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fix to remove leftover boost

release/4.3a0
Varun Agrawal 2023-02-13 20:00:09 -05:00
parent e36440b08d
commit 04daae036e
1 changed files with 8 additions and 5 deletions
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13
gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp
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@ -348,7 +348,8 @@ TEST(HybridGaussianFactorGraph, Switching) {
// GTSAM_PRINT(*hfg); // GTSAM_PRINT(*hfg);
// GTSAM_PRINT(ordering_full); // GTSAM_PRINT(ordering_full);
const auto [hbt, remaining] = hfg->eliminatePartialMultifrontal(ordering_full); const auto [hbt, remaining] =
hfg->eliminatePartialMultifrontal(ordering_full);
// 12 cliques in the bayes tree and 0 remaining variables to eliminate. // 12 cliques in the bayes tree and 0 remaining variables to eliminate.
EXPECT_LONGS_EQUAL(12, hbt->size()); EXPECT_LONGS_EQUAL(12, hbt->size());
@ -401,7 +402,8 @@ TEST(HybridGaussianFactorGraph, SwitchingISAM) {
} }
auto ordering_full = Ordering(ordering); auto ordering_full = Ordering(ordering);
const auto [hbt, remaining] = hfg->eliminatePartialMultifrontal(ordering_full); const auto [hbt, remaining] =
hfg->eliminatePartialMultifrontal(ordering_full);
auto new_fg = makeSwitchingChain(12); auto new_fg = makeSwitchingChain(12);
auto isam = HybridGaussianISAM(*hbt); auto isam = HybridGaussianISAM(*hbt);
@ -470,7 +472,8 @@ TEST(HybridGaussianFactorGraph, SwitchingTwoVar) {
ordering_partial.emplace_back(X(i)); ordering_partial.emplace_back(X(i));
ordering_partial.emplace_back(Y(i)); ordering_partial.emplace_back(Y(i));
} }
const auto [hbn, remaining] = hfg->eliminatePartialSequential(ordering_partial); const auto [hbn, remaining] =
hfg->eliminatePartialSequential(ordering_partial);
EXPECT_LONGS_EQUAL(14, hbn->size()); EXPECT_LONGS_EQUAL(14, hbn->size());
EXPECT_LONGS_EQUAL(11, remaining->size()); EXPECT_LONGS_EQUAL(11, remaining->size());
@ -747,9 +750,9 @@ TEST(HybridGaussianFactorGraph, EliminateTiny1Swapped) {
// Create Gaussian mixture on X(0). // Create Gaussian mixture on X(0).
// regression, but mean checked to be 5.0 in both cases: // regression, but mean checked to be 5.0 in both cases:
const auto conditional0 = boost::make_shared<GaussianConditional>( const auto conditional0 = std::make_shared<GaussianConditional>(
X(0), Vector1(10.1379), I_1x1 * 2.02759), X(0), Vector1(10.1379), I_1x1 * 2.02759),
conditional1 = boost::make_shared<GaussianConditional>( conditional1 = std::make_shared<GaussianConditional>(
X(0), Vector1(14.1421), I_1x1 * 2.82843); X(0), Vector1(14.1421), I_1x1 * 2.82843);
expectedBayesNet.emplace_back( expectedBayesNet.emplace_back(
new GaussianMixture({X(0)}, {}, {mode}, {conditional0, conditional1})); new GaussianMixture({X(0)}, {}, {mode}, {conditional0, conditional1}));