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gtsam 4.1.1
gtsam
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Global functions in a separate testing namespace. More...
Namespaces | |
| namespace | imuBias |
| All bias models live in the imuBias namespace. | |
| namespace | noiseModel |
| All noise models live in the noiseModel namespace. | |
| namespace | treeTraversal |
| Internal functions used for traversing trees. | |
Classes | |
| struct | _ValuesConstKeyValuePair |
| struct | _ValuesKeyValuePair |
| class | AcceleratedPowerMethod |
| Compute maximum Eigenpair with accelerated power method. More... | |
| class | AcceleratingScenario |
| Accelerating from an arbitrary initial state, with optional rotation. More... | |
| class | ActiveSetSolver |
| This class implements the active set algorithm for solving convex Programming problems. More... | |
| class | AdaptAutoDiff |
| The AdaptAutoDiff class uses ceres-style autodiff to adapt a ceres-style Function evaluation, i.e., a function FUNCTOR that defines an operator template<typename T> bool operator()(const T* const, const T* const, T*
predicted) const; For now only binary operators are supported. More... | |
| struct | additive_group_tag |
| class | AHRS |
| class | AHRSFactor |
| class | AlgebraicDecisionTree |
| Algebraic Decision Trees fix the range to double Just has some nice constructors and some syntactic sugar TODO: consider eliminating this class altogether? More... | |
| class | AllDiff |
| General AllDiff constraint Returns 1 if values for all keys are different, 0 otherwise DiscreteFactors are all awkward in that they have to store two types of keys: for each variable we have a Key and an Key. More... | |
| class | AntiFactor |
| class | Assignment |
| An assignment from labels to value index (size_t). More... | |
| class | AttitudeFactor |
| class | Basis |
| CRTP Base class for function bases. More... | |
| class | BatchFixedLagSmoother |
| class | BayesNet |
| A BayesNet is a tree of conditionals, stored in elimination order. More... | |
| class | BayesTree |
| class | BayesTreeCliqueBase |
| This is the base class for BayesTree cliques. More... | |
| struct | BayesTreeCliqueData |
| store all the sizes More... | |
| struct | BayesTreeCliqueStats |
| clique statistics More... | |
| class | BayesTreeOrphanWrapper |
| struct | Bearing |
| struct | Bearing< Pose2, T > |
| struct | Bearing< Pose3, Point3 > |
| struct | Bearing< Pose3, Pose3 > |
| struct | BearingFactor |
| struct | BearingRange |
| Bearing-Range product for a particular A1,A2 combination will use the functors above to create a similar functor of type A1*A2 -> pair<Bearing::return_type,Range::return_type> For example BearingRange<Pose2,Point2>(pose,point) will return pair<Rot2,double> and BearingRange<Pose3,Point3>(pose,point) will return pair<Unit3,double> More... | |
| class | BearingRangeFactor |
| class | BetweenConstraint |
| Binary between constraint - forces between to a given value This constraint requires the underlying type to a Lie type. More... | |
| class | BetweenFactor |
| class | BetweenFactorEM |
| class | BiasedGPSFactor |
| class | BinaryAllDiff |
| Binary AllDiff constraint Returns 1 if values for two keys are different, 0 otherwise DiscreteFactors are all awkward in that they have to store two types of keys: for each variable we have a Index and an Index. More... | |
| struct | BinaryJacobianFactor |
| A binary JacobianFactor specialization that uses fixed matrix math for speed. More... | |
| class | BinaryMeasurement |
| class | BinarySumExpression |
| A BinarySumExpression is a specialization of Expression that adds two expressions together It optimizes the Jacobian calculation for this specific case. More... | |
| class | BlockJacobiPreconditioner |
| struct | BlockJacobiPreconditionerParameters |
| struct | BoundingConstraint1 |
| struct | BoundingConstraint2 |
| Binary scalar inequality constraint, with a similar value() function to implement for specific systems. More... | |
| class | BTree |
| class | Cal3 |
| class | Cal3_S2 |
| class | Cal3_S2Stereo |
| class | Cal3Bundler |
| class | Cal3DS2 |
| class | Cal3DS2_Base |
| class | Cal3Fisheye |
| class | Cal3Unified |
| class | CalibratedCamera |
| struct | CameraProjectionMatrix |
| Create a 3*4 camera projection matrix from calibration and pose. More... | |
| class | CameraSet |
| A set of cameras, all with their own calibration. More... | |
| struct | CGState |
| struct | Chebyshev1Basis |
| Basis of Chebyshev polynomials of the first kind https://en.wikipedia.org/wiki/Chebyshev_polynomials#First_kind These are typically denoted with the symbol T_n, where n is the degree. More... | |
| class | Chebyshev2 |
| Chebyshev Interpolation on Chebyshev points of the second kind Note that N here, the number of points, is one less than N from 'Approximation Theory and Approximation Practice by L. More... | |
| struct | Chebyshev2Basis |
| Basis of Chebyshev polynomials of the second kind. More... | |
| class | CheiralityException |
| class | CholeskyFailed |
| Indicate Cholesky factorization failure. More... | |
| class | ClusterTree |
| A cluster-tree is associated with a factor graph and is defined as in Koller-Friedman: each node k represents a subset \( C_k \sub X \), and the tree is family preserving, in that each factor \( f_i \) is associated with a single cluster and \( scope(f_i) \sub C_k \). More... | |
| class | CombinedImuFactor |
| class | ComponentDerivativeFactor |
A unary factor which enforces the evaluation of the derivative of a BASIS polynomial is equal to the scalar value at a specific index i of a vector-valued measurement z. More... | |
| class | compose_key_visitor |
| class | ConcurrentBatchFilter |
| A Levenberg-Marquardt Batch Filter that implements the Concurrent Filtering and Smoother interface. More... | |
| class | ConcurrentBatchSmoother |
| A Levenberg-Marquardt Batch Smoother that implements the Concurrent Filtering and Smoother interface. More... | |
| class | ConcurrentFilter |
| The interface for the 'Filter' portion of the Concurrent Filtering and Smoother architecture. More... | |
| class | ConcurrentIncrementalFilter |
| An iSAM2-based Batch Filter that implements the Concurrent Filtering and Smoother interface. More... | |
| class | ConcurrentIncrementalSmoother |
| A Levenberg-Marquardt Batch Smoother that implements the Concurrent Filtering and Smoother interface. More... | |
| class | ConcurrentMap |
| class | ConcurrentSmoother |
| The interface for the 'Smoother' portion of the Concurrent Filtering and Smoother architecture. More... | |
| class | Conditional |
| TODO: Update comments. More... | |
| class | ConjugateGradientParameters |
| parameters for the conjugate gradient method More... | |
| struct | const_selector |
| Helper class that uses templates to select between two types based on whether TEST_TYPE is const or not. More... | |
| struct | const_selector< BASIC_TYPE, BASIC_TYPE, AS_NON_CONST, AS_CONST > |
| Specialization for the non-const version. More... | |
| struct | const_selector< const BASIC_TYPE, BASIC_TYPE, AS_NON_CONST, AS_CONST > |
| Specialization for the const version. More... | |
| class | ConstantTwistScenario |
| Scenario with constant twist 3D trajectory. More... | |
| class | ConstantVelocityFactor |
| Binary factor for applying a constant velocity model to a moving body represented as a NavState. More... | |
| class | Constraint |
| Base class for discrete probabilistic factors The most general one is the derived DecisionTreeFactor. More... | |
| struct | ConstructorTraversalData |
| class | CRefCallAddCopy |
| Helper. More... | |
| class | CRefCallPushBack |
| Helper. More... | |
| class | CSP |
| Constraint Satisfaction Problem class A specialization of a DiscreteFactorGraph. More... | |
| class | CustomFactor |
| class | Cyclic |
| Cyclic group of order N. More... | |
| class | DecisionTree |
| Decision Tree L = label for variables Y = function range (any algebra), e.g., bool, int, double. More... | |
| class | DecisionTreeFactor |
| A discrete probabilistic factor. More... | |
| class | DeltaFactor |
| DeltaFactor: relative 2D measurement between Pose2 and Point2. More... | |
| class | DeltaFactorBase |
| DeltaFactorBase: relative 2D measurement between Pose2 and Point2, with Basenodes. More... | |
| struct | DeltaImpl |
| class | DerivativeFactor |
A unary factor which enforces the evaluation of the derivative of a BASIS polynomial at a specified pointx is equal to the scalar measurement z. More... | |
| struct | DGroundConstraint |
| Ground constraint: forces the robot to be upright (no roll, pitch), a fixed height, and no velocity in z direction Dim: 4. More... | |
| struct | DHeightPrior |
| Forces the value of the height (z) in a PoseRTV to a specific value. More... | |
| class | DirectProduct |
| class | DirectSum |
| Template to construct the direct sum of two additive groups Assumes existence of three additive operators for both groups. More... | |
| class | DiscreteBayesNet |
| A Bayes net made from linear-Discrete densities. More... | |
| class | DiscreteBayesTree |
| A Bayes tree representing a Discrete density. More... | |
| class | DiscreteBayesTreeClique |
| A clique in a DiscreteBayesTree. More... | |
| class | DiscreteConditional |
| Discrete Conditional Density Derives from DecisionTreeFactor. More... | |
| class | DiscreteEliminationTree |
| class | DiscreteEulerPoincareHelicopter |
| Implement the Discrete Euler-Poincare' equation: More... | |
| class | DiscreteFactor |
| Base class for discrete probabilistic factors The most general one is the derived DecisionTreeFactor. More... | |
| class | DiscreteFactorGraph |
| A Discrete Factor Graph is a factor graph where all factors are Discrete, i.e. More... | |
| class | DiscreteJunctionTree |
| struct | DiscreteKeys |
| DiscreteKeys is a set of keys that can be assembled using the & operator. More... | |
| class | DiscreteMarginals |
| A class for computing marginals of variables in a DiscreteFactorGraph. More... | |
| class | DoglegOptimizer |
| This class performs Dogleg nonlinear optimization. More... | |
| struct | DoglegOptimizerImpl |
| This class contains the implementation of the Dogleg algorithm. More... | |
| class | DoglegParams |
| Parameters for Levenberg-Marquardt optimization. More... | |
| class | Domain |
| Domain restriction constraint. More... | |
| struct | DRollPrior |
| Forces the roll to a particular value - useful for flying robots Implied value is zero Dim: 1. More... | |
| class | DSF |
| class | DSFBase |
| class | DSFMap |
| class | DSFVector |
| struct | Dummy |
| class | DummyFactor |
| class | DummyPreconditioner |
| struct | DummyPreconditionerParameters |
| class | DynamicValuesMismatched |
| class | EliminatableClusterTree |
| A cluster-tree that eliminates to a Bayes tree. More... | |
| class | EliminateableFactorGraph |
| EliminateableFactorGraph is a base class for factor graphs that contains elimination algorithms. More... | |
| struct | EliminationData |
| struct | EliminationTraits |
| Traits class for eliminateable factor graphs, specifies the types that result from elimination, etc. More... | |
| struct | EliminationTraits< DiscreteFactorGraph > |
| struct | EliminationTraits< GaussianFactorGraph > |
| struct | EliminationTraits< SymbolicFactorGraph > |
| class | EliminationTree |
| An elimination tree is a data structure used intermediately during elimination. More... | |
| class | EqualityFactorGraph |
| Collection of all Linear Equality constraints Ax=b of a Programming problem as a Factor Graph. More... | |
| struct | equals |
| Template to create a binary predicate. More... | |
| struct | equals_star |
| Binary predicate on shared pointers. More... | |
| class | EquivInertialNavFactor_GlobalVel |
| class | EquivInertialNavFactor_GlobalVel_NoBias |
| class | Errors |
| vector of errors More... | |
| class | EssentialMatrix |
| An essential matrix is like a Pose3, except with translation up to scale It is named after the 3*3 matrix aEb = [aTb]x aRb from computer vision, but here we choose instead to parameterize it as a (Rot3,Unit3) pair. More... | |
| class | EssentialMatrixConstraint |
| class | EssentialMatrixFactor |
| Factor that evaluates epipolar error p'Ep for given essential matrix. More... | |
| class | EssentialMatrixFactor2 |
| Binary factor that optimizes for E and inverse depth d: assumes measurement in image 2 is perfect, and returns re-projection error in image 1. More... | |
| class | EssentialMatrixFactor3 |
| Binary factor that optimizes for E and inverse depth d: assumes measurement in image 2 is perfect, and returns re-projection error in image 1 This version takes an extrinsic rotation to allow for omni-directional rigs. More... | |
| class | EssentialMatrixFactor4 |
| Binary factor that optimizes for E and calibration K using the algebraic epipolar error (K^-1 pA)'E (K^-1 pB). More... | |
| class | EvaluationFactor |
Factor for enforcing the scalar value of the polynomial BASIS representation at x is the same as the measurement z when using a pseudo-spectral parameterization. More... | |
| class | Expression |
| Expression class that supports automatic differentiation. More... | |
| class | ExpressionFactor |
| Factor that supports arbitrary expressions via AD. More... | |
| class | ExpressionFactorGraph |
| Factor graph that supports adding ExpressionFactors directly. More... | |
| class | ExpressionFactorN |
| N-ary variadic template for ExpressionFactor meant as a base class for N-ary factors. More... | |
| class | ExtendedKalmanFilter |
| This is a generic Extended Kalman Filter class implemented using nonlinear factors. More... | |
| class | Factor |
| This is the base class for all factor types. More... | |
| class | FactorGraph |
| A factor graph is a bipartite graph with factor nodes connected to variable nodes. More... | |
| class | FastList |
| class | FastMap |
| class | FastSet |
| class | FitBasis |
| Class that does regression via least squares Example usage: size_t N = 3; auto fit = FitBasis<Chebyshev2>(data_points, noise_model, N); Vector coefficients = fit.parameters();. More... | |
| struct | FixedDimension |
| Give fixed size dimension of a type, fails at compile time if dynamic. More... | |
| class | FixedLagSmoother |
| class | FixedVector |
| Fixed size vectors - compatible with boost vectors, but with compile-type size checking. More... | |
| class | FourierBasis |
| Fourier basis. More... | |
| class | FrobeniusBetweenFactor |
| FrobeniusBetweenFactor is a BetweenFactor that evaluates the Frobenius norm of the rotation error between measured and predicted (rather than the Logmap of the error). More... | |
| class | FrobeniusFactor |
| FrobeniusFactor calculates the Frobenius norm between rotation matrices. More... | |
| class | FrobeniusPrior |
| FrobeniusPrior calculates the Frobenius norm between a given matrix and an element of SO(3) or SO(4). More... | |
| class | FullIMUFactor |
| Class that represents integrating IMU measurements over time for dynamic systems This factor has dimension 9, with a built-in constraint for velocity modeling. More... | |
| class | FunctorizedFactor |
| Factor which evaluates provided unary functor and uses the result to compute error with respect to the provided measurement. More... | |
| class | FunctorizedFactor2 |
| Factor which evaluates provided binary functor and uses the result to compute error with respect to the provided measurement. More... | |
| class | G_x1 |
| Helper class that computes the derivative of f w.r.t. More... | |
| class | GaussianBayesNet |
| A Bayes net made from linear-Gaussian densities. More... | |
| class | GaussianBayesTree |
| A Bayes tree representing a Gaussian density. More... | |
| class | GaussianBayesTreeClique |
| A clique in a GaussianBayesTree. More... | |
| class | GaussianConditional |
| A conditional Gaussian functions as the node in a Bayes network It has a set of parents y,z, etc. More... | |
| class | GaussianDensity |
| A Gaussian density. More... | |
| class | GaussianEliminationTree |
| class | GaussianFactor |
| An abstract virtual base class for JacobianFactor and HessianFactor. More... | |
| class | GaussianFactorGraph |
| A Linear Factor Graph is a factor graph where all factors are Gaussian, i.e. More... | |
| class | GaussianFactorGraphSystem |
| System class needed for calling preconditionedConjugateGradient. More... | |
| class | GaussianISAM |
| class | GaussianJunctionTree |
| class | GaussMarkov1stOrderFactor |
| class | GaussNewtonOptimizer |
| This class performs Gauss-Newton nonlinear optimization. More... | |
| class | GaussNewtonParams |
| Parameters for Gauss-Newton optimization, inherits from NonlinearOptimizationParams. More... | |
| class | GeneralSFMFactor |
| class | GeneralSFMFactor2 |
| Non-linear factor for a constraint derived from a 2D measurement. More... | |
| class | GenericProjectionFactor |
| class | GenericStereoFactor |
| class | GenericValue |
| Wraps any type T so it can play as a Value. More... | |
| class | GncOptimizer |
| class | GncParams |
| class | GPSFactor |
| class | GPSFactor2 |
| struct | GraphvizFormatting |
| Formatting options when saving in GraphViz format using NonlinearFactorGraph::saveGraph. More... | |
| struct | group_tag |
| tag to assert a type is a group More... | |
| struct | HasBearing |
| struct | HasRange |
| struct | HasTestablePrereqs |
| Requirements on type to pass it to Testable template below. More... | |
| class | HessianFactor |
| A Gaussian factor using the canonical parameters (information form) More... | |
| class | IMUFactor |
| Class that represents integrating IMU measurements over time for dynamic systems Templated to allow for different key types, but variables all assumed to be PoseRTV. More... | |
| class | ImuFactor |
| class | ImuFactor2 |
| class | InconsistentEliminationRequested |
| An inference algorithm was called with inconsistent arguments. More... | |
| class | IncrementalFixedLagSmoother |
| This is a base class for the various HMF2 implementations. More... | |
| class | IndeterminantLinearSystemException |
| Thrown when a linear system is ill-posed. More... | |
| class | IndexPair |
| Small utility class for representing a wrappable pairs of ints. More... | |
| class | InequalityFactorGraph |
| Collection of all Linear Inequality constraints Ax-b <= 0 of a Programming problem as a Factor Graph. More... | |
| class | InertialNavFactor_GlobalVelocity |
| class | InfeasibleInitialValues |
| An exception indicating that the provided initial value is infeasible Also used to inzdicatethat the noise model dimension passed into a JacobianFactor has a different dimensionality than the factor. More... | |
| class | InfeasibleOrUnboundedProblem |
| struct | InitializePose3 |
| class | InvalidArgumentThreadsafe |
| Thread-safe invalid argument exception. More... | |
| class | InvalidDenseElimination |
| class | InvalidMatrixBlock |
| An exception indicating that a matrix block passed into a JacobianFactor has a different dimensionality than the factor. More... | |
| class | InvalidNoiseModel |
| An exception indicating that the noise model dimension passed into a JacobianFactor has a different dimensionality than the factor. More... | |
| class | InvDepthFactor3 |
| Ternary factor representing a visual measurement that includes inverse depth. More... | |
| class | InvDepthFactorVariant1 |
| Binary factor representing a visual measurement using an inverse-depth parameterization. More... | |
| class | InvDepthFactorVariant2 |
| Binary factor representing a visual measurement using an inverse-depth parameterization. More... | |
| class | InvDepthFactorVariant3a |
| Binary factor representing the first visual measurement using an inverse-depth parameterization. More... | |
| class | InvDepthFactorVariant3b |
| Ternary factor representing a visual measurement using an inverse-depth parameterization. More... | |
| class | ISAM |
| A Bayes tree with an update methods that implements the iSAM algorithm. More... | |
| class | ISAM2 |
| class | ISAM2BayesTree |
| class | ISAM2Clique |
| Specialized Clique structure for ISAM2, incorporating caching and gradient contribution TODO: more documentation. More... | |
| struct | ISAM2DoglegParams |
| struct | ISAM2GaussNewtonParams |
| class | ISAM2JunctionTree |
| struct | ISAM2Params |
| struct | ISAM2Result |
| struct | ISAM2UpdateParams |
| class | IsGroup |
| Group Concept. More... | |
| class | IsLieGroup |
| Lie Group Concept. More... | |
| class | IsTestable |
| class | IsVectorSpace |
| Vector Space concept. More... | |
| class | IterativeOptimizationParameters |
| parameters for iterative linear solvers More... | |
| class | IterativeSolver |
| Base class for Iterative Solvers like SubgraphSolver. More... | |
| class | JacobianFactor |
| A Gaussian factor in the squared-error form. More... | |
| class | JacobianFactorQ |
| JacobianFactor for Schur complement that uses Q noise model. More... | |
| class | JacobianFactorQR |
| JacobianFactor for Schur complement that uses Q noise model. More... | |
| class | JacobianFactorSVD |
| JacobianFactor for Schur complement that uses the "Nullspace Trick" by Mourikis et al. More... | |
| class | JointMarginal |
| A class to store and access a joint marginal, returned from Marginals::jointMarginalCovariance and Marginals::jointMarginalInformation. More... | |
| class | JunctionTree |
| class | KalmanFilter |
| Kalman Filter class. More... | |
| class | KarcherMeanFactor |
| The KarcherMeanFactor creates a constraint on all SO(n) variables with given keys that the Karcher mean (see above) will stay the same. More... | |
| class | key_formatter |
| Output stream manipulator that will format gtsam::Keys according to the given KeyFormatter, as long as Key values are wrapped in a gtsam::StreamedKey. More... | |
| class | KeyInfo |
| Handy data structure for iterative solvers. More... | |
| struct | KeyInfoEntry |
| Handy data structure for iterative solvers key to (index, dimension, start) More... | |
| class | LabeledSymbol |
| Customized version of gtsam::Symbol for multi-robot use. More... | |
| class | LevenbergMarquardtOptimizer |
| This class performs Levenberg-Marquardt nonlinear optimization. More... | |
| class | LevenbergMarquardtParams |
| Parameters for Levenberg-Marquardt optimization. More... | |
| struct | lie_group_tag |
| tag to assert a type is a Lie group More... | |
| struct | LieGroup |
| A CRTP helper class that implements Lie group methods Prerequisites: methods operator*, inverse, and AdjointMap, as well as a ChartAtOrigin struct that will be used to define the manifold Chart To use, simply derive, but also say "using LieGroup<Class,N>::inverse" For derivative math, see doc/math.pdf. More... | |
| class | Line3 |
| class | LinearContainerFactor |
| Dummy version of a generic linear factor to be injected into a nonlinear factor graph. More... | |
| class | LinearCost |
| This class defines a linear cost function c'x which is a JacobianFactor with only one row. More... | |
| class | LinearEquality |
| This class defines a linear equality constraints, inheriting JacobianFactor with the special Constrained noise model. More... | |
| class | LinearInequality |
| This class defines a linear inequality constraint Ax-b <= 0, inheriting JacobianFactor with the special Constrained noise model. More... | |
| class | LinearizedGaussianFactor |
| A base factor class for the Jacobian and Hessian linearized factors. More... | |
| class | LinearizedHessianFactor |
| A factor that takes a linear, Hessian factor and inserts it into a nonlinear graph. More... | |
| class | LinearizedJacobianFactor |
| A factor that takes a linear, Jacobian factor and inserts it into a nonlinear graph. More... | |
| class | ListOfOneContainer |
| A helper class that behaves as a container with one element, and works with boost::range. More... | |
| class | LocalOrientedPlane3Factor |
| Factor to measure a planar landmark from a given pose, with a given local linearization point. More... | |
| struct | LP |
| Data structure of a Linear Program. More... | |
| class | LPInitSolver |
| This LPInitSolver implements the strategy in Matlab: http://www.mathworks.com/help/optim/ug/linear-programming-algorithms.html#brozyzb-9 Solve for x and y: 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. More... | |
| struct | LPPolicy |
| Policy for ActivetSetSolver to solve Linear Programming. More... | |
| class | MagFactor |
| Factor to estimate rotation given magnetometer reading This version uses model measured bM = scale * bRn * direction + bias and assumes scale, direction, and the bias are given. More... | |
| class | MagFactor1 |
| Factor to estimate rotation given magnetometer reading This version uses model measured bM = scale * bRn * direction + bias and assumes scale, direction, and the bias are given. More... | |
| class | MagFactor2 |
| Factor to calibrate local Earth magnetic field as well as magnetometer bias This version uses model measured bM = bRn * nM + bias and optimizes for both nM and the bias, where nM is in units defined by magnetometer. More... | |
| class | MagFactor3 |
| Factor to calibrate local Earth magnetic field as well as magnetometer bias This version uses model measured bM = scale * bRn * direction + bias and optimizes for both scale, direction, and the bias. More... | |
| class | MagPoseFactor |
| Factor to estimate rotation of a Pose2 or Pose3 given a magnetometer reading. More... | |
| struct | MakeJacobian |
| : meta-function to generate Jacobian More... | |
| struct | MakeOptionalJacobian |
| : meta-function to generate JacobianTA optional reference Used mainly by Expressions More... | |
| struct | manifold_tag |
| tag to assert a type is a manifold More... | |
| class | ManifoldEvaluationFactor |
| For a measurement value of type T i.e. More... | |
| class | ManifoldPreintegration |
| IMU pre-integration on NavSatet manifold. More... | |
| class | MarginalizeNonleafException |
| Thrown when requesting to marginalize out variables from ISAM2 that are not leaves. More... | |
| class | Marginals |
| A class for computing Gaussian marginals of variables in a NonlinearFactorGraph. More... | |
| class | Mechanization_bRn2 |
| class | MetisIndex |
| The MetisIndex class converts a factor graph into the Compressed Sparse Row format for use in METIS algorithms. More... | |
| class | MFAS |
| struct | multiplicative_group_tag |
| Group operator syntax flavors. More... | |
| struct | MultiplyWithInverse |
| Functor that implements multiplication of a vector b with the inverse of a matrix A. More... | |
| struct | MultiplyWithInverseFunction |
| Functor that implements multiplication with the inverse of a matrix, itself the result of a function f. More... | |
| class | MultiProjectionFactor |
| class | NavState |
| Navigation state: Pose (rotation, translation) + velocity NOTE(frank): it does not make sense to make this a Lie group, but it is a 9D manifold. More... | |
| struct | needs_eigen_aligned_allocator |
| A SFINAE trait to mark classes that need special alignment. More... | |
| struct | needs_eigen_aligned_allocator< T, void_t< typename T::_eigen_aligned_allocator_trait > > |
| class | NoiseModelFactor |
| A nonlinear sum-of-squares factor with a zero-mean noise model implementing the density \( P(z|x) \propto exp -0.5*|z-h(x)|^2_C \) Templated on the parameter type X and the values structure Values There is no return type specified for h(x). More... | |
| class | NoiseModelFactor1 |
| A convenient base class for creating your own NoiseModelFactor with 1 variable. More... | |
| class | NoiseModelFactor2 |
| A convenient base class for creating your own NoiseModelFactor with 2 variables. More... | |
| class | NoiseModelFactor3 |
| A convenient base class for creating your own NoiseModelFactor with 3 variables. More... | |
| class | NoiseModelFactor4 |
| A convenient base class for creating your own NoiseModelFactor with 4 variables. More... | |
| class | NoiseModelFactor5 |
| A convenient base class for creating your own NoiseModelFactor with 5 variables. More... | |
| class | NoiseModelFactor6 |
| A convenient base class for creating your own NoiseModelFactor with 6 variables. More... | |
| class | NoMatchFoundForFixed |
| class | NonlinearClusterTree |
| class | NonlinearConjugateGradientOptimizer |
| An implementation of the nonlinear CG method using the template below. More... | |
| class | NonlinearEquality |
| An equality factor that forces either one variable to a constant, or a set of variables to be equal to each other. More... | |
| class | NonlinearEquality1 |
| Simple unary equality constraint - fixes a value for a variable. More... | |
| class | NonlinearEquality2 |
| Simple binary equality constraint - this constraint forces two variables to be the same. More... | |
| class | NonlinearFactor |
| Nonlinear factor base class. More... | |
| class | NonlinearFactorGraph |
| A non-linear factor graph is a graph of non-Gaussian, i.e. More... | |
| class | NonlinearISAM |
| Wrapper class to manage ISAM in a nonlinear context. More... | |
| class | NonlinearOptimizer |
| This is the abstract interface for classes that can optimize for the maximum-likelihood estimate of a NonlinearFactorGraph. More... | |
| class | NonlinearOptimizerParams |
| The common parameters for Nonlinear optimizers. More... | |
| class | OdometryFactorBase |
| OdometryFactorBase: Pose2 odometry, with Basenodes. More... | |
| class | OptionalJacobian |
| OptionalJacobian is an Eigen::Ref like class that can take be constructed using either a fixed size or dynamic Eigen matrix. More... | |
| class | OptionalJacobian< Eigen::Dynamic, Eigen::Dynamic > |
| class | Ordering |
| class | ordering_key_visitor |
| class | OrientedPlane3 |
| Represents an infinite plane in 3D, which is composed of a planar normal and its perpendicular distance to the origin. More... | |
| class | OrientedPlane3DirectionPrior |
| class | OrientedPlane3Factor |
| Factor to measure a planar landmark from a given pose. More... | |
| class | OutOfRangeThreadsafe |
| Thread-safe out of range exception. More... | |
| class | ParameterMatrix |
| A matrix abstraction of MxN values at the Basis points. More... | |
| class | PartialPriorFactor |
| A class for a soft partial prior on any Lie type, with a mask over Expmap parameters. More... | |
| class | PCGSolver |
| A virtual base class for the preconditioned conjugate gradient solver. More... | |
| struct | PCGSolverParameters |
| Parameters for PCG. More... | |
| class | PendulumFactor1 |
| This class implements the first constraint. More... | |
| class | PendulumFactor2 |
| This class implements the second constraint the. More... | |
| class | PendulumFactorPk |
| 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}) More... | |
| class | PendulumFactorPk1 |
| 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}) More... | |
| class | PinholeBase |
| class | PinholeBaseK |
| class | PinholeCamera |
| class | PinholePose |
| class | PinholeSet |
| PinholeSet: triangulates point and keeps an estimate of it around. More... | |
| class | Pose2 |
| class | Pose3 |
| class | Pose3AttitudeFactor |
| class | PoseBetweenFactor |
| class | PoseConcept |
| Pose Concept A must contain a translation and a rotation, with each structure accessable directly and a type provided for each. More... | |
| class | PosePriorFactor |
| class | PoseRotationPrior |
| class | PoseRTV |
| Robot state for use with IMU measurements. More... | |
| class | PoseToPointFactor |
| class | PoseTranslationPrior |
| A prior on the translation part of a pose. More... | |
| class | Potentials |
| A base class for both DiscreteFactor and DiscreteConditional. More... | |
| class | PowerMethod |
| Compute maximum Eigenpair with power method. More... | |
| class | Preconditioner |
| struct | PreconditionerParameters |
| class | PredecessorMap |
| Map from variable key to parent key. More... | |
| class | PreintegratedAhrsMeasurements |
| PreintegratedAHRSMeasurements accumulates (integrates) the Gyroscope measurements (rotation rates) and the corresponding covariance matrix. More... | |
| class | PreintegratedCombinedMeasurements |
| class | PreintegratedImuMeasurements |
| class | PreintegratedRotation |
| PreintegratedRotation is the base class for all PreintegratedMeasurements classes (in AHRSFactor, ImuFactor, and CombinedImuFactor). More... | |
| struct | PreintegratedRotationParams |
| Parameters for pre-integration: Usage: Create just a single Params and pass a shared pointer to the constructor. More... | |
| class | PreintegrationBase |
| PreintegrationBase is the base class for PreintegratedMeasurements (in ImuFactor) and CombinedPreintegratedMeasurements (in CombinedImuFactor). More... | |
| struct | PreintegrationCombinedParams |
| Parameters for pre-integration using PreintegratedCombinedMeasurements: Usage: Create just a single Params and pass a shared pointer to the constructor. More... | |
| struct | PreintegrationParams |
| Parameters for pre-integration: Usage: Create just a single Params and pass a shared pointer to the constructor. More... | |
| class | PriorFactor |
| class | ProductLieGroup |
| Template to construct the product Lie group of two other Lie groups Assumes Lie group structure for G and H. More... | |
| class | ProjectionFactorPPP |
| class | ProjectionFactorPPPC |
| class | ProjectionFactorRollingShutter |
| struct | QP |
| Struct contains factor graphs of a Quadratic Programming problem. More... | |
| class | QPInitSolver |
| This class finds a feasible solution for a QP problem. More... | |
| struct | QPPolicy |
| Policy for ActivetSetSolver to solve Linear Programming. More... | |
| class | QPSParser |
| class | QPSParserException |
| struct | Range |
| struct | Range< CalibratedCamera, T > |
| struct | Range< PinholeCamera< Calibration >, T > |
| struct | Range< Point2, Point2 > |
| struct | Range< Point3, Point3 > |
| struct | Range< Pose2, T > |
| struct | Range< Pose3, T > |
| struct | Range< PoseRTV, PoseRTV > |
| class | RangeFactor |
| class | RangeFactorWithTransform |
| class | Reconstruction |
| Implement the Reconstruction equation: \( g_{k+1} = g_k \exp (h\xi_k) \), where \( h \): timestep (parameter) \( g_{k+1}, g_{k} \): poses at the current and the next timestep \( \xi_k \): the body-fixed velocity (Lie algebra) It is somewhat similar to BetweenFactor, but treats the body-fixed velocity \( \xi_k \) as a variable. More... | |
| struct | RedirectCout |
| For Python str(). More... | |
| class | RefCallPushBack |
| Helper. More... | |
| class | ReferenceFrameFactor |
| A constraint between two landmarks in separate maps Templated on: Point : Type of landmark Transform : Transform variable class. More... | |
| class | RegularHessianFactor |
| class | RegularImplicitSchurFactor |
| RegularImplicitSchurFactor. More... | |
| class | RegularJacobianFactor |
| JacobianFactor with constant sized blocks Provides raw memory access versions of linear operator. More... | |
| class | RelativeElevationFactor |
| Binary factor for a relative elevation. More... | |
| struct | Reshape |
| Reshape functor. More... | |
| struct | Reshape< M, M, InOptions, M, M, InOptions > |
| Reshape specialization that does nothing as shape stays the same (needed to not be ambiguous for square input equals square output) More... | |
| struct | Reshape< M, N, InOptions, M, N, InOptions > |
| Reshape specialization that does nothing as shape stays the same. More... | |
| struct | Reshape< N, M, InOptions, M, N, InOptions > |
| Reshape specialization that does transpose. More... | |
| class | Rot2 |
| class | Rot3 |
| class | Rot3AttitudeFactor |
| class | RotateDirectionsFactor |
| Factor on unknown rotation iRc that relates two directions c Directions provide less constraints than a full rotation. More... | |
| class | RotateFactor |
| Factor on unknown rotation iRC that relates two incremental rotations c1Rc2 = iRc' * i1Ri2 * iRc Which we can write (see doc/math.lyx) e^[z] = iRc' * e^[p] * iRc = e^([iRc'*p]) with z and p measured and predicted angular velocities, and hence p = iRc * z. More... | |
| class | RuntimeErrorThreadsafe |
| Thread-safe runtime error exception. More... | |
| class | Sampler |
| Sampling structure that keeps internal random number generators for diagonal distributions specified by NoiseModel. More... | |
| class | ScalarMultiplyExpression |
| A ScalarMultiplyExpression is a specialization of Expression that multiplies with a scalar It optimizes the Jacobian calculation for this specific case. More... | |
| class | Scatter |
| Scatter is an intermediate data structure used when building a HessianFactor incrementally, to get the keys in the right order. More... | |
| class | Scenario |
| Simple trajectory simulator. More... | |
| class | ScenarioRunner |
| class | Scheduler |
| Scheduler class Creates one variable for each student, and three variables for each of the student's areas, for a total of 4*nrStudents variables. More... | |
| class | SDGraph |
| SDGraph is undirected graph with variable keys and double edge weights. More... | |
| struct | SfmData |
| Define the structure for SfM data. More... | |
| struct | SfmTrack |
| Define the structure for the 3D points. More... | |
| class | SGraph |
| class | ShonanAveraging |
| Class that implements Shonan Averaging from our ECCV'20 paper. More... | |
| class | ShonanAveraging2 |
| class | ShonanAveraging3 |
| struct | ShonanAveragingParameters |
| Parameters governing optimization etc. More... | |
| class | ShonanFactor |
| ShonanFactor is a BetweenFactor that moves in SO(p), but will land on the SO(d) sub-manifold of SO(p) at the global minimum. More... | |
| class | ShonanGaugeFactor |
| The ShonanGaugeFactor creates a constraint on a single SO(n) to avoid moving in the stabilizer. More... | |
| class | Signature |
| Signature for a discrete conditional density, used to construct conditionals. More... | |
| class | Similarity3 |
| 3D similarity transform More... | |
| class | SingleValue |
| SingleValue constraint. More... | |
| struct | SlotEntry |
| One SlotEntry stores the slot index for a variable, as well its dim. More... | |
| class | SmartFactorBase |
| Base class for smart factors. More... | |
| class | SmartProjectionFactor |
| SmartProjectionFactor: triangulates point and keeps an estimate of it around. More... | |
| struct | SmartProjectionParams |
| class | SmartProjectionPoseFactor |
| class | SmartProjectionPoseFactorRollingShutter |
| class | SmartProjectionRigFactor |
| class | SmartRangeFactor |
| class | SmartStereoProjectionFactor |
| SmartStereoProjectionFactor: triangulates point and keeps an estimate of it around. More... | |
| class | SmartStereoProjectionFactorPP |
| class | SmartStereoProjectionPoseFactor |
| class | SO |
| Manifold of special orthogonal rotation matrices SO<N>. More... | |
| class | StereoCamera |
| class | StereoCheiralityException |
| class | StereoPoint2 |
| struct | StreamedKey |
| To use the key_formatter on Keys, they must be wrapped in a StreamedKey. More... | |
| class | Subgraph |
| class | SubgraphBuilder |
| struct | SubgraphBuilderParameters |
| class | SubgraphPreconditioner |
| Subgraph conditioner class, as explained in the RSS 2010 submission. More... | |
| struct | SubgraphPreconditionerParameters |
| class | SubgraphSolver |
| This class implements the linear SPCG solver presented in Dellaert et al in IROS'10. More... | |
| struct | SubgraphSolverParameters |
| class | Symbol |
| Character and index key used to refer to variables. More... | |
| class | SymbolGenerator |
| Generates symbol shorthands with alternative names different than the one-letter predefined ones. More... | |
| class | SymbolicBayesNet |
| Symbolic Bayes Net. More... | |
| class | SymbolicBayesTree |
| A Bayes tree that represents the connectivity between variables but is not associated with any probability functions. More... | |
| class | SymbolicBayesTreeClique |
| A clique in a SymbolicBayesTree. More... | |
| class | SymbolicConditional |
| SymbolicConditional is a conditional with keys but no probability data, produced by symbolic elimination of SymbolicFactor. More... | |
| class | SymbolicEliminationTree |
| class | SymbolicFactor |
| SymbolicFactor represents a symbolic factor that specifies graph topology but is not associated with any numerical function. More... | |
| class | SymbolicFactorGraph |
| Symbolic Factor Graph. More... | |
| class | SymbolicISAM |
| class | SymbolicJunctionTree |
| class | SymmetricBlockMatrix |
| class | System |
| Helper class encapsulating the combined system |Ax-b_|^2 Needed to run Conjugate Gradients on matrices. More... | |
| class | TangentPreintegration |
| Integrate on the 9D tangent space of the NavState manifold. More... | |
| class | TbbOpenMPMixedScope |
| An object whose scope defines a block where TBB and OpenMP parallelism are mixed. More... | |
| struct | Testable |
| A helper that implements the traits interface for GTSAM types. More... | |
| class | ThreadsafeException |
| Base exception type that uses tbb_allocator if GTSAM is compiled with TBB. More... | |
| class | TOAFactor |
| A "Time of Arrival" factor - so little code seems hardly worth it :-) More... | |
| struct | traits |
| A manifold defines a space in which there is a notion of a linear tangent space that can be centered around a given point on the manifold. More... | |
| struct | traits< BearingFactor< A1, A2, T > > |
| traits More... | |
| struct | traits< BearingRange< A1, A2 > > |
| struct | traits< BearingRangeFactor< A1, A2, B, R > > |
| traits More... | |
| struct | traits< BetweenConstraint< VALUE > > |
| traits More... | |
| struct | traits< BetweenFactor< VALUE > > |
| traits More... | |
| struct | traits< BinaryJacobianFactor< M, N1, N2 > > |
| struct | traits< Cal3_S2 > |
| struct | traits< Cal3_S2Stereo > |
| struct | traits< Cal3Bundler > |
| struct | traits< Cal3DS2 > |
| struct | traits< Cal3Fisheye > |
| struct | traits< Cal3Unified > |
| struct | traits< CalibratedCamera > |
| struct | traits< CameraSet< CAMERA > > |
| struct | traits< CombinedImuFactor > |
| struct | traits< ConcurrentBatchFilter > |
| traits More... | |
| struct | traits< ConcurrentBatchSmoother > |
| traits More... | |
| struct | traits< ConcurrentIncrementalFilter > |
| traits More... | |
| struct | traits< ConcurrentIncrementalSmoother > |
| traits More... | |
| struct | traits< const Cal3_S2 > |
| struct | traits< const Cal3_S2Stereo > |
| struct | traits< const Cal3Bundler > |
| struct | traits< const Cal3DS2 > |
| struct | traits< const Cal3Fisheye > |
| struct | traits< const Cal3Unified > |
| struct | traits< const CalibratedCamera > |
| struct | traits< const CameraSet< CAMERA > > |
| struct | traits< const EssentialMatrix > |
| struct | traits< const Line3 > |
| struct | traits< const OrientedPlane3 > |
| struct | traits< const PinholeCamera< Calibration > > |
| struct | traits< const PinholePose< CALIBRATION > > |
| struct | traits< const PinholeSet< CAMERA > > |
| struct | traits< const Pose2 > |
| struct | traits< const Pose3 > |
| struct | traits< const Rot2 > |
| struct | traits< const Rot3 > |
| struct | traits< const Similarity3 > |
| struct | traits< const SO3 > |
| struct | traits< const SO4 > |
| struct | traits< const SO< N > > |
| struct | traits< const StereoCamera > |
| struct | traits< const StereoPoint2 > |
| struct | traits< const Unit3 > |
| struct | traits< Cyclic< N > > |
| Define cyclic group to be a model of the Additive Group concept. More... | |
| struct | traits< DecisionTreeFactor > |
| struct | traits< DirectProduct< G, H > > |
| struct | traits< DirectSum< G, H > > |
| struct | traits< DiscreteBayesNet > |
| struct | traits< DiscreteConditional > |
| struct | traits< DiscreteFactor > |
| struct | traits< DiscreteFactor::Values > |
| struct | traits< DiscreteFactorGraph > |
| traits More... | |
| struct | traits< double > |
| double More... | |
| struct | traits< Eigen::Matrix< double, -1, -1, Options, MaxRows, MaxCols > > |
| struct | traits< Eigen::Matrix< double, -1, 1, Options, MaxRows, MaxCols > > |
| struct | traits< Eigen::Matrix< double, 1, -1, Options, MaxRows, MaxCols > > |
| struct | traits< Eigen::Matrix< double, M, N, Options, MaxRows, MaxCols > > |
| struct | traits< EqualityFactorGraph > |
| traits More... | |
| struct | traits< Errors > |
| traits More... | |
| struct | traits< EssentialMatrix > |
| struct | traits< ExpressionFactor< T > > |
| traits More... | |
| struct | traits< ExpressionFactorN< T, Args... > > |
| traits More... | |
| struct | traits< float > |
| float More... | |
| struct | traits< FunctorizedFactor2< R, T1, T2 > > |
| traits More... | |
| struct | traits< FunctorizedFactor< R, T > > |
| traits More... | |
| struct | traits< GaussianBayesNet > |
| traits More... | |
| struct | traits< GaussianBayesTree > |
| traits More... | |
| struct | traits< GaussianConditional > |
| traits More... | |
| struct | traits< GaussianFactor > |
| traits More... | |
| struct | traits< GaussianFactorGraph > |
| traits More... | |
| struct | traits< GaussianISAM > |
| traits More... | |
| struct | traits< GaussMarkov1stOrderFactor< VALUE > > |
| traits More... | |
| struct | traits< GeneralSFMFactor2< CALIBRATION > > |
| struct | traits< GeneralSFMFactor< CAMERA, LANDMARK > > |
| struct | traits< GenericProjectionFactor< POSE, LANDMARK, CALIBRATION > > |
| traits More... | |
| struct | traits< GenericStereoFactor< T1, T2 > > |
| traits More... | |
| struct | traits< GenericValue< ValueType > > |
| struct | traits< HessianFactor > |
| traits More... | |
| struct | traits< imuBias::ConstantBias > |
| struct | traits< ImuFactor > |
| struct | traits< ImuFactor2 > |
| struct | traits< InequalityFactorGraph > |
| traits More... | |
| struct | traits< InertialNavFactor_GlobalVelocity< POSE, VELOCITY, IMUBIAS > > |
| traits More... | |
| struct | traits< ISAM2 > |
| traits More... | |
| struct | traits< JacobianFactor > |
| traits More... | |
| struct | traits< JacobianFactorQ< D, ZDim > > |
| struct | traits< Key > |
| struct | traits< LabeledSymbol > |
| traits More... | |
| struct | traits< Line3 > |
| struct | traits< LinearContainerFactor > |
| struct | traits< LinearCost > |
| traits More... | |
| struct | traits< LinearEquality > |
| traits More... | |
| struct | traits< LinearInequality > |
| traits More... | |
| struct | traits< LinearizedHessianFactor > |
| traits More... | |
| struct | traits< LinearizedJacobianFactor > |
| traits More... | |
| struct | traits< LP > |
| traits More... | |
| struct | traits< NavState > |
| struct | traits< noiseModel::Constrained > |
| struct | traits< noiseModel::Diagonal > |
| struct | traits< noiseModel::Gaussian > |
| traits More... | |
| struct | traits< noiseModel::Isotropic > |
| struct | traits< noiseModel::Unit > |
| struct | traits< NonlinearEquality1< VALUE > > |
| struct | traits< NonlinearEquality2< VALUE > > |
| struct | traits< NonlinearEquality< VALUE > > |
| struct | traits< NonlinearFactor > |
| traits More... | |
| struct | traits< NonlinearFactorGraph > |
| traits More... | |
| struct | traits< Ordering > |
| traits More... | |
| struct | traits< OrientedPlane3 > |
| struct | traits< ParameterMatrix< M > > |
| struct | traits< PinholeCamera< Calibration > > |
| struct | traits< PinholePose< CALIBRATION > > |
| struct | traits< PinholeSet< CAMERA > > |
| struct | traits< Pose2 > |
| struct | traits< Pose3 > |
| struct | traits< Pose3AttitudeFactor > |
| traits More... | |
| struct | traits< PoseRTV > |
| struct | traits< Potentials > |
| struct | traits< Potentials::ADT > |
| struct | traits< PreintegratedCombinedMeasurements > |
| struct | traits< PreintegratedImuMeasurements > |
| struct | traits< PreintegratedRotation > |
| struct | traits< PreintegrationCombinedParams > |
| struct | traits< PriorFactor< VALUE > > |
| traits More... | |
| struct | traits< ProductLieGroup< G, H > > |
| struct | traits< ProjectionFactorPPP< POSE, LANDMARK, CALIBRATION > > |
| traits More... | |
| struct | traits< ProjectionFactorPPPC< POSE, LANDMARK, CALIBRATION > > |
| traits More... | |
| struct | traits< ProjectionFactorRollingShutter > |
| traits More... | |
| struct | traits< QUATERNION_TYPE > |
| struct | traits< RangeFactor< A1, A2, T > > |
| traits More... | |
| struct | traits< RangeFactorWithTransform< A1, A2, T > > |
| traits More... | |
| struct | traits< ReferenceFrameFactor< T1, T2 > > |
| traits More... | |
| struct | traits< RegularHessianFactor< D > > |
| struct | traits< RegularImplicitSchurFactor< CAMERA > > |
| struct | traits< Rot2 > |
| struct | traits< Rot3 > |
| struct | traits< Rot3AttitudeFactor > |
| traits More... | |
| struct | traits< SfmData > |
| traits More... | |
| struct | traits< SfmTrack > |
| traits More... | |
| struct | traits< Similarity3 > |
| struct | traits< SmartProjectionFactor< CAMERA > > |
| traits More... | |
| struct | traits< SmartProjectionPoseFactor< CALIBRATION > > |
| traits More... | |
| struct | traits< SmartProjectionPoseFactorRollingShutter< CAMERA > > |
| traits More... | |
| struct | traits< SmartProjectionRigFactor< CAMERA > > |
| traits More... | |
| struct | traits< SmartStereoProjectionFactor > |
| traits More... | |
| struct | traits< SmartStereoProjectionFactorPP > |
| traits More... | |
| struct | traits< SmartStereoProjectionPoseFactor > |
| traits More... | |
| struct | traits< SO3 > |
| struct | traits< SO4 > |
| struct | traits< SO< N > > |
| struct | traits< StereoCamera > |
| struct | traits< StereoPoint2 > |
| struct | traits< Symbol > |
| traits More... | |
| struct | traits< SymbolicBayesNet > |
| traits More... | |
| struct | traits< SymbolicBayesTree > |
| struct | traits< SymbolicBayesTreeClique > |
| traits More... | |
| struct | traits< SymbolicConditional > |
| traits More... | |
| struct | traits< SymbolicEliminationTree > |
| traits More... | |
| struct | traits< SymbolicFactor > |
| traits More... | |
| struct | traits< SymbolicFactorGraph > |
| traits More... | |
| struct | traits< TransformBtwRobotsUnaryFactor< VALUE > > |
| traits More... | |
| struct | traits< TransformBtwRobotsUnaryFactorEM< VALUE > > |
| traits More... | |
| struct | traits< Unit3 > |
| struct | traits< Values > |
| traits More... | |
| struct | traits< VariableIndex > |
| traits More... | |
| struct | traits< VariableSlots > |
| traits More... | |
| struct | traits< VectorValues > |
| traits More... | |
| class | TransformBtwRobotsUnaryFactor |
| class | TransformBtwRobotsUnaryFactorEM |
| class | TransformCovariance |
| Functor for transforming covariance of T. More... | |
| class | TranslationFactor |
| class | TranslationRecovery |
| class | TriangulationCheiralityException |
| Exception thrown by triangulateDLT when landmark is behind one or more of the cameras. More... | |
| class | TriangulationFactor |
| struct | TriangulationParameters |
| class | TriangulationResult |
| TriangulationResult is an optional point, along with the reasons why it is invalid. More... | |
| class | TriangulationUnderconstrainedException |
| Exception thrown by triangulateDLT when SVD returns rank < 3. More... | |
| class | Unit3 |
| Represents a 3D point on a unit sphere. More... | |
| struct | UpdateImpl |
| Implementation functions for update method All of the methods below have clear inputs and outputs, even if not functional: iSAM2 is inherintly imperative. More... | |
| class | Value |
| This is the base class for any type to be stored in Values. More... | |
| class | ValueCloneAllocator |
| class | Values |
| A non-templated config holding any types of Manifold-group elements. More... | |
| struct | ValuesCastHelper |
| struct | ValuesCastHelper< const Value, CastedKeyValuePairType, KeyValuePairType > |
| struct | ValuesCastHelper< Value, CastedKeyValuePairType, KeyValuePairType > |
| class | ValuesIncorrectType |
| class | ValuesKeyAlreadyExists |
| class | ValuesKeyDoesNotExist |
| struct | ValueWithDefault |
| Helper struct that encapsulates a value with a default, this is just used as a member object so you don't have to specify defaults in the class constructor. More... | |
| class | VariableIndex |
| The VariableIndex class computes and stores the block column structure of a factor graph. More... | |
| class | VariableSlots |
| A combined factor is assembled as one block of rows for each component factor. More... | |
| struct | vector_space_tag |
| tag to assert a type is a vector space More... | |
| class | VectorComponentFactor |
| Unary factor for enforcing BASIS polynomial evaluation on a ParameterMatrix of size (P, N) is equal to specified measurement at the same point, when using a pseudo-spectral parameterization. More... | |
| class | VectorDerivativeFactor |
A unary factor which enforces the evaluation of the derivative of a BASIS polynomial at a specified point x is equal to the vector value z. More... | |
| class | VectorEvaluationFactor |
| Unary factor for enforcing BASIS polynomial evaluation on a ParameterMatrix of size (M, N) is equal to a vector-valued measurement at the same point, when using a pseudo-spectral parameterization. More... | |
| class | VectorValues |
| This class represents a collection of vector-valued variables associated each with a unique integer index. More... | |
| class | VelocityConstraint |
| Constraint to enforce dynamics between the velocities and poses, using a prediction based on a numerical integration flag. More... | |
| class | VelocityConstraint3 |
| struct | VelocityPrior |
| Constrains the full velocity of a state to a particular value Useful for enforcing a stationary state Dim: 3. More... | |
| class | VerticalBlockMatrix |
| class | WeightedSampler |
| class | WhiteNoiseFactor |
| Binary factor to estimate parameters of zero-mean Gaussian white noise. More... | |
Typedefs | |
| typedef std::vector< IndexPair > | IndexPairVector |
| typedef std::set< IndexPair > | IndexPairSet |
| typedef std::map< IndexPair, IndexPairSet > | IndexPairSetMap |
| typedef DSFMap< IndexPair > | DSFMapIndexPair |
| template<typename T > | |
| using | FastVector = std::vector< T, typename internal::FastDefaultVectorAllocator< T >::type > |
| template<bool B, class T = void> | |
| using | enable_if_t = typename std::enable_if< B, T >::type |
| An shorthand alias for accessing the ::type inside std::enable_if that can be used in a template directly. | |
| typedef Eigen::MatrixXd | Matrix |
| typedef Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor > | MatrixRowMajor |
| typedef Eigen::Block< Matrix > | SubMatrix |
| typedef Eigen::Block< const Matrix > | ConstSubMatrix |
| typedef std::uint64_t | Key |
| Integer nonlinear key type. | |
| typedef std::uint64_t | FactorIndex |
| Integer nonlinear factor index type. | |
| typedef ptrdiff_t | DenseIndex |
| The index type for Eigen objects. | |
| template<typename ... > | |
| using | void_t = void |
Convenience void_t as we assume C++11, it will not conflict the std one in C++17 as this is in gtsam:: | |
| typedef Eigen::VectorXd | Vector |
| typedef Eigen::Matrix< double, 1, 1 > | Vector1 |
| typedef Eigen::Vector2d | Vector2 |
| typedef Eigen::Vector3d | Vector3 |
| typedef Eigen::VectorBlock< Vector > | SubVector |
| typedef Eigen::VectorBlock< const Vector > | ConstSubVector |
| using | Weights = Eigen::Matrix< double, 1, -1 > |
| using | Sequence = std::map< double, double > |
| Our sequence representation is a map of {x: y} values where y = f(x) | |
| using | Sample = std::pair< double, double > |
| A sample is a key-value pair from a sequence. | |
| typedef std::pair< Key, size_t > | DiscreteKey |
| Key type for discrete conditionals Includes name and cardinality. | |
| typedef Vector2 | Point2 |
| As of GTSAM 4, in order to make GTSAM more lean, it is now possible to just typedef Point2 to Vector2. | |
| using | Point2Pair = std::pair< Point2, Point2 > |
| Calculate pose between a vector of 2D point correspondences (p,q) where q = Pose2::transformFrom(p) = t + R*p. | |
| using | Point2Pairs = std::vector< Point2Pair > |
| typedef std::vector< Point2, Eigen::aligned_allocator< Point2 > > | Point2Vector |
| typedef Vector3 | Point3 |
| As of GTSAM 4, in order to make GTSAM more lean, it is now possible to just typedef Point3 to Vector3. | |
| using | Point3Pair = std::pair< Point3, Point3 > |
| using | Point3Pairs = std::vector< Point3Pair > |
| using | Pose3Pair = std::pair< Pose3, Pose3 > |
| using | Pose3Pairs = std::vector< std::pair< Pose3, Pose3 > > |
| typedef std::vector< Pose3 > | Pose3Vector |
| typedef Eigen::Quaternion< double, Eigen::DontAlign > | Quaternion |
| using | PinholeCameraCal3_S2 = gtsam::PinholeCamera< gtsam::Cal3_S2 > |
| Convenient aliases for Pinhole camera classes with different calibrations. More... | |
| using | PinholeCameraCal3Bundler = gtsam::PinholeCamera< gtsam::Cal3Bundler > |
| using | PinholeCameraCal3DS2 = gtsam::PinholeCamera< gtsam::Cal3DS2 > |
| using | PinholeCameraCal3Unified = gtsam::PinholeCamera< gtsam::Cal3Unified > |
| using | PinholeCameraCal3Fisheye = gtsam::PinholeCamera< gtsam::Cal3Fisheye > |
| using | SO3 = SO< 3 > |
| using | SO4 = SO< 4 > |
| using | SOn = SO< Eigen::Dynamic > |
| using | DynamicJacobian = OptionalJacobian< Eigen::Dynamic, Eigen::Dynamic > |
| typedef std::vector< StereoPoint2 > | StereoPoint2Vector |
| using | CameraSetCal3Bundler = CameraSet< PinholeCamera< Cal3Bundler > > |
| using | CameraSetCal3_S2 = CameraSet< PinholeCamera< Cal3_S2 > > |
| using | CameraSetCal3Fisheye = CameraSet< PinholeCamera< Cal3Fisheye > > |
| using | CameraSetCal3Unified = CameraSet< PinholeCamera< Cal3Unified > > |
| typedef FastVector< FactorIndex > | FactorIndices |
| Define collection types: More... | |
| typedef FastSet< FactorIndex > | FactorIndexSet |
| using | KeyFormatter = std::function< std::string(Key)> |
| Typedef for a function to format a key, i.e. to convert it to a string. | |
| using | KeyVector = FastVector< Key > |
| Define collection type once and for all - also used in wrappers. | |
| using | KeyList = FastList< Key > |
| using | KeySet = FastSet< Key > |
| using | KeyGroupMap = FastMap< Key, int > |
| using | Sparse = Eigen::SparseMatrix< double > |
| using | SparseTriplets = std::vector< std::tuple< int, int, double > > |
| typedef noiseModel::Base::shared_ptr | SharedNoiseModel |
| Note, deliberately not in noiseModel namespace. More... | |
| typedef noiseModel::Gaussian::shared_ptr | SharedGaussian |
| typedef noiseModel::Diagonal::shared_ptr | SharedDiagonal |
| typedef noiseModel::Constrained::shared_ptr | SharedConstrained |
| typedef noiseModel::Isotropic::shared_ptr | SharedIsotropic |
| typedef Eigen::SparseMatrix< double, Eigen::ColMajor, int > | SparseEigen |
| Eigen-format sparse matrix. More... | |
| typedef ManifoldPreintegration | PreintegrationType |
| typedef Expression< NavState > | NavState_ |
| typedef Expression< Velocity3 > | Velocity3_ |
| typedef Vector3 | Velocity3 |
| Velocity is currently typedef'd to Vector3. More... | |
| using | JacobianVector = std::vector< Matrix > |
| using | CustomErrorFunction = std::function< Vector(const CustomFactor &, const Values &, const JacobianVector *)> |
| typedef internal::DoglegState | State |
| typedef Expression< double > | Double_ |
| typedef Expression< Vector1 > | Vector1_ |
| typedef Expression< Vector2 > | Vector2_ |
| typedef Expression< Vector3 > | Vector3_ |
| typedef Expression< Vector4 > | Vector4_ |
| typedef Expression< Vector5 > | Vector5_ |
| typedef Expression< Vector6 > | Vector6_ |
| typedef Expression< Vector7 > | Vector7_ |
| typedef Expression< Vector8 > | Vector8_ |
| typedef Expression< Vector9 > | Vector9_ |
| typedef FastMap< char, Vector > | ISAM2ThresholdMap |
| typedef ISAM2ThresholdMap::value_type | ISAM2ThresholdMapValue |
| typedef NonlinearOptimizerParams | SuccessiveLinearizationParams |
| typedef std::map< std::pair< Key, Key >, double > | KeyPairDoubleMap |
| using | ShonanAveragingParameters2 = ShonanAveragingParameters< 2 > |
| using | ShonanAveragingParameters3 = ShonanAveragingParameters< 3 > |
| using | ShonanFactor2 = ShonanFactor< 2 > |
| using | ShonanFactor3 = ShonanFactor< 3 > |
| template<typename T > | |
| using | Parser = std::function< boost::optional< T >(istream &is, const string &tag)> |
| using | BearingRange2D = BearingRange< Pose2, Point2 > |
| typedef std::pair< size_t, Pose2 > | IndexedPose |
| Return type for auxiliary functions. | |
| typedef std::pair< size_t, Point2 > | IndexedLandmark |
| typedef std::pair< std::pair< size_t, size_t >, Pose2 > | IndexedEdge |
| using | GraphAndValues = std::pair< NonlinearFactorGraph::shared_ptr, Values::shared_ptr > |
| Return type for load functions, which return a graph and initial values. More... | |
| typedef std::pair< size_t, Point2 > | SfmMeasurement |
| A measurement with its camera index. | |
| typedef std::pair< size_t, size_t > | SiftIndex |
| Sift index for SfmTrack. | |
| typedef PinholeCamera< Cal3Bundler > | SfmCamera |
| Define the structure for the camera poses. | |
| using | BetweenFactorPose2s = std::vector< BetweenFactor< Pose2 >::shared_ptr > |
| using | BetweenFactorPose3s = std::vector< BetweenFactor< Pose3 >::shared_ptr > |
| using | BinaryMeasurementsUnit3 = std::vector< BinaryMeasurement< Unit3 > > |
| typedef Expression< Point2 > | Point2_ |
| typedef Expression< Rot2 > | Rot2_ |
| typedef Expression< Pose2 > | Pose2_ |
| typedef Expression< Point3 > | Point3_ |
| typedef Expression< Unit3 > | Unit3_ |
| typedef Expression< Rot3 > | Rot3_ |
| typedef Expression< Pose3 > | Pose3_ |
| typedef Expression< Line3 > | Line3_ |
| typedef Expression< Cal3_S2 > | Cal3_S2_ |
| typedef Expression< Cal3Bundler > | Cal3Bundler_ |
| typedef std::map< Key, std::vector< size_t > > | KeyVectorMap |
| typedef std::map< Key, Rot3 > | KeyRotMap |
| typedef DSF< int > | DSFInt |
| typedef Eigen::RowVectorXd | RowVector |
| using | KeyDimMap = std::map< Key, size_t > |
| Mapping between variable's key and its corresponding dimensionality. | |
| using | LPSolver = ActiveSetSolver< LP, LPPolicy, LPInitSolver > |
| using | QPSolver = ActiveSetSolver< QP, QPPolicy, QPInitSolver > |
| typedef qi::grammar< boost::spirit::basic_istream_iterator< char > > | base_grammar |
| typedef ConcurrentBatchFilter::Result | ConcurrentBatchFilterResult |
| Typedef for Matlab wrapping. | |
| typedef ConcurrentBatchSmoother::Result | ConcurrentBatchSmootherResult |
| Typedef for Matlab wrapping. | |
| typedef ConcurrentIncrementalFilter::Result | ConcurrentIncrementalFilterResult |
| Typedef for Matlab wrapping. | |
| typedef ConcurrentIncrementalSmoother::Result | ConcurrentIncrementalSmootherResult |
| Typedef for Matlab wrapping. | |
| typedef FixedLagSmoother::KeyTimestampMap | FixedLagSmootherKeyTimestampMap |
| Typedef for matlab wrapping. | |
| typedef FixedLagSmootherKeyTimestampMap::value_type | FixedLagSmootherKeyTimestampMapValue |
| typedef FixedLagSmoother::Result | FixedLagSmootherResult |
| typedef SmartProjectionParams | SmartStereoProjectionParams |
Enumerations | |
| enum | GncLossType { GM , TLS } |
| Choice of robust loss function for GNC. | |
| enum | NoiseFormat { NoiseFormatG2O , NoiseFormatTORO , NoiseFormatGRAPH , NoiseFormatCOV , NoiseFormatAUTO } |
| Indicates how noise parameters are stored in file. More... | |
| enum | KernelFunctionType { KernelFunctionTypeNONE , KernelFunctionTypeHUBER , KernelFunctionTypeTUKEY } |
| Robust kernel type to wrap around quadratic noise model. | |
| enum | LinearizationMode { HESSIAN , IMPLICIT_SCHUR , JACOBIAN_Q , JACOBIAN_SVD } |
| SmartFactorParams: parameters and (linearization/degeneracy) modes for SmartProjection and SmartStereoProjection factors. More... | |
| enum | DegeneracyMode { IGNORE_DEGENERACY , ZERO_ON_DEGENERACY , HANDLE_INFINITY } |
| How to manage degeneracy. | |
Functions | |
| template<typename T > | |
| void | testDefaultChart (TestResult &result_, const std::string &name_, const T &value) |
| pair< size_t, bool > | choleskyCareful (Matrix &ATA, int order=-1) |
| "Careful" Cholesky computes the positive square-root of a positive symmetric semi-definite matrix (i.e. More... | |
| bool | choleskyPartial (Matrix &ABC, size_t nFrontal, size_t topleft=0) |
| Partial Cholesky computes a factor [R S such that [R' 0 [R S = [A B 0 L] S' I] 0 L] B' C]. More... | |
| bool | guardedIsDebug (const std::string &s) |
| void | guardedSetDebug (const std::string &s, const bool v) |
| bool | isDebugVersion () |
| IndexPairVector | IndexPairSetAsArray (IndexPairSet &set) |
| template<class T > | |
| GenericValue< T > | genericValue (const T &v) |
| Functional constructor of GenericValue<T> so T can be automatically deduced. | |
| template<typename G > | |
| BOOST_CONCEPT_REQUIRES (((IsGroup< G >)),(bool)) check_group_invariants(const G &a | |
| Check invariants. | |
| template<class Class > | |
| Class | between_default (const Class &l1, const Class &l2) |
| These core global functions can be specialized by new Lie types for better performance. More... | |
| template<class Class > | |
| Vector | logmap_default (const Class &l0, const Class &lp) |
| Log map centered at l0, s.t. More... | |
| template<class Class > | |
| Class | expmap_default (const Class &t, const Vector &d) |
| Exponential map centered at l0, s.t. More... | |
| template<class T > | |
| T | BCH (const T &X, const T &Y) |
| Three term approximation of the Baker-Campbell-Hausdorff formula In non-commutative Lie groups, when composing exp(Z) = exp(X)exp(Y) it is not true that Z = X+Y. More... | |
| template<class T > | |
| Matrix | wedge (const Vector &x) |
| Declaration of wedge (see Murray94book) used to convert from n exponential coordinates to n*n element of the Lie algebra. | |
| template<class T > | |
| T | expm (const Vector &x, int K=7) |
| Exponential map given exponential coordinates class T needs a wedge<> function and a constructor from Matrix. More... | |
| template<typename T > | |
| T | interpolate (const T &X, const T &Y, double t, typename MakeOptionalJacobian< T, T >::type Hx=boost::none, typename MakeOptionalJacobian< T, T >::type Hy=boost::none) |
| Linear interpolation between X and Y by coefficient t. More... | |
| template<typename T , typename ... Args> | |
| gtsam::enable_if_t< needs_eigen_aligned_allocator< T >::value, boost::shared_ptr< T > > | make_shared (Args &&... args) |
Add our own make_shared as a layer of wrapping on boost::make_shared This solves the problem with the stock make_shared that custom alignment is not respected, causing SEGFAULTs at runtime, which is notoriously hard to debug. More... | |
| template<typename T , typename ... Args> | |
| gtsam::enable_if_t<!needs_eigen_aligned_allocator< T >::value, boost::shared_ptr< T > > | make_shared (Args &&... args) |
| Fall back to the boost version if no need for alignment. | |
| template<typename T > | |
| BOOST_CONCEPT_REQUIRES (((IsTestable< T >)),(bool)) check_manifold_invariants(const T &a | |
| Check invariants for Manifold type. | |
| bool | assert_equal (const Matrix &A, const Matrix &B, double tol=1e-9) |
| equals with an tolerance, prints out message if unequal | |
| bool | assert_inequal (const Matrix &A, const Matrix &B, double tol=1e-9) |
| inequals with an tolerance, prints out message if within tolerance | |
| bool | assert_equal (const std::list< Matrix > &As, const std::list< Matrix > &Bs, double tol=1e-9) |
| equals with an tolerance, prints out message if unequal | |
| bool | linear_independent (const Matrix &A, const Matrix &B, double tol=1e-9) |
| check whether the rows of two matrices are linear independent | |
| bool | linear_dependent (const Matrix &A, const Matrix &B, double tol=1e-9) |
| check whether the rows of two matrices are linear dependent | |
| Vector | operator^ (const Matrix &A, const Vector &v) |
| overload ^ for trans(A)*v We transpose the vectors for speed. | |
| const Eigen::IOFormat & | matlabFormat () |
| void | print (const Matrix &A, const std::string &s, std::ostream &stream) |
| print without optional string, must specify cout yourself | |
| void | print (const Matrix &A, const std::string &s="") |
| print with optional string to cout | |
| void | save (const Matrix &A, const std::string &s, const std::string &filename) |
| save a matrix to file, which can be loaded by matlab | |
| istream & | operator>> (std::istream &inputStream, Matrix &destinationMatrix) |
| Read a matrix from an input stream, such as a file. More... | |
| Matrix | diag (const std::vector< Matrix > &Hs) |
| Create a matrix with submatrices along its diagonal. | |
| Vector | columnNormSquare (const Matrix &A) |
| pair< Matrix, Matrix > | qr (const Matrix &A) |
| Householder QR factorization, Golub & Van Loan p 224, explicit version More... | |
| list< boost::tuple< Vector, double, double > > | weighted_eliminate (Matrix &A, Vector &b, const Vector &sigmas) |
| Imperative algorithm for in-place full elimination with weights and constraint handling. More... | |
| void | householder_ (Matrix &A, size_t k, bool copy_vectors) |
| Imperative version of Householder QR factorization, Golub & Van Loan p 224 version with Householder vectors below diagonal, as in GVL. More... | |
| void | householder (Matrix &A, size_t k) |
| Householder tranformation, zeros below diagonal. More... | |
| Vector | backSubstituteLower (const Matrix &L, const Vector &b, bool unit=false) |
| backSubstitute L*x=b More... | |
| Vector | backSubstituteUpper (const Matrix &U, const Vector &b, bool unit=false) |
| backSubstitute U*x=b More... | |
| Vector | backSubstituteUpper (const Vector &b, const Matrix &U, bool unit=false) |
| backSubstitute x'*U=b' More... | |
| Matrix | stack (size_t nrMatrices,...) |
| create a matrix by stacking other matrices Given a set of matrices: A1, A2, A3... More... | |
| Matrix | stack (const std::vector< Matrix > &blocks) |
| Matrix | collect (const std::vector< const Matrix * > &matrices, size_t m=0, size_t n=0) |
| create a matrix by concatenating Given a set of matrices: A1, A2, A3... If all matrices have the same size, specifying single matrix dimensions will avoid the lookup of dimensions More... | |
| Matrix | collect (size_t nrMatrices,...) |
| void | vector_scale_inplace (const Vector &v, Matrix &A, bool inf_mask=false) |
| scales a matrix row or column by the values in a vector Arguments (Matrix, Vector) scales the columns, (Vector, Matrix) scales the rows More... | |
| Matrix | vector_scale (const Vector &v, const Matrix &A, bool inf_mask) |
| Matrix | vector_scale (const Matrix &A, const Vector &v, bool inf_mask) |
| Matrix | LLt (const Matrix &A) |
| Matrix | RtR (const Matrix &A) |
| Matrix | cholesky_inverse (const Matrix &A) |
| Return the inverse of a S.P.D. More... | |
| Matrix | inverse_square_root (const Matrix &A) |
| Use Cholesky to calculate inverse square root of a matrix. | |
| void | svd (const Matrix &A, Matrix &U, Vector &S, Matrix &V) |
| SVD computes economy SVD A=U*S*V'. More... | |
| boost::tuple< int, double, Vector > | DLT (const Matrix &A, double rank_tol=1e-9) |
| Direct linear transform algorithm that calls svd to find a vector v that minimizes the algebraic error A*v. More... | |
| Matrix | expm (const Matrix &A, size_t K=7) |
| Numerical exponential map, naive approach, not industrial strength !!! More... | |
| std::string | formatMatrixIndented (const std::string &label, const Matrix &matrix, bool makeVectorHorizontal) |
| void | inplace_QR (Matrix &A) |
| QR factorization using Eigen's internal block QR algorithm. More... | |
| template<class MATRIX > | |
| bool | equal_with_abs_tol (const Eigen::DenseBase< MATRIX > &A, const Eigen::DenseBase< MATRIX > &B, double tol=1e-9) |
| equals with a tolerance | |
| bool | operator== (const Matrix &A, const Matrix &B) |
| equality is just equal_with_abs_tol 1e-9 | |
| bool | operator!= (const Matrix &A, const Matrix &B) |
| inequality | |
| template<class MATRIX > | |
| MATRIX | prod (const MATRIX &A, const MATRIX &B) |
| products using old-style format to improve compatibility | |
| template<class MATRIX > | |
| Eigen::Block< const MATRIX > | sub (const MATRIX &A, size_t i1, size_t i2, size_t j1, size_t j2) |
| extract submatrix, slice semantics, i.e. More... | |
| template<typename Derived1 , typename Derived2 > | |
| void | insertSub (Eigen::MatrixBase< Derived1 > &fullMatrix, const Eigen::MatrixBase< Derived2 > &subMatrix, size_t i, size_t j) |
| insert a submatrix IN PLACE at a specified location in a larger matrix NOTE: there is no size checking More... | |
| template<class MATRIX > | |
| const MATRIX::ConstColXpr | column (const MATRIX &A, size_t j) |
| Extracts a column view from a matrix that avoids a copy. More... | |
| template<class MATRIX > | |
| const MATRIX::ConstRowXpr | row (const MATRIX &A, size_t j) |
| Extracts a row view from a matrix that avoids a copy. More... | |
| template<class MATRIX > | |
| void | zeroBelowDiagonal (MATRIX &A, size_t cols=0) |
| Zeros all of the elements below the diagonal of a matrix, in place. More... | |
| Matrix | trans (const Matrix &A) |
| static transpose function, just calls Eigen transpose member function | |
| template<int OutM, int OutN, int OutOptions, int InM, int InN, int InOptions> | |
| Reshape< OutM, OutN, OutOptions, InM, InN, InOptions >::ReshapedType | reshape (const Eigen::Matrix< double, InM, InN, InOptions > &m) |
| Matrix3 | skewSymmetric (double wx, double wy, double wz) |
| skew symmetric matrix returns this: 0 -wz wy wz 0 -wx -wy wx 0 More... | |
| template<class Derived > | |
| Matrix3 | skewSymmetric (const Eigen::MatrixBase< Derived > &w) |
| template<class X , int N = traits<X>::dimension> | |
| Eigen::Matrix< double, N, 1 > | numericalGradient (std::function< double(const X &)> h, const X &x, double delta=1e-5) |
| Numerically compute gradient of scalar function. More... | |
| template<class Y , class X , int N = traits<X>::dimension> | |
| internal::FixedSizeMatrix< Y, X >::type | numericalDerivative11 (std::function< Y(const X &)> h, const X &x, double delta=1e-5) |
| New-style numerical derivatives using manifold_traits. More... | |
| template<class Y , class X > | |
| internal::FixedSizeMatrix< Y, X >::type | numericalDerivative11 (Y(*h)(const X &), const X &x, double delta=1e-5) |
| use a raw C++ function pointer | |
| template<class Y , class X1 , class X2 , int N = traits<X1>::dimension> | |
| internal::FixedSizeMatrix< Y, X1 >::type | numericalDerivative21 (const std::function< Y(const X1 &, const X2 &)> &h, const X1 &x1, const X2 &x2, double delta=1e-5) |
| Compute numerical derivative in argument 1 of binary function. More... | |
| template<class Y , class X1 , class X2 > | |
| internal::FixedSizeMatrix< Y, X1 >::type | numericalDerivative21 (Y(*h)(const X1 &, const X2 &), const X1 &x1, const X2 &x2, double delta=1e-5) |
| use a raw C++ function pointer | |
| template<class Y , class X1 , class X2 , int N = traits<X2>::dimension> | |
| internal::FixedSizeMatrix< Y, X2 >::type | numericalDerivative22 (std::function< Y(const X1 &, const X2 &)> h, const X1 &x1, const X2 &x2, double delta=1e-5) |
| Compute numerical derivative in argument 2 of binary function. More... | |
| template<class Y , class X1 , class X2 > | |
| internal::FixedSizeMatrix< Y, X2 >::type | numericalDerivative22 (Y(*h)(const X1 &, const X2 &), const X1 &x1, const X2 &x2, double delta=1e-5) |
| use a raw C++ function pointer | |
| template<class Y , class X1 , class X2 , class X3 , int N = traits<X1>::dimension> | |
| internal::FixedSizeMatrix< Y, X1 >::type | numericalDerivative31 (std::function< Y(const X1 &, const X2 &, const X3 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| Compute numerical derivative in argument 1 of ternary function. More... | |
| template<class Y , class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< Y, X1 >::type | numericalDerivative31 (Y(*h)(const X1 &, const X2 &, const X3 &), const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , int N = traits<X2>::dimension> | |
| internal::FixedSizeMatrix< Y, X2 >::type | numericalDerivative32 (std::function< Y(const X1 &, const X2 &, const X3 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| Compute numerical derivative in argument 2 of ternary function. More... | |
| template<class Y , class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< Y, X2 >::type | numericalDerivative32 (Y(*h)(const X1 &, const X2 &, const X3 &), const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , int N = traits<X3>::dimension> | |
| internal::FixedSizeMatrix< Y, X3 >::type | numericalDerivative33 (std::function< Y(const X1 &, const X2 &, const X3 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| Compute numerical derivative in argument 3 of ternary function. More... | |
| template<class Y , class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< Y, X3 >::type | numericalDerivative33 (Y(*h)(const X1 &, const X2 &, const X3 &), const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , int N = traits<X1>::dimension> | |
| internal::FixedSizeMatrix< Y, X1 >::type | numericalDerivative41 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, double delta=1e-5) |
| Compute numerical derivative in argument 1 of 4-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 > | |
| internal::FixedSizeMatrix< Y, X1 >::type | numericalDerivative41 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , int N = traits<X2>::dimension> | |
| internal::FixedSizeMatrix< Y, X2 >::type | numericalDerivative42 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, double delta=1e-5) |
| Compute numerical derivative in argument 2 of 4-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 > | |
| internal::FixedSizeMatrix< Y, X2 >::type | numericalDerivative42 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , int N = traits<X3>::dimension> | |
| internal::FixedSizeMatrix< Y, X3 >::type | numericalDerivative43 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, double delta=1e-5) |
| Compute numerical derivative in argument 3 of 4-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 > | |
| internal::FixedSizeMatrix< Y, X3 >::type | numericalDerivative43 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , int N = traits<X4>::dimension> | |
| internal::FixedSizeMatrix< Y, X4 >::type | numericalDerivative44 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, double delta=1e-5) |
| Compute numerical derivative in argument 4 of 4-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 > | |
| internal::FixedSizeMatrix< Y, X4 >::type | numericalDerivative44 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , int N = traits<X1>::dimension> | |
| internal::FixedSizeMatrix< Y, X1 >::type | numericalDerivative51 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, double delta=1e-5) |
| Compute numerical derivative in argument 1 of 5-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 > | |
| internal::FixedSizeMatrix< Y, X1 >::type | numericalDerivative51 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , int N = traits<X2>::dimension> | |
| internal::FixedSizeMatrix< Y, X2 >::type | numericalDerivative52 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, double delta=1e-5) |
| Compute numerical derivative in argument 2 of 5-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 > | |
| internal::FixedSizeMatrix< Y, X2 >::type | numericalDerivative52 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , int N = traits<X3>::dimension> | |
| internal::FixedSizeMatrix< Y, X3 >::type | numericalDerivative53 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, double delta=1e-5) |
| Compute numerical derivative in argument 3 of 5-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 > | |
| internal::FixedSizeMatrix< Y, X3 >::type | numericalDerivative53 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , int N = traits<X4>::dimension> | |
| internal::FixedSizeMatrix< Y, X4 >::type | numericalDerivative54 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, double delta=1e-5) |
| Compute numerical derivative in argument 4 of 5-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 > | |
| internal::FixedSizeMatrix< Y, X4 >::type | numericalDerivative54 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , int N = traits<X5>::dimension> | |
| internal::FixedSizeMatrix< Y, X5 >::type | numericalDerivative55 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, double delta=1e-5) |
| Compute numerical derivative in argument 5 of 5-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 > | |
| internal::FixedSizeMatrix< Y, X5 >::type | numericalDerivative55 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , class X6 , int N = traits<X1>::dimension> | |
| internal::FixedSizeMatrix< Y, X1 >::type | numericalDerivative61 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, const X6 &x6, double delta=1e-5) |
| Compute numerical derivative in argument 1 of 6-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , class X6 > | |
| internal::FixedSizeMatrix< Y, X1 >::type | numericalDerivative61 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, const X6 &x6, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , class X6 , int N = traits<X2>::dimension> | |
| internal::FixedSizeMatrix< Y, X2 >::type | numericalDerivative62 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, const X6 &x6, double delta=1e-5) |
| Compute numerical derivative in argument 2 of 6-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , class X6 > | |
| internal::FixedSizeMatrix< Y, X2 >::type | numericalDerivative62 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, const X6 &x6, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , class X6 , int N = traits<X3>::dimension> | |
| internal::FixedSizeMatrix< Y, X3 >::type | numericalDerivative63 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, const X6 &x6, double delta=1e-5) |
| Compute numerical derivative in argument 3 of 6-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , class X6 > | |
| internal::FixedSizeMatrix< Y, X3 >::type | numericalDerivative63 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, const X6 &x6, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , class X6 , int N = traits<X4>::dimension> | |
| internal::FixedSizeMatrix< Y, X4 >::type | numericalDerivative64 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, const X6 &x6, double delta=1e-5) |
| Compute numerical derivative in argument 4 of 6-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , class X6 > | |
| internal::FixedSizeMatrix< Y, X4 >::type | numericalDerivative64 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, const X6 &x6, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , class X6 , int N = traits<X5>::dimension> | |
| internal::FixedSizeMatrix< Y, X5 >::type | numericalDerivative65 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, const X6 &x6, double delta=1e-5) |
| Compute numerical derivative in argument 5 of 6-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , class X6 > | |
| internal::FixedSizeMatrix< Y, X5 >::type | numericalDerivative65 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, const X6 &x6, double delta=1e-5) |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , class X6 , int N = traits<X6>::dimension> | |
| internal::FixedSizeMatrix< Y, X6 >::type | numericalDerivative66 (std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &)> h, const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, const X6 &x6, double delta=1e-5) |
| Compute numerical derivative in argument 6 of 6-argument function. More... | |
| template<class Y , class X1 , class X2 , class X3 , class X4 , class X5 , class X6 > | |
| internal::FixedSizeMatrix< Y, X6 >::type | numericalDerivative66 (Y(*h)(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &), const X1 &x1, const X2 &x2, const X3 &x3, const X4 &x4, const X5 &x5, const X6 &x6, double delta=1e-5) |
| template<class X > | |
| internal::FixedSizeMatrix< X, X >::type | numericalHessian (std::function< double(const X &)> f, const X &x, double delta=1e-5) |
| Compute numerical Hessian matrix. More... | |
| template<class X > | |
| internal::FixedSizeMatrix< X, X >::type | numericalHessian (double(*f)(const X &), const X &x, double delta=1e-5) |
| template<class X1 , class X2 > | |
| internal::FixedSizeMatrix< X1, X2 >::type | numericalHessian212 (std::function< double(const X1 &, const X2 &)> f, const X1 &x1, const X2 &x2, double delta=1e-5) |
| template<class X1 , class X2 > | |
| internal::FixedSizeMatrix< X1, X2 >::type | numericalHessian212 (double(*f)(const X1 &, const X2 &), const X1 &x1, const X2 &x2, double delta=1e-5) |
| template<class X1 , class X2 > | |
| internal::FixedSizeMatrix< X1, X1 >::type | numericalHessian211 (std::function< double(const X1 &, const X2 &)> f, const X1 &x1, const X2 &x2, double delta=1e-5) |
| template<class X1 , class X2 > | |
| internal::FixedSizeMatrix< X1, X1 >::type | numericalHessian211 (double(*f)(const X1 &, const X2 &), const X1 &x1, const X2 &x2, double delta=1e-5) |
| template<class X1 , class X2 > | |
| internal::FixedSizeMatrix< X2, X2 >::type | numericalHessian222 (std::function< double(const X1 &, const X2 &)> f, const X1 &x1, const X2 &x2, double delta=1e-5) |
| template<class X1 , class X2 > | |
| internal::FixedSizeMatrix< X2, X2 >::type | numericalHessian222 (double(*f)(const X1 &, const X2 &), const X1 &x1, const X2 &x2, double delta=1e-5) |
| template<class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< X1, X1 >::type | numericalHessian311 (std::function< double(const X1 &, const X2 &, const X3 &)> f, const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| Numerical Hessian for tenary functions. | |
| template<class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< X1, X1 >::type | numericalHessian311 (double(*f)(const X1 &, const X2 &, const X3 &), const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< X2, X2 >::type | numericalHessian322 (std::function< double(const X1 &, const X2 &, const X3 &)> f, const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< X2, X2 >::type | numericalHessian322 (double(*f)(const X1 &, const X2 &, const X3 &), const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< X3, X3 >::type | numericalHessian333 (std::function< double(const X1 &, const X2 &, const X3 &)> f, const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< X3, X3 >::type | numericalHessian333 (double(*f)(const X1 &, const X2 &, const X3 &), const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< X1, X2 >::type | numericalHessian312 (std::function< double(const X1 &, const X2 &, const X3 &)> f, const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< X1, X3 >::type | numericalHessian313 (std::function< double(const X1 &, const X2 &, const X3 &)> f, const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< X2, X3 >::type | numericalHessian323 (std::function< double(const X1 &, const X2 &, const X3 &)> f, const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< X1, X2 >::type | numericalHessian312 (double(*f)(const X1 &, const X2 &, const X3 &), const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< X1, X3 >::type | numericalHessian313 (double(*f)(const X1 &, const X2 &, const X3 &), const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| template<class X1 , class X2 , class X3 > | |
| internal::FixedSizeMatrix< X2, X3 >::type | numericalHessian323 (double(*f)(const X1 &, const X2 &, const X3 &), const X1 &x1, const X2 &x2, const X3 &x3, double delta=1e-5) |
| void | print (float v, const std::string &s="") |
| void | print (double v, const std::string &s="") |
| template<class T > | |
| bool | equal (const T &obj1, const T &obj2, double tol) |
| Call equal on the object. | |
| template<class T > | |
| bool | equal (const T &obj1, const T &obj2) |
| Call equal without tolerance (use default tolerance) | |
| template<class V > | |
| bool | assert_equal (const V &expected, const V &actual, double tol=1e-9) |
| This template works for any type with equals. | |
| bool | assert_equal (const Key &expected, const Key &actual, double tol=0.0) |
| Equals testing for basic types. | |
| template<class V > | |
| bool | assert_equal (const boost::optional< V > &expected, const boost::optional< V > &actual, double tol=1e-9) |
| Comparisons for boost.optional objects that checks whether objects exist before comparing their values. More... | |
| template<class V > | |
| bool | assert_equal (const V &expected, const boost::optional< V > &actual, double tol=1e-9) |
| template<class V > | |
| bool | assert_equal (const V &expected, const boost::optional< const V & > &actual, double tol=1e-9) |
| template<class V > | |
| bool GTSAM_DEPRECATED | assert_equal (const std::vector< V > &expected, const std::vector< V > &actual, double tol=1e-9) |
| Version of assert_equals to work with vectors. More... | |
| template<class V1 , class V2 > | |
| bool | assert_container_equal (const std::map< V1, V2 > &expected, const std::map< V1, V2 > &actual, double tol=1e-9) |
| Function for comparing maps of testable->testable TODO: replace with more generalized version. | |
| template<class V2 > | |
| bool | assert_container_equal (const std::map< size_t, V2 > &expected, const std::map< size_t, V2 > &actual, double tol=1e-9) |
| Function for comparing maps of size_t->testable. | |
| template<class V1 , class V2 > | |
| bool | assert_container_equal (const std::vector< std::pair< V1, V2 > > &expected, const std::vector< std::pair< V1, V2 > > &actual, double tol=1e-9) |
| Function for comparing vector of pairs (testable, testable) | |
| template<class V > | |
| bool | assert_container_equal (const V &expected, const V &actual, double tol=1e-9) |
| General function for comparing containers of testable objects. | |
| template<class V2 > | |
| bool | assert_container_equality (const std::map< size_t, V2 > &expected, const std::map< size_t, V2 > &actual) |
| Function for comparing maps of size_t->testable Types are assumed to have operator ==. | |
| template<class V > | |
| bool | assert_container_equality (const V &expected, const V &actual) |
| General function for comparing containers of objects with operator==. | |
| bool | assert_equal (const std::string &expected, const std::string &actual) |
| Compare strings for unit tests. | |
| template<class V > | |
| bool | assert_inequal (const V &expected, const V &actual, double tol=1e-9) |
| Allow for testing inequality. | |
| template<class V > | |
| bool | assert_stdout_equal (const std::string &expected, const V &actual) |
| Capture std out via cout stream and compare against string. | |
| template<class V > | |
| bool | assert_print_equal (const std::string &expected, const V &actual, const std::string &s="") |
| Capture print function output and compare against string. More... | |
| template<typename G > | |
| void | testLieGroupDerivatives (TestResult &result_, const std::string &name_, const G &t1, const G &t2) |
| template<typename G > | |
| void | testChartDerivatives (TestResult &result_, const std::string &name_, const G &t1, const G &t2) |
| void | tictoc_finishedIteration_ () |
| void | tictoc_print_ () |
| void | tictoc_print2_ () |
| void | tictoc_reset_ () |
| std::string | demangle (const char *name) |
| Pretty print Value type name. More... | |
| BOOST_CONCEPT_ASSERT ((boost::RandomAccessRangeConcept< ListOfOneContainer< int > >)) | |
| template<typename T > | |
| ListOfOneContainer< T > | ListOfOne (const T &element) |
| Factory function for ListOfOneContainer to enable ListOfOne(e) syntax. | |
| bool | fpEqual (double a, double b, double tol, bool check_relative_also=true) |
| Ensure we are not including a different version of Eigen in user code than while compiling gtsam, since it can lead to hard-to-understand runtime crashes. More... | |
| void | print (const Vector &v, const std::string &s, std::ostream &stream) |
| print without optional string, must specify cout yourself | |
| void | print (const Vector &v, const std::string &s="") |
| print with optional string to cout | |
| void | save (const Vector &A, const std::string &s, const std::string &filename) |
| save a vector to file, which can be loaded by matlab | |
| bool | operator== (const Vector &vec1, const Vector &vec2) |
| operator==() | |
| bool | greaterThanOrEqual (const Vector &v1, const Vector &v2) |
| Greater than or equal to operation returns true if all elements in v1 are greater than corresponding elements in v2. | |
| bool | equal_with_abs_tol (const Vector &vec1, const Vector &vec2, double tol=1e-9) |
| VecA == VecB up to tolerance. | |
| bool | equal_with_abs_tol (const SubVector &vec1, const SubVector &vec2, double tol) |
| bool | assert_equal (const Vector &vec1, const Vector &vec2, double tol=1e-9) |
| Same, prints if error. More... | |
| bool | assert_inequal (const Vector &vec1, const Vector &vec2, double tol=1e-9) |
| Not the same, prints if error. More... | |
| bool | assert_equal (const SubVector &vec1, const SubVector &vec2, double tol=1e-9) |
| Same, prints if error. More... | |
| bool | assert_equal (const ConstSubVector &expected, const ConstSubVector &actual, double tol) |
| bool | linear_dependent (const Vector &vec1, const Vector &vec2, double tol=1e-9) |
| check whether two vectors are linearly dependent More... | |
| Vector | ediv_ (const Vector &a, const Vector &b) |
| elementwise division, but 0/0 = 0, not inf More... | |
| double | houseInPlace (Vector &x) |
| beta = house(x) computes the HouseHolder vector in place | |
| pair< double, Vector > | house (const Vector &x) |
| house(x,j) computes HouseHolder vector v and scaling factor beta from x, such that the corresponding Householder reflection zeroes out all but x. More... | |
| double | weightedPseudoinverse (const Vector &a, const Vector &weights, Vector &pseudo) |
| pair< Vector, double > | weightedPseudoinverse (const Vector &v, const Vector &weights) |
| Weighted Householder solution vector, a.k.a., the pseudoinverse of the column NOTE: if any sigmas are zero (indicating a constraint) the pseudoinverse will be a selection vector, and the variance will be zero. More... | |
| Vector | concatVectors (const std::list< Vector > &vs) |
| concatenate Vectors | |
| Vector | concatVectors (size_t nrVectors,...) |
| concatenate Vectors | |
| bool | equal (const Vector &vec1, const Vector &vec2, double tol) |
| Override of equal in Lie.h. | |
| bool | equal (const Vector &vec1, const Vector &vec2) |
| Override of equal in Lie.h. | |
| template<class V1 , class V2 > | |
| double | dot (const V1 &a, const V2 &b) |
| Dot product. | |
| template<class V1 , class V2 > | |
| double | inner_prod (const V1 &a, const V2 &b) |
| compatibility version for ublas' inner_prod() | |
| void GTSAM_DEPRECATED | scal (double alpha, Vector &x) |
| BLAS Level 1 scal: x <- alpha*x. More... | |
| template<class V1 , class V2 > | |
| void GTSAM_DEPRECATED | axpy (double alpha, const V1 &x, V2 &y) |
| BLAS Level 1 axpy: y <- alpha*x + y. More... | |
| void | axpy (double alpha, const Vector &x, SubVector y) |
| template<size_t M> | |
| Matrix | kroneckerProductIdentity (const Weights &w) |
Function for computing the kronecker product of the 1*N Weight vector w with the MxM identity matrix I efficiently. More... | |
| template<int M> | |
| std::ostream & | operator<< (std::ostream &os, const ParameterMatrix< M > ¶meterMatrix) |
| template<typename L > | |
| std::vector< Assignment< L > > | cartesianProduct (const std::vector< std::pair< L, size_t > > &keys) |
| Get Cartesian product consisting all possible configurations. More... | |
| template<typename Y , typename L > | |
| DecisionTree< L, Y > | apply (const DecisionTree< L, Y > &f, const typename DecisionTree< L, Y >::Unary &op) |
| free versions of apply | |
| template<typename Y , typename L > | |
| DecisionTree< L, Y > | apply (const DecisionTree< L, Y > &f, const DecisionTree< L, Y > &g, const typename DecisionTree< L, Y >::Binary &op) |
| std::pair< DiscreteConditional::shared_ptr, DecisionTreeFactor::shared_ptr > | EliminateDiscrete (const DiscreteFactorGraph &factors, const Ordering &keys) |
| Main elimination function for DiscreteFactorGraph. | |
| DiscreteKeys | operator& (const DiscreteKey &key1, const DiscreteKey &key2) |
| Create a list from two keys. | |
| ostream & | operator<< (ostream &os, const Signature::Row &row) |
| ostream & | operator<< (ostream &os, const Signature::Table &table) |
| ostream & | operator<< (ostream &os, const Signature &s) |
| Signature | operator| (const DiscreteKey &key, const DiscreteKey &parent) |
| Helper function to create Signature objects example: Signature s = D | E;. | |
| Signature | operator% (const DiscreteKey &key, const std::string &parent) |
| Helper function to create Signature objects example: Signature s(D % "99/1"); Uses string parser, which requires BOOST 1.42 or higher. | |
| Signature | operator% (const DiscreteKey &key, const Signature::Table &parent) |
| Helper function to create Signature objects, using table construction directly example: Signature s(D % table);. | |
| std::ostream & | operator<< (std::ostream &os, const Cal3 &cal) |
| template<typename Cal , size_t Dim> | |
| void | calibrateJacobians (const Cal &calibration, const Point2 &pn, OptionalJacobian< 2, Dim > Dcal=boost::none, OptionalJacobian< 2, 2 > Dp=boost::none) |
Function which makes use of the Implicit Function Theorem to compute the Jacobians of calibrate using uncalibrate. More... | |
| std::ostream & | operator<< (std::ostream &os, const Cal3_S2 &cal) |
| std::ostream & | operator<< (std::ostream &os, const Cal3_S2Stereo &cal) |
| std::ostream & | operator<< (std::ostream &os, const Cal3Bundler &cal) |
| std::ostream & | operator<< (std::ostream &os, const Cal3DS2 &cal) |
| std::ostream & | operator<< (std::ostream &os, const Cal3DS2_Base &cal) |
| std::ostream & | operator<< (std::ostream &os, const Cal3Fisheye &cal) |
| std::ostream & | operator<< (std::ostream &os, const Cal3Unified &cal) |
| ostream & | operator<< (ostream &os, const EssentialMatrix &E) |
| istream & | operator>> (istream &is, EssentialMatrix &E) |
| Line3 | transformTo (const Pose3 &wTc, const Line3 &wL, OptionalJacobian< 4, 6 > Dpose=boost::none, OptionalJacobian< 4, 4 > Dline=boost::none) |
| Transform a line from world to camera frame. More... | |
| double | norm2 (const Point2 &p, OptionalJacobian< 1, 2 > H=boost::none) |
| Distance of the point from the origin, with Jacobian. | |
| double | distance2 (const Point2 &p1, const Point2 &q, OptionalJacobian< 1, 2 > H1=boost::none, OptionalJacobian< 1, 2 > H2=boost::none) |
| distance between two points | |
| boost::optional< Point2 > | circleCircleIntersection (double R_d, double r_d, double tol) |
| list< Point2 > | circleCircleIntersection (Point2 c1, Point2 c2, boost::optional< Point2 > fh) |
| list< Point2 > | circleCircleIntersection (Point2 c1, double r1, Point2 c2, double r2, double tol=1e-9) |
| Intersect 2 circles. More... | |
| ostream & | operator<< (ostream &os, const gtsam::Point2Pair &p) |
| Point2 | operator* (double s, const Point2 &p) |
| multiply with scalar | |
| double | distance3 (const Point3 &p1, const Point3 &q, OptionalJacobian< 1, 3 > H1=boost::none, OptionalJacobian< 1, 3 > H2=boost::none) |
| distance between two points | |
| double | norm3 (const Point3 &p, OptionalJacobian< 1, 3 > H=boost::none) |
| Distance of the point from the origin, with Jacobian. | |
| Point3 | normalize (const Point3 &p, OptionalJacobian< 3, 3 > H=boost::none) |
| normalize, with optional Jacobian | |
| Point3 | cross (const Point3 &p, const Point3 &q, OptionalJacobian< 3, 3 > H_p=boost::none, OptionalJacobian< 3, 3 > H_q=boost::none) |
| cross product More... | |
| double | dot (const Point3 &p, const Point3 &q, OptionalJacobian< 1, 3 > H_p=boost::none, OptionalJacobian< 1, 3 > H_q=boost::none) |
| dot product | |
| Point3Pair | means (const std::vector< Point3Pair > &abPointPairs) |
| Calculate the two means of a set of Point3 pairs. | |
| ostream & | operator<< (ostream &os, const gtsam::Point3Pair &p) |
| template<class CONTAINER > | |
| Point3 | mean (const CONTAINER &points) |
| mean | |
| std::ostream & | operator<< (std::ostream &os, const Pose2 &pose) |
| boost::optional< Pose2 > | align (const vector< Point2Pair > &pairs) |
| template<> | |
| Matrix | wedge< Pose2 > (const Vector &xi) |
| specialization for pose2 wedge function (generic template in Lie.h) | |
| boost::optional< Pose3 > | align (const Point3Pairs &baPointPairs) |
| std::ostream & | operator<< (std::ostream &os, const Pose3 &pose) |
| template<> | |
| Matrix | wedge< Pose3 > (const Vector &xi) |
| wedge for Pose3: More... | |
| pair< Matrix3, Vector3 > | RQ (const Matrix3 &A, OptionalJacobian< 3, 9 > H=boost::none) |
| [RQ] receives a 3 by 3 matrix and returns an upper triangular matrix R and 3 rotation angles corresponding to the rotation matrix Q=Qz'*Qy'*Qx' such that A = R*Q = R*Qz'*Qy'*Qx'. More... | |
| ostream & | operator<< (ostream &os, const Rot3 &R) |
| std::ostream & | operator<< (std::ostream &os, const Similarity3 &p) |
| template<> | |
| Matrix | wedge< Similarity3 > (const Vector &xi) |
| template<class Archive > | |
| void | serialize (Archive &ar, SO3 &R, const unsigned int) |
| Serialization function. | |
| GTSAM_EXPORT Matrix3 | topLeft (const SO4 &Q, OptionalJacobian< 9, 6 > H=boost::none) |
| Project to top-left 3*3 matrix. More... | |
| GTSAM_EXPORT Matrix43 | stiefel (const SO4 &Q, OptionalJacobian< 12, 6 > H=boost::none) |
| Project to Stiefel manifold of 4*3 orthonormal 3-frames in R^4, i.e., pi(Q) -> S \in St(3,4). | |
| template<class Archive > | |
| void | serialize (Archive &ar, SO4 &Q, const unsigned int) |
| Serialization function. | |
| template<class Archive > | |
| void | serialize (Archive &ar, SOn &Q, const unsigned int file_version) |
| Serialization function. | |
| ostream & | operator<< (ostream &os, const StereoPoint2 &p) |
| Vector4 | triangulateHomogeneousDLT (const std::vector< Matrix34, Eigen::aligned_allocator< Matrix34 > > &projection_matrices, const Point2Vector &measurements, double rank_tol=1e-9) |
| DLT triangulation: See Hartley and Zisserman, 2nd Ed., page 312. More... | |
| Point3 | triangulateDLT (const std::vector< Matrix34, Eigen::aligned_allocator< Matrix34 > > &projection_matrices, const Point2Vector &measurements, double rank_tol=1e-9) |
| DLT triangulation: See Hartley and Zisserman, 2nd Ed., page 312. More... | |
| Point3 | optimize (const NonlinearFactorGraph &graph, const Values &values, Key landmarkKey) |
| Optimize for triangulation. More... | |
| template<class CALIBRATION > | |
| std::pair< NonlinearFactorGraph, Values > | triangulationGraph (const std::vector< Pose3 > &poses, boost::shared_ptr< CALIBRATION > sharedCal, const Point2Vector &measurements, Key landmarkKey, const Point3 &initialEstimate) |
| Create a factor graph with projection factors from poses and one calibration. More... | |
| template<class CAMERA > | |
| std::pair< NonlinearFactorGraph, Values > | triangulationGraph (const CameraSet< CAMERA > &cameras, const typename CAMERA::MeasurementVector &measurements, Key landmarkKey, const Point3 &initialEstimate) |
| Create a factor graph with projection factors from pinhole cameras (each camera has a pose and calibration) More... | |
| template<class CALIBRATION > | |
| Point3 | triangulateNonlinear (const std::vector< Pose3 > &poses, boost::shared_ptr< CALIBRATION > sharedCal, const Point2Vector &measurements, const Point3 &initialEstimate) |
| Given an initial estimate , refine a point using measurements in several cameras. More... | |
| template<class CAMERA > | |
| Point3 | triangulateNonlinear (const CameraSet< CAMERA > &cameras, const typename CAMERA::MeasurementVector &measurements, const Point3 &initialEstimate) |
| Given an initial estimate , refine a point using measurements in several cameras. More... | |
| template<class CALIBRATION > | |
| Point3 | triangulatePoint3 (const std::vector< Pose3 > &poses, boost::shared_ptr< CALIBRATION > sharedCal, const Point2Vector &measurements, double rank_tol=1e-9, bool optimize=false) |
| Function to triangulate 3D landmark point from an arbitrary number of poses (at least 2) using the DLT. More... | |
| template<class CAMERA > | |
| Point3 | triangulatePoint3 (const CameraSet< CAMERA > &cameras, const typename CAMERA::MeasurementVector &measurements, double rank_tol=1e-9, bool optimize=false) |
| Function to triangulate 3D landmark point from an arbitrary number of poses (at least 2) using the DLT. More... | |
| template<class CALIBRATION > | |
| Point3 | triangulatePoint3 (const CameraSet< PinholeCamera< CALIBRATION > > &cameras, const Point2Vector &measurements, double rank_tol=1e-9, bool optimize=false) |
| Pinhole-specific version. | |
| template<class CAMERA > | |
| TriangulationResult | triangulateSafe (const CameraSet< CAMERA > &cameras, const typename CAMERA::MeasurementVector &measured, const TriangulationParameters ¶ms) |
| triangulateSafe: extensive checking of the outcome | |
| std::ostream & | operator<< (std::ostream &os, const Unit3 &pair) |
| template<class CLIQUE > | |
| bool | check_sharedCliques (const std::pair< Key, typename BayesTree< CLIQUE >::sharedClique > &v1, const std::pair< Key, typename BayesTree< CLIQUE >::sharedClique > &v2) |
| template<class KEY > | |
| std::list< KEY > | predecessorMap2Keys (const PredecessorMap< KEY > &p_map) |
| Generate a list of keys from a spanning tree represented by its predecessor map. | |
| template<class G , class F , class KEY > | |
| SDGraph< KEY > | toBoostGraph (const G &graph) |
| Convert the factor graph to an SDGraph G = Graph type F = Factor type Key = Key type. | |
| template<class G , class V , class KEY > | |
| boost::tuple< G, V, std::map< KEY, V > > | predecessorMap2Graph (const PredecessorMap< KEY > &p_map) |
| Build takes a predecessor map, and builds a directed graph corresponding to the tree. More... | |
| template<class G , class Factor , class POSE , class KEY > | |
| boost::shared_ptr< Values > | composePoses (const G &graph, const PredecessorMap< KEY > &tree, const POSE &rootPose) |
| Compose the poses by following the chain specified by the spanning tree. | |
| template<class G , class KEY , class FACTOR2 > | |
| PredecessorMap< KEY > | findMinimumSpanningTree (const G &g) |
| find the minimum spanning tree using boost graph library | |
| template<class G , class KEY , class FACTOR2 > | |
| void | split (const G &g, const PredecessorMap< KEY > &tree, G &Ab1, G &Ab2) |
| Split the graph into two parts: one corresponds to the given spanning tree, and the other corresponds to the rest of the factors. | |
| string | _defaultKeyFormatter (Key key) |
| void | PrintKey (Key key, const std::string &s="", const KeyFormatter &keyFormatter=DefaultKeyFormatter) |
| Utility function to print one key with optional prefix. | |
| string | _multirobotKeyFormatter (Key key) |
| template<class CONTAINER > | |
| void | Print (const CONTAINER &keys, const string &s, const KeyFormatter &keyFormatter) |
| void | PrintKeyList (const KeyList &keys, const std::string &s="", const KeyFormatter &keyFormatter=DefaultKeyFormatter) |
| Utility function to print sets of keys with optional prefix. | |
| void | PrintKeyVector (const KeyVector &keys, const std::string &s="", const KeyFormatter &keyFormatter=DefaultKeyFormatter) |
| Utility function to print sets of keys with optional prefix. | |
| void | PrintKeySet (const KeySet &keys, const std::string &s="", const KeyFormatter &keyFormatter=DefaultKeyFormatter) |
| Utility function to print sets of keys with optional prefix. | |
| ostream & | operator<< (ostream &os, const key_formatter &m) |
| ostream & | operator<< (ostream &os, const StreamedKey &streamedKey) |
| GTSAM_EXPORT std::ostream & | operator<< (std::ostream &os, const LabeledSymbol &symbol) |
| Key | mrsymbol (unsigned char c, unsigned char label, size_t j) |
| Create a symbol key from a character, label and index, i.e. More... | |
| unsigned char | mrsymbolChr (Key key) |
| Return the character portion of a symbol key. | |
| unsigned char | mrsymbolLabel (Key key) |
| Return the label portion of a symbol key. | |
| size_t | mrsymbolIndex (Key key) |
| Return the index portion of a symbol key. | |
| GTSAM_EXPORT std::ostream & | operator<< (std::ostream &os, const Symbol &symbol) |
| Key | symbol (unsigned char c, std::uint64_t j) |
| Create a symbol key from a character and index, i.e. More... | |
| unsigned char | symbolChr (Key key) |
| Return the character portion of a symbol key. | |
| std::uint64_t | symbolIndex (Key key) |
| Return the index portion of a symbol key. | |
| template<class S , class V > | |
| V | preconditionedConjugateGradient (const S &system, const V &initial, const ConjugateGradientParameters ¶meters) |
| double | dot (const Errors &a, const Errors &b) |
| dot product | |
| template<> | |
| void | axpy (double alpha, const Errors &x, Errors &y) |
| BLAS level 2 style. | |
| void | print (const Errors &a, const std::string &s="Error") |
| print with optional string | |
| template<> | |
| GTSAM_EXPORT void | axpy (double alpha, const Errors &x, Errors &y) |
| BLAS level 2 style. | |
| bool | hasConstraints (const GaussianFactorGraph &factors) |
| Evaluates whether linear factors have any constrained noise models. More... | |
| std::pair< boost::shared_ptr< GaussianConditional >, boost::shared_ptr< HessianFactor > > | EliminateCholesky (const GaussianFactorGraph &factors, const Ordering &keys) |
| std::pair< boost::shared_ptr< GaussianConditional >, boost::shared_ptr< GaussianFactor > > | EliminatePreferCholesky (const GaussianFactorGraph &factors, const Ordering &keys) |
| template<class S , class V , class E > | |
| V | conjugateGradients (const S &Ab, V x, const ConjugateGradientParameters ¶meters, bool steepest=false) |
| Method of conjugate gradients (CG) template "System" class S needs gradient(S,v), e=S*v, v=S^e "Vector" class V needs dot(v,v), -v, v+v, s*v "Vector" class E needs dot(v,v) More... | |
| Vector | steepestDescent (const System &Ab, const Vector &x, const ConjugateGradientParameters ¶meters) |
| Vector | conjugateGradientDescent (const System &Ab, const Vector &x, const ConjugateGradientParameters ¶meters) |
| Method of conjugate gradients (CG), System version. | |
| Vector | steepestDescent (const Matrix &A, const Vector &b, const Vector &x, const ConjugateGradientParameters ¶meters) |
| convenience calls using matrices, will create System class internally: More... | |
| Vector | conjugateGradientDescent (const Matrix &A, const Vector &b, const Vector &x, const ConjugateGradientParameters ¶meters) |
| Method of conjugate gradients (CG), Matrix version. | |
| VectorValues | steepestDescent (const GaussianFactorGraph &fg, const VectorValues &x, const ConjugateGradientParameters ¶meters) |
| Method of steepest gradients, Gaussian Factor Graph version. | |
| VectorValues | conjugateGradientDescent (const GaussianFactorGraph &fg, const VectorValues &x, const ConjugateGradientParameters ¶meters) |
| Method of conjugate gradients (CG), Gaussian Factor Graph version. | |
| GTSAM_EXPORT Vector | steepestDescent (const System &Ab, const Vector &x, const IterativeOptimizationParameters ¶meters) |
| Method of steepest gradients, System version. | |
| ostream & | operator<< (ostream &os, const IterativeOptimizationParameters &p) |
| FastVector< VariableSlots::const_iterator > | orderedSlotsHelper (const Ordering &ordering, const VariableSlots &variableSlots) |
| std::pair< GaussianConditional::shared_ptr, JacobianFactor::shared_ptr > | EliminateQR (const GaussianFactorGraph &factors, const Ordering &keys) |
| Multiply all factors and eliminate the given keys from the resulting factor using a QR variant that handles constraints (zero sigmas). More... | |
| ostream & | operator<< (ostream &os, const PreconditionerParameters &p) |
| boost::shared_ptr< Preconditioner > | createPreconditioner (const boost::shared_ptr< PreconditionerParameters > params) |
| SparseEigen | sparseJacobianEigen (const GaussianFactorGraph &gfg, const Ordering &ordering) |
| Constructs an Eigen-format SparseMatrix of a GaussianFactorGraph. | |
| SparseEigen | sparseJacobianEigen (const GaussianFactorGraph &gfg) |
| ostream & | operator<< (ostream &os, const Subgraph::Edge &edge) |
| ostream & | operator<< (ostream &os, const Subgraph &subgraph) |
| ostream & | operator<< (ostream &os, const SubgraphBuilderParameters &p) |
| GaussianFactorGraph::shared_ptr | buildFactorSubgraph (const GaussianFactorGraph &gfg, const Subgraph &subgraph, const bool clone) |
| Select the factors in a factor graph according to the subgraph. | |
| std::pair< GaussianFactorGraph::shared_ptr, GaussianFactorGraph::shared_ptr > | splitFactorGraph (const GaussianFactorGraph &factorGraph, const Subgraph &subgraph) |
| Split the graph into a subgraph and the remaining edges. More... | |
| GTSAM_EXPORT ostream & | operator<< (ostream &os, const VectorValues &v) |
| VectorValues | operator* (const double a, const VectorValues &v) |
| std::ostream & | operator<< (std::ostream &os, const CombinedImuFactor &f) |
| Rot3_ | attitude (const NavState_ &X) |
| Point3_ | position (const NavState_ &X) |
| Velocity3_ | velocity (const NavState_ &X) |
| std::ostream & | operator<< (std::ostream &os, const ImuFactor &f) |
| std::ostream & | operator<< (std::ostream &os, const ImuFactor2 &f) |
| ostream & | operator<< (ostream &os, const NavState &state) |
| ostream & | operator<< (ostream &os, const PreintegrationBase &pim) |
| template<typename T > | |
| Expression< T > | operator* (const Expression< T > &expression1, const Expression< T > &expression2) |
| Construct a product expression, assumes T::compose(T) -> T. More... | |
| template<typename T > | |
| std::vector< Expression< T > > | createUnknowns (size_t n, char c, size_t start) |
| Construct an array of leaves. More... | |
| template<typename T , typename A > | |
| Expression< T > | linearExpression (const std::function< T(A)> &f, const Expression< A > &expression, const Eigen::Matrix< double, traits< T >::dimension, traits< A >::dimension > &dTdA) |
| Create an expression out of a linear function f:T->A with (constant) Jacobian dTdA TODO(frank): create a more efficient version like ScalarMultiplyExpression. More... | |
| template<typename T > | |
| ScalarMultiplyExpression< T > | operator* (double s, const Expression< T > &e) |
| Construct an expression that executes the scalar multiplication with an input expression The type T must be a vector space Example: Expression<Point2> a(0), b = 12 * a;. | |
| template<typename T > | |
| BinarySumExpression< T > | operator+ (const Expression< T > &e1, const Expression< T > &e2) |
| Construct an expression that sums two input expressions of the same type T The type T must be a vector space Example: Expression<Point2> a(0), b(1), c = a + b;. | |
| template<typename T > | |
| BinarySumExpression< T > | operator- (const Expression< T > &e1, const Expression< T > &e2) |
| Construct an expression that subtracts one expression from another. | |
| template<typename T > | |
| Expression< T > | between (const Expression< T > &t1, const Expression< T > &t2) |
| template<typename T > | |
| Expression< T > | compose (const Expression< T > &t1, const Expression< T > &t2) |
| JacobianFactor | linearizeNumerically (const NoiseModelFactor &factor, const Values &values, double delta=1e-5) |
| Linearize a nonlinear factor using numerical differentiation The benefit of this method is that it does not need to know what types are involved to evaluate the factor. More... | |
| template<typename T , typename R , typename FUNC > | |
| FunctorizedFactor< R, T > | MakeFunctorizedFactor (Key key, const R &z, const SharedNoiseModel &model, const FUNC func) |
| Helper function to create a functorized factor. More... | |
| template<typename T1 , typename T2 , typename R , typename FUNC > | |
| FunctorizedFactor2< R, T1, T2 > | MakeFunctorizedFactor2 (Key key1, Key key2, const R &z, const SharedNoiseModel &model, const FUNC func) |
| Helper function to create a functorized factor. More... | |
| size_t | optimizeWildfire (const ISAM2Clique::shared_ptr &root, double threshold, const KeySet &replaced, VectorValues *delta) |
| Optimize the BayesTree, starting from the root. More... | |
| size_t | optimizeWildfireNonRecursive (const ISAM2Clique::shared_ptr &root, double threshold, const KeySet &keys, VectorValues *delta) |
| template<class S , class V , class W > | |
| double | lineSearch (const S &system, const V currentValues, const W &gradient) |
| Implement the golden-section line search algorithm. | |
| template<class S , class V > | |
| boost::tuple< V, int > | nonlinearConjugateGradient (const S &system, const V &initial, const NonlinearOptimizerParams ¶ms, const bool singleIteration, const bool gradientDescent=false) |
| Implement the nonlinear conjugate gradient method using the Polak-Ribiere formula suggested in http://en.wikipedia.org/wiki/Nonlinear_conjugate_gradient_method. More... | |
| bool | checkConvergence (double relativeErrorTreshold, double absoluteErrorTreshold, double errorThreshold, double currentError, double newError, NonlinearOptimizerParams::Verbosity verbosity=NonlinearOptimizerParams::SILENT) |
| Check whether the relative error decrease is less than relativeErrorTreshold, the absolute error decrease is less than absoluteErrorTreshold, or the error itself is less than errorThreshold. | |
| GTSAM_EXPORT bool | checkConvergence (const NonlinearOptimizerParams ¶ms, double currentError, double newError) |
| string | findExampleDataFile (const std::string &name) |
| Find the full path to an example dataset distributed with gtsam. More... | |
| string | createRewrittenFileName (const std::string &name) |
| Creates a temporary file name that needs to be ignored in .gitingnore for checking read-write oprations. | |
| template<typename T > | |
| map< size_t, T > | parseToMap (const string &filename, Parser< pair< size_t, T > > parse, size_t maxIndex) |
| boost::optional< IndexedPose > | parseVertexPose (std::istream &is, const std::string &tag) |
| Parse TORO/G2O vertex "id x y yaw". More... | |
| template<> | |
| std::map< size_t, Pose2 > | parseVariables< Pose2 > (const std::string &filename, size_t maxIndex) |
| boost::optional< IndexedLandmark > | parseVertexLandmark (std::istream &is, const std::string &tag) |
| Parse G2O landmark vertex "id x y". More... | |
| template<> | |
| std::map< size_t, Point2 > | parseVariables< Point2 > (const std::string &filename, size_t maxIndex) |
| boost::optional< IndexedEdge > | parseEdge (std::istream &is, const std::string &tag) |
| Parse TORO/G2O edge "id1 id2 x y yaw". More... | |
| boost::shared_ptr< Sampler > | createSampler (const SharedNoiseModel &model) |
| template<> | |
| std::vector< BinaryMeasurement< Pose2 > > | parseMeasurements (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
| template<> | |
| std::vector< BinaryMeasurement< Rot2 > > | parseMeasurements (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
| template<> | |
| std::vector< BetweenFactor< Pose2 >::shared_ptr > | parseFactors< Pose2 > (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
| GraphAndValues | load2D (const std::string &filename, SharedNoiseModel model=SharedNoiseModel(), size_t maxIndex=0, bool addNoise=false, bool smart=true, NoiseFormat noiseFormat=NoiseFormatAUTO, KernelFunctionType kernelFunctionType=KernelFunctionTypeNONE) |
| Load TORO/G2O style graph files. More... | |
| GraphAndValues | load2D (pair< string, SharedNoiseModel > dataset, size_t maxIndex, bool addNoise, bool smart, NoiseFormat noiseFormat, KernelFunctionType kernelFunctionType) |
| Load TORO 2D Graph. More... | |
| GraphAndValues | load2D_robust (const string &filename, const noiseModel::Base::shared_ptr &model, size_t maxIndex) |
| void | save2D (const NonlinearFactorGraph &graph, const Values &config, const noiseModel::Diagonal::shared_ptr model, const std::string &filename) |
| save 2d graph | |
| GraphAndValues | readG2o (const std::string &g2oFile, const bool is3D=false, KernelFunctionType kernelFunctionType=KernelFunctionTypeNONE) |
| This function parses a g2o file and stores the measurements into a NonlinearFactorGraph and the initial guess in a Values structure. More... | |
| void | writeG2o (const NonlinearFactorGraph &graph, const Values &estimate, const std::string &filename) |
| This function writes a g2o file from NonlinearFactorGraph and a Values structure. More... | |
| istream & | operator>> (istream &is, Quaternion &q) |
| istream & | operator>> (istream &is, Rot3 &R) |
| boost::optional< pair< size_t, Pose3 > > | parseVertexPose3 (istream &is, const string &tag) |
| template<> | |
| std::map< size_t, Pose3 > | parseVariables< Pose3 > (const std::string &filename, size_t maxIndex) |
| boost::optional< pair< size_t, Point3 > > | parseVertexPoint3 (istream &is, const string &tag) |
| template<> | |
| std::map< size_t, Point3 > | parseVariables< Point3 > (const std::string &filename, size_t maxIndex) |
| istream & | operator>> (istream &is, Matrix6 &m) |
| template<> | |
| std::vector< BinaryMeasurement< Pose3 > > | parseMeasurements (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
| template<> | |
| std::vector< BinaryMeasurement< Rot3 > > | parseMeasurements (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
| template<> | |
| std::vector< BetweenFactor< Pose3 >::shared_ptr > | parseFactors< Pose3 > (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
| GraphAndValues | load3D (const std::string &filename) |
| Load TORO 3D Graph. | |
| Rot3 | openGLFixedRotation () |
| Pose3 | openGL2gtsam (const Rot3 &R, double tx, double ty, double tz) |
| This function converts an openGL camera pose to an GTSAM camera pose. More... | |
| Pose3 | gtsam2openGL (const Rot3 &R, double tx, double ty, double tz) |
| This function converts a GTSAM camera pose to an openGL camera pose. More... | |
| Pose3 | gtsam2openGL (const Pose3 &PoseGTSAM) |
| This function converts a GTSAM camera pose to an openGL camera pose. More... | |
| bool | readBundler (const std::string &filename, SfmData &data) |
| This function parses a bundler output file and stores the data into a SfmData structure. More... | |
| bool | readBAL (const std::string &filename, SfmData &data) |
| This function parses a "Bundle Adjustment in the Large" (BAL) file and stores the data into a SfmData structure. More... | |
| SfmData | readBal (const std::string &filename) |
| This function parses a "Bundle Adjustment in the Large" (BAL) file and returns the data as a SfmData structure. More... | |
| bool | writeBAL (const std::string &filename, SfmData &data) |
| This function writes a "Bundle Adjustment in the Large" (BAL) file from a SfmData structure. More... | |
| bool | writeBALfromValues (const std::string &filename, const SfmData &data, Values &values) |
| This function writes a "Bundle Adjustment in the Large" (BAL) file from a SfmData structure and a value structure (measurements are the same as the SfM input data, while camera poses and values are read from Values) More... | |
| Values | initialCamerasEstimate (const SfmData &db) |
| This function creates initial values for cameras from db. More... | |
| Values | initialCamerasAndPointsEstimate (const SfmData &db) |
| This function creates initial values for cameras and points from db. More... | |
| BetweenFactorPose2s | parse2DFactors (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
| BetweenFactorPose3s | parse3DFactors (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
| template<typename T > | |
| GTSAM_EXPORT std::map< size_t, T > | parseVariables (const std::string &filename, size_t maxIndex=0) |
| Parse variables in a line-based text format (like g2o) into a map. More... | |
| template<typename T > | |
| GTSAM_EXPORT std::vector< BinaryMeasurement< T > > | parseMeasurements (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model=nullptr, size_t maxIndex=0) |
| Parse binary measurements in a line-based text format (like g2o) into a vector. More... | |
| template<typename T > | |
| GTSAM_EXPORT std::vector< typename BetweenFactor< T >::shared_ptr > | parseFactors (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model=nullptr, size_t maxIndex=0) |
| Parse BetweenFactors in a line-based text format (like g2o) into a vector of shared pointers. More... | |
| GTSAM_EXPORT GraphAndValues | load2D (std::pair< std::string, SharedNoiseModel > dataset, size_t maxIndex=0, bool addNoise=false, bool smart=true, NoiseFormat noiseFormat=NoiseFormatAUTO, KernelFunctionType kernelFunctionType=KernelFunctionTypeNONE) |
| Load TORO 2D Graph. More... | |
| Point2_ | transformTo (const Pose2_ &x, const Point2_ &p) |
| Point3_ | transformTo (const Pose3_ &x, const Point3_ &p) |
| Point3_ | transformFrom (const Pose3_ &x, const Point3_ &p) |
| Line3_ | transformTo (const Pose3_ &wTc, const Line3_ &wL) |
| Point3_ | cross (const Point3_ &a, const Point3_ &b) |
| Double_ | dot (const Point3_ &a, const Point3_ &b) |
| Rot3_ | rotation (const Pose3_ &pose) |
| Point3_ | rotate (const Rot3_ &x, const Point3_ &p) |
| Unit3_ | rotate (const Rot3_ &x, const Unit3_ &p) |
| Point3_ | unrotate (const Rot3_ &x, const Point3_ &p) |
| Unit3_ | unrotate (const Rot3_ &x, const Unit3_ &p) |
| Point2_ | project (const Point3_ &p_cam) |
| Expression version of PinholeBase::Project. | |
| Point2_ | project (const Unit3_ &p_cam) |
| template<class CAMERA , class POINT > | |
| Point2_ | project2 (const Expression< CAMERA > &camera_, const Expression< POINT > &p_) |
| template<class CALIBRATION , class POINT > | |
| Point2_ | project3 (const Pose3_ &x, const Expression< POINT > &p, const Expression< CALIBRATION > &K) |
| template<class CALIBRATION > | |
| Point2_ | uncalibrate (const Expression< CALIBRATION > &K, const Point2_ &xy_hat) |
| template<typename T > | |
| gtsam::Expression< typename gtsam::traits< T >::TangentVector > | logmap (const gtsam::Expression< T > &x1, const gtsam::Expression< T > &x2) |
| logmap | |
| SharedNoiseModel | ConvertNoiseModel (const SharedNoiseModel &model, size_t n, bool defaultToUnit=true) |
| When creating (any) FrobeniusFactor we can convert a Rot/Pose BetweenFactor noise model into a n-dimensional isotropic noise model used to weight the Frobenius norm. More... | |
| template<class T , class ALLOC > | |
| T | FindKarcherMeanImpl (const vector< T, ALLOC > &rotations) |
| template<class T , typename = typename std::enable_if< std::is_same<gtsam::Rot3, T>::value >::type> | |
| T | FindKarcherMean (const std::vector< T > &rotations) |
| template<class T > | |
| T | FindKarcherMean (const std::vector< T, Eigen::aligned_allocator< T > > &rotations) |
| Optimize for the Karcher mean, minimizing the geodesic distance to each of the given rotations, by constructing a factor graph out of simple PriorFactors. | |
| template<class T > | |
| T | FindKarcherMean (std::initializer_list< T > &&rotations) |
| template<class T , class P > | |
| P | transform_point (const T &trans, const P &global, boost::optional< Matrix & > Dtrans, boost::optional< Matrix & > Dglobal) |
| Transform function that must be specialized specific domains. More... | |
| std::pair< boost::shared_ptr< SymbolicConditional >, boost::shared_ptr< SymbolicFactor > > | EliminateSymbolic (const SymbolicFactorGraph &factors, const Ordering &keys) |
| Dense elimination function for symbolic factors. More... | |
| template<class PROBLEM > | |
| Key | maxKey (const PROBLEM &problem) |
| Find the max key in a problem. More... | |
| template<class LinearGraph > | |
| KeyDimMap | collectKeyDim (const LinearGraph &linearGraph) |
| void | synchronize (ConcurrentFilter &filter, ConcurrentSmoother &smoother) |
| void | recursiveMarkAffectedKeys (const Key &key, const ISAM2Clique::shared_ptr &clique, std::set< Key > &additionalKeys) |
| std::string | serializeGraph (const NonlinearFactorGraph &graph) |
| NonlinearFactorGraph::shared_ptr | deserializeGraph (const std::string &serialized_graph) |
| std::string | serializeGraphXML (const NonlinearFactorGraph &graph, const std::string &name="graph") |
| NonlinearFactorGraph::shared_ptr | deserializeGraphXML (const std::string &serialized_graph, const std::string &name="graph") |
| std::string | serializeValues (const Values &values) |
| Values::shared_ptr | deserializeValues (const std::string &serialized_values) |
| std::string | serializeValuesXML (const Values &values, const std::string &name="values") |
| Values::shared_ptr | deserializeValuesXML (const std::string &serialized_values, const std::string &name="values") |
| bool | serializeGraphToFile (const NonlinearFactorGraph &graph, const std::string &fname) |
| bool | serializeGraphToXMLFile (const NonlinearFactorGraph &graph, const std::string &fname, const std::string &name="graph") |
| bool | serializeValuesToFile (const Values &values, const std::string &fname) |
| bool | serializeValuesToXMLFile (const Values &values, const std::string &fname, const std::string &name="values") |
| NonlinearFactorGraph::shared_ptr | deserializeGraphFromFile (const std::string &fname) |
| NonlinearFactorGraph::shared_ptr | deserializeGraphFromXMLFile (const std::string &fname, const std::string &name="graph") |
| Values::shared_ptr | deserializeValuesFromFile (const std::string &fname) |
| Values::shared_ptr | deserializeValuesFromXMLFile (const std::string &fname, const std::string &name="values") |
| double | bound (double a, double min, double max) |
Standard serialization | |
Serialization in default compressed format | |
| template<class T > | |
| void | serializeToStream (const T &input, std::ostream &out_archive_stream) |
| template<class T > | |
| void | deserializeFromStream (std::istream &in_archive_stream, T &output) |
| deserializes from a stream | |
| template<class T > | |
| std::string | serializeToString (const T &input) |
| serializes to a string | |
| template<class T > | |
| void | deserializeFromString (const std::string &serialized, T &output) |
| deserializes from a string | |
| template<class T > | |
| bool | serializeToFile (const T &input, const std::string &filename) |
| serializes to a file | |
| template<class T > | |
| bool | deserializeFromFile (const std::string &filename, T &output) |
| deserializes from a file | |
| template<class T > | |
| std::string | serialize (const T &input) |
| serializes to a string | |
| template<class T > | |
| void | deserialize (const std::string &serialized, T &output) |
| deserializes from a string | |
XML Serialization | |
Serialization to XML format with named structures | |
| template<class T > | |
| void | serializeToXMLStream (const T &input, std::ostream &out_archive_stream, const std::string &name="data") |
| template<class T > | |
| void | deserializeFromXMLStream (std::istream &in_archive_stream, T &output, const std::string &name="data") |
| deserializes from a stream in XML | |
| template<class T > | |
| std::string | serializeToXMLString (const T &input, const std::string &name="data") |
| serializes to a string in XML | |
| template<class T > | |
| void | deserializeFromXMLString (const std::string &serialized, T &output, const std::string &name="data") |
| deserializes from a string in XML | |
| template<class T > | |
| bool | serializeToXMLFile (const T &input, const std::string &filename, const std::string &name="data") |
| serializes to an XML file | |
| template<class T > | |
| bool | deserializeFromXMLFile (const std::string &filename, T &output, const std::string &name="data") |
| deserializes from an XML file | |
| template<class T > | |
| std::string | serializeXML (const T &input, const std::string &name="data") |
| serializes to a string in XML | |
| template<class T > | |
| void | deserializeXML (const std::string &serialized, T &output, const std::string &name="data") |
| deserializes from a string in XML | |
Binary Serialization | |
Serialization to binary format with named structures | |
| template<class T > | |
| void | serializeToBinaryStream (const T &input, std::ostream &out_archive_stream, const std::string &name="data") |
| template<class T > | |
| void | deserializeFromBinaryStream (std::istream &in_archive_stream, T &output, const std::string &name="data") |
| deserializes from a stream in binary | |
| template<class T > | |
| std::string | serializeToBinaryString (const T &input, const std::string &name="data") |
| serializes to a string in binary | |
| template<class T > | |
| void | deserializeFromBinaryString (const std::string &serialized, T &output, const std::string &name="data") |
| deserializes from a string in binary | |
| template<class T > | |
| bool | serializeToBinaryFile (const T &input, const std::string &filename, const std::string &name="data") |
| serializes to a binary file | |
| template<class T > | |
| bool | deserializeFromBinaryFile (const std::string &filename, T &output, const std::string &name="data") |
| deserializes from a binary file | |
| template<class T > | |
| std::string | serializeBinary (const T &input, const std::string &name="data") |
| serializes to a string in binary | |
| template<class T > | |
| void | deserializeBinary (const std::string &serialized, T &output, const std::string &name="data") |
| deserializes from a string in binary | |
utility functions | |
| VectorValues | buildVectorValues (const Vector &v, const Ordering &ordering, const std::map< Key, size_t > &dimensions) |
| Create VectorValues from a Vector. | |
| VectorValues | buildVectorValues (const Vector &v, const KeyInfo &keyInfo) |
| Create VectorValues from a Vector and a KeyInfo class. | |
Variables | |
| GTSAM_EXPORT FastMap< std::string, ValueWithDefault< bool, false > > | debugFlags |
| const G & | b |
| const G double | tol |
| template class GTSAM_EXPORT | Conditional< DecisionTreeFactor, DiscreteConditional > |
| const double | logSqrt2PI = log(std::sqrt(2.0 * M_PI)) |
| constant needed below | |
Global functions in a separate testing namespace.
This file supports creating continuous functions f(x;p) as a linear combination of basis functions such as the Fourier basis on SO(2) or a set of Chebyshev polynomials on [-1,1].
Matrix is a typedef in the gtsam namespace TODO: make a version to work with matlab wrapping we use the default < double,col_major,unbounded_array<double> >
These should not be used outside of tests, as they are just remappings of the original functions. We use these to avoid needing to do too much std::bind magic or writing a bunch of separate proxy functions.
Don't expect all classes to work for all of these functions.
In the expression f(x;p) the variable x is the continuous argument at which the function is evaluated, and p are the parameters which are coefficients of the different basis functions, e.g. p = [4; 3; 2] => 4 + 3x + 2x^2 for a polynomial. However, different parameterizations are also possible.
The Basis class below defines a number of functors that can be used to evaluate f(x;p) at a given x, and these functors also calculate the Jacobian of f(x;p) with respect to the parameters p. This is actually the most important calculation, as it will allow GTSAM to optimize over the parameters p.
This functionality is implemented using the CRTP or "Curiously recurring
template pattern" C++ idiom, which is a meta-programming technique in which the derived class is passed as a template argument to Basis<DERIVED>. The DERIVED class is assumed to satisfy a C++ concept, i.e., we expect it to define the following types and methods:
Parameters: the parameters p in f(x;p)CalculateWeights(size_t N, double x, double a=default, double b=default)DerivativeWeights(size_t N, double x, double a=default, double b=default)where Weights is an N*1 row vector which defines the basis values for the polynomial at the specified point x.
E.g. A Fourier series would give the following:
CalculateWeights -> For N=5, the values for the bases: [1, cos(x), sin(x), cos(2x), sin(2x)]DerivativeWeights -> For N=5, these are: [0, -sin(x), cos(x), -2sin(2x), 2cos(x)]Note that for a pseudo-spectral basis (as in Chebyshev2), the weights are instead the values for the Barycentric interpolation formula, since the values at the polynomial points (e.g. Chebyshev points) define the bases.
| typedef FastVector< FactorIndex > gtsam::FactorIndices |
Define collection types:
Define collection type:
| using gtsam::GraphAndValues = typedef std::pair<NonlinearFactorGraph::shared_ptr, Values::shared_ptr> |
Return type for load functions, which return a graph and initial values.
For landmarks, the gtsam::Symbol L(index) is used to insert into the Values. Bearing-range measurements also refer to landmarks with L(index).
| using gtsam::PinholeCameraCal3_S2 = typedef gtsam::PinholeCamera<gtsam::Cal3_S2> |
Convenient aliases for Pinhole camera classes with different calibrations.
Also needed as forward declarations in the wrapper.
| typedef noiseModel::Base::shared_ptr gtsam::SharedNoiseModel |
Note, deliberately not in noiseModel namespace.
Deprecated. Only for compatibility with previous version.
| typedef Eigen::SparseMatrix<double, Eigen::ColMajor, int> gtsam::SparseEigen |
Eigen-format sparse matrix.
Note: ColMajor is ~20% faster since InnerIndices must be sorted
| typedef Vector3 gtsam::Velocity3 |
Velocity is currently typedef'd to Vector3.
Syntactic sugar to clarify components.
SmartFactorParams: parameters and (linearization/degeneracy) modes for SmartProjection and SmartStereoProjection factors.
Linearization mode: what factor to linearize to
| enum gtsam::NoiseFormat |
Indicates how noise parameters are stored in file.
| bool gtsam::assert_equal | ( | const boost::optional< V > & | expected, |
| const boost::optional< V > & | actual, | ||
| double | tol = 1e-9 |
||
| ) |
Comparisons for boost.optional objects that checks whether objects exist before comparing their values.
First version allows for both to be boost::none, but the second, with expected given rather than optional
Concept requirement: V is testable
| bool GTSAM_DEPRECATED gtsam::assert_equal | ( | const std::vector< V > & | expected, |
| const std::vector< V > & | actual, | ||
| double | tol = 1e-9 |
||
| ) |
Version of assert_equals to work with vectors.
| GTSAM_EXPORT bool gtsam::assert_equal | ( | const SubVector & | vec1, |
| const SubVector & | vec2, | ||
| double | tol = 1e-9 |
||
| ) |
Same, prints if error.
| vec1 | Vector |
| vec2 | Vector |
| tol | 1e-9 |
| GTSAM_EXPORT bool gtsam::assert_equal | ( | const Vector & | vec1, |
| const Vector & | vec2, | ||
| double | tol = 1e-9 |
||
| ) |
Same, prints if error.
| vec1 | Vector |
| vec2 | Vector |
| tol | 1e-9 |
| GTSAM_EXPORT bool gtsam::assert_inequal | ( | const Vector & | vec1, |
| const Vector & | vec2, | ||
| double | tol = 1e-9 |
||
| ) |
Not the same, prints if error.
| vec1 | Vector |
| vec2 | Vector |
| tol | 1e-9 |
| bool gtsam::assert_print_equal | ( | const std::string & | expected, |
| const V & | actual, | ||
| const std::string & | s = "" |
||
| ) |
Capture print function output and compare against string.
| s | Optional string to pass to the print() method. |
|
inline |
BLAS Level 1 axpy: y <- alpha*x + y.
| GTSAM_EXPORT Vector gtsam::backSubstituteLower | ( | const Matrix & | L, |
| const Vector & | b, | ||
| bool | unit = false |
||
| ) |
backSubstitute L*x=b
| L | an lower triangular matrix |
| b | an RHS vector |
| unit,set | true if unit triangular |
| GTSAM_EXPORT Vector gtsam::backSubstituteUpper | ( | const Matrix & | U, |
| const Vector & | b, | ||
| bool | unit = false |
||
| ) |
backSubstitute U*x=b
| U | an upper triangular matrix |
| b | an RHS vector |
| unit,set | true if unit triangular |
| GTSAM_EXPORT Vector gtsam::backSubstituteUpper | ( | const Vector & | b, |
| const Matrix & | U, | ||
| bool | unit = false |
||
| ) |
backSubstitute x'*U=b'
| U | an upper triangular matrix |
| b | an RHS vector |
| unit,set | true if unit triangular |
| T gtsam::BCH | ( | const T & | X, |
| const T & | Y | ||
| ) |
Three term approximation of the Baker-Campbell-Hausdorff formula In non-commutative Lie groups, when composing exp(Z) = exp(X)exp(Y) it is not true that Z = X+Y.
Instead, Z can be calculated using the BCH formula: Z = X + Y + [X,Y]/2 + [X-Y,[X,Y]]/12 - [Y,[X,[X,Y]]]/24 http://en.wikipedia.org/wiki/Baker-Campbell-Hausdorff_formula AGC: bracket() only appears in Rot3 tests, should this be used elsewhere?
|
inline |
These core global functions can be specialized by new Lie types for better performance.
Compute l0 s.t. l2=l1*l0
| void gtsam::calibrateJacobians | ( | const Cal & | calibration, |
| const Point2 & | pn, | ||
| OptionalJacobian< 2, Dim > | Dcal = boost::none, |
||
| OptionalJacobian< 2, 2 > | Dp = boost::none |
||
| ) |
Function which makes use of the Implicit Function Theorem to compute the Jacobians of calibrate using uncalibrate.
This is useful when there are iterative operations in the calibrate function which make computing jacobians difficult.
Given f(pi, pn) = uncalibrate(pn) - pi, and g(pi) = calibrate, we can easily compute the Jacobians: df/pi = -I (pn and pi are independent args) Dp = -inv(H_uncal_pn) * df/pi = -inv(H_uncal_pn) * (-I) = inv(H_uncal_pn) Dcal = -inv(H_uncal_pn) * df/K = -inv(H_uncal_pn) * H_uncal_K
| Cal | Calibration model. |
| Dim | The number of parameters in the calibration model. |
| p | Calibrated point. |
| Dcal | optional 2*p Jacobian wrpt p Cal3DS2 parameters. |
| Dp | optional 2*2 Jacobian wrpt intrinsic coordinates. |
| std::vector< Assignment< L > > gtsam::cartesianProduct | ( | const std::vector< std::pair< L, size_t > > & | keys | ) |
Get Cartesian product consisting all possible configurations.
| vector | list of keys (label,cardinality) pairs. |
This function returns a vector of Assignment values for all possible (Cartesian product) configurations of set of Keys which are nothing but (Label,cardinality) pairs. This function should NOT be called for more than a small number of variables and cardinalities. E.g. For 6 variables with each having cardinalities 4, we get 4096 possible configurations!!
| GTSAM_EXPORT Matrix gtsam::cholesky_inverse | ( | const Matrix & | A | ) |
Return the inverse of a S.P.D.
matrix. Inversion is done via Cholesky decomposition.
| GTSAM_EXPORT std::pair< size_t, bool > gtsam::choleskyCareful | ( | Matrix & | ATA, |
| int | order = -1 |
||
| ) |
"Careful" Cholesky computes the positive square-root of a positive symmetric semi-definite matrix (i.e.
that may be rank-deficient). Unlike standard Cholesky, the square-root factor may have all-zero rows for free variables.
Additionally, this function returns the index of the row after the last non-zero row in the computed factor, so that it may be truncated to an upper-trapazoidal matrix.
The second element of the return value is true if the matrix was factored successfully, or false if it was non-positive-semidefinite (i.e. indefinite or negative-(semi-)definite.
Note that this returned index is the rank of the matrix if and only if all of the zero-rows of the factor occur after any non-zero rows. This is (always?) the case during elimination of a fully-constrained least-squares problem.
The optional order argument specifies the size of the square upper-left submatrix to operate on, ignoring the rest of the matrix.
| GTSAM_EXPORT bool gtsam::choleskyPartial | ( | Matrix & | ABC, |
| size_t | nFrontal, | ||
| size_t | topleft = 0 |
||
| ) |
Partial Cholesky computes a factor [R S such that [R' 0 [R S = [A B 0 L] S' I] 0 L] B' C].
The input to this function is the matrix ABC = [A B], and the parameter [B' C] nFrontal determines the split between A, B, and C, with A being of size nFrontal x nFrontal.
if non-zero, factorization proceeds in bottom-right corner starting at topleft
true if the decomposition is successful, false if A was not positive-definite. | GTSAM_EXPORT std::list< Point2 > gtsam::circleCircleIntersection | ( | Point2 | c1, |
| double | r1, | ||
| Point2 | c2, | ||
| double | r2, | ||
| double | tol = 1e-9 |
||
| ) |
Intersect 2 circles.
| c1 | center of first circle |
| r1 | radius of first circle |
| c2 | center of second circle |
| r2 | radius of second circle |
| tol | absolute tolerance below which we consider touching circles |
| GTSAM_EXPORT Matrix gtsam::collect | ( | const std::vector< const Matrix * > & | matrices, |
| size_t | m = 0, |
||
| size_t | n = 0 |
||
| ) |
create a matrix by concatenating Given a set of matrices: A1, A2, A3... If all matrices have the same size, specifying single matrix dimensions will avoid the lookup of dimensions
| matrices | is a vector of matrices in the order to be collected |
| m | is the number of rows of a single matrix |
| n | is the number of columns of a single matrix |
| const MATRIX::ConstColXpr gtsam::column | ( | const MATRIX & | A, |
| size_t | j | ||
| ) |
Extracts a column view from a matrix that avoids a copy.
| A | matrix to extract column from |
| j | index of the column |
| V gtsam::conjugateGradients | ( | const S & | Ab, |
| V | x, | ||
| const ConjugateGradientParameters & | parameters, | ||
| bool | steepest = false |
||
| ) |
Method of conjugate gradients (CG) template "System" class S needs gradient(S,v), e=S*v, v=S^e "Vector" class V needs dot(v,v), -v, v+v, s*v "Vector" class E needs dot(v,v)
| Ab,the | "system" that needs to be solved, examples below |
| x | is the initial estimate |
| steepest | flag, if true does steepest descent, not CG |
| GTSAM_EXPORT SharedNoiseModel gtsam::ConvertNoiseModel | ( | const SharedNoiseModel & | model, |
| size_t | n, | ||
| bool | defaultToUnit = true |
||
| ) |
When creating (any) FrobeniusFactor we can convert a Rot/Pose BetweenFactor noise model into a n-dimensional isotropic noise model used to weight the Frobenius norm.
If the noise model passed is null we return a n-dimensional isotropic noise model with sigma=1.0. If not, we we check if the d-dimensional noise model on rotations is isotropic. If it is, we extend to 'n' dimensions, otherwise we throw an error. If the noise model is a robust error model, we use the sigmas of the underlying noise model.
If defaultToUnit == false throws an exception on unexepcted input.
| std::vector< Expression< T > > gtsam::createUnknowns | ( | size_t | n, |
| char | c, | ||
| size_t | start | ||
| ) |
Construct an array of leaves.
Construct an array of unknown expressions with successive symbol keys Example: createUnknowns<Pose2>(3,'x') creates unknown expressions for x0,x1,x2.
| GTSAM_EXPORT Point3 gtsam::cross | ( | const Point3 & | p, |
| const Point3 & | q, | ||
| OptionalJacobian< 3, 3 > | H_p = boost::none, |
||
| OptionalJacobian< 3, 3 > | H_q = boost::none |
||
| ) |
cross product
| std::string GTSAM_EXPORT gtsam::demangle | ( | const char * | name | ) |
Pretty print Value type name.
Function to demangle type name of variable, e.g. demangle(typeid(x).name())
| GTSAM_EXPORT boost::tuple< int, double, Vector > gtsam::DLT | ( | const Matrix & | A, |
| double | rank_tol = 1e-9 |
||
| ) |
Direct linear transform algorithm that calls svd to find a vector v that minimizes the algebraic error A*v.
| A | of size m*n, where m>=n (pad with zero rows if not!) Returns rank of A, minimum error (singular value), and corresponding eigenvector (column of V, with A=U*S*V') |
| GTSAM_EXPORT Vector gtsam::ediv_ | ( | const Vector & | a, |
| const Vector & | b | ||
| ) |
elementwise division, but 0/0 = 0, not inf
| a | first vector |
| b | second vector |
| GTSAM_EXPORT std::pair< boost::shared_ptr< GaussianConditional >, boost::shared_ptr< JacobianFactor > > gtsam::EliminateQR | ( | const GaussianFactorGraph & | factors, |
| const Ordering & | keys | ||
| ) |
Multiply all factors and eliminate the given keys from the resulting factor using a QR variant that handles constraints (zero sigmas).
Computation happens in noiseModel::Gaussian::QR Returns a conditional on those keys, and a new factor on the separator.
| GTSAM_EXPORT std::pair< boost::shared_ptr< SymbolicConditional >, boost::shared_ptr< SymbolicFactor > > gtsam::EliminateSymbolic | ( | const SymbolicFactorGraph & | factors, |
| const Ordering & | keys | ||
| ) |
Dense elimination function for symbolic factors.
This is usually provided as an argument to one of the factor graph elimination functions (see EliminateableFactorGraph). The factor graph elimination functions do sparse variable elimination, and use this function to eliminate single variables or variable cliques.
| GTSAM_EXPORT Matrix gtsam::expm | ( | const Matrix & | A, |
| size_t | K = 7 |
||
| ) |
Numerical exponential map, naive approach, not industrial strength !!!
| A | matrix to exponentiate |
| K | number of iterations |
| T gtsam::expm | ( | const Vector & | x, |
| int | K = 7 |
||
| ) |
Exponential map given exponential coordinates class T needs a wedge<> function and a constructor from Matrix.
| x | exponential coordinates, vector of size n @ return a T |
|
inline |
Exponential map centered at l0, s.t.
exp(t,d) = t*exp(d)
| GTSAM_EXPORT std::string gtsam::findExampleDataFile | ( | const std::string & | name | ) |
Find the full path to an example dataset distributed with gtsam.
The name may be specified with or without a file extension - if no extension is given, this function first looks for the .graph extension, then .txt. We first check the gtsam source tree for the file, followed by the installed example dataset location. Both the source tree and installed locations are obtained from CMake during compilation.
| std::invalid_argument | if no matching file could be found using the search process described above. |
| GTSAM_EXPORT bool gtsam::fpEqual | ( | double | a, |
| double | b, | ||
| double | tol, | ||
| bool | check_relative_also = true |
||
| ) |
Ensure we are not including a different version of Eigen in user code than while compiling gtsam, since it can lead to hard-to-understand runtime crashes.
Numerically stable function for comparing if floating point values are equal within epsilon tolerance. Used for vector and matrix comparison with C++11 compatible functions.
If either value is NaN or Inf, we check for both values to be NaN or Inf respectively for the comparison to be true. If one is NaN/Inf and the other is not, returns false.
| check_relative_also | is a flag which toggles additional checking for relative error. This means that if either the absolute error or the relative error is within the tolerance, the result will be true. By default, the flag is true. |
Return true if two numbers are close wrt tol.
This function converts a GTSAM camera pose to an openGL camera pose.
| PoseGTSAM | pose in GTSAM format |
This function converts a GTSAM camera pose to an openGL camera pose.
| R | rotation in GTSAM |
| tx | x component of the translation in GTSAM |
| ty | y component of the translation in GTSAM |
| tz | z component of the translation in GTSAM |
| GTSAM_EXPORT bool gtsam::hasConstraints | ( | const GaussianFactorGraph & | factors | ) |
Evaluates whether linear factors have any constrained noise models.
| GTSAM_EXPORT std::pair< double, Vector > gtsam::house | ( | const Vector & | x | ) |
house(x,j) computes HouseHolder vector v and scaling factor beta from x, such that the corresponding Householder reflection zeroes out all but x.
(j), j is base 0. Golub & Van Loan p 210.
| GTSAM_EXPORT void gtsam::householder | ( | Matrix & | A, |
| size_t | k | ||
| ) |
Householder tranformation, zeros below diagonal.
| k | number of columns to zero out below diagonal |
| A | matrix |
| GTSAM_EXPORT void gtsam::householder_ | ( | Matrix & | A, |
| size_t | k, | ||
| bool | copy_vectors = true |
||
| ) |
Imperative version of Householder QR factorization, Golub & Van Loan p 224 version with Householder vectors below diagonal, as in GVL.
Householder transformation, Householder vectors below diagonal.
| k | number of columns to zero out below diagonal |
| A | matrix |
| copy_vectors | - true to copy Householder vectors below diagonal |
| GTSAM_EXPORT void gtsam::inplace_QR | ( | Matrix & | A | ) |
QR factorization using Eigen's internal block QR algorithm.
| A | is the input matrix, and is the output |
| clear_below_diagonal | enables zeroing out below diagonal |
| void gtsam::insertSub | ( | Eigen::MatrixBase< Derived1 > & | fullMatrix, |
| const Eigen::MatrixBase< Derived2 > & | subMatrix, | ||
| size_t | i, | ||
| size_t | j | ||
| ) |
insert a submatrix IN PLACE at a specified location in a larger matrix NOTE: there is no size checking
| fullMatrix | matrix to be updated |
| subMatrix | matrix to be inserted |
| i | is the row of the upper left corner insert location |
| j | is the column of the upper left corner insert location |
| T gtsam::interpolate | ( | const T & | X, |
| const T & | Y, | ||
| double | t, | ||
| typename MakeOptionalJacobian< T, T >::type | Hx = boost::none, |
||
| typename MakeOptionalJacobian< T, T >::type | Hy = boost::none |
||
| ) |
Linear interpolation between X and Y by coefficient t.
Typically t \in [0,1], but can also be used to extrapolate before pose X or after pose Y.
| Matrix gtsam::kroneckerProductIdentity | ( | const Weights & | w | ) |
Function for computing the kronecker product of the 1*N Weight vector w with the MxM identity matrix I efficiently.
The main reason for this is so we don't need to use Eigen's Unsupported library.
| M | Size of the identity matrix. |
| w | The weights of the polynomial. |
| GTSAM_EXPORT bool gtsam::linear_dependent | ( | const Vector & | vec1, |
| const Vector & | vec2, | ||
| double | tol = 1e-9 |
||
| ) |
check whether two vectors are linearly dependent
| vec1 | Vector |
| vec2 | Vector |
| tol | 1e-9 |
| Expression< T > gtsam::linearExpression | ( | const std::function< T(A)> & | f, |
| const Expression< A > & | expression, | ||
| const Eigen::Matrix< double, traits< T >::dimension, traits< A >::dimension > & | dTdA | ||
| ) |
Create an expression out of a linear function f:T->A with (constant) Jacobian dTdA TODO(frank): create a more efficient version like ScalarMultiplyExpression.
This version still does a malloc every linearize.
| JacobianFactor gtsam::linearizeNumerically | ( | const NoiseModelFactor & | factor, |
| const Values & | values, | ||
| double | delta = 1e-5 |
||
| ) |
Linearize a nonlinear factor using numerical differentiation The benefit of this method is that it does not need to know what types are involved to evaluate the factor.
If all the machinery of gtsam is working correctly, we should get the correct numerical derivatives out the other side. NOTE(frank): factors that have non vector-space measurements use between or LocalCoordinates to evaluate the error, and their derivatives will only be correct for near-zero errors. This is fixable but expensive, and does not matter in practice as most factors will sit near zero errors anyway. However, it means that below will only be exact for the correct measurement.
| GTSAM_EXPORT GraphAndValues gtsam::load2D | ( | const std::string & | filename, |
| SharedNoiseModel | model = SharedNoiseModel(), |
||
| size_t | maxIndex = 0, |
||
| bool | addNoise = false, |
||
| bool | smart = true, |
||
| NoiseFormat | noiseFormat = NoiseFormatAUTO, |
||
| KernelFunctionType | kernelFunctionType = KernelFunctionTypeNONE |
||
| ) |
Load TORO/G2O style graph files.
| filename | |
| model | optional noise model to use instead of one specified by file |
| maxIndex | if non-zero cut out vertices >= maxIndex |
| addNoise | add noise to the edges |
| smart | try to reduce complexity of covariance to cheapest model |
| noiseFormat | how noise parameters are stored |
| kernelFunctionType | whether to wrap the noise model in a robust kernel |
| GraphAndValues gtsam::load2D | ( | std::pair< std::string, SharedNoiseModel > | dataset, |
| size_t | maxIndex = 0, |
||
| bool | addNoise = false, |
||
| bool | smart = true, |
||
| NoiseFormat | noiseFormat = NoiseFormatAUTO, |
||
| KernelFunctionType | kernelFunctionType = KernelFunctionTypeNONE |
||
| ) |
Load TORO 2D Graph.
| dataset/model | pair as constructed by [dataset] |
| maxIndex | if non-zero cut out vertices >= maxIndex |
| addNoise | add noise to the edges |
| smart | try to reduce complexity of covariance to cheapest model |
| GTSAM_EXPORT GraphAndValues gtsam::load2D | ( | std::pair< std::string, SharedNoiseModel > | dataset, |
| size_t | maxIndex = 0, |
||
| bool | addNoise = false, |
||
| bool | smart = true, |
||
| NoiseFormat | noiseFormat = NoiseFormatAUTO, |
||
| KernelFunctionType | kernelFunctionType = KernelFunctionTypeNONE |
||
| ) |
Load TORO 2D Graph.
| dataset/model | pair as constructed by [dataset] |
| maxIndex | if non-zero cut out vertices >= maxIndex |
| addNoise | add noise to the edges |
| smart | try to reduce complexity of covariance to cheapest model |
| GTSAM_EXPORT GraphAndValues gtsam::load2D_robust | ( | const std::string & | filename, |
| const noiseModel::Base::shared_ptr & | model, | ||
| size_t | maxIndex = 0 |
||
| ) |
|
inline |
Log map centered at l0, s.t.
exp(l0,log(l0,lp)) = lp
| gtsam::enable_if_t< needs_eigen_aligned_allocator< T >::value, boost::shared_ptr< T > > gtsam::make_shared | ( | Args &&... | args | ) |
Add our own make_shared as a layer of wrapping on boost::make_shared This solves the problem with the stock make_shared that custom alignment is not respected, causing SEGFAULTs at runtime, which is notoriously hard to debug.
The template needs_eigen_aligned_allocator<T>::value will evaluate to std::true_type if the type alias _eigen_aligned_allocator_trait = void is present in a class, which is automatically added by the GTSAM_MAKE_ALIGNED_OPERATOR_NEW macro.
This function declaration will only be taken when the above condition is true, so if some object does not need to be aligned, gtsam::make_shared will fall back to the next definition, which is a simple wrapper for boost::make_shared.
| T | The type of object being constructed |
| Args | Type of the arguments of the constructor |
| args | Arguments of the constructor |
| FunctorizedFactor< R, T > gtsam::MakeFunctorizedFactor | ( | Key | key, |
| const R & | z, | ||
| const SharedNoiseModel & | model, | ||
| const FUNC | func | ||
| ) |
Helper function to create a functorized factor.
Uses function template deduction to identify return type and functor type, so template list only needs the functor argument type.
| FunctorizedFactor2< R, T1, T2 > gtsam::MakeFunctorizedFactor2 | ( | Key | key1, |
| Key | key2, | ||
| const R & | z, | ||
| const SharedNoiseModel & | model, | ||
| const FUNC | func | ||
| ) |
Helper function to create a functorized factor.
Uses function template deduction to identify return type and functor type, so template list only needs the functor argument type.
| Key gtsam::maxKey | ( | const PROBLEM & | problem | ) |
Find the max key in a problem.
Useful to determine unique keys for additional slack variables
|
inline |
Create a symbol key from a character, label and index, i.e.
xA5.
| boost::tuple< V, int > gtsam::nonlinearConjugateGradient | ( | const S & | system, |
| const V & | initial, | ||
| const NonlinearOptimizerParams & | params, | ||
| const bool | singleIteration, | ||
| const bool | gradientDescent = false |
||
| ) |
Implement the nonlinear conjugate gradient method using the Polak-Ribiere formula suggested in http://en.wikipedia.org/wiki/Nonlinear_conjugate_gradient_method.
The S (system) class requires three member functions: error(state), gradient(state) and advance(state, step-size, direction). The V class denotes the state or the solution.
The last parameter is a switch between gradient-descent and conjugate gradient
| internal::FixedSizeMatrix< Y, X >::type gtsam::numericalDerivative11 | ( | std::function< Y(const X &)> | h, |
| const X & | x, | ||
| double | delta = 1e-5 |
||
| ) |
New-style numerical derivatives using manifold_traits.
Computes numerical derivative in argument 1 of unary function
| h | unary function yielding m-vector |
| x | n-dimensional value at which to evaluate h |
| delta | increment for numerical derivative Class Y is the output argument Class X is the input argument |
| int | N is the dimension of the X input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X1 >::type gtsam::numericalDerivative21 | ( | const std::function< Y(const X1 &, const X2 &)> & | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 1 of binary function.
| h | binary function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X1 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X2 >::type gtsam::numericalDerivative22 | ( | std::function< Y(const X1 &, const X2 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 2 of binary function.
| h | binary function yielding m-vector |
| x1 | first argument value |
| x2 | n-dimensional second argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X2 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X1 >::type gtsam::numericalDerivative31 | ( | std::function< Y(const X1 &, const X2 &, const X3 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 1 of ternary function.
| h | ternary function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X1 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X2 >::type gtsam::numericalDerivative32 | ( | std::function< Y(const X1 &, const X2 &, const X3 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 2 of ternary function.
| h | ternary function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X2 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X3 >::type gtsam::numericalDerivative33 | ( | std::function< Y(const X1 &, const X2 &, const X3 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 3 of ternary function.
| h | ternary function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X3 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X1 >::type gtsam::numericalDerivative41 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 1 of 4-argument function.
| h | quartic function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X1 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X2 >::type gtsam::numericalDerivative42 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 2 of 4-argument function.
| h | quartic function yielding m-vector |
| x1 | first argument value |
| x2 | n-dimensional second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X2 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X3 >::type gtsam::numericalDerivative43 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 3 of 4-argument function.
| h | quartic function yielding m-vector |
| x1 | first argument value |
| x2 | second argument value |
| x3 | n-dimensional third argument value |
| x4 | fourth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X3 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X4 >::type gtsam::numericalDerivative44 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 4 of 4-argument function.
| h | quartic function yielding m-vector |
| x1 | first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | n-dimensional fourth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X4 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X1 >::type gtsam::numericalDerivative51 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| const X5 & | x5, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 1 of 5-argument function.
| h | quintic function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| x5 | fifth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X1 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X2 >::type gtsam::numericalDerivative52 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| const X5 & | x5, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 2 of 5-argument function.
| h | quintic function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| x5 | fifth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X2 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X3 >::type gtsam::numericalDerivative53 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| const X5 & | x5, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 3 of 5-argument function.
| h | quintic function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| x5 | fifth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X3 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X4 >::type gtsam::numericalDerivative54 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| const X5 & | x5, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 4 of 5-argument function.
| h | quintic function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| x5 | fifth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X4 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X5 >::type gtsam::numericalDerivative55 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| const X5 & | x5, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 5 of 5-argument function.
| h | quintic function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| x5 | fifth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X5 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X1 >::type gtsam::numericalDerivative61 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| const X5 & | x5, | ||
| const X6 & | x6, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 1 of 6-argument function.
| h | quintic function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| x5 | fifth argument value |
| x6 | sixth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X1 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X2 >::type gtsam::numericalDerivative62 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| const X5 & | x5, | ||
| const X6 & | x6, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 2 of 6-argument function.
| h | quintic function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| x5 | fifth argument value |
| x6 | sixth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X2 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X3 >::type gtsam::numericalDerivative63 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| const X5 & | x5, | ||
| const X6 & | x6, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 3 of 6-argument function.
| h | quintic function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| x5 | fifth argument value |
| x6 | sixth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X3 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X4 >::type gtsam::numericalDerivative64 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| const X5 & | x5, | ||
| const X6 & | x6, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 4 of 6-argument function.
| h | quintic function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| x5 | fifth argument value |
| x6 | sixth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X4 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X5 >::type gtsam::numericalDerivative65 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| const X5 & | x5, | ||
| const X6 & | x6, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 5 of 6-argument function.
| h | quintic function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| x5 | fifth argument value |
| x6 | sixth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X5 input value if variable dimension type but known at test time |
| internal::FixedSizeMatrix< Y, X6 >::type gtsam::numericalDerivative66 | ( | std::function< Y(const X1 &, const X2 &, const X3 &, const X4 &, const X5 &, const X6 &)> | h, |
| const X1 & | x1, | ||
| const X2 & | x2, | ||
| const X3 & | x3, | ||
| const X4 & | x4, | ||
| const X5 & | x5, | ||
| const X6 & | x6, | ||
| double | delta = 1e-5 |
||
| ) |
Compute numerical derivative in argument 6 of 6-argument function.
| h | quintic function yielding m-vector |
| x1 | n-dimensional first argument value |
| x2 | second argument value |
| x3 | third argument value |
| x4 | fourth argument value |
| x5 | fifth argument value |
| x6 | sixth argument value |
| delta | increment for numerical derivative |
| int | N is the dimension of the X6 input value if variable dimension type but known at test time |
| Eigen::Matrix< double, N, 1 > gtsam::numericalGradient | ( | std::function< double(const X &)> | h, |
| const X & | x, | ||
| double | delta = 1e-5 |
||
| ) |
Numerically compute gradient of scalar function.
|
inline |
Compute numerical Hessian matrix.
Requires a single-argument Lie->scalar function. This is implemented simply as the derivative of the gradient.
| f | A function taking a Lie object as input and returning a scalar |
| x | The center point for computing the Hessian |
| delta | The numerical derivative step size |
This function converts an openGL camera pose to an GTSAM camera pose.
| R | rotation in openGL |
| tx | x component of the translation in openGL |
| ty | y component of the translation in openGL |
| tz | z component of the translation in openGL |
| Expression< T > gtsam::operator* | ( | const Expression< T > & | expression1, |
| const Expression< T > & | expression2 | ||
| ) |
Construct a product expression, assumes T::compose(T) -> T.
Construct a product expression, assumes T::compose(T) -> T Example: Expression<Point2> a(0), b(1), c = a*b;.
| GTSAM_EXPORT std::istream & gtsam::operator>> | ( | std::istream & | inputStream, |
| Matrix & | destinationMatrix | ||
| ) |
Read a matrix from an input stream, such as a file.
Entries can be either tab-, space-, or comma-separated, similar to the format read by the MATLAB dlmread command.
| GTSAM_EXPORT Point3 gtsam::optimize | ( | const NonlinearFactorGraph & | graph, |
| const Values & | values, | ||
| Key | landmarkKey | ||
| ) |
Optimize for triangulation.
| graph | nonlinear factors for projection |
| values | initial values |
| landmarkKey | to refer to landmark |
| size_t gtsam::optimizeWildfire | ( | const ISAM2Clique::shared_ptr & | root, |
| double | threshold, | ||
| const KeySet & | replaced, | ||
| VectorValues * | delta | ||
| ) |
Optimize the BayesTree, starting from the root.
| threshold | The maximum change against the PREVIOUS delta for non-replaced variables that can be ignored, ie. the old delta entry is kept and recursive backsubstitution might eventually stop if none of the changed variables are contained in the subtree. |
| replaced | Needs to contain all variables that are contained in the top of the Bayes tree that has been redone. |
| delta | The current solution, an offset from the linearization point. |
| GTSAM_EXPORT boost::optional< IndexedEdge > gtsam::parseEdge | ( | std::istream & | is, |
| const std::string & | tag | ||
| ) |
Parse TORO/G2O edge "id1 id2 x y yaw".
| is | input stream |
| tag | string parsed from input stream, will only parse if edge type |
| GTSAM_EXPORT std::vector< typename BetweenFactor< T >::shared_ptr > gtsam::parseFactors | ( | const std::string & | filename, |
| const noiseModel::Diagonal::shared_ptr & | model = nullptr, |
||
| size_t | maxIndex = 0 |
||
| ) |
| GTSAM_EXPORT std::vector< BinaryMeasurement< T > > gtsam::parseMeasurements | ( | const std::string & | filename, |
| const noiseModel::Diagonal::shared_ptr & | model = nullptr, |
||
| size_t | maxIndex = 0 |
||
| ) |
| GTSAM_EXPORT std::map< size_t, T > gtsam::parseVariables | ( | const std::string & | filename, |
| size_t | maxIndex = 0 |
||
| ) |
| GTSAM_EXPORT boost::optional< IndexedLandmark > gtsam::parseVertexLandmark | ( | std::istream & | is, |
| const std::string & | tag | ||
| ) |
Parse G2O landmark vertex "id x y".
| is | input stream |
| tag | string parsed from input stream, will only parse if vertex type |
| GTSAM_EXPORT boost::optional< IndexedPose > gtsam::parseVertexPose | ( | std::istream & | is, |
| const std::string & | tag | ||
| ) |
Parse TORO/G2O vertex "id x y yaw".
| is | input stream |
| tag | string parsed from input stream, will only parse if vertex type |
| boost::tuple< G, V, std::map< KEY, V > > gtsam::predecessorMap2Graph | ( | const PredecessorMap< KEY > & | p_map | ) |
Build takes a predecessor map, and builds a directed graph corresponding to the tree.
G = Graph type V = Vertex type
| GTSAM_EXPORT std::pair< Matrix, Matrix > gtsam::qr | ( | const Matrix & | A | ) |
Householder QR factorization, Golub & Van Loan p 224, explicit version
QR factorization, inefficient, best use imperative householder below m*n matrix -> m*m Q, m*n R.
| A | a matrix |
| GTSAM_EXPORT SfmData gtsam::readBal | ( | const std::string & | filename | ) |
This function parses a "Bundle Adjustment in the Large" (BAL) file and returns the data as a SfmData structure.
Mainly used by wrapped code.
| filename | The name of the BAL file. |
| GTSAM_EXPORT bool gtsam::readBAL | ( | const std::string & | filename, |
| SfmData & | data | ||
| ) |
This function parses a "Bundle Adjustment in the Large" (BAL) file and stores the data into a SfmData structure.
| filename | The name of the BAL file |
| data | SfM structure where the data is stored |
| GTSAM_EXPORT bool gtsam::readBundler | ( | const std::string & | filename, |
| SfmData & | data | ||
| ) |
This function parses a bundler output file and stores the data into a SfmData structure.
| filename | The name of the bundler file |
| data | SfM structure where the data is stored |
| GTSAM_EXPORT GraphAndValues gtsam::readG2o | ( | const std::string & | g2oFile, |
| const bool | is3D = false, |
||
| KernelFunctionType | kernelFunctionType = KernelFunctionTypeNONE |
||
| ) |
This function parses a g2o file and stores the measurements into a NonlinearFactorGraph and the initial guess in a Values structure.
| filename | The name of the g2o file\ |
| is3D | indicates if the file describes a 2D or 3D problem |
| kernelFunctionType | whether to wrap the noise model in a robust kernel |
| const MATRIX::ConstRowXpr gtsam::row | ( | const MATRIX & | A, |
| size_t | j | ||
| ) |
Extracts a row view from a matrix that avoids a copy.
| A | matrix to extract row from |
| j | index of the row |
| GTSAM_EXPORT std::pair< Matrix3, Vector3 > gtsam::RQ | ( | const Matrix3 & | A, |
| OptionalJacobian< 3, 9 > | H = boost::none |
||
| ) |
[RQ] receives a 3 by 3 matrix and returns an upper triangular matrix R and 3 rotation angles corresponding to the rotation matrix Q=Qz'*Qy'*Qx' such that A = R*Q = R*Qz'*Qy'*Qx'.
When A is a rotation matrix, R will be the identity and Q is a yaw-pitch-roll decomposition of A. The implementation uses Givens rotations and is based on Hartley-Zisserman.
| A | 3 by 3 matrix A=RQ |
|
inline |
BLAS Level 1 scal: x <- alpha*x.
| void gtsam::serializeToBinaryStream | ( | const T & | input, |
| std::ostream & | out_archive_stream, | ||
| const std::string & | name = "data" |
||
| ) |
serializes to a stream in binary
| void gtsam::serializeToStream | ( | const T & | input, |
| std::ostream & | out_archive_stream | ||
| ) |
serializes to a stream
| void gtsam::serializeToXMLStream | ( | const T & | input, |
| std::ostream & | out_archive_stream, | ||
| const std::string & | name = "data" |
||
| ) |
serializes to a stream in XML
|
inline |
skew symmetric matrix returns this: 0 -wz wy wz 0 -wx -wy wx 0
| wx | 3 dimensional vector |
| wy | |
| wz |
| std::pair< boost::shared_ptr< GaussianFactorGraph >, boost::shared_ptr< GaussianFactorGraph > > gtsam::splitFactorGraph | ( | const GaussianFactorGraph & | factorGraph, |
| const Subgraph & | subgraph | ||
| ) |
Split the graph into a subgraph and the remaining edges.
Note that the remaining factorgraph has null factors.
| GTSAM_EXPORT Matrix gtsam::stack | ( | size_t | nrMatrices, |
| ... | |||
| ) |
create a matrix by stacking other matrices Given a set of matrices: A1, A2, A3...
| ... | pointers to matrices to be stacked |
| GTSAM_EXPORT Vector gtsam::steepestDescent | ( | const Matrix & | A, |
| const Vector & | b, | ||
| const Vector & | x, | ||
| const ConjugateGradientParameters & | parameters | ||
| ) |
convenience calls using matrices, will create System class internally:
Method of steepest gradients, Matrix version
| Eigen::Block< const MATRIX > gtsam::sub | ( | const MATRIX & | A, |
| size_t | i1, | ||
| size_t | i2, | ||
| size_t | j1, | ||
| size_t | j2 | ||
| ) |
extract submatrix, slice semantics, i.e.
range = [i1,i2[ excluding i2
| A | matrix |
| i1 | first row index |
| i2 | last row index + 1 |
| j1 | first col index |
| j2 | last col index + 1 |
| GTSAM_EXPORT void gtsam::svd | ( | const Matrix & | A, |
| Matrix & | U, | ||
| Vector & | S, | ||
| Matrix & | V | ||
| ) |
SVD computes economy SVD A=U*S*V'.
| A | an m*n matrix |
| U | output argument: rotation matrix |
| S | output argument: sorted vector of singular values |
| V | output argument: rotation matrix if m > n then U*S*V' = (m*n)*(n*n)*(n*n) if m < n then U*S*V' = (m*m)*(m*m)*(m*n) Careful! The dimensions above reflect V', not V, which is n*m if m<n. U is a basis in R^m, V is a basis in R^n You can just pass empty matrices U,V, and vector S, they will be re-allocated. |
|
inline |
Create a symbol key from a character and index, i.e.
x5.
| GTSAM_EXPORT Matrix3 gtsam::topLeft | ( | const SO4 & | Q, |
| OptionalJacobian< 9, 6 > | H = boost::none |
||
| ) |
Project to top-left 3*3 matrix.
Note this is not in general \in SO(3).
| P gtsam::transform_point | ( | const T & | trans, |
| const P & | global, | ||
| boost::optional< Matrix & > | Dtrans, | ||
| boost::optional< Matrix & > | Dglobal | ||
| ) |
Transform function that must be specialized specific domains.
| T | is a Transform type |
| P | is a point type |
| Line3 gtsam::transformTo | ( | const Pose3 & | wTc, |
| const Line3 & | wL, | ||
| OptionalJacobian< 4, 6 > | Dpose = boost::none, |
||
| OptionalJacobian< 4, 4 > | Dline = boost::none |
||
| ) |
Transform a line from world to camera frame.
| wTc | - Pose3 of camera in world frame |
| wL | - Line3 in world frame |
| Dpose | - OptionalJacobian of transformed line with respect to p |
| Dline | - OptionalJacobian of transformed line with respect to l |
| GTSAM_EXPORT Point3 gtsam::triangulateDLT | ( | const std::vector< Matrix34, Eigen::aligned_allocator< Matrix34 > > & | projection_matrices, |
| const Point2Vector & | measurements, | ||
| double | rank_tol = 1e-9 |
||
| ) |
DLT triangulation: See Hartley and Zisserman, 2nd Ed., page 312.
| projection_matrices | Projection matrices (K*P^-1) |
| measurements | 2D measurements |
| rank_tol | SVD rank tolerance |
| GTSAM_EXPORT Vector4 gtsam::triangulateHomogeneousDLT | ( | const std::vector< Matrix34, Eigen::aligned_allocator< Matrix34 > > & | projection_matrices, |
| const Point2Vector & | measurements, | ||
| double | rank_tol = 1e-9 |
||
| ) |
DLT triangulation: See Hartley and Zisserman, 2nd Ed., page 312.
| projection_matrices | Projection matrices (K*P^-1) |
| measurements | 2D measurements |
| rank_tol | SVD rank tolerance |
| Point3 gtsam::triangulateNonlinear | ( | const CameraSet< CAMERA > & | cameras, |
| const typename CAMERA::MeasurementVector & | measurements, | ||
| const Point3 & | initialEstimate | ||
| ) |
Given an initial estimate , refine a point using measurements in several cameras.
| cameras | pinhole cameras (monocular or stereo) |
| measurements | 2D measurements |
| initialEstimate |
| Point3 gtsam::triangulateNonlinear | ( | const std::vector< Pose3 > & | poses, |
| boost::shared_ptr< CALIBRATION > | sharedCal, | ||
| const Point2Vector & | measurements, | ||
| const Point3 & | initialEstimate | ||
| ) |
Given an initial estimate , refine a point using measurements in several cameras.
| poses | Camera poses |
| sharedCal | shared pointer to single calibration object |
| measurements | 2D measurements |
| initialEstimate |
| Point3 gtsam::triangulatePoint3 | ( | const CameraSet< CAMERA > & | cameras, |
| const typename CAMERA::MeasurementVector & | measurements, | ||
| double | rank_tol = 1e-9, |
||
| bool | optimize = false |
||
| ) |
Function to triangulate 3D landmark point from an arbitrary number of poses (at least 2) using the DLT.
This function is similar to the one above, except that each camera has its own calibration. The function checks that the resulting point lies in front of all cameras, but has no other checks to verify the quality of the triangulation.
| cameras | pinhole cameras |
| measurements | A vector of camera measurements |
| rank_tol | rank tolerance, default 1e-9 |
| optimize | Flag to turn on nonlinear refinement of triangulation |
| Point3 gtsam::triangulatePoint3 | ( | const std::vector< Pose3 > & | poses, |
| boost::shared_ptr< CALIBRATION > | sharedCal, | ||
| const Point2Vector & | measurements, | ||
| double | rank_tol = 1e-9, |
||
| bool | optimize = false |
||
| ) |
Function to triangulate 3D landmark point from an arbitrary number of poses (at least 2) using the DLT.
The function checks that the resulting point lies in front of all cameras, but has no other checks to verify the quality of the triangulation.
| poses | A vector of camera poses |
| sharedCal | shared pointer to single calibration object |
| measurements | A vector of camera measurements |
| rank_tol | rank tolerance, default 1e-9 |
| optimize | Flag to turn on nonlinear refinement of triangulation |
| std::pair< NonlinearFactorGraph, Values > gtsam::triangulationGraph | ( | const CameraSet< CAMERA > & | cameras, |
| const typename CAMERA::MeasurementVector & | measurements, | ||
| Key | landmarkKey, | ||
| const Point3 & | initialEstimate | ||
| ) |
Create a factor graph with projection factors from pinhole cameras (each camera has a pose and calibration)
| cameras | pinhole cameras (monocular or stereo) |
| measurements | 2D measurements |
| landmarkKey | to refer to landmark |
| initialEstimate |
| std::pair< NonlinearFactorGraph, Values > gtsam::triangulationGraph | ( | const std::vector< Pose3 > & | poses, |
| boost::shared_ptr< CALIBRATION > | sharedCal, | ||
| const Point2Vector & | measurements, | ||
| Key | landmarkKey, | ||
| const Point3 & | initialEstimate | ||
| ) |
Create a factor graph with projection factors from poses and one calibration.
| poses | Camera poses |
| sharedCal | shared pointer to single calibration object (monocular only!) |
| measurements | 2D measurements |
| landmarkKey | to refer to landmark |
| initialEstimate |
| GTSAM_EXPORT void gtsam::vector_scale_inplace | ( | const Vector & | v, |
| Matrix & | A, | ||
| bool | inf_mask = false |
||
| ) |
scales a matrix row or column by the values in a vector Arguments (Matrix, Vector) scales the columns, (Vector, Matrix) scales the rows
| inf_mask | when true, will not scale with a NaN or inf value. |
|
inline |
wedge for Pose3:
| xi | 6-dim twist (omega,v) where omega = 3D angular velocity v = 3D velocity |
| GTSAM_EXPORT std::list< boost::tuple< Vector, double, double > > gtsam::weighted_eliminate | ( | Matrix & | A, |
| Vector & | b, | ||
| const Vector & | sigmas | ||
| ) |
Imperative algorithm for in-place full elimination with weights and constraint handling.
| A | is a matrix to eliminate |
| b | is the rhs |
| sigmas | is a vector of the measurement standard deviation |
| GTSAM_EXPORT std::pair< Vector, double > gtsam::weightedPseudoinverse | ( | const Vector & | v, |
| const Vector & | weights | ||
| ) |
Weighted Householder solution vector, a.k.a., the pseudoinverse of the column NOTE: if any sigmas are zero (indicating a constraint) the pseudoinverse will be a selection vector, and the variance will be zero.
| v | is the first column of the matrix to solve |
| weights | is a vector of weights/precisions where w=1/(s*s) |
| GTSAM_EXPORT bool gtsam::writeBAL | ( | const std::string & | filename, |
| SfmData & | data | ||
| ) |
This function writes a "Bundle Adjustment in the Large" (BAL) file from a SfmData structure.
| filename | The name of the BAL file to write |
| data | SfM structure where the data is stored |
| GTSAM_EXPORT bool gtsam::writeBALfromValues | ( | const std::string & | filename, |
| const SfmData & | data, | ||
| Values & | values | ||
| ) |
This function writes a "Bundle Adjustment in the Large" (BAL) file from a SfmData structure and a value structure (measurements are the same as the SfM input data, while camera poses and values are read from Values)
| filename | The name of the BAL file to write |
| data | SfM structure where the data is stored |
| values | structure where the graph values are stored (values can be either Pose3 or PinholeCamera<Cal3Bundler> for the cameras, and should be Point3 for the 3D points). Note that the current version assumes that the keys are "x1" for pose 1 (or "c1" for camera 1) and "l1" for landmark 1 |
| GTSAM_EXPORT void gtsam::writeG2o | ( | const NonlinearFactorGraph & | graph, |
| const Values & | estimate, | ||
| const std::string & | filename | ||
| ) |
This function writes a g2o file from NonlinearFactorGraph and a Values structure.
| filename | The name of the g2o file to write |
| graph | NonlinearFactor graph storing the measurements |
| estimate | Values |
Note:behavior change in PR #471: to be consistent with load2D and load3D, we write the indices to file and not the full Keys. This change really only affects landmarks, which get read as indices but stored in values with the symbol L(index).
| void gtsam::zeroBelowDiagonal | ( | MATRIX & | A, |
| size_t | cols = 0 |
||
| ) |
Zeros all of the elements below the diagonal of a matrix, in place.
| A | is a matrix, to be modified in place |
| cols | is the number of columns to zero, use zero for all columns |
1.9.3