diff --git a/gtsam/base/make_shared.h b/gtsam/base/make_shared.h index 5281eec6d..164bae77a 100644 --- a/gtsam/base/make_shared.h +++ b/gtsam/base/make_shared.h @@ -26,7 +26,7 @@ #include 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 using enable_if_t = typename std::enable_if::type; } diff --git a/gtsam/base/timing.h b/gtsam/base/timing.h index 972bb45f7..db0060bfb 100644 --- a/gtsam/base/timing.h +++ b/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_; diff --git a/gtsam/geometry/Rot2.h b/gtsam/geometry/Rot2.h index 2690ca248..b0b7fd52a 100644 --- a/gtsam/geometry/Rot2.h +++ b/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); diff --git a/gtsam/geometry/Rot3.h b/gtsam/geometry/Rot3.h index 01ca7778c..09abb70bc 100644 --- a/gtsam/geometry/Rot3.h +++ b/gtsam/geometry/Rot3.h @@ -129,7 +129,7 @@ class GTSAM_EXPORT Rot3 : public LieGroup { 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); diff --git a/gtsam/geometry/SO4.h b/gtsam/geometry/SO4.h index 33bd8c161..7503b012b 100644 --- a/gtsam/geometry/SO4.h +++ b/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$. */ GTSAM_EXPORT Matrix43 stiefel(const SO4 &Q, OptionalJacobian<12, 6> H = boost::none); diff --git a/gtsam/geometry/SOn.h b/gtsam/geometry/SOn.h index af0e7a3cf..fc2092af1 100644 --- a/gtsam/geometry/SOn.h +++ b/gtsam/geometry/SOn.h @@ -121,7 +121,8 @@ class SO : public LieGroup, internal::DimensionSO(N)> { /// currently only defined for SO3. static SO ClosestTo(const MatrixNN& M); - /// Named constructor that finds chordal mean = argmin_R \sum sqr(|R-R_i|_F), + /// Named constructor that finds chordal mean + /// \f$ mu = argmin_R \sum sqr(|R-R_i|_F) \f$, /// currently only defined for SO3. static SO ChordalMean(const std::vector& rotations); diff --git a/gtsam/linear/AcceleratedPowerMethod.h b/gtsam/linear/AcceleratedPowerMethod.h index 6653d43c9..daa59fc1b 100644 --- a/gtsam/linear/AcceleratedPowerMethod.h +++ b/gtsam/linear/AcceleratedPowerMethod.h @@ -74,8 +74,8 @@ class AcceleratedPowerMethod : public PowerMethod { /** * Run accelerated power iteration to get ritzVector with beta and previous - * two ritzVector x0 and x00, and return y = (A * x0 - \beta * x00) / || A * x0 - * - \beta * x00 || + * two ritzVector x0 and x00, and return + * \f$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 { /** * 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 - * - \beta * x00 || + * two ritzVector x0 and x00, and return + * \f$y = (A * x0 - \beta * x00) / || A * x0 - \beta * x00 ||\f$ */ Vector acceleratedPowerIteration () const { Vector y = acceleratedPowerIteration(this->ritzVector_, previousVector_, beta_); diff --git a/gtsam/linear/HessianFactor.h b/gtsam/linear/HessianFactor.h index 7020d6edd..8394b2ee8 100644 --- a/gtsam/linear/HessianFactor.h +++ b/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; diff --git a/gtsam/nonlinear/ExtendedKalmanFilter.h b/gtsam/nonlinear/ExtendedKalmanFilter.h index df27d16ff..dc51de7bb 100644 --- a/gtsam/nonlinear/ExtendedKalmanFilter.h +++ b/gtsam/nonlinear/ExtendedKalmanFilter.h @@ -86,8 +86,9 @@ class ExtendedKalmanFilter { /// @{ /** - * Calculate predictive density P(x_) ~ \int P(x_min) P(x_min, x_) - * The motion model should be given as a factor with key1 for x_min and key2_ for x + * Calculate predictive density + * \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); diff --git a/gtsam_unstable/dynamics/Pendulum.h b/gtsam_unstable/dynamics/Pendulum.h index 470d7108b..1e0ca621c 100644 --- a/gtsam_unstable/dynamics/Pendulum.h +++ b/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) - * = (1/h)mr^2 (q_{k+1}-q_k) + mgrh(1-alpha) sin ((1-alpha)q_k+\alpha q_{k+1}) + * \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$ + * \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 { 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) - * = (1/h)mr^2 (q_{k+1}-q_k) - mgrh alpha sin ((1-alpha)q_k+\alpha q_{k+1}) + * \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$ + * \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 { public: diff --git a/gtsam_unstable/dynamics/SimpleHelicopter.h b/gtsam_unstable/dynamics/SimpleHelicopter.h index bf3b95c0f..1fb895833 100644 --- a/gtsam_unstable/dynamics/SimpleHelicopter.h +++ b/gtsam_unstable/dynamics/SimpleHelicopter.h @@ -40,7 +40,7 @@ public: return boost::static_pointer_cast( 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$, with optional derivatives */ Vector evaluateError(const Pose3& gk1, const Pose3& gk, const Vector6& xik, boost::optional H1 = boost::none, boost::optional H2 = boost::none, @@ -195,5 +195,4 @@ public: }; - -} /* namespace gtsam */ +} // namespace gtsam diff --git a/gtsam_unstable/linear/ActiveSetSolver.h b/gtsam_unstable/linear/ActiveSetSolver.h index 318912cf3..ad8367c06 100644 --- a/gtsam_unstable/linear/ActiveSetSolver.h +++ b/gtsam_unstable/linear/ActiveSetSolver.h @@ -102,7 +102,7 @@ protected: /** * Compute minimum step size alpha to move from the current point @p xk to the * next feasible point along a direction @p p: x' = xk + alpha*p, - * where alpha \in [0,maxAlpha]. + * where alpha \f$\in\f$ [0,maxAlpha]. * * For QP, maxAlpha = 1. For LP: maxAlpha = Inf. * diff --git a/gtsam_unstable/linear/LPInitSolver.h b/gtsam_unstable/linear/LPInitSolver.h index 14e5fb000..7e326117b 100644 --- a/gtsam_unstable/linear/LPInitSolver.h +++ b/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 diff --git a/gtsam_unstable/nonlinear/LinearizedFactor.h b/gtsam_unstable/nonlinear/LinearizedFactor.h index 1ae8a7906..151bf8a25 100644 --- a/gtsam_unstable/nonlinear/LinearizedFactor.h +++ b/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 upper-triangular part of the + /** Return a copy of the block at (j1,j2) of the upper-triangular part 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 upper-triangular part of the full squared term, as described above. + /** Return the upper-triangular part 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. */