More consistent order of private/protected/public - typedefs, private/protected variables, public interface, private/protected functions

gtsam/base/DerivedValue.h

@@ -24,9 +24,6 @@ namespace gtsam {
 
 template<class DERIVED>
 class DerivedValue : public Value {
-private:
-	/// Fake Tag struct for singleton pool allocator. In fact, it is never used!
-	struct PoolTag { };
 
 protected:
 	DerivedValue() {}
@@ -119,6 +116,10 @@ protected:
 	  return *this;
 	}
 
+private:
+	/// Fake Tag struct for singleton pool allocator. In fact, it is never used!
+	struct PoolTag { };
+
 };
 
 } /* namespace gtsam */

gtsam/inference/BayesTree.h

@@ -94,51 +94,6 @@ namespace gtsam {
     /** Map from keys to Clique */
     typedef std::deque<sharedClique> Nodes;
 
-	protected:
-
-    /** Map from keys to Clique */
-		Nodes nodes_;
-
-		/** private helper method for saving the Tree to a text file in GraphViz format */
-		void saveGraph(std::ostream &s, sharedClique clique, const IndexFormatter& indexFormatter,
-				int parentnum = 0) const;
-
-		/** Gather data on a single clique */
-		void getCliqueData(CliqueData& stats, sharedClique clique) const;
-
-		/** Root clique */
-		sharedClique root_;
-
-		/** remove a clique: warning, can result in a forest */
-		void removeClique(sharedClique clique);
-
-		/** add a clique (top down) */
-		sharedClique addClique(const sharedConditional& conditional, const sharedClique& parent_clique = sharedClique());
-
-    /** add a clique (top down) */
-    void addClique(const sharedClique& clique, const sharedClique& parent_clique = sharedClique());
-
-		/** add a clique (bottom up) */
-		sharedClique addClique(const sharedConditional& conditional, std::list<sharedClique>& child_cliques);
-
-		/**
-		 * Add a conditional to the front of a clique, i.e. a conditional whose
-		 * parents are already in the clique or its separators.  This function does
-		 * not check for this condition, it just updates the data structures.
-		 */
-		static void addToCliqueFront(BayesTree<CONDITIONAL,CLIQUE>& bayesTree,
-		    const sharedConditional& conditional, const sharedClique& clique);
-
-		/** Fill the nodes index for a subtree */
-		void fillNodesIndex(const sharedClique& subtree);
-
-    /** Helper function to build a non-symbolic tree (e.g. Gaussian) using a
-     * symbolic tree, used in the BT(BN) constructor.
-     */
-		void recursiveTreeBuild(const boost::shared_ptr<BayesTreeClique<IndexConditional> >& symbolic,
-		      const std::vector<boost::shared_ptr<CONDITIONAL> >& conditionals,
-		      const typename BayesTree<CONDITIONAL,CLIQUE>::sharedClique& parent);
-
 	public:
 
 		/// @name Standard Constructors
@@ -184,8 +139,6 @@ namespace gtsam {
 		/// @name Standard Interface
 		/// @{
 
-	public:
-
 		/**
 		 * Find parent clique of a conditional.  It will look at all parents and
 		 * return the one with the lowest index in the ordering.
@@ -285,6 +238,51 @@ namespace gtsam {
 				std::list<sharedClique>& children, bool isRootClique = false);
 
 		
+	protected:
+
+    /** Map from keys to Clique */
+		Nodes nodes_;
+
+		/** private helper method for saving the Tree to a text file in GraphViz format */
+		void saveGraph(std::ostream &s, sharedClique clique, const IndexFormatter& indexFormatter,
+				int parentnum = 0) const;
+
+		/** Gather data on a single clique */
+		void getCliqueData(CliqueData& stats, sharedClique clique) const;
+
+		/** Root clique */
+		sharedClique root_;
+
+		/** remove a clique: warning, can result in a forest */
+		void removeClique(sharedClique clique);
+
+		/** add a clique (top down) */
+		sharedClique addClique(const sharedConditional& conditional, const sharedClique& parent_clique = sharedClique());
+
+    /** add a clique (top down) */
+    void addClique(const sharedClique& clique, const sharedClique& parent_clique = sharedClique());
+
+		/** add a clique (bottom up) */
+		sharedClique addClique(const sharedConditional& conditional, std::list<sharedClique>& child_cliques);
+
+		/**
+		 * Add a conditional to the front of a clique, i.e. a conditional whose
+		 * parents are already in the clique or its separators.  This function does
+		 * not check for this condition, it just updates the data structures.
+		 */
+		static void addToCliqueFront(BayesTree<CONDITIONAL,CLIQUE>& bayesTree,
+		    const sharedConditional& conditional, const sharedClique& clique);
+
+		/** Fill the nodes index for a subtree */
+		void fillNodesIndex(const sharedClique& subtree);
+
+    /** Helper function to build a non-symbolic tree (e.g. Gaussian) using a
+     * symbolic tree, used in the BT(BN) constructor.
+     */
+		void recursiveTreeBuild(const boost::shared_ptr<BayesTreeClique<IndexConditional> >& symbolic,
+		      const std::vector<boost::shared_ptr<CONDITIONAL> >& conditionals,
+		      const typename BayesTree<CONDITIONAL,CLIQUE>::sharedClique& parent);
+
   private:
 
     /** deep copy to another tree */

gtsam/inference/EliminationTree.h

@@ -73,39 +73,11 @@ private:
   Factors factors_; ///< factors associated with root
   SubTrees subTrees_; ///< sub-trees
 
+public:
+
 	/// @name Standard Constructors
 	/// @{
 
-  /** default constructor, private, as you should use Create below */
-  EliminationTree(Index key = 0) : key_(key) {}
-
-	/// @}
-	/// @name Advanced Interface
-	/// @{
-
-  /**
-   * Static internal function to build a vector of parent pointers using the
-   * algorithm of Gilbert et al., 2001, BIT.
-   */
-  static std::vector<Index> ComputeParents(const VariableIndex& structure);
-
-  /** add a factor, for Create use only */
-  void add(const sharedFactor& factor) { factors_.push_back(factor); }
-
-  /** add a subtree, for Create use only */
-  void add(const shared_ptr& child) { subTrees_.push_back(child); }
-
-  /**
-   * Recursive routine that eliminates the factors arranged in an elimination tree
-   * @param Conditionals is a vector of shared pointers that will be modified in place
-   */
-  sharedFactor eliminate_(Eliminate function, Conditionals& conditionals) const;
-
-  /// Allow access to constructor and add methods for testing purposes
-  friend class ::EliminationTreeTester;
-
-public:
-
   /**
    * Named constructor to build the elimination tree of a factor graph using
    * pre-computed column structure.
@@ -151,6 +123,32 @@ public:
 
 	/// @}
 
+private:
+	
+  /** default constructor, private, as you should use Create below */
+  EliminationTree(Index key = 0) : key_(key) {}
+
+  /**
+   * Static internal function to build a vector of parent pointers using the
+   * algorithm of Gilbert et al., 2001, BIT.
+   */
+  static std::vector<Index> ComputeParents(const VariableIndex& structure);
+
+  /** add a factor, for Create use only */
+  void add(const sharedFactor& factor) { factors_.push_back(factor); }
+
+  /** add a subtree, for Create use only */
+  void add(const shared_ptr& child) { subTrees_.push_back(child); }
+
+  /**
+   * Recursive routine that eliminates the factors arranged in an elimination tree
+   * @param Conditionals is a vector of shared pointers that will be modified in place
+   */
+  sharedFactor eliminate_(Eliminate function, Conditionals& conditionals) const;
+
+  /// Allow access to constructor and add methods for testing purposes
+  friend class ::EliminationTreeTester;
+
 };
 
 

gtsam/inference/Factor.h

@@ -81,15 +81,6 @@ protected:
   /// The keys involved in this factor
   std::vector<KeyType> keys_;
 
-  friend class JacobianFactor;
-  friend class HessianFactor;
-
-protected:
-
-  /// Internal consistency check that is run frequently when in debug mode.
-  /// If NDEBUG is defined, this is empty and optimized out.
-  void assertInvariants() const;
-
 public:
 
 	/// @name Standard Constructors
@@ -212,9 +203,15 @@ public:
   iterator begin() { return keys_.begin(); }	///TODO: comment
   iterator end() { return keys_.end(); }			///TODO: comment
 
+protected:
+	friend class JacobianFactor;
+	friend class HessianFactor;
+
+	/// Internal consistency check that is run frequently when in debug mode.
+	/// If NDEBUG is defined, this is empty and optimized out.
+	void assertInvariants() const;
 
 private:
-
   /** Serialization function */
   friend class boost::serialization::access;
   template<class Archive>

gtsam/linear/JacobianFactor.h

@@ -78,11 +78,9 @@ namespace gtsam {
    * \f[ E(x) = \frac{1}{2} (A_1 x_{j1} + A_2 x_{j2} - b)^T \Sigma^{-1} (A_1 x_{j1} + A_2 x_{j2} - b) . \f]
    */
   class JacobianFactor : public GaussianFactor {
-  public:
-  	typedef Matrix AbMatrix;
-  	typedef VerticalBlockView<AbMatrix> BlockAb;
-
   protected:
+		typedef Matrix AbMatrix;
+		typedef VerticalBlockView<AbMatrix> BlockAb;
 
     noiseModel::Diagonal::shared_ptr model_; // Gaussian noise model with diagonal covariance matrix
     std::vector<size_t> firstNonzeroBlocks_;
@@ -97,8 +95,6 @@ namespace gtsam {
     typedef BlockAb::Column BVector;
     typedef BlockAb::constColumn constBVector;
 
-  public:
-
     /** Copy constructor */
     JacobianFactor(const JacobianFactor& gf);
 

gtsam/nonlinear/DoglegOptimizer.h

@@ -67,7 +67,6 @@ private:
  */
 class DoglegState : public NonlinearOptimizerState {
 public:
-
   double Delta;
 
   DoglegState() {}
@@ -86,8 +85,11 @@ protected:
  */
 class DoglegOptimizer : public NonlinearOptimizer {
 
-public:
+protected:
+	DoglegParams params_;
+	DoglegState state_;
 
+public:
   typedef boost::shared_ptr<DoglegOptimizer> shared_ptr;
 
   /// @name Standard interface
@@ -143,9 +145,6 @@ public:
   /// @}
 
 protected:
-  DoglegParams params_;
-  DoglegState state_;
-
   /** Access the parameters (base class version) */
   virtual const NonlinearOptimizerParams& _params() const { return params_; }
 

gtsam/nonlinear/GaussNewtonOptimizer.h

@@ -43,8 +43,11 @@ protected:
  */
 class GaussNewtonOptimizer : public NonlinearOptimizer {
 
-public:
+protected:
+	GaussNewtonParams params_;
+	GaussNewtonState state_;
 
+public:
   /// @name Standard interface
   /// @{
 
@@ -94,10 +97,6 @@ public:
   /// @}
 
 protected:
-
-  GaussNewtonParams params_;
-  GaussNewtonState state_;
-
   /** Access the parameters (base class version) */
   virtual const NonlinearOptimizerParams& _params() const { return params_; }
 

gtsam/nonlinear/LevenbergMarquardtOptimizer.h

@@ -42,12 +42,6 @@ public:
     DAMPED
   };
 
-private:
-  VerbosityLM verbosityLMTranslator(const std::string &s) const;
-  std::string verbosityLMTranslator(VerbosityLM value) const;
-
-public:
-
   double lambdaInitial; ///< The initial Levenberg-Marquardt damping term (default: 1e-5)
   double lambdaFactor; ///< The amount by which to multiply or divide lambda when adjusting lambda (default: 10.0)
   double lambdaUpperBound; ///< The maximum lambda to try before assuming the optimization has failed (default: 1e5)
@@ -67,6 +61,10 @@ public:
   inline void setlambdaFactor(double value) { lambdaFactor = value; }
   inline void setlambdaUpperBound(double value) { lambdaUpperBound = value; }
   inline void setVerbosityLM(const std::string &s) { verbosityLM = verbosityLMTranslator(s); }
+
+private:
+	VerbosityLM verbosityLMTranslator(const std::string &s) const;
+	std::string verbosityLMTranslator(VerbosityLM value) const;
 };
 
 /**
@@ -74,20 +72,18 @@ public:
  */
 class LevenbergMarquardtState : public NonlinearOptimizerState {
 
-protected:
-
-  LevenbergMarquardtState(const NonlinearFactorGraph& graph, const Values& initialValues, const LevenbergMarquardtParams& params, unsigned int iterations = 0) :
-    NonlinearOptimizerState(graph, initialValues, iterations), lambda(params.lambdaInitial) {}
-
-  friend class LevenbergMarquardtOptimizer;
-
 public:
-
   double lambda;
 
   LevenbergMarquardtState() {}
 
   virtual ~LevenbergMarquardtState() {}
+
+protected:
+	LevenbergMarquardtState(const NonlinearFactorGraph& graph, const Values& initialValues, const LevenbergMarquardtParams& params, unsigned int iterations = 0) :
+		NonlinearOptimizerState(graph, initialValues, iterations), lambda(params.lambdaInitial) {}
+
+	friend class LevenbergMarquardtOptimizer;
 };
 
 /**
@@ -96,26 +92,11 @@ public:
 class LevenbergMarquardtOptimizer : public NonlinearOptimizer {
 
 protected:
-
   LevenbergMarquardtParams params_; ///< LM parameters
   LevenbergMarquardtState state_;   ///< optimization state
   std::vector<size_t> dimensions_;  ///< undocumented
 
-  /** Access the parameters (base class version) */
-  virtual const NonlinearOptimizerParams& _params() const { return params_; }
-
-  /** Access the state (base class version) */
-  virtual const NonlinearOptimizerState& _state() const { return state_; }
-
-  /** Internal function for computing a COLAMD ordering if no ordering is specified */
-  LevenbergMarquardtParams ensureHasOrdering(LevenbergMarquardtParams params, const NonlinearFactorGraph& graph, const Values& values) const {
-    if(!params.ordering)
-      params.ordering = *graph.orderingCOLAMD(values);
-    return params;
-  }
-
 public:
-
   typedef boost::shared_ptr<LevenbergMarquardtOptimizer> shared_ptr;
 
   /// @name Standard interface
@@ -176,6 +157,20 @@ public:
   const LevenbergMarquardtState& state() const { return state_; }
 
   /// @}
+
+protected:
+	/** Access the parameters (base class version) */
+	virtual const NonlinearOptimizerParams& _params() const { return params_; }
+
+	/** Access the state (base class version) */
+	virtual const NonlinearOptimizerState& _state() const { return state_; }
+
+	/** Internal function for computing a COLAMD ordering if no ordering is specified */
+	LevenbergMarquardtParams ensureHasOrdering(LevenbergMarquardtParams params, const NonlinearFactorGraph& graph, const Values& values) const {
+		if(!params.ordering)
+			params.ordering = *graph.orderingCOLAMD(values);
+		return params;
+	}
 };
 
 }

gtsam/nonlinear/Marginals.h

@@ -88,11 +88,6 @@ protected:
   BlockView blockView_;
   Ordering indices_;
 
-  JointMarginal(const Matrix& fullMatrix, const std::vector<size_t>& dims, const Ordering& indices) :
-    fullMatrix_(fullMatrix), blockView_(fullMatrix_, dims.begin(), dims.end()), indices_(indices) {}
-
-  friend class Marginals;
-
 public:
   /** A block view of the joint marginal - this stores a reference to the
    * JointMarginal object, so the JointMarginal object must be kept in scope
@@ -129,6 +124,13 @@ public:
 
 	/** Print */
 	void print(const std::string& s = "", const KeyFormatter& formatter = DefaultKeyFormatter) const;
+
+protected:
+	JointMarginal(const Matrix& fullMatrix, const std::vector<size_t>& dims, const Ordering& indices) :
+		fullMatrix_(fullMatrix), blockView_(fullMatrix_, dims.begin(), dims.end()), indices_(indices) {}
+
+	friend class Marginals;
+
 };
 
 } /* namespace gtsam */

gtsam/nonlinear/NonlinearOptimizer.h

@@ -177,23 +177,9 @@ Values::const_shared_ptr result = DoglegOptimizer(graph, initialValues, params).
 class NonlinearOptimizer {
 
 protected:
-
   NonlinearFactorGraph graph_;
 
-  /** A default implementation of the optimization loop, which calls iterate()
-   * until checkConvergence returns true.
-   */
-  void defaultOptimize();
-
-  virtual const NonlinearOptimizerState& _state() const = 0;
-
-  virtual const NonlinearOptimizerParams& _params() const = 0;
-
-  /** Constructor for initial construction of base classes. */
-  NonlinearOptimizer(const NonlinearFactorGraph& graph) : graph_(graph) {}
-
 public:
-
   /** A shared pointer to this class */
   typedef boost::shared_ptr<const NonlinearOptimizer> shared_ptr;
 
@@ -243,6 +229,20 @@ public:
   virtual void iterate() = 0;
 
   /// @}
+
+protected:	
+  /** A default implementation of the optimization loop, which calls iterate()
+   * until checkConvergence returns true.
+   */
+  void defaultOptimize();
+
+  virtual const NonlinearOptimizerState& _state() const = 0;
+
+  virtual const NonlinearOptimizerParams& _params() const = 0;
+
+  /** Constructor for initial construction of base classes. */
+  NonlinearOptimizer(const NonlinearFactorGraph& graph) : graph_(graph) {}
+
 };
 
 /** Check whether the relative error decrease is less than relativeErrorTreshold,

gtsam/nonlinear/Values.h

@@ -123,8 +123,6 @@ namespace gtsam {
 
     typedef KeyValuePair value_type;
 
-  public:
-
     /** A filtered view of a Values, returned from Values::filter. */
     template<class ValueType = Value>
     class Filtered;
@@ -196,7 +194,6 @@ namespace gtsam {
     /** Get a zero VectorValues of the correct structure */
     VectorValues zeroVectors(const Ordering& ordering) const;
 
-  public:
     const_iterator begin() const { return boost::make_transform_iterator(values_.begin(), &make_const_deref_pair); }
     const_iterator end() const { return boost::make_transform_iterator(values_.end(), &make_const_deref_pair); }
     iterator begin() { return boost::make_transform_iterator(values_.begin(), &make_deref_pair); }