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Remove const, use size_t everywhere.

release/4.3a0
Frank Dellaert 2023-01-10 09:58:29 -08:00
parent 6a035b88d7
commit 416cb65f6b
1 changed files with 4 additions and 4 deletions
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8
gtsam/hybrid/tests/TinyHybridExample.h
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@ -36,12 +36,12 @@ const DiscreteKey mode{M(0), 2};
* num_measurements is the number of measurements of the continuous variable x0. * num_measurements is the number of measurements of the continuous variable x0.
* If manyModes is true, then we introduce one mode per measurement. * If manyModes is true, then we introduce one mode per measurement.
*/ */
inline HybridBayesNet createHybridBayesNet(int num_measurements = 1, inline HybridBayesNet createHybridBayesNet(size_t num_measurements = 1,
bool manyModes = false) { bool manyModes = false) {
HybridBayesNet bayesNet; HybridBayesNet bayesNet;
// Create Gaussian mixture z_i = x0 + noise for each measurement. // Create Gaussian mixture z_i = x0 + noise for each measurement.
for (int i = 0; i < num_measurements; i++) { for (size_t i = 0; i < num_measurements; i++) {
const auto mode_i = manyModes ? DiscreteKey{M(i), 2} : mode; const auto mode_i = manyModes ? DiscreteKey{M(i), 2} : mode;
bayesNet.emplace_back( bayesNet.emplace_back(
new GaussianMixture({Z(i)}, {X(0)}, {mode_i}, new GaussianMixture({Z(i)}, {X(0)}, {mode_i},
@ -57,7 +57,7 @@ inline HybridBayesNet createHybridBayesNet(int num_measurements = 1,
// Add prior on mode. // Add prior on mode.
const size_t nrModes = manyModes ? num_measurements : 1; const size_t nrModes = manyModes ? num_measurements : 1;
for (const size_t i = 0; i < nrModes; i++) { for (size_t i = 0; i < nrModes; i++) {
bayesNet.emplace_back(new DiscreteConditional({M(i), 2}, "4/6")); bayesNet.emplace_back(new DiscreteConditional({M(i), 2}, "4/6"));
} }
return bayesNet; return bayesNet;
@ -70,7 +70,7 @@ inline HybridBayesNet createHybridBayesNet(int num_measurements = 1,
* the generative Bayes net model HybridBayesNet::Example(num_measurements) * the generative Bayes net model HybridBayesNet::Example(num_measurements)
*/ */
inline HybridGaussianFactorGraph createHybridGaussianFactorGraph( inline HybridGaussianFactorGraph createHybridGaussianFactorGraph(
int num_measurements = 1, size_t num_measurements = 1,
boost::optional<VectorValues> measurements = boost::none, boost::optional<VectorValues> measurements = boost::none,
bool manyModes = false) { bool manyModes = false) {
auto bayesNet = createHybridBayesNet(num_measurements, manyModes); auto bayesNet = createHybridBayesNet(num_measurements, manyModes);