Class sym::Linearizer¶

template<typename ScalarType> class Linearizer¶

Class for evaluating multiple Factors at the linearization point given by a Values.

Stores the original Factors as well as the LinearizedFactors, and provides tools for aggregating keys and building a large jacobian / hessian for optimization.

For efficiency, prefer calling Relinearize() instead of re-constructing this object!

Public Types

using Scalar = ScalarType ¶

using LinearizedDenseFactor = typename Factor<Scalar>::LinearizedDenseFactor¶

using LinearizedSparseFactor = typename Factor<Scalar>::LinearizedSparseFactor¶

using LinearizationType = SparseLinearization<Scalar>¶

Public Functions

Linearizer(const std::string &name, const std::vector<Factor<Scalar>> &factors, const std::vector<Key> &key_order = {}, bool include_jacobians = false, bool debug_checks = false)¶

Construct a Linearizer from factors and optional keys

Parameters:

factors – Only stores a pointer, MUST be in scope for the lifetime of this object!
key_order – If provided, acts as an ordered set of keys that form the state vector to optimize. Can equal the set of all factor keys or a subset of all factor keys. If not provided, it is computed from all keys for all factors using a default ordering.
debug_checks – Whether to perform additional sanity checks for NaNs. This uses additional compute but not additional memory except for logging.

void Relinearize(const Values<Scalar> &values, SparseLinearization<Scalar> &linearization)¶

Update linearization at a new evaluation point

This is more efficient than reconstructing this object repeatedly. On the first call, it will allocate memory and perform analysis needed for efficient repeated relinearization.

TODO(aaron): This should be const except that it can initialize the object

bool IsInitialized() const¶: Whether this contains values, versus having not been evaluated yet

const std::vector<LinearizedSparseFactor> &LinearizedSparseFactors() const¶

const std::vector<Key> &Keys() const¶

const std::unordered_map<key_t, index_entry_t> &StateIndex() const¶