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Fix compilation issues

release/4.3a0
Frank Dellaert 2021-12-30 12:18:49 -05:00
parent c659336cf8
commit 910f879a0b
4 changed files with 8 additions and 8 deletions
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2
gtsam/linear/SubgraphPreconditioner.cpp
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@ -264,7 +264,7 @@ void SubgraphPreconditioner::build(const GaussianFactorGraph &gfg, const KeyInfo
auto gfg_subgraph = buildFactorSubgraph(gfg, subgraph, true);
/* factorize and cache BayesNet */
Rc1_ = gfg_subgraph.eliminateSequential();
Rc1_ = *gfg_subgraph.eliminateSequential();
}
/*****************************************************************************/

4
gtsam/linear/SubgraphSolver.cpp
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@ -40,7 +40,7 @@ SubgraphSolver::SubgraphSolver(const GaussianFactorGraph &Ab,
cout << "Split A into (A1) " << Ab1.size() << " and (A2) " << Ab2.size()
<< " factors" << endl;
auto Rc1 = Ab1.eliminateSequential(ordering, EliminateQR);
auto Rc1 = *Ab1.eliminateSequential(ordering, EliminateQR);
auto xbar = Rc1.optimize();
pc_ = boost::make_shared<SubgraphPreconditioner>(Ab2, Rc1, xbar);
}
@ -62,7 +62,7 @@ SubgraphSolver::SubgraphSolver(const GaussianFactorGraph &Ab1,
const GaussianFactorGraph &Ab2,
const Parameters &parameters,
const Ordering &ordering)
: SubgraphSolver(Ab1.eliminateSequential(ordering, EliminateQR), Ab2,
: SubgraphSolver(*Ab1.eliminateSequential(ordering, EliminateQR), Ab2,
parameters) {}
/**************************************************************************************************/

8
tests/testSubgraphPreconditioner.cpp
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@ -77,7 +77,7 @@ TEST(SubgraphPreconditioner, planarGraph) {
DOUBLES_EQUAL(0, error(A, xtrue), 1e-9); // check zero error for xtrue
// Check that xtrue is optimal
GaussianBayesNet R1 = A.eliminateSequential();
GaussianBayesNet R1 = *A.eliminateSequential();
VectorValues actual = R1.optimize();
EXPECT(assert_equal(xtrue, actual));
}
@ -96,7 +96,7 @@ TEST(SubgraphPreconditioner, splitOffPlanarTree) {
LONGS_EQUAL(4, C.size());
// Check that the tree can be solved to give the ground xtrue
GaussianBayesNet R1 = T.eliminateSequential();
GaussianBayesNet R1 = *T.eliminateSequential();
VectorValues xbar = R1.optimize();
EXPECT(assert_equal(xtrue, xbar));
}
@ -115,7 +115,7 @@ TEST(SubgraphPreconditioner, system) {
// Eliminate the spanning tree to build a prior
const Ordering ord = planarOrdering(N);
auto Rc1 = Ab1.eliminateSequential(ord); // R1*x-c1
auto Rc1 = *Ab1.eliminateSequential(ord); // R1*x-c1
VectorValues xbar = Rc1.optimize(); // xbar = inv(R1)*c1
// Create Subgraph-preconditioned system
@ -279,7 +279,7 @@ TEST(SubgraphPreconditioner, conjugateGradients) {
boost::tie(Ab1, Ab2) = splitOffPlanarTree(N, Ab);
// Eliminate the spanning tree to build a prior
GaussianBayesNet Rc1 = Ab1.eliminateSequential(); // R1*x-c1
GaussianBayesNet Rc1 = *Ab1.eliminateSequential(); // R1*x-c1
VectorValues xbar = Rc1.optimize(); // xbar = inv(R1)*c1
// Create Subgraph-preconditioned system

2
tests/testSubgraphSolver.cpp
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@ -123,7 +123,7 @@ TEST( SubgraphSolver, constructor3 )
std::tie(Ab1, Ab2) = example::splitOffPlanarTree(N, Ab);
// The caller solves |A1*x-b1|^2 == |R1*x-c1|^2, where R1 is square UT
auto Rc1 = Ab1.eliminateSequential();
auto Rc1 = *Ab1.eliminateSequential();
// The third constructor allows the caller to pass an already solved preconditioner Rc1_
// as a Bayes net, in addition to the "loop closing constraints" Ab2, as before