fix latex symbol warnings

gtsam/base/make_shared.h

@@ -26,7 +26,7 @@
 #include <type_traits>
 
 namespace gtsam {
-  /// An shorthand alias for accessing the ::type inside std::enable_if that can be used in a template directly
+  /// An shorthand alias for accessing the \::type inside std::enable_if that can be used in a template directly
   template<bool B, class T = void>
   using enable_if_t = typename std::enable_if<B, T>::type;
 }

gtsam/base/timing.h

@@ -147,7 +147,7 @@ namespace gtsam {
       size_t id_;
       size_t t_;
       size_t tWall_;
-      double t2_ ; ///< cache the \sum t_i^2
+      double t2_ ; ///< cache the \f$ \sum t_i^2 \f$
       size_t tIt_;
       size_t tMax_;
       size_t tMin_;

gtsam/geometry/Rot2.h

@@ -86,7 +86,7 @@ namespace gtsam {
     static Rot2 atan2(double y, double x);
 
     /**
-     * Random, generates random angle \in [-p,pi]
+     * Random, generates random angle \f$\in\f$ [-pi,pi]
      * Example:
      *   std::mt19937 engine(42);
      *   Unit3 unit = Unit3::Random(engine);

gtsam/geometry/Rot3.h

@@ -129,7 +129,7 @@ class GTSAM_EXPORT Rot3 : public LieGroup<Rot3, 3> {
     Rot3(double w, double x, double y, double z) : Rot3(Quaternion(w, x, y, z)) {}
 
     /**
-     * Random, generates a random axis, then random angle \in [-p,pi]
+     * Random, generates a random axis, then random angle \f$\in\f$ [-pi,pi]
      * Example:
      *   std::mt19937 engine(42);
      *   Unit3 unit = Unit3::Random(engine);

gtsam/geometry/SO4.h

@@ -74,7 +74,7 @@ GTSAM_EXPORT Matrix3 topLeft(const SO4 &Q, OptionalJacobian<9, 6> H = boost::non
 
 /**
  * Project to Stiefel manifold of 4*3 orthonormal 3-frames in R^4, i.e., pi(Q)
- * -> S \in St(3,4).
+ * -> \f$ S \in St(3,4) \f$.
  */
 GTSAM_EXPORT Matrix43 stiefel(const SO4 &Q, OptionalJacobian<12, 6> H = boost::none);
 

gtsam/geometry/SOn.h

@@ -121,7 +121,8 @@ class SO : public LieGroup<SO<N>, internal::DimensionSO(N)> {
   /// currently only defined for SO3.
   static SO ClosestTo(const MatrixNN& M);
 
-  /// Named constructor that finds chordal mean = argmin_R \sum sqr(|R-R_i|_F),
+  /// Named constructor that finds chordal mean
+  /// \f$ mu = argmin_R \sum sqr(|R-R_i|_F) \f$,
   /// currently only defined for SO3.
   static SO ChordalMean(const std::vector<SO>& rotations);
 

gtsam/linear/AcceleratedPowerMethod.h

@@ -74,8 +74,8 @@ class AcceleratedPowerMethod : public PowerMethod<Operator> {
 
   /**
    * Run accelerated power iteration to get ritzVector with beta and previous
-   * two ritzVector x0 and x00, and return y = (A * x0 - \beta * x00) / || A * x0
+   * two ritzVector x0 and x00, and return 
-   * - \beta * x00 ||
+   *   \f$y = (A * x0 - \beta * x00) / || A * x0 - \beta * x00 ||\f$
    */
   Vector acceleratedPowerIteration (const Vector &x1, const Vector &x0,
                         const double beta) const {
@@ -86,8 +86,8 @@ class AcceleratedPowerMethod : public PowerMethod<Operator> {
 
   /**
    * Run accelerated power iteration to get ritzVector with beta and previous
-   * two ritzVector x0 and x00, and return y = (A * x0 - \beta * x00) / || A * x0
+   * two ritzVector x0 and x00, and return
-   * - \beta * x00 ||
+   *  \f$y = (A * x0 - \beta * x00) / || A * x0 - \beta * x00 ||\f$
    */
   Vector acceleratedPowerIteration () const {
     Vector y = acceleratedPowerIteration(this->ritzVector_, previousVector_, beta_);

gtsam/linear/HessianFactor.h

@@ -338,7 +338,7 @@ namespace gtsam {
 
     /**
      * Compute the gradient at a key:
-     *      \grad f(x_i) = \sum_j G_ij*x_j - g_i
+     *  \f$ \grad f(x_i) = \sum_j G_ij*x_j - g_i \f$
      */
     Vector gradient(Key key, const VectorValues& x) const override;
 

gtsam/nonlinear/ExtendedKalmanFilter.h

@@ -86,8 +86,9 @@ class ExtendedKalmanFilter {
   /// @{
 
   /**
-   * Calculate predictive density P(x_) ~ \int  P(x_min) P(x_min, x_)
+   * Calculate predictive density
-   * The motion model should be given as a factor with key1 for x_min and key2_ for x
+   *     \f$ P(x_) ~ \int  P(x_min) P(x_min, x_)\f$ 
+   * The motion model should be given as a factor with key1 for \f$x_min\f$ and key2 for \f$x_\f$ 
    */
   T predict(const NoiseModelFactor& motionFactor);
 

gtsam_unstable/dynamics/Pendulum.h

@@ -110,8 +110,8 @@ public:
 //*************************************************************************
 /**
  * This class implements the first position-momentum update rule
- *    p_k = -D_1 L_d(q_k,q_{k+1},h) = \frac{1}{h}mr^{2}\left(q_{k+1}-q_{k}\right)+mgrh(1-\alpha)\,\sin\left((1-\alpha)q_{k}+\alpha q_{k+1}\right)
+ *  \f$ p_k = -D_1 L_d(q_k,q_{k+1},h) = \frac{1}{h}mr^{2}\left(q_{k+1}-q_{k}\right)+mgrh(1-\alpha)\,\sin\left((1-\alpha)q_{k}+\alpha q_{k+1}\right) \f$
- *    = (1/h)mr^2 (q_{k+1}-q_k) + mgrh(1-alpha) sin ((1-alpha)q_k+\alpha q_{k+1})
+ *  \f$ = (1/h)mr^2 (q_{k+1}-q_k) + mgrh(1-alpha) sin ((1-alpha)q_k+\alpha q_{k+1}) \f$
  */
 class PendulumFactorPk: public NoiseModelFactor3<double, double, double> {
 public:
@@ -166,8 +166,8 @@ public:
 //*************************************************************************
 /**
  * This class implements the second position-momentum update rule
- *    p_k1 = D_2 L_d(q_k,q_{k+1},h) = \frac{1}{h}mr^{2}\left(q_{k+1}-q_{k}\right)-mgrh\alpha\sin\left((1-\alpha)q_{k}+\alpha q_{k+1}\right)
+ *  \f$ p_k1 = D_2 L_d(q_k,q_{k+1},h) = \frac{1}{h}mr^{2}\left(q_{k+1}-q_{k}\right)-mgrh\alpha\sin\left((1-\alpha)q_{k}+\alpha q_{k+1}\right) \f$
- *    = (1/h)mr^2 (q_{k+1}-q_k) - mgrh alpha sin ((1-alpha)q_k+\alpha q_{k+1})
+ *  \f$ = (1/h)mr^2 (q_{k+1}-q_k) - mgrh alpha sin ((1-alpha)q_k+\alpha q_{k+1}) \f$
  */
 class PendulumFactorPk1: public NoiseModelFactor3<double, double, double> {
 public:

gtsam_unstable/dynamics/SimpleHelicopter.h

@@ -40,7 +40,7 @@ public:
     return boost::static_pointer_cast<gtsam::NonlinearFactor>(
         gtsam::NonlinearFactor::shared_ptr(new Reconstruction(*this))); }
 
-  /** \f$ log((g_k\exp(h\xi_k))^{-1}g_{k+1}) = 0, with optional derivatives */
+  /** \f$ log((g_k\exp(h\xi_k))^{-1}g_{k+1}) = 0 \f$, with optional derivatives */
   Vector evaluateError(const Pose3& gk1, const Pose3& gk, const Vector6& xik,
       boost::optional<Matrix&> H1 = boost::none,
       boost::optional<Matrix&> H2 = boost::none,
@@ -195,5 +195,4 @@ public:
 
 };
 
-
+}  // namespace gtsam
-} /* namespace gtsam */

gtsam_unstable/linear/ActiveSetSolver.h

@@ -102,7 +102,7 @@ protected:
   /**
    * Compute minimum step size alpha to move from the current point @p xk to the
    * next feasible point along a direction @p p:  x' = xk + alpha*p,
-   * where alpha \in [0,maxAlpha].
+   * where alpha \f$\in\f$ [0,maxAlpha].
    *
    * For QP, maxAlpha = 1. For LP: maxAlpha = Inf.
    *

gtsam_unstable/linear/LPInitSolver.h

@@ -30,7 +30,7 @@ namespace gtsam {
  *    min y
  *    st Ax = b
  *       Cx - y <= d
- * where y \in R, x \in R^n, and Ax = b and Cx <= d is the constraints of the original problem.
+ * where \f$y \in R\f$, \f$x \in R^n\f$, and Ax = b and Cx <= d is the constraints of the original problem.
  *
  * If the solution for this problem {x*,y*} has y* <= 0, we'll have x* a feasible initial point
  * of the original problem

gtsam_unstable/nonlinear/LinearizedFactor.h

@@ -236,7 +236,7 @@ public:
     return info_.aboveDiagonalRange(0, size(), size(), size() + 1).col(0);
   }
 
-  /** Return a copy of the block at (j1,j2) of the <emph>upper-triangular part</emph> of the
+  /** Return a copy of the block at (j1,j2) of the <em>upper-triangular part</em> of the
    * squared term \f$ H \f$, no data is copied.  See HessianFactor class documentation
    * above to explain that only the upper-triangular part of the information matrix is stored
    * and returned by this function.
@@ -252,7 +252,7 @@ public:
     return info_.block(J1, J2);
   }
 
-  /** Return the <emph>upper-triangular part</emph> of the full squared term, as described above.
+  /** Return the <em>upper-triangular part</em> of the full squared term, as described above.
    * See HessianFactor class documentation above to explain that only the
    * upper-triangular part of the information matrix is stored and returned by this function.
    */