public bool Equals(PState obj)
{
if (ReferenceEquals(obj, null))
{
return(false);
}
else
{
return(fromstate == obj.fromstate && tostate == obj.tostate);
}
}
PopulationMatrix Build()
{
var listofstates = (from s in transitions select new List <string>()
{
s.Key.fromstate, s.Key.tostate
})
.SelectMany(x => x)
.Distinct()
.ToList();
Matrix <double> M = Matrix <double> .Build.Dense(listofstates.Count(), listofstates.Count());
for (int i = 0; i < M.RowCount; ++i)
{
for (int j = i; j < M.ColumnCount; ++j)
{
var state = new PState(listofstates[i], listofstates[j]);
if (transitions.Keys.Contains(state))
{
M[i, j] = transitions[state];
M[j, i] = M[j, i];
}
else
{
M[i, j] = M[j, i] = 0.0;
}
}
if (M.Row(i).Sum() != 1.0)
{
throw new Exception(String.Format("Invalid transtion matrix for P(x/{0})", listofstates[i]));
}
}
if (Po == null)
{
throw new Exception(String.Format("No initial State matrix has been provided"));
}
return(new PopulationMatrix(M, Po, listofstates.ToArray()));
}
public PopulationPMatrixBuilder WithTransitionProbability(PState s, double p)
{
transitions[s] = p;
return(this);
}