public static void GetProbabilityTest()
{
MarkovChain <string> matrix = new MarkovChain <string>(
new double[, ] {
{ 1.0 / 3, 2.0 / 3, 0, 0 },
{ 1.0 / 3, 1.0 / 3, 1.0 / 3, 0 },
{ 1.0 / 3, 1.0 / 3, 1.0 / 6, 1.0 / 6 },
{ 0, 0, 0, 1 }
}, "A", "B", "C", "D");
double res = matrix.GetProbability(new double[] { 2.0 / 3, 1.0 / 3, 0, 0 }, "C", 2);
AssertEquals(11.0 / 54, res, 0.001);
res = matrix.GetProbability(new double[] { 2.0 / 3, 1.0 / 3, 0, 0 }, "A", 3);
AssertEquals(0.32716, res, 0.00001);
res = matrix.GetProbability(new double[] { 2.0 / 3, 1.0 / 3, 0, 0 }, "D", 1);
AssertEquals(0, res, 0.001);
res = matrix.GetProbability("B", "A", 2);
AssertEquals(1.0 / 3, res, 0.001);
res = matrix.GetProbability("B", "D", 3);
AssertEquals(9.0 / 108, res, 0.0001);
res = matrix.GetProbability("C", "A", 1);
AssertEquals(1.0 / 3, res, 0.0001);
res = matrix.GetProbability("C", "C", 0);
AssertEquals(1.0, res, 0.0001);
res = matrix.GetProbability("C", "D", 0);
AssertEquals(0.0, res, 0.0001);
res = matrix.GetProbability("C", "B", 0);
AssertEquals(0.0, res, 0.0001);
res = matrix.GetProbability("C", "A", 0);
AssertEquals(0.0, res, 0.0001);
}
public static void GetChainProbabilityTest()
{
MarkovChain <char> markov = new MarkovChain <char>(
new double[, ] {
{ 1.0 / 3, 2.0 / 3, 0, 0 },
{ 1.0 / 3, 1.0 / 3, 1.0 / 3, 0 },
{ 1.0 / 3, 1.0 / 3, 1.0 / 6, 1.0 / 6 },
{ 0, 0, 0, 1 }
}, 'A', 'B', 'C', 'D');
double res;
res = markov.GetProbability('B', 'A', 2);
AssertEquals(1.0 / 3, res, 0.0001);
res = markov.GetProbability('B', 'D', 3);
AssertEquals(9.0 / 108, res, 0.0001);
res = markov.GetProbability('C', 'A', 1);
AssertEquals(1.0 / 3, res, 0.0001);
res = markov.GetProbability('C', 'D', 1);
AssertEquals(1.0 / 6, res, 0.0001);
res = markov.GetProbability('C', 'C', 0);
AssertEquals(1.0, res, 0.0001);
res = markov.GetProbability('C', 'A', 0);
AssertEquals(0.0, res, 0.0001);
res = markov.GetProbability('C', 'B', 0);
AssertEquals(0.0, res, 0.0001);
res = markov.GetProbability('C', 'D', 0);
AssertEquals(0.0, res, 0.0001);
// condition: state letter must be after B
res = markov.GetProbability('C', 2, state => state > 'B');
AssertEquals(12.0 / 36, res, 0.0001);
}
public static void CalcPiTest()
{
MarkovChain <int> matrix = new MarkovChain <int>(
new double[, ] {
{ 1.0 / 3, 2.0 / 3, 0, 0 },
{ 1.0 / 3, 1.0 / 3, 1.0 / 3, 0 },
{ 1.0 / 3, 1.0 / 3, 1.0 / 6, 1.0 / 6 },
{ 0, 0, 0, 1 }
}, 100, 200, 300, 400);
// p_2
double[] expectedResult = { 1.0 / 3, 4.0 / 9, 11.0 / 54, 1.0 / 54 };
double[] result = matrix.GetPi(
new double[] { 2.0 / 3, 1.0 / 3, 0, 0 }, // p_0
2);
AssertEquals(expectedResult.Length, result.Length);
for (int i = 0; i < result.Length; i++)
{
AssertEquals(expectedResult[i], result[i], 0.001);
}
// p_3
expectedResult = new double[] { 0.32716, 0.43827, 0.18210, 0.05247 };
result = matrix.GetPi(
new double[] { 2.0 / 3, 1.0 / 3, 0, 0 }, // p_0
3);
AssertEquals(expectedResult.Length, result.Length);
for (int i = 0; i < result.Length; i++)
{
AssertEquals(expectedResult[i], result[i], 0.0001);
}
// p_1
expectedResult = new double[] { 1.0 / 3, 5.0 / 9, 1.0 / 9, 0 };
result = matrix.GetPi(
new double[] { 2.0 / 3, 1.0 / 3, 0, 0 }, // p_0
1);
AssertEquals(expectedResult.Length, result.Length);
for (int i = 0; i < result.Length; i++)
{
AssertEquals(expectedResult[i], result[i], 0.0001);
}
}
