Merge branch 'master' of https://github.com/aabghari/mlpack into aabg…

…hari-master

src/mlpack/methods/hmm/hmm.hpp

@@ -201,14 +201,14 @@ class HMM
    * of the most probable sequence is returned.
    *
    * @param dataSeq Sequence of observations.
-   * @param stateProb Matrix in which the log probabilities of each state at each
-   *    time interval will be stored.
-   * @param forwardProb Matrix in which the forward log probabilities of each state
-   *    at each time interval will be stored.
+   * @param stateProb Matrix in which the log probabilities of each state at
+   *    each time interval will be stored.
+   * @param forwardProb Matrix in which the forward log probabilities of each
+   *    state at each time interval will be stored.
    * @param backwardProb Matrix in which the backward log probabilities of each
    *    state at each time interval will be stored.
-   * @param scales Vector in which the log of scaling factors at each time interval
-   *    will be stored.
+   * @param scales Vector in which the log of scaling factors at each time
+   *    interval will be stored.
    * @return Log-likelihood of most likely state sequence.
    */
   double LogEstimate(const arma::mat& dataSeq,
@@ -323,14 +323,15 @@ class HMM
               arma::mat& smoothSeq) const;
 
   //! Return the vector of initial state probabilities.
-  const arma::vec& Initial() const { return initial; }
+  const arma::vec Initial() const { return initialProxy; }
   //! Modify the vector of initial state probabilities.
-  arma::vec& Initial() { return initial; }
+  arma::vec& Initial() { recalculateInitial = true; return initialProxy; }
 
   //! Return the transition matrix.
-  const arma::mat& Transition() const { return transition; }
+  const arma::mat Transition() const { return transitionProxy; }
   //! Return a modifiable transition matrix reference.
-  arma::mat& Transition() { return transition; }
+  arma::mat& Transition() { recalculateTransition = true;
+                            return transitionProxy; }
 
   //! Return the emission distributions.
   const std::vector<Distribution>& Emission() const { return emission; }
@@ -351,7 +352,13 @@ class HMM
    * Serialize the object.
    */
   template<typename Archive>
-  void serialize(Archive& ar, const unsigned int version);
+  void load(Archive& ar, const unsigned int version);
+
+  template<typename Archive>
+  void save(Archive& ar, const unsigned int version) const;
+
+  BOOST_SERIALIZATION_SPLIT_MEMBER()
+
 
  protected:
   // Helper functions.
@@ -387,18 +394,49 @@ class HMM
   //! Set of emission probability distributions; one for each state.
   std::vector<Distribution> emission;
 
-  //! Transition probability matrix.
-  arma::mat transition;
+  /**
+   *a proxy vriable in linear space for logTransition.
+   *Should be removed in mlpack 4.0.
+   */
+  arma::mat transitionProxy;
+
+  //! Transition probability matrix. No need to be mutable in mlpack 4.0.
+  mutable arma::mat logTransition;
 
  private:
-  //! Initial state probability vector.
-  arma::vec initial;
+  /**
+   * Make sure the variables in log space are in sync
+   * with the linear counter parts.
+   * Should be removed in mlpack 4.0.
+   */
+  void ConvertToLogSpace() const;
+
+  /**
+   * a proxy vriable in linear space for logInitial.
+   * Should be removed in mlpack 4.0.
+   */
+  arma::vec initialProxy;
+
+  //! Initial state probability vector. No need to be mutable in mlpack 4.0.
+  mutable arma::vec logInitial;
 
   //! Dimensionality of observations.
   size_t dimensionality;
 
   //! Tolerance of Baum-Welch algorithm.
   double tolerance;
+
+  /**
+   * Whether or not we need to update the logInitial from initialProxy.
+   * Should be removed in mlpack 4.0.
+   */
+  mutable bool recalculateInitial;
+
+  /**
+   * Whether or not we need to update the logTransition from transitionProxy.
+   * Should be removed in mlpack 4.0.
+   */
+  mutable bool recalculateTransition;
 };
 
 } // namespace hmm