|
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...
|
|
struct | additive_group_tag |
|
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 | AntiFactor |
| A class for downdating an existing factor from a graph. More...
|
|
class | Assignment |
| An assignment from labels to value index (size_t). More...
|
|
class | AttitudeFactor |
| Base class for prior on attitude Example: More...
|
|
class | BarometricFactor |
| Prior on height in a cartesian frame. More...
|
|
class | Basis |
| CRTP Base class for function bases. More...
|
|
class | BayesNet |
| A BayesNet is a tree of conditionals, stored in elimination order. More...
|
|
class | BayesTree |
| Bayes tree. More...
|
|
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 |
|
class | BayesTreeOrphanWrapper< HybridBayesTreeClique > |
| Class for Hybrid Bayes tree orphan subtrees. More...
|
|
struct | Bearing |
|
struct | Bearing< Pose2, T > |
|
struct | Bearing< Pose3, Point3 > |
|
struct | Bearing< Pose3, Pose3 > |
|
struct | BearingFactor |
| Binary factor for a bearing measurement Works for any two types A1,A2 for which the functor Bearing<A1,A2>() is defined. More...
|
|
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 |
| Binary factor for a bearing/range measurement. More...
|
|
class | BetweenConstraint |
| Binary between constraint - forces between to a given value This constraint requires the underlying type to a Lie type. More...
|
|
class | BetweenFactor |
| A class for a measurement predicted by "between(config[key1],config[key2])". 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 |
| Unary inequality constraint forcing a scalar to be greater/less than a fixed threshold. More...
|
|
struct | BoundingConstraint2 |
| Binary scalar inequality constraint, with a similar value() function to implement for specific systems. More...
|
|
class | Cal3 |
| Common base class for all calibration models. More...
|
|
class | Cal3_S2 |
| The most common 5DOF 3D->2D calibration. More...
|
|
class | Cal3_S2Stereo |
| The most common 5DOF 3D->2D calibration, stereo version. More...
|
|
class | Cal3Bundler |
| Calibration used by Bundler. More...
|
|
class | Cal3DS2 |
| Calibration of a camera with radial distortion that also supports Lie-group behaviors for optimization. More...
|
|
class | Cal3DS2_Base |
| Calibration of a camera with radial distortion. More...
|
|
class | Cal3Fisheye |
| Calibration of a fisheye camera. More...
|
|
class | Cal3Unified |
| Calibration of a omni-directional camera with mirror + lens radial distortion. More...
|
|
class | CalibratedCamera |
| A Calibrated camera class [R|-R't], calibration K=I. 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 |
| CombinedImuFactor is a 6-ways factor involving previous state (pose and velocity of the vehicle, as well as bias at previous time step), and current state (pose, velocity, bias at current time step). More...
|
|
class | CombinedScenarioRunner |
|
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 | ConcurrentMap |
| FastMap is a thin wrapper around std::map that uses the boost fast_pool_allocator instead of the default STL allocator. More...
|
|
class | Conditional |
|
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...
|
|
struct | ConstructorTraversalData |
|
class | CRefCallAddCopy |
| Helper. More...
|
|
class | CRefCallPushBack |
| Helper. 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...
|
|
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...
|
|
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 discrete conditional distributions. 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 | DiscreteDistribution |
| A prior probability on a set of discrete variables. More...
|
|
class | DiscreteEliminationTree |
| Elimination tree for discrete factors. 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 |
| An EliminatableClusterTree, i.e., a set of variable clusters with factors, arranged in a tree, with the additional property that it represents the clique tree associated with a Bayes net. More...
|
|
struct | DiscreteKeys |
| DiscreteKeys is a set of keys that can be assembled using the & operator. More...
|
|
class | DiscreteLookupDAG |
| A DAG made from lookup tables, as defined above. More...
|
|
class | DiscreteLookupTable |
| DiscreteLookupTable table for max-product. More...
|
|
class | DiscreteMarginals |
| A class for computing marginals of variables in a DiscreteFactorGraph. More...
|
|
class | DiscreteValues |
| A map from keys to values. 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...
|
|
struct | DotWriter |
| DotWriter is a helper class for writing graphviz .dot files. More...
|
|
class | DSFBase |
| A fast implementation of disjoint set forests that uses vector as underly data structure. More...
|
|
class | DSFMap |
| Disjoint set forest using an STL map data structure underneath Uses rank compression and union by rank, iterator version. More...
|
|
class | DSFVector |
| DSFVector additionally keeps a vector of keys to support more expensive operations. More...
|
|
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< HybridGaussianFactorGraph > |
|
struct | EliminationTraits< SymbolicFactorGraph > |
|
class | EliminationTree |
| An elimination tree is a data structure used intermediately during elimination. More...
|
|
class | EmptyCal |
| Empty calibration. More...
|
|
struct | equals |
| Template to create a binary predicate. More...
|
|
struct | equals_star |
| Binary predicate on shared pointers. 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 |
| Binary factor between two Pose3 variables induced by an EssentialMatrix measurement. More...
|
|
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 |
|
class | FactorGraph |
| A factor graph is a bipartite graph with factor nodes connected to variable nodes. More...
|
|
class | FastList |
| FastList is a thin wrapper around std::list that uses the boost fast_pool_allocator instead of the default STL allocator. More...
|
|
class | FastMap |
| FastMap is a thin wrapper around std::map that uses the boost fast_pool_allocator instead of the default STL allocator. More...
|
|
class | FastSet |
| FastSet is a thin wrapper around std::set that uses the boost fast_pool_allocator instead of the default STL allocator. More...
|
|
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 | 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 | 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 |
| GaussianBayesNet is a Bayes net made from linear-Gaussian conditionals. More...
|
|
class | GaussianBayesTree |
| A Bayes tree representing a Gaussian density. More...
|
|
class | GaussianBayesTreeClique |
| A clique in a GaussianBayesTree. More...
|
|
class | GaussianConditional |
| A GaussianConditional functions as the node in a Bayes network. More...
|
|
class | GaussianDensity |
| A GaussianDensity is a GaussianConditional without parents. 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 |
| A junction tree specialized to Gaussian factors, i.e., it is a cluster tree with Gaussian factors stored in each cluster. More...
|
|
class | GaussianMixture |
| A conditional of gaussian mixtures indexed by discrete variables, as part of a Bayes Network. More...
|
|
class | GaussianMixtureFactor |
| Implementation of a discrete conditional mixture factor. More...
|
|
class | GaussNewtonOptimizer |
| This class performs Gauss-Newton nonlinear optimization. More...
|
|
class | GaussNewtonParams |
| Parameters for Gauss-Newton optimization, inherits from NonlinearOptimizationParams. More...
|
|
class | GeneralSFMFactor |
| Non-linear factor for a constraint derived from a 2D measurement. More...
|
|
class | GeneralSFMFactor2 |
| Non-linear factor for a constraint derived from a 2D measurement. More...
|
|
class | GenericProjectionFactor |
| Non-linear factor for a constraint derived from a 2D measurement. More...
|
|
class | GenericStereoFactor |
| A Generic Stereo Factor. More...
|
|
class | GenericValue |
| Wraps any type T so it can play as a Value. More...
|
|
class | GncOptimizer |
|
class | GncParams |
|
class | GPSFactor |
| Prior on position in a Cartesian frame. More...
|
|
class | GPSFactor2 |
| Version of GPSFactor for NavState. More...
|
|
struct | GraphvizFormatting |
| Formatting options and functions for saving a NonlinearFactorGraph instance in GraphViz format. 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 | HybridBayesNet |
| A hybrid Bayes net is a collection of HybridConditionals, which can have discrete conditionals, Gaussian mixtures, or pure Gaussian conditionals. More...
|
|
class | HybridBayesTree |
| A Bayes tree representing a Hybrid density. More...
|
|
class | HybridBayesTreeClique |
| A clique in a HybridBayesTree which is a HybridConditional internally. More...
|
|
class | HybridConditional |
| Hybrid Conditional Density. More...
|
|
class | HybridEliminationTree |
| Elimination Tree type for Hybrid Factor Graphs. More...
|
|
class | HybridFactor |
| Base class for truly hybrid probabilistic factors. More...
|
|
class | HybridFactorGraph |
| Hybrid Factor Graph Factor graph with utilities for hybrid factors. More...
|
|
class | HybridGaussianFactorGraph |
|
class | HybridGaussianISAM |
|
class | HybridJunctionTree |
| An EliminatableClusterTree, i.e., a set of variable clusters with factors, arranged in a tree, with the additional property that it represents the clique tree associated with a Bayes net. More...
|
|
class | HybridNonlinearFactorGraph |
|
class | HybridNonlinearISAM |
| Wrapper class to manage ISAM in a nonlinear context. More...
|
|
class | HybridSmoother |
|
class | HybridValues |
| HybridValues represents a collection of DiscreteValues and VectorValues. More...
|
|
class | ImuFactor |
| ImuFactor is a 5-ways factor involving previous state (pose and velocity of the vehicle at previous time step), current state (pose and velocity at current time step), and the bias estimate. More...
|
|
class | ImuFactor2 |
| ImuFactor2 is a ternary factor that uses NavStates rather than Pose/Velocity. More...
|
|
class | InconsistentEliminationRequested |
| An inference algorithm was called with inconsistent arguments. 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...
|
|
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 | ISAM |
| A Bayes tree with an update methods that implements the iSAM algorithm. More...
|
|
class | ISAM2 |
| Implementation of the full ISAM2 algorithm for incremental nonlinear optimization. More...
|
|
class | ISAM2BayesTree |
|
class | ISAM2Clique |
| Specialized Clique structure for ISAM2, incorporating caching and gradient contribution TODO: more documentation. More...
|
|
struct | ISAM2DoglegParams |
| Parameters for ISAM2 using Dogleg optimization. More...
|
|
struct | ISAM2GaussNewtonParams |
| Parameters for ISAM2 using Gauss-Newton optimization. More...
|
|
class | ISAM2JunctionTree |
|
struct | ISAM2Params |
|
struct | ISAM2Result |
| This struct is returned from ISAM2::update() and contains information about the update that is useful for determining whether the solution is converging, and about how much work was required for the update. More...
|
|
struct | ISAM2UpdateParams |
| This struct is used by ISAM2::update() to pass additional parameters to give the user a fine-grained control on how factors and relinearized, etc. More...
|
|
class | IsGroup |
| Group Concept. More...
|
|
class | IsLieGroup |
| Lie Group Concept. More...
|
|
class | IsTestable |
| A testable concept check that should be placed in applicable unit tests and in generic algorithms. More...
|
|
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 |
| A JunctionTree is a cluster tree, a set of variable clusters with factors, arranged in a tree, with the additional property that it represents the clique tree associated with a Bayes Net. More...
|
|
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 |
| A 3D line (R,a,b) : (Rot3,Scalar,Scalar) More...
|
|
class | LinearContainerFactor |
| Dummy version of a generic linear factor to be injected into a nonlinear factor graph. More...
|
|
class | ListOfOneContainer |
| A helper class that behaves as a container with one element, and works with boost::range. 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 | MetisIndex |
| The MetisIndex class converts a factor graph into the Compressed Sparse Row format for use in METIS algorithms. More...
|
|
class | MFAS |
| The MFAS class to solve a Minimum feedback arc set (MFAS) problem. More...
|
|
class | MixtureFactor |
| Implementation of a discrete conditional mixture factor. More...
|
|
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 | 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 | NoiseModelFactorN |
| A convenient base class for creating your own NoiseModelFactor with n variables. More...
|
|
class | NoMatchFoundForFixed |
|
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 |
|
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 | 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 | PCGSolver |
| A virtual base class for the preconditioned conjugate gradient solver. More...
|
|
struct | PCGSolverParameters |
| Parameters for PCG. More...
|
|
class | PinholeBase |
| A pinhole camera class that has a Pose3, functions as base class for all pinhole cameras. More...
|
|
class | PinholeBaseK |
| A pinhole camera class that has a Pose3 and a fixed Calibration. More...
|
|
class | PinholeCamera |
| A pinhole camera class that has a Pose3 and a Calibration. More...
|
|
class | PinholePose |
| A pinhole camera class that has a Pose3 and a fixed Calibration. More...
|
|
class | PinholeSet |
| PinholeSet: triangulates point and keeps an estimate of it around. More...
|
|
class | Pose2 |
| A 2D pose (Point2,Rot2) More...
|
|
class | Pose3 |
| A 3D pose (R,t) : (Rot3,Point3) More...
|
|
class | Pose3AttitudeFactor |
| Version of AttitudeFactor for Pose3. More...
|
|
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 | PoseRotationPrior |
|
class | PoseTranslationPrior |
| A prior on the translation part of a pose. 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 |
| PreintegratedCombinedMeasurements integrates the IMU measurements (rotation rates and accelerations) and the corresponding covariance matrix. More...
|
|
class | PreintegratedImuMeasurements |
| PreintegratedImuMeasurements accumulates (integrates) the IMU measurements (rotation rates and accelerations) and the corresponding covariance matrix. More...
|
|
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 |
| A class for a soft prior on any Value type. More...
|
|
class | ProductLieGroup |
| Template to construct the product Lie group of two other Lie groups Assumes Lie group structure for G and H. More...
|
|
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 > |
|
class | RangeFactor |
| Binary factor for a range measurement Works for any two types A1,A2 for which the functor Range<A1,A2>() is defined. More...
|
|
class | RangeFactorWithTransform |
| Binary factor for a range measurement, with a transform applied. 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...
|
|
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 |
| Rotation matrix NOTE: the angle theta is in radians unless explicitly stated. More...
|
|
class | Rot3 |
| Rot3 is a 3D rotation represented as a rotation matrix if the preprocessor symbol GTSAM_USE_QUATERNIONS is not defined, or as a quaternion if it is defined. More...
|
|
class | Rot3AttitudeFactor |
| Version of AttitudeFactor for Rot3. More...
|
|
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 | SDGraph |
| SDGraph is undirected graph with variable keys and double edge weights. More...
|
|
struct | SfmData |
| SfmData stores a bunch of SfmTracks. More...
|
|
struct | SfmTrack |
|
struct | SfmTrack2d |
| Track containing 2D measurements associated with a single 3D point. 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 | Similarity2 |
| 2D similarity transform More...
|
|
class | Similarity3 |
| 3D similarity transform 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 |
| If you are using the factor, please cite: L. More...
|
|
class | SmartProjectionRigFactor |
| If you are using the factor, please cite: L. More...
|
|
class | SO |
| Manifold of special orthogonal rotation matrices SO<N>. More...
|
|
class | SphericalCamera |
| A spherical camera class that has a Pose3 and measures bearing vectors. More...
|
|
class | StereoCamera |
| A stereo camera class, parameterize by left camera pose and stereo calibration. More...
|
|
class | StereoCheiralityException |
|
class | StereoPoint2 |
| A 2D stereo point, v will be same for rectified images. More...
|
|
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 |
| A SymbolicBayesNet is a Bayes Net of purely symbolic conditionals. 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 |
| A EliminatableClusterTree, i.e., a set of variable clusters with factors, arranged in a tree, with the additional property that it represents the clique tree associated with a Bayes net. More...
|
|
class | SymmetricBlockMatrix |
| This class stores a dense matrix and allows it to be accessed as a collection of blocks. More...
|
|
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...
|
|
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< AlgebraicDecisionTree< T > > |
|
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< 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 Similarity2 > |
|
struct | traits< const Similarity3 > |
|
struct | traits< const SO3 > |
|
struct | traits< const SO4 > |
|
struct | traits< const SO< N > > |
|
struct | traits< const SphericalCamera > |
|
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< DecisionTree< L, Y > > |
|
struct | traits< DecisionTreeFactor > |
|
struct | traits< DirectProduct< G, H > > |
|
struct | traits< DirectSum< G, H > > |
|
struct | traits< DiscreteBayesNet > |
|
struct | traits< DiscreteConditional > |
|
struct | traits< DiscreteDistribution > |
|
struct | traits< DiscreteFactor > |
|
struct | traits< DiscreteFactorGraph > |
| traits More...
|
|
struct | traits< DiscreteKeys > |
|
struct | traits< DiscreteLookupDAG > |
|
struct | traits< DiscreteValues > |
|
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< 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< GaussianMixture > |
|
struct | traits< GaussianMixtureFactor > |
|
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< HybridBayesNet > |
| traits More...
|
|
struct | traits< HybridBayesTree > |
| traits More...
|
|
struct | traits< HybridConditional > |
|
struct | traits< HybridFactor > |
|
struct | traits< HybridGaussianISAM > |
| traits More...
|
|
struct | traits< HybridNonlinearFactorGraph > |
|
struct | traits< HybridValues > |
|
struct | traits< imuBias::ConstantBias > |
|
struct | traits< ImuFactor > |
|
struct | traits< ImuFactor2 > |
|
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< 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< PreintegratedCombinedMeasurements > |
|
struct | traits< PreintegratedImuMeasurements > |
|
struct | traits< PreintegratedRotation > |
|
struct | traits< PreintegrationCombinedParams > |
|
struct | traits< PriorFactor< VALUE > > |
| traits More...
|
|
struct | traits< ProductLieGroup< G, H > > |
|
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 > |
|
struct | traits< Similarity2 > |
|
struct | traits< Similarity3 > |
|
struct | traits< SmartProjectionFactor< CAMERA > > |
| traits More...
|
|
struct | traits< SmartProjectionPoseFactor< CALIBRATION > > |
| traits More...
|
|
struct | traits< SmartProjectionRigFactor< CAMERA > > |
| traits More...
|
|
struct | traits< SO3 > |
|
struct | traits< SO4 > |
|
struct | traits< SO< N > > |
|
struct | traits< SphericalCamera > |
|
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< Unit3 > |
|
struct | traits< Values > |
| traits More...
|
|
struct | traits< VariableIndex > |
| traits More...
|
|
struct | traits< VariableSlots > |
| traits More...
|
|
struct | traits< VectorValues > |
| traits More...
|
|
class | TransformCovariance |
| Functor for transforming covariance of T. More...
|
|
class | TranslationFactor |
| Binary factor for a relative translation direction measurement w_aZb. More...
|
|
class | TranslationRecovery |
|
class | TriangulationCheiralityException |
| Exception thrown by triangulateDLT when landmark is behind one or more of the cameras. More...
|
|
class | TriangulationFactor |
| Non-linear factor for a constraint derived from a 2D measurement. More...
|
|
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...
|
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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...
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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...
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class | VectorValues |
| VectorValues represents a collection of vector-valued variables associated each with a unique integer index. More...
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class | VerticalBlockMatrix |
| This class stores a dense matrix and allows it to be accessed as a collection of vertical blocks. More...
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struct | Visit |
| Functor performing depth-first visit to each leaf with the leaf value as the argument. More...
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struct | VisitLeaf |
| Functor performing depth-first visit to each leaf with the Leaf object passed as an argument. More...
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struct | VisitWith |
| Functor performing depth-first visit to each leaf with the leaf's Assignment<L> and value passed as arguments. More...
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class | WeightedSampler |
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class | WhiteNoiseFactor |
| Binary factor to estimate parameters of zero-mean Gaussian white noise. More...
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template<typename T > |
void | testDefaultChart (TestResult &result_, const std::string &name_, const T &value) |
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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.
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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].
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bool | guardedIsDebug (const std::string &s) |
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void | guardedSetDebug (const std::string &s, const bool v) |
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bool | isDebugVersion () |
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IndexPairVector | IndexPairSetAsArray (IndexPairSet &set) |
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template<class T > |
GenericValue< T > | genericValue (const T &v) |
| Functional constructor of GenericValue<T> so T can be automatically deduced.
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template<typename G > |
| BOOST_CONCEPT_REQUIRES (((IsGroup< G >)),(bool)) check_group_invariants(const G &a |
| Check invariants.
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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.
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template<class Class > |
Vector | logmap_default (const Class &l0, const Class &lp) |
| Log map centered at l0, s.t.
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template<class Class > |
Class | expmap_default (const Class &t, const Vector &d) |
| Exponential map centered at l0, s.t.
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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.
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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.
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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.
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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.
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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.
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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.
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template<typename T > |
| BOOST_CONCEPT_REQUIRES (((IsTestable< T >)),(bool)) check_manifold_invariants(const T &a |
| Check invariants for Manifold type.
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bool | assert_equal (const Matrix &A, const Matrix &B, double tol=1e-9) |
| equals with an tolerance, prints out message if unequal
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bool | assert_inequal (const Matrix &A, const Matrix &B, double tol=1e-9) |
| inequals with an tolerance, prints out message if within tolerance
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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
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bool | linear_independent (const Matrix &A, const Matrix &B, double tol=1e-9) |
| check whether the rows of two matrices are linear independent
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bool | linear_dependent (const Matrix &A, const Matrix &B, double tol=1e-9) |
| check whether the rows of two matrices are linear dependent
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Vector | operator^ (const Matrix &A, const Vector &v) |
| overload ^ for trans(A)*v We transpose the vectors for speed.
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const Eigen::IOFormat & | matlabFormat () |
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void | print (const Matrix &A, const std::string &s, std::ostream &stream) |
| print without optional string, must specify cout yourself
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void | print (const Matrix &A, const std::string &s="") |
| print with optional string to cout
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void | save (const Matrix &A, const std::string &s, const std::string &filename) |
| save a matrix to file, which can be loaded by matlab
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istream & | operator>> (std::istream &inputStream, Matrix &destinationMatrix) |
| Read a matrix from an input stream, such as a file.
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Matrix | diag (const std::vector< Matrix > &Hs) |
| Create a matrix with submatrices along its diagonal.
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Vector | columnNormSquare (const Matrix &A) |
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pair< Matrix, Matrix > | qr (const Matrix &A) |
| Householder QR factorization, Golub & Van Loan p 224, explicit version
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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.
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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.
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void | householder (Matrix &A, size_t k) |
| Householder tranformation, zeros below diagonal.
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Vector | backSubstituteLower (const Matrix &L, const Vector &b, bool unit=false) |
| backSubstitute L*x=b
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Vector | backSubstituteUpper (const Matrix &U, const Vector &b, bool unit=false) |
| backSubstitute U*x=b
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Vector | backSubstituteUpper (const Vector &b, const Matrix &U, bool unit=false) |
| backSubstitute x'*U=b'
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Matrix | stack (size_t nrMatrices,...) |
| create a matrix by stacking other matrices Given a set of matrices: A1, A2, A3...
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Matrix | stack (const std::vector< Matrix > &blocks) |
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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
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Matrix | collect (size_t nrMatrices,...) |
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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
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Matrix | vector_scale (const Vector &v, const Matrix &A, bool inf_mask) |
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Matrix | vector_scale (const Matrix &A, const Vector &v, bool inf_mask) |
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Matrix | LLt (const Matrix &A) |
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Matrix | RtR (const Matrix &A) |
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Matrix | cholesky_inverse (const Matrix &A) |
| Return the inverse of a S.P.D.
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Matrix | inverse_square_root (const Matrix &A) |
| Use Cholesky to calculate inverse square root of a matrix.
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void | svd (const Matrix &A, Matrix &U, Vector &S, Matrix &V) |
| SVD computes economy SVD A=U*S*V'.
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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.
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Matrix | expm (const Matrix &A, size_t K=7) |
| Numerical exponential map, naive approach, not industrial strength !!!
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std::string | formatMatrixIndented (const std::string &label, const Matrix &matrix, bool makeVectorHorizontal) |
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void | inplace_QR (Matrix &A) |
| QR factorization using Eigen's internal block QR algorithm.
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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
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bool | operator== (const Matrix &A, const Matrix &B) |
| equality is just equal_with_abs_tol 1e-9
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bool | operator!= (const Matrix &A, const Matrix &B) |
| inequality
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template<class MATRIX > |
MATRIX | prod (const MATRIX &A, const MATRIX &B) |
| products using old-style format to improve compatibility
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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.
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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
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template<class MATRIX > |
const MATRIX::ConstColXpr | column (const MATRIX &A, size_t j) |
| Extracts a column view from a matrix that avoids a copy.
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template<class MATRIX > |
const MATRIX::ConstRowXpr | row (const MATRIX &A, size_t j) |
| Extracts a row view from a matrix that avoids a copy.
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template<class MATRIX > |
void | zeroBelowDiagonal (MATRIX &A, size_t cols=0) |
| Zeros all of the elements below the diagonal of a matrix, in place.
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Matrix | trans (const Matrix &A) |
| static transpose function, just calls Eigen transpose member function
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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) |
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Matrix3 | skewSymmetric (double wx, double wy, double wz) |
| skew symmetric matrix returns this: 0 -wz wy wz 0 -wx -wy wx 0
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template<class Derived > |
Matrix3 | skewSymmetric (const Eigen::MatrixBase< Derived > &w) |
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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.
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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.
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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
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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.
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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
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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.
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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
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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.
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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) |
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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.
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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) |
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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.
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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) |
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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.
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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) |
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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.
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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) |
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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.
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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) |
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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.
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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) |
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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.
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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) |
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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.
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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) |
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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.
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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) |
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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.
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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) |
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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.
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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) |
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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.
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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) |
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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.
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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) |
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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.
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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.
|
|
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.
|
|
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.
|
|
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.
|
|
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.
|
|
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 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.
|
|
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.
|
|
| 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.
|
|
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.
|
|
bool | assert_inequal (const Vector &vec1, const Vector &vec2, double tol=1e-9) |
| Not the same, prints if error.
|
|
bool | assert_equal (const SubVector &vec1, const SubVector &vec2, double tol=1e-9) |
| Same, prints if error.
|
|
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
|
|
Vector | ediv_ (const Vector &a, const Vector &b) |
| elementwise division, but 0/0 = 0, not inf
|
|
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.
|
|
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.
|
|
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()
|
|
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.
|
|
template<int M> |
std::ostream & | operator<< (std::ostream &os, const ParameterMatrix< M > ¶meterMatrix) |
|
template<typename L , typename Y > |
DecisionTree< L, Y > | apply (const DecisionTree< L, Y > &f, const typename DecisionTree< L, Y >::Unary &op) |
| free versions of apply
|
|
template<typename L , typename Y > |
DecisionTree< L, Y > | apply (const DecisionTree< L, Y > &f, const typename DecisionTree< L, Y >::UnaryAssignment &op) |
| Apply unary operator op with Assignment to DecisionTree f .
|
|
template<typename L , typename Y > |
DecisionTree< L, Y > | apply (const DecisionTree< L, Y > &f, const DecisionTree< L, Y > &g, const typename DecisionTree< L, Y >::Binary &op) |
| Apply binary operator op to DecisionTree f .
|
|
template<typename L , typename T1 , typename T2 > |
std::pair< DecisionTree< L, T1 >, DecisionTree< L, T2 > > | unzip (const DecisionTree< L, std::pair< T1, T2 > > &input) |
| unzip a DecisionTree with std::pair values.
|
|
std::vector< double > | expNormalize (const std::vector< double > &logProbs) |
| Normalize a set of log probabilities.
|
|
std::pair< DiscreteConditional::shared_ptr, DecisionTreeFactor::shared_ptr > | EliminateForMPE (const DiscreteFactorGraph &factors, const Ordering &frontalKeys) |
|
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.
|
|
string | markdown (const DiscreteValues &values, const KeyFormatter &keyFormatter=DefaultKeyFormatter, const DiscreteValues::Names &names={}) |
| Free version of markdown.
|
|
string | html (const DiscreteValues &values, const KeyFormatter &keyFormatter=DefaultKeyFormatter, const DiscreteValues::Names &names={}) |
| Free version of html.
|
|
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");.
|
|
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 .
|
|
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.
|
|
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.
|
|
Point2Pair | means (const std::vector< Point2Pair > &abPointPairs) |
| Calculate the two means of a set of Point2 pairs.
|
|
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
|
|
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) |
|
template<> |
Matrix | wedge< Pose2 > (const Vector &xi) |
| specialization for pose2 wedge function (generic template in Lie.h)
|
|
std::ostream & | operator<< (std::ostream &os, const Pose3 &pose) |
|
template<> |
Matrix | wedge< Pose3 > (const Vector &xi) |
| wedge for Pose3:
|
|
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'.
|
|
ostream & | operator<< (ostream &os, const Rot3 &R) |
|
std::ostream & | operator<< (std::ostream &os, const Similarity2 &p) |
|
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.
|
|
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.
|
|
Vector4 | triangulateHomogeneousDLT (const std::vector< Matrix34, Eigen::aligned_allocator< Matrix34 > > &projection_matrices, const std::vector< Unit3 > &measurements, double rank_tol=1e-9) |
| Same math as Hartley and Zisserman, 2nd Ed., page 312, but with unit-norm bearing vectors (contrarily to pinhole projection, the z entry is not assumed to be 1 as in Hartley and Zisserman)
|
|
Point3 | triangulateLOST (const std::vector< Pose3 > &poses, const Point3Vector &calibratedMeasurements, const SharedIsotropic &measurementNoise) |
| Triangulation using the LOST (Linear Optimal Sine Triangulation) algorithm proposed in https://arxiv.org/pdf/2205.12197.pdf by Sebastien Henry and John Christian.
|
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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.
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Point3 | triangulateDLT (const std::vector< Matrix34, Eigen::aligned_allocator< Matrix34 > > &projection_matrices, const std::vector< Unit3 > &measurements, double rank_tol=1e-9) |
| overload of previous function to work with Unit3 (projected to canonical camera)
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Point3 | optimize (const NonlinearFactorGraph &graph, const Values &values, Key landmarkKey) |
| Optimize for triangulation.
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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, const SharedNoiseModel &model=noiseModel::Unit::Create(2)) |
| Create a factor graph with projection factors from poses and one calibration.
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template<class CAMERA > |
std::pair< NonlinearFactorGraph, Values > | triangulationGraph (const CameraSet< CAMERA > &cameras, const typename CAMERA::MeasurementVector &measurements, Key landmarkKey, const Point3 &initialEstimate, const SharedNoiseModel &model=nullptr) |
| Create a factor graph with projection factors from pinhole cameras (each camera has a pose and calibration)
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template<class CALIBRATION > |
Point3 | triangulateNonlinear (const std::vector< Pose3 > &poses, boost::shared_ptr< CALIBRATION > sharedCal, const Point2Vector &measurements, const Point3 &initialEstimate, const SharedNoiseModel &model=nullptr) |
| Given an initial estimate , refine a point using measurements in several cameras.
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template<class CAMERA > |
Point3 | triangulateNonlinear (const CameraSet< CAMERA > &cameras, const typename CAMERA::MeasurementVector &measurements, const Point3 &initialEstimate, const SharedNoiseModel &model=nullptr) |
| Given an initial estimate , refine a point using measurements in several cameras.
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template<class CAMERA > |
std::vector< Matrix34, Eigen::aligned_allocator< Matrix34 > > | projectionMatricesFromCameras (const CameraSet< CAMERA > &cameras) |
|
template<class CALIBRATION > |
std::vector< Matrix34, Eigen::aligned_allocator< Matrix34 > > | projectionMatricesFromPoses (const std::vector< Pose3 > &poses, boost::shared_ptr< CALIBRATION > sharedCal) |
|
template<class CALIBRATION > |
Cal3_S2 | createPinholeCalibration (const CALIBRATION &cal) |
| Create a pinhole calibration from a different Cal3 object, removing distortion.
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template<class CALIBRATION , class MEASUREMENT > |
MEASUREMENT | undistortMeasurementInternal (const CALIBRATION &cal, const MEASUREMENT &measurement, boost::optional< Cal3_S2 > pinholeCal=boost::none) |
| Internal undistortMeasurement to be used by undistortMeasurement and undistortMeasurements.
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template<class CALIBRATION > |
Point2Vector | undistortMeasurements (const CALIBRATION &cal, const Point2Vector &measurements) |
| Remove distortion for measurements so as if the measurements came from a pinhole camera.
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template<> |
Point2Vector | undistortMeasurements (const Cal3_S2 &cal, const Point2Vector &measurements) |
| Specialization for Cal3_S2 as it doesn't need to be undistorted.
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template<class CAMERA > |
CAMERA::MeasurementVector | undistortMeasurements (const CameraSet< CAMERA > &cameras, const typename CAMERA::MeasurementVector &measurements) |
| Remove distortion for measurements so as if the measurements came from a pinhole camera.
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template<class CAMERA = PinholeCamera<Cal3_S2>> |
PinholeCamera< Cal3_S2 >::MeasurementVector | undistortMeasurements (const CameraSet< PinholeCamera< Cal3_S2 > > &cameras, const PinholeCamera< Cal3_S2 >::MeasurementVector &measurements) |
| Specialize for Cal3_S2 to do nothing.
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template<class CAMERA = SphericalCamera> |
SphericalCamera::MeasurementVector | undistortMeasurements (const CameraSet< SphericalCamera > &cameras, const SphericalCamera::MeasurementVector &measurements) |
| Specialize for SphericalCamera to do nothing.
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template<class CALIBRATION > |
Point3Vector | calibrateMeasurementsShared (const CALIBRATION &cal, const Point2Vector &measurements) |
| Convert pixel measurements in image to homogeneous measurements in the image plane using shared camera intrinsics.
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template<class CAMERA > |
Point3Vector | calibrateMeasurements (const CameraSet< CAMERA > &cameras, const typename CAMERA::MeasurementVector &measurements) |
| Convert pixel measurements in image to homogeneous measurements in the image plane using camera intrinsics of each measurement.
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|
template<class CAMERA = SphericalCamera> |
Point3Vector | calibrateMeasurements (const CameraSet< SphericalCamera > &cameras, const SphericalCamera::MeasurementVector &measurements) |
| Specialize for SphericalCamera to do nothing.
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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, const SharedNoiseModel &model=nullptr, const bool useLOST=false) |
| Function to triangulate 3D landmark point from an arbitrary number of poses (at least 2) using the DLT.
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|
template<class CAMERA > |
Point3 | triangulatePoint3 (const CameraSet< CAMERA > &cameras, const typename CAMERA::MeasurementVector &measurements, double rank_tol=1e-9, bool optimize=false, const SharedNoiseModel &model=nullptr, const bool useLOST=false) |
| Function to triangulate 3D landmark point from an arbitrary number of poses (at least 2) using the DLT.
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template<class CALIBRATION > |
Point3 | triangulatePoint3 (const CameraSet< PinholeCamera< CALIBRATION > > &cameras, const Point2Vector &measurements, double rank_tol=1e-9, bool optimize=false, const SharedNoiseModel &model=nullptr, const bool useLOST=false) |
| Pinhole-specific version.
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|
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) |
|
std::set< DiscreteKey > | DiscreteKeysAsSet (const DiscreteKeys &discreteKeys) |
| Return the DiscreteKey vector as a set.
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|
std::function< double(const Assignment< Key > &, double)> | prunerFunc (const DecisionTreeFactor &prunedDecisionTree, const HybridConditional &conditional) |
| Helper function to get the pruner functional.
|
|
KeyVector | CollectKeys (const KeyVector &continuousKeys, const DiscreteKeys &discreteKeys) |
|
KeyVector | CollectKeys (const KeyVector &keys1, const KeyVector &keys2) |
|
DiscreteKeys | CollectDiscreteKeys (const DiscreteKeys &key1, const DiscreteKeys &key2) |
|
const Ordering | HybridOrdering (const HybridGaussianFactorGraph &graph) |
| Return a Colamd constrained ordering where the discrete keys are eliminated after the continuous keys.
|
|
GaussianFactorGraphTree | removeEmpty (const GaussianFactorGraphTree &sum) |
|
std::pair< HybridConditional::shared_ptr, boost::shared_ptr< Factor > > | EliminateHybrid (const HybridGaussianFactorGraph &factors, const Ordering &keys) |
| Main elimination function for HybridGaussianFactorGraph.
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|
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.
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|
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.
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|
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.
|
|
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.
|
|
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) |
|
Errors | createErrors (const VectorValues &V) |
| Break V into pieces according to its start indices.
|
|
void | print (const Errors &e, const std::string &s="Errors") |
| Print an Errors instance.
|
|
bool | equality (const Errors &actual, const Errors &expected, double tol) |
|
Errors | operator+ (const Errors &a, const Errors &b) |
| Addition.
|
|
Errors | operator- (const Errors &a, const Errors &b) |
| Subtraction.
|
|
Errors | operator- (const Errors &a) |
| Negation.
|
|
double | dot (const Errors &a, const Errors &b) |
| Dot product.
|
|
void | axpy (double alpha, const Errors &x, Errors &y) |
| BLAS level 2 style AXPY, y := alpha*x + y
|
|
bool | hasConstraints (const GaussianFactorGraph &factors) |
| Evaluates whether linear factors have any constrained noise models.
|
|
std::pair< boost::shared_ptr< GaussianConditional >, boost::shared_ptr< HessianFactor > > | EliminateCholesky (const GaussianFactorGraph &factors, const Ordering &keys) |
| Densely partially eliminate with Cholesky factorization.
|
|
std::pair< boost::shared_ptr< GaussianConditional >, boost::shared_ptr< GaussianFactor > > | EliminatePreferCholesky (const GaussianFactorGraph &factors, const Ordering &keys) |
| Densely partially eliminate with Cholesky factorization.
|
|
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)
|
|
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:
|
|
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).
|
|
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 | buildFactorSubgraph (const GaussianFactorGraph &gfg, const Subgraph &subgraph, const bool clone) |
| Select the factors in a factor graph according to the subgraph.
|
|
std::pair< GaussianFactorGraph, GaussianFactorGraph > | splitFactorGraph (const GaussianFactorGraph &factorGraph, const Subgraph &subgraph) |
| Split the graph into a subgraph and the remaining edges.
|
|
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.
|
|
template<typename T > |
std::vector< Expression< T > > | createUnknowns (size_t n, char c, size_t start) |
| Construct an array of leaves.
|
|
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.
|
|
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.
|
|
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.
|
|
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.
|
|
size_t | optimizeWildfire (const ISAM2Clique::shared_ptr &root, double threshold, const KeySet &replaced, VectorValues *delta) |
| Optimize the BayesTree, starting from the root.
|
|
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.
|
|
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) |
|
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.
|
|
Pose3 | gtsam2openGL (const Rot3 &R, double tx, double ty, double tz) |
| This function converts a GTSAM camera pose to an openGL camera pose.
|
|
Pose3 | gtsam2openGL (const Pose3 &PoseGTSAM) |
| This function converts a GTSAM camera pose to an openGL camera pose.
|
|
bool | writeBAL (const std::string &filename, const SfmData &data) |
| This function writes a "Bundle Adjustment in the Large" (BAL) file from a SfmData structure.
|
|
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.
|
|
bool | writeBALfromValues (const std::string &filename, const SfmData &data, const 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)
|
|
Values | initialCamerasEstimate (const SfmData &db) |
| This function creates initial values for cameras from db.
|
|
Values | initialCamerasAndPointsEstimate (const SfmData &db) |
| This function creates initial values for cameras and points from db.
|
|
string | findExampleDataFile (const std::string &name) |
| Find the full path to an example dataset distributed with gtsam.
|
|
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".
|
|
template<> |
GTSAM_EXPORT 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".
|
|
template<> |
GTSAM_EXPORT 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".
|
|
boost::shared_ptr< Sampler > | createSampler (const SharedNoiseModel &model) |
|
template<> |
GTSAM_EXPORT std::vector< BinaryMeasurement< Pose2 > > | parseMeasurements (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
|
template<> |
GTSAM_EXPORT std::vector< BinaryMeasurement< Rot2 > > | parseMeasurements (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
|
template<> |
GTSAM_EXPORT 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.
|
|
GraphAndValues | load2D (pair< string, SharedNoiseModel > dataset, size_t maxIndex, bool addNoise, bool smart, NoiseFormat noiseFormat, KernelFunctionType kernelFunctionType) |
| Load TORO 2D Graph.
|
|
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.
|
|
void | writeG2o (const NonlinearFactorGraph &graph, const Values &estimate, const std::string &filename) |
| This function writes a g2o file from NonlinearFactorGraph and a Values structure.
|
|
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<> |
GTSAM_EXPORT 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<> |
GTSAM_EXPORT std::map< size_t, Point3 > | parseVariables< Point3 > (const std::string &filename, size_t maxIndex) |
|
istream & | operator>> (istream &is, Matrix6 &m) |
|
template<> |
GTSAM_EXPORT std::vector< BinaryMeasurement< Pose3 > > | parseMeasurements (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
|
template<> |
GTSAM_EXPORT std::vector< BinaryMeasurement< Rot3 > > | parseMeasurements (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
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template<> |
GTSAM_EXPORT std::vector< BetweenFactor< Pose3 >::shared_ptr > | parseFactors< Pose3 > (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
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GraphAndValues | load3D (const std::string &filename) |
| Load TORO 3D Graph.
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BetweenFactorPose2s | parse2DFactors (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
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BetweenFactorPose3s | parse3DFactors (const std::string &filename, const noiseModel::Diagonal::shared_ptr &model, size_t maxIndex) |
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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.
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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.
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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.
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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.
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Point2_ | transformTo (const Pose2_ &x, const Point2_ &p) |
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Double_ | range (const Point2_ &p, const Point2_ &q) |
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Point3_ | transformTo (const Pose3_ &x, const Point3_ &p) |
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Point3_ | transformFrom (const Pose3_ &x, const Point3_ &p) |
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Line3_ | transformTo (const Pose3_ &wTc, const Line3_ &wL) |
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Pose3_ | transformPoseTo (const Pose3_ &p, const Pose3_ &q) |
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Point3_ | normalize (const Point3_ &a) |
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Point3_ | cross (const Point3_ &a, const Point3_ &b) |
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Double_ | dot (const Point3_ &a, const Point3_ &b) |
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Rot3_ | rotation (const Pose3_ &pose) |
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Point3_ | translation (const Pose3_ &pose) |
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Point3_ | rotate (const Rot3_ &x, const Point3_ &p) |
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Point3_ | point3 (const Unit3_ &v) |
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Unit3_ | rotate (const Rot3_ &x, const Unit3_ &p) |
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Point3_ | unrotate (const Rot3_ &x, const Point3_ &p) |
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Unit3_ | unrotate (const Rot3_ &x, const Unit3_ &p) |
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Double_ | distance (const OrientedPlane3_ &p) |
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Unit3_ | normal (const OrientedPlane3_ &p) |
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Point2_ | project (const Point3_ &p_cam) |
| Expression version of PinholeBase::Project.
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Point2_ | project (const Unit3_ &p_cam) |
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template<class CAMERA , class POINT > |
Point2_ | project2 (const Expression< CAMERA > &camera_, const Expression< POINT > &p_) |
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template<class CALIBRATION , class POINT > |
Point2_ | project3 (const Pose3_ &x, const Expression< POINT > &p, const Expression< CALIBRATION > &K) |
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template<class CALIBRATION > |
Point2_ | uncalibrate (const Expression< CALIBRATION > &K, const Point2_ &xy_hat) |
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template<class CALIBRATION > |
Pose3_ | getPose (const Expression< PinholeCamera< CALIBRATION > > &cam) |
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template<typename T > |
gtsam::Expression< typename gtsam::traits< T >::TangentVector > | logmap (const gtsam::Expression< T > &x1, const gtsam::Expression< T > &x2) |
| logmap
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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.
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template<class T , class ALLOC > |
T | FindKarcherMeanImpl (const vector< T, ALLOC > &rotations) |
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template<class T > |
T | FindKarcherMean (const std::vector< T > &rotations) |
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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.
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template<class T > |
T | FindKarcherMean (std::initializer_list< T > &&rotations) |
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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.
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std::pair< boost::shared_ptr< SymbolicConditional >, boost::shared_ptr< SymbolicFactor > > | EliminateSymbolic (const SymbolicFactorGraph &factors, const Ordering &keys) |
| Dense elimination function for symbolic factors.
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Serialization in default compressed format
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template<class T > |
void | serializeToStream (const T &input, std::ostream &out_archive_stream) |
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template<class T > |
void | deserializeFromStream (std::istream &in_archive_stream, T &output) |
| deserializes from a stream
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template<class T > |
std::string | serializeToString (const T &input) |
| serializes to a string
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template<class T > |
void | deserializeFromString (const std::string &serialized, T &output) |
| deserializes from a string
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template<class T > |
bool | serializeToFile (const T &input, const std::string &filename) |
| serializes to a file
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template<class T > |
bool | deserializeFromFile (const std::string &filename, T &output) |
| deserializes from a file
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template<class T > |
std::string | serialize (const T &input) |
| serializes to a string
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template<class T > |
void | deserialize (const std::string &serialized, T &output) |
| deserializes from a string
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Serialization to XML format with named structures
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template<class T > |
void | serializeToXMLStream (const T &input, std::ostream &out_archive_stream, const std::string &name="data") |
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template<class T > |
void | deserializeFromXMLStream (std::istream &in_archive_stream, T &output, const std::string &name="data") |
| deserializes from a stream in XML
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template<class T > |
std::string | serializeToXMLString (const T &input, const std::string &name="data") |
| serializes to a string in XML
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template<class T > |
void | deserializeFromXMLString (const std::string &serialized, T &output, const std::string &name="data") |
| deserializes from a string in XML
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template<class T > |
bool | serializeToXMLFile (const T &input, const std::string &filename, const std::string &name="data") |
| serializes to an XML file
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template<class T > |
bool | deserializeFromXMLFile (const std::string &filename, T &output, const std::string &name="data") |
| deserializes from an XML file
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template<class T > |
std::string | serializeXML (const T &input, const std::string &name="data") |
| serializes to a string in XML
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template<class T > |
void | deserializeXML (const std::string &serialized, T &output, const std::string &name="data") |
| deserializes from a string in XML
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Serialization to binary format with named structures
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template<class T > |
void | serializeToBinaryStream (const T &input, std::ostream &out_archive_stream, const std::string &name="data") |
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template<class T > |
void | deserializeFromBinaryStream (std::istream &in_archive_stream, T &output, const std::string &name="data") |
| deserializes from a stream in binary
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template<class T > |
std::string | serializeToBinaryString (const T &input, const std::string &name="data") |
| serializes to a string in binary
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template<class T > |
void | deserializeFromBinaryString (const std::string &serialized, T &output, const std::string &name="data") |
| deserializes from a string in binary
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template<class T > |
bool | serializeToBinaryFile (const T &input, const std::string &filename, const std::string &name="data") |
| serializes to a binary file
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template<class T > |
bool | deserializeFromBinaryFile (const std::string &filename, T &output, const std::string &name="data") |
| deserializes from a binary file
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template<class T > |
std::string | serializeBinary (const T &input, const std::string &name="data") |
| serializes to a string in binary
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template<class T > |
void | deserializeBinary (const std::string &serialized, T &output, const std::string &name="data") |
| deserializes from a string in binary
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VectorValues | buildVectorValues (const Vector &v, const Ordering &ordering, const std::map< Key, size_t > &dimensions) |
| Create VectorValues from a Vector.
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VectorValues | buildVectorValues (const Vector &v, const KeyInfo &keyInfo) |
| Create VectorValues from a Vector and a KeyInfo class.
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