public ViterbiCalculator(IMLDataSet oseq, HiddenMarkovModel hmm)
{
if (oseq.Count < 1)
{
throw new EncogError("Must not have empty sequence");
}
this.delta = EngineArray.AllocateDouble2D((int)oseq.Count, hmm.StateCount);
this.psy = EngineArray.AllocateInt2D((int)oseq.Count, hmm.StateCount);
this._stateSequence = new int[oseq.Count];
for (int i = 0; i < hmm.StateCount; i++)
{
this.delta[0][i] = -Math.Log(hmm.GetPi(i))
- Math.Log(hmm.StateDistributions[i].Probability(
oseq[0]));
this.psy[0][i] = 0;
}
int t = 1;
for (int index = 1; index < oseq.Count; index++)
{
IMLDataPair observation = oseq[index];
for (int i = 0; i < hmm.StateCount; i++)
{
ComputeStep(hmm, observation, t, i);
}
t++;
}
this.lnProbability = Double.PositiveInfinity;
for (int i = 0; i < hmm.StateCount; i++)
{
double thisProbability = this.delta[oseq.Count - 1][i];
if (this.lnProbability > thisProbability)
{
this.lnProbability = thisProbability;
_stateSequence[oseq.Count - 1] = i;
}
}
this.lnProbability = -this.lnProbability;
for (int t2 = (int)(oseq.Count - 2); t2 >= 0; t2--)
{
_stateSequence[t2] = this.psy[t2 + 1][_stateSequence[t2 + 1]];
}
}
public ViterbiCalculator(IMLDataSet oseq, HiddenMarkovModel hmm)
{
if (oseq.Count < 1)
{
throw new EncogError("Must not have empty sequence");
}
this.delta = EngineArray.AllocateDouble2D((int)oseq.Count, hmm.StateCount);
this.psy = EngineArray.AllocateInt2D((int)oseq.Count, hmm.StateCount);
this._stateSequence = new int[oseq.Count];
for (int i = 0; i < hmm.StateCount; i++)
{
this.delta[0][i] = -Math.Log(hmm.GetPi(i))
- Math.Log(hmm.StateDistributions[i].Probability(
oseq[0]));
this.psy[0][i] = 0;
}
int t = 1;
for (int index = 1; index < oseq.Count; index++)
{
IMLDataPair observation = oseq[index];
for (int i = 0; i < hmm.StateCount; i++)
{
ComputeStep(hmm, observation, t, i);
}
t++;
}
this.lnProbability = Double.PositiveInfinity;
for (int i = 0; i < hmm.StateCount; i++)
{
double thisProbability = this.delta[oseq.Count - 1][i];
if (this.lnProbability > thisProbability)
{
this.lnProbability = thisProbability;
_stateSequence[oseq.Count - 1] = i;
}
}
this.lnProbability = -this.lnProbability;
for (int t2 = (int)(oseq.Count - 2); t2 >= 0; t2--)
{
_stateSequence[t2] = this.psy[t2 + 1][_stateSequence[t2 + 1]];
}
}
public void NewSequence()
{
double rand = ThreadSafeRandom.NextDouble();
double current = 0.0;
for (int i = 0; i < (_hmm.StateCount - 1); i++)
{
current += _hmm.GetPi(i);
if (current > rand)
{
_currentState = i;
return;
}
}
_currentState = _hmm.StateCount - 1;
}
/// <summary>
/// Compute the probability.
/// </summary>
/// <param name="oseq">The sequence.</param>
/// <param name="hmm">THe hidden markov model.</param>
/// <param name="doAlpha">Perform alpha step?</param>
/// <param name="doBeta">Perform beta step?</param>
private void ComputeProbability(IMLDataSet oseq,
HiddenMarkovModel hmm, bool doAlpha, bool doBeta)
{
probability = 0.0;
if (doAlpha)
{
for (int i = 0; i < hmm.StateCount; i++)
{
probability += Alpha[oseq.Count - 1][i];
}
}
else
{
for (int i = 0; i < hmm.StateCount; i++)
{
probability += hmm.GetPi(i)
* hmm.StateDistributions[i].Probability(oseq[0])
* Beta[0][i];
}
}
}
/// <summary>
/// Compute the alpha init.
/// </summary>
/// <param name="hmm">THe hidden markov model.</param>
/// <param name="o">The element.</param>
/// <param name="i">The state.</param>
protected void ComputeAlphaInit(HiddenMarkovModel hmm,
IMLDataPair o, int i)
{
Alpha[0][i] = hmm.GetPi(i)
* hmm.StateDistributions[i].Probability(o);
}
/// <summary>
/// Compute the probability.
/// </summary>
/// <param name="oseq">The sequence.</param>
/// <param name="hmm">THe hidden markov model.</param>
/// <param name="doAlpha">Perform alpha step?</param>
/// <param name="doBeta">Perform beta step?</param>
private void ComputeProbability(IMLDataSet oseq,
HiddenMarkovModel hmm, bool doAlpha, bool doBeta)
{
probability = 0.0;
if (doAlpha)
{
for (int i = 0; i < hmm.StateCount; i++)
{
probability += Alpha[oseq.Count - 1][i];
}
}
else
{
for (int i = 0; i < hmm.StateCount; i++)
{
probability += hmm.GetPi(i)
*hmm.StateDistributions[i].Probability(oseq[0])
*Beta[0][i];
}
}
}
/// <summary>
/// Compute the alpha init.
/// </summary>
/// <param name="hmm">THe hidden markov model.</param>
/// <param name="o">The element.</param>
/// <param name="i">The state.</param>
protected void ComputeAlphaInit(HiddenMarkovModel hmm,
IMLDataPair o, int i)
{
Alpha[0][i] = hmm.GetPi(i)
*hmm.StateDistributions[i].Probability(o);
}
