/// <summary>
/// Reorganizes source chain.
/// </summary>
/// <param name="source">
/// Source chain.
/// </param>
/// <returns>
/// <see cref="AbstractChain"/>.
/// </returns>
/// <exception cref="InvalidOperationException">
/// Thrown if level is less than 0.
/// </exception>
public override AbstractChain Reorganize(AbstractChain source)
{
if (level < 0)
{
throw new InvalidOperationException("Markov chain level can't be less than 0");
}
if (level == 0)
{
return source;
}
var result = new BaseChain();
result.ClearAndSetNewLength(source.GetLength() + level);
for (int i = 0; i < source.GetLength(); i++)
{
result[i] = source[i];
}
var iterator = new IteratorStart(source, level, 1);
iterator.Reset();
iterator.Next();
AbstractChain addition = iterator.Current();
for (int i = 0; i < addition.GetLength(); i++)
{
result[source.GetLength() + i] = addition[i];
}
return result;
}
/// <summary>
/// Teaches markov chain using provided sequence.
/// </summary>
/// <param name="chain">
/// Sequence used for teaching.
/// </param>
/// <param name="method">
/// Chain preprocessing method.
/// </param>
public virtual void Teach(BaseChain chain, TeachingMethod method)
{
var builder = new MatrixBuilder();
var absMatrix = new IAbsoluteMatrix[HeterogeneityRank + 1];
Alphabet = chain.Alphabet;
for (int i = 0; i < HeterogeneityRank + 1; i++)
{
absMatrix[i] = (IAbsoluteMatrix)builder.Create(Alphabet.Cardinality, Rank);
}
SpaceReorganizer reorganizer = GetRebuilder(method);
chain = (BaseChain)reorganizer.Reorganize(chain);
var it = new IteratorStart(chain, Rank, 1);
it.Reset();
int k = 0;
// filling matrixes
while (it.Next())
{
++k;
int m = k % (HeterogeneityRank + 1);
if (m == 0)
{
m = HeterogeneityRank + 1;
}
BaseChain chainToTeach = (BaseChain)it.Current();
var indexedChain = new int[Rank];
for (int i = 0; i < Rank; i++)
{
indexedChain[i] = chain.Alphabet.IndexOf(chainToTeach[i]);
}
absMatrix[m - 1].Add(indexedChain);
}
for (int i = 0; i < HeterogeneityRank + 1; i++)
{
ProbabilityMatrixes[i] = absMatrix[i].ProbabilityMatrix();
}
}
