Merged in feature/allowMap (pull request #18)

Replaced range adaptor pattern with more explicit loop to create dimensions, which also allows maps to be supplied as TERMS containers.
release/4.3a0
Frank Dellaert 2014-09-30 11:33:35 +02:00
commit e408159545
3 changed files with 53 additions and 26 deletions

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@ -13,6 +13,22 @@
* @brief Incremental and batch solving, timing, and accuracy comparisons
* @author Richard Roberts
* @date August, 2013
*
* Here is an example. Below, to run in batch mode, we first generate an initialization in incremental mode.
*
* Solve in incremental and write to file w_inc:
* ./SolverComparer --incremental -d w10000 -o w_inc
*
* You can then perturb that initialization to get batch something to optimize.
* Read in w_inc, perturb it with noise of stddev 0.6, and write to w_pert:
* ./SolverComparer --perturb 0.6 -i w_inc -o w_pert
*
* Then optimize with batch, read in w_pert, solve in batch, and write to w_batch:
* ./SolverComparer --batch -d w10000 -i w_pert -o w_batch
*
* And finally compare solutions in w_inc and w_batch to check that batch converged to the global minimum
* ./SolverComparer --compare w_inc w_batch
*
*/
#include <gtsam/base/timing.h>

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@ -19,10 +19,6 @@
#pragma once
#include <gtsam/linear/linearExceptions.h>
#include <boost/assign/list_of.hpp>
#include <boost/range/adaptor/transformed.hpp>
#include <boost/range/algorithm/for_each.hpp>
#include <boost/foreach.hpp>
namespace gtsam {
@ -59,20 +55,10 @@ namespace gtsam {
model_ = model;
}
/* ************************************************************************* */
namespace internal {
static inline DenseIndex getColsJF(const std::pair<Key,Matrix>& p) {
return p.second.cols();
}
}
/* ************************************************************************* */
template<typename TERMS>
void JacobianFactor::fillTerms(const TERMS& terms, const Vector& b, const SharedDiagonal& noiseModel)
{
using boost::adaptors::transformed;
namespace br = boost::range;
// Check noise model dimension
if(noiseModel && (DenseIndex)noiseModel->dim() != b.size())
throw InvalidNoiseModel(b.size(), noiseModel->dim());
@ -80,25 +66,32 @@ namespace gtsam {
// Resize base class key vector
Base::keys_.resize(terms.size());
// Construct block matrix - this uses the boost::range 'transformed' construct to apply
// internal::getColsJF (defined just above here in this file) to each term. This
// transforms the list of terms into a list of variable dimensions, by extracting the
// number of columns in each matrix. This is done to avoid separately allocating an
// array of dimensions before constructing the VerticalBlockMatrix.
Ab_ = VerticalBlockMatrix(terms | transformed(&internal::getColsJF), b.size(), true);
// Get dimensions of matrices
std::vector<size_t> dimensions;
dimensions.reserve(terms.size());
for(typename TERMS::const_iterator it = terms.begin(); it != terms.end(); ++it) {
const std::pair<Key, Matrix>& term = *it;
const Matrix& Ai = term.second;
dimensions.push_back(Ai.cols());
}
// Construct block matrix
Ab_ = VerticalBlockMatrix(dimensions, b.size(), true);
// Check and add terms
DenseIndex i = 0; // For block index
for(typename TERMS::const_iterator termIt = terms.begin(); termIt != terms.end(); ++termIt) {
const std::pair<Key, Matrix>& term = *termIt;
for(typename TERMS::const_iterator it = terms.begin(); it != terms.end(); ++it) {
const std::pair<Key, Matrix>& term = *it;
Key key = term.first;
const Matrix& Ai = term.second;
// Check block rows
if(term.second.rows() != Ab_.rows())
throw InvalidMatrixBlock(Ab_.rows(), term.second.rows());
if(Ai.rows() != Ab_.rows())
throw InvalidMatrixBlock(Ab_.rows(), Ai.rows());
// Assign key and matrix
Base::keys_[i] = term.first;
Ab_(i) = term.second;
Base::keys_[i] = key;
Ab_(i) = Ai;
// Increment block index
++ i;

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@ -105,6 +105,24 @@ TEST(JacobianFactor, constructors_and_accessors)
EXPECT(noise == expected.get_model());
EXPECT(noise == actual.get_model());
}
{
// Test three-term constructor with std::map
JacobianFactor expected(
boost::make_iterator_range(terms.begin(), terms.begin() + 3), b, noise);
map<Key,Matrix> mapTerms;
// note order of insertion plays no role: order will be determined by keys
mapTerms.insert(terms[2]);
mapTerms.insert(terms[1]);
mapTerms.insert(terms[0]);
JacobianFactor actual(mapTerms, b, noise);
EXPECT(assert_equal(expected, actual));
LONGS_EQUAL((long)terms[2].first, (long)actual.keys().back());
EXPECT(assert_equal(terms[2].second, actual.getA(actual.end() - 1)));
EXPECT(assert_equal(b, expected.getb()));
EXPECT(assert_equal(b, actual.getb()));
EXPECT(noise == expected.get_model());
EXPECT(noise == actual.get_model());
}
{
// VerticalBlockMatrix constructor
JacobianFactor expected(