4, 5, 0.2);
CollectionAssert.AreEquivalent(new List <List <int> > {
new List <int> {
0, 1, 2, 3
}, new List <int> {
4, 5
}, new List <int> {
6
}
}, chains.GetComponents(new List <int> {
0, 1, 2, 3, 4, 5, 6
}).Select(c => c.OrderBy(v => v).ToList()).ToList());
}
public void ComputeProbability()
{
double samplingRate = 0.5d;
double timeSpan = 40.0d;
double errorTolerance = 1e-16;
MarkovChain <int> chains = new MarkovChain <int>(6);
chains.InitialDistribution[1] = 0.9;
chains.InitialDistribution[2] = 0.1;
chains.InitialDistribution[3] = 0;
chains.InitialDistribution[4] = 1;
chains.InitialDistribution[5] = chains.InitialDistribution[6] = 0;
chains.AddEdge(1, 2, 0.2d);
chains.AddEdge(2, 1, 0.1d);
chains[2, 3] = 0.1d;
chains[3, 2] = 0.05d;
chains[4, 5] = 0.1d;
chains[5, 6] = 0.05d;
var result = chains.ComputeProbability(samplingRate, timeSpan, errorTolerance);
}