## Uses of Interface
org.biojava.bio.dp.State

Packages that use State
org.biojava.bio.dp: HMM and Dynamic Programming Algorithms.
org.biojava.bio.dp.onehead
org.biojava.bio.dp.twohead
org.biojava.bio.program.hmmer: Tools for working with profile Hidden Markov Models from the HMMer package.

Uses of State in org.biojava.bio.dp

Subinterfaces of State in org.biojava.bio.dp
`interface` `DotState` A Dot state.
`interface` `EmissionState` A state in a markov process that has an emission spectrum.
`interface` `ModelInState` A state that contains an entire sub-model.

Classes in org.biojava.bio.dp that implement State
`class` `MagicalState` Start/end state for HMMs.
`class` `SimpleDotState` A Dot state that you can make and use.
`class` `SimpleEmissionState`
`class` `SimpleModelInState`

Fields in org.biojava.bio.dp declared as State
`State` `Transition.from`
`State` `TrainerTransition.from`
`State` `BackPointer.state` The state with which this backpointer is associated.
`State` `Transition.to`
`State` `TrainerTransition.to`

Methods in org.biojava.bio.dp that return State
`State` `IllegalTransitionException.getFrom()`
`State[]` `DP.getStates()`
`State` `IllegalTransitionException.getTo()`
`State[]` `DP.stateList(MarkovModel mm)`
`State[]` `DPMatrix.states()`

Methods in org.biojava.bio.dp with parameters of type State
`void` `TransitionTrainer.addCount(State from, State to, double count)` Add 'count' to the transition from->to.
`void` `WMAsMM.addState(State toAdd)`
`void` `SimpleMarkovModel.addState(State toAdd)`
`void` `MarkovModel.addState(State newState)` Adds a state to the model.
`static int[][]` `DP.backwardTransitions(MarkovModel model, State[] states)`
`static double[][]` `DP.backwardTransitionScores(MarkovModel model, State[] states, int[][] transitions, ScoreType scoreType)`
`boolean` `WMAsMM.containsTransition(State from, State to)`
`boolean` `SimpleMarkovModel.containsTransition(State from, State to)`
`boolean` `MarkovModel.containsTransition(State from, State to)` Returns wether a transition exists or not.
`void` `WMAsMM.createTransition(State from, State to)`
`void` `SimpleMarkovModel.createTransition(State from, State to)`
`void` `MarkovModel.createTransition(State from, State to)` Makes a transition between two states legal.
`void` `WMAsMM.destroyTransition(State from, State to)`
`void` `SimpleMarkovModel.destroyTransition(State from, State to)`
`void` `MarkovModel.destroyTransition(State from, State to)` Breaks a transition between two states legal.
`static int[][]` `DP.forwardTransitions(MarkovModel model, State[] states)` Returns a matrix for the specified States describing all valid Transitions between those States.
`static double[][]` `DP.forwardTransitionScores(MarkovModel model, State[] states, int[][] transitions, ScoreType scoreType)` Compute the log(score) of all transitions between the specified States.
`Distribution` `WMAsMM.getWeights(State source)`
`Distribution` `SimpleMarkovModel.getWeights(State source)`
`Distribution` `MarkovModel.getWeights(State source)` Get a probability Distribution over the transition from 'source'.
`protected int` `WMAsMM.index(State s)`
`void` `SimpleHMMTrainer.recordEmittedSymbol(State state, Symbol symbol, double weight)`
`void` `HMMTrainer.recordEmittedSymbol(State state, Symbol symbol, double weight)` record that the specified symbol was emitted from the specified state.
`void` `SimpleHMMTrainer.recordTransition(State source, State dest, double weight)`
`void` `HMMTrainer.recordTransition(State source, State dest, double weight)` record that a transition was observed between the specified states.
`void` `WMAsMM.removeState(State toAdd)`
`void` `SimpleMarkovModel.removeState(State toGo)`
`void` `MarkovModel.removeState(State toGo)` Remove a state from the model.
`void` `WMAsMM.setWeights(State source, Distribution dist)`
`void` `SimpleMarkovModel.setWeights(State source, Distribution dist)` Use this methods to customize the transition probabilities.
`void` `MarkovModel.setWeights(State source, Distribution dist)` Set the probability distribution over the transitions from 'source'.
`FiniteAlphabet` `WMAsMM.transitionsFrom(State from)`
`FiniteAlphabet` `SimpleMarkovModel.transitionsFrom(State from)`
`FiniteAlphabet` `MarkovModel.transitionsFrom(State source)` Returns the FiniteAlphabet of all states that have a transition from 'source'.
`FiniteAlphabet` `WMAsMM.transitionsTo(State to)`
`FiniteAlphabet` `SimpleMarkovModel.transitionsTo(State to)`
`FiniteAlphabet` `MarkovModel.transitionsTo(State dest)` Returns the FiniteAlphabet of all states that have a transition to 'dest'.

Constructors in org.biojava.bio.dp with parameters of type State
`BackPointer(State s)`
`BackPointer(State state, BackPointer back, double score)`
`IllegalTransitionException(State from, State to)`
`IllegalTransitionException(State from, State to, String message)`
`TrainerTransition(TransitionTrainer trainer, State from, State to)`
`Transition(State from, State to)`

Uses of State in org.biojava.bio.dp.onehead

Fields in org.biojava.bio.dp.onehead declared as State
`protected State[]` `SingleDPMatrix.states`

Methods in org.biojava.bio.dp.onehead that return State
`State[]` `SingleDPMatrix.states()`

Constructors in org.biojava.bio.dp.onehead with parameters of type State
`SmallCursor(State[] states, SymbolList symList, Iterator symIterator)`

Uses of State in org.biojava.bio.dp.twohead

Methods in org.biojava.bio.dp.twohead that return State
`State[]` `PairDPMatrix.states()`

Constructors in org.biojava.bio.dp.twohead with parameters of type State
`EmissionCache(Alphabet alpha, State[] states, int dsi, ScoreType scoreType)`

Uses of State in org.biojava.bio.program.hmmer

Classes in org.biojava.bio.program.hmmer that implement State
`class` `ProfileEmissionState` A state in a HMMer model.

Methods in org.biojava.bio.program.hmmer with parameters of type State
`double` `HmmerProfileHMM.transScore(State from, State to, Symbol symFrom, Symbol symTo)`