Changes in progress

gtsam/nonlinear/DoglegOptimizer.h

@@ -22,6 +22,44 @@
 
 namespace gtsam {
 
+/** Parameters for Levenberg-Marquardt optimization.  Note that this parameters
+ * class inherits from NonlinearOptimizerParams, which specifies the parameters
+ * common to all nonlinear optimization algorithms.  This class also contains
+ * all of those parameters.
+ */
+class DoglegParams : public SuccessiveLinearizationParams {
+public:
+  /** See DoglegParams::dlVerbosity */
+  enum DLVerbosity {
+    SILENT,
+    VERBOSE
+  };
+
+  double deltaInitial; ///< The initial trust region radius (default: 1.0)
+  DLVerbosity dlVerbosity; ///< The verbosity level for Dogleg (default: SILENT), see also NonlinearOptimizerParams::verbosity
+
+  DoglegParams() :
+    deltaInitial(1.0), dlVerbosity(SILENT) {}
+
+  virtual ~DoglegParams() {}
+
+  virtual void print(const std::string& str = "") const {
+    SuccessiveLinearizationParams::print(str);
+    std::cout << "               deltaInitial: " << deltaInitial << "\n";
+    std::cout.flush();
+  }
+};
+
+/**
+ * State for DoglegOptimizer
+ */
+class DoglegState : public SuccessiveLinearizationState {
+public:
+
+  double delta;
+
+};
+
 /**
  * This class performs Dogleg nonlinear optimization
  */
@@ -98,42 +136,4 @@ protected:
   }
 };
 
-/** Parameters for Levenberg-Marquardt optimization.  Note that this parameters
- * class inherits from NonlinearOptimizerParams, which specifies the parameters
- * common to all nonlinear optimization algorithms.  This class also contains
- * all of those parameters.
- */
-class DoglegParams : public SuccessiveLinearizationParams {
-public:
-  /** See DoglegParams::dlVerbosity */
-  enum DLVerbosity {
-    SILENT,
-    VERBOSE
-  };
-
-  double deltaInitial; ///< The initial trust region radius (default: 1.0)
-  DLVerbosity dlVerbosity; ///< The verbosity level for Dogleg (default: SILENT), see also NonlinearOptimizerParams::verbosity
-
-  DoglegParams() :
-    deltaInitial(1.0), dlVerbosity(SILENT) {}
-
-  virtual ~DoglegParams() {}
-
-  virtual void print(const std::string& str = "") const {
-    SuccessiveLinearizationParams::print(str);
-    std::cout << "               deltaInitial: " << deltaInitial << "\n";
-    std::cout.flush();
-  }
-};
-
-/**
- * State for DoglegOptimizer
- */
-class DoglegState : public SuccessiveLinearizationState {
-public:
-
-  double delta;
-
-};
-
 }

gtsam/nonlinear/GaussNewtonOptimizer.h

@@ -22,6 +22,12 @@
 
 namespace gtsam {
 
+/** Parameters for Gauss-Newton optimization, inherits from
+ * NonlinearOptimizationParams.
+ */
+class GaussNewtonParams : public SuccessiveLinearizationParams {
+};
+
 /**
  * This class performs Gauss-Newton nonlinear optimization
  */
@@ -98,10 +104,4 @@ protected:
 
 };
 
-/** Parameters for Gauss-Newton optimization, inherits from
- * NonlinearOptimizationParams.
- */
-class GaussNewtonParams : public SuccessiveLinearizationParams {
-};
-
 }

gtsam/nonlinear/LevenbergMarquardtOptimizer.h

@@ -22,6 +22,52 @@
 
 namespace gtsam {
 
+/** Parameters for Levenberg-Marquardt optimization.  Note that this parameters
+ * class inherits from NonlinearOptimizerParams, which specifies the parameters
+ * common to all nonlinear optimization algorithms.  This class also contains
+ * all of those parameters.
+ */
+class LevenbergMarquardtParams : public SuccessiveLinearizationParams {
+public:
+  /** See LevenbergMarquardtParams::lmVerbosity */
+  enum LMVerbosity {
+    SILENT,
+    LAMBDA,
+    TRYLAMBDA,
+    TRYCONFIG,
+    TRYDELTA,
+    DAMPED
+  };
+
+  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)
+  LMVerbosity lmVerbosity; ///< The verbosity level for Levenberg-Marquardt (default: SILENT), see also NonlinearOptimizerParams::verbosity
+
+  LevenbergMarquardtParams() :
+    lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), lmVerbosity(SILENT) {}
+
+  virtual ~LevenbergMarquardtParams() {}
+
+  virtual void print(const std::string& str = "") const {
+    SuccessiveLinearizationParams::print(str);
+    std::cout << "              lambdaInitial: " << lambdaInitial << "\n";
+    std::cout << "               lambdaFactor: " << lambdaFactor << "\n";
+    std::cout << "           lambdaUpperBound: " << lambdaUpperBound << "\n";
+    std::cout.flush();
+  }
+};
+
+/**
+ * State for LevenbergMarquardtOptimizer
+ */
+class LevenbergMarquardtState : public NonlinearOptimizerState {
+public:
+
+  double lambda;
+
+};
+
 /**
  * This class performs Levenberg-Marquardt nonlinear optimization
  */
@@ -44,7 +90,8 @@ public:
    */
   LevenbergMarquardtOptimizer(const NonlinearFactorGraph& graph, const Values& initialValues,
       const LevenbergMarquardtParams& params = LevenbergMarquardtParams()) :
-        NonlinearOptimizer(graph), params_(ensureHasOrdering(params)), state_(graph, initialValues), dimensions_(initialValues.dims(*params_.ordering)) {}
+        NonlinearOptimizer(graph), params_(ensureHasOrdering(params)),
+        state_(graph, initialValues), dimensions_(initialValues.dims(*params_.ordering)) {}
 
   /** Standard constructor, requires a nonlinear factor graph, initial
    * variable assignments, and optimization parameters.  For convenience this
@@ -100,50 +147,4 @@ protected:
   }
 };
 
-/** Parameters for Levenberg-Marquardt optimization.  Note that this parameters
- * class inherits from NonlinearOptimizerParams, which specifies the parameters
- * common to all nonlinear optimization algorithms.  This class also contains
- * all of those parameters.
- */
-class LevenbergMarquardtParams : public SuccessiveLinearizationParams {
-public:
-  /** See LevenbergMarquardtParams::lmVerbosity */
-  enum LMVerbosity {
-    SILENT,
-    LAMBDA,
-    TRYLAMBDA,
-    TRYCONFIG,
-    TRYDELTA,
-    DAMPED
-  };
-
-  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)
-  LMVerbosity lmVerbosity; ///< The verbosity level for Levenberg-Marquardt (default: SILENT), see also NonlinearOptimizerParams::verbosity
-
-  LevenbergMarquardtParams() :
-    lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), lmVerbosity(SILENT) {}
-
-  virtual ~LevenbergMarquardtParams() {}
-
-  virtual void print(const std::string& str = "") const {
-    SuccessiveLinearizationParams::print(str);
-    std::cout << "              lambdaInitial: " << lambdaInitial << "\n";
-    std::cout << "               lambdaFactor: " << lambdaFactor << "\n";
-    std::cout << "           lambdaUpperBound: " << lambdaUpperBound << "\n";
-    std::cout.flush();
-  }
-};
-
-/**
- * State for LevenbergMarquardtOptimizer
- */
-class LevenbergMarquardtState : public NonlinearOptimizerState {
-public:
-
-  double lambda;
-
-};
-
 }