/// Construct new Hidden MarkovModel with the given transition, observation, and initial
/// state matrices and vectors already as `Prob` values.
Construct new Hidden MarkovModel with the given transition, observation, and initial
state matrices and vectors already as `Prob` values.
Construct new Hidden MarkovModel with the given transition observation and initial state matrices and vectors already as ` Prob ` values .
pub fn with_prob(
            transition: &Array2<Prob>,
            observation: &Array2<Prob>,
            initial: &Array1<Prob>,
        ) -> Result<Self> {
            Self::new(
                transition.map(|x| LogProb::from(*x)),
                observation.map(|x| LogProb::from(*x)),
                initial.map(|x| LogProb::from(*x)),
            )
        }
pub fn with_prob ( transition : & Array2 < Prob > , observation : & Array2 < Prob > , initial : & Array1 < Prob > , ) -> Result < Self > { Self :: new ( transition . map ( | x | LogProb :: from ( * x ) ) , observation . map ( | x | LogProb :: from ( * x ) ) , initial . map ( | x | LogProb :: from ( * x ) ) , ) }
Construct new Hidden MarkovModel with the given transition, observation, and initial
state matrices and vectors already as `Prob` values.
Construct new Hidden MarkovModel with the given transition observation and initial state matrices and vectors already as ` Prob ` values .
transition
&Array2<Prob>
observation
&Array2<Prob>
initial
&Array1<Prob>