From 9e7fcc81cda1ad5e129fe0c6ff59ef375dd74a9a Mon Sep 17 00:00:00 2001 From: Varun Agrawal Date: Tue, 3 Jan 2023 05:18:13 -0500 Subject: [PATCH] make header functions as inline --- gtsam/hybrid/tests/TinyHybridExample.h | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/gtsam/hybrid/tests/TinyHybridExample.h b/gtsam/hybrid/tests/TinyHybridExample.h index 1df7e3a31..ba04263f8 100644 --- a/gtsam/hybrid/tests/TinyHybridExample.h +++ b/gtsam/hybrid/tests/TinyHybridExample.h @@ -34,7 +34,7 @@ const DiscreteKey mode{M(0), 2}; * Create a tiny two variable hybrid model which represents * the generative probability P(z,x,mode) = P(z|x,mode)P(x)P(mode). */ -HybridBayesNet createHybridBayesNet(int num_measurements = 1) { +inline HybridBayesNet createHybridBayesNet(int num_measurements = 1) { HybridBayesNet bayesNet; // Create Gaussian mixture z_i = x0 + noise for each measurement. @@ -61,8 +61,8 @@ HybridBayesNet createHybridBayesNet(int num_measurements = 1) { /** * Convert a hybrid Bayes net to a hybrid Gaussian factor graph. */ -HybridGaussianFactorGraph convertBayesNet(const HybridBayesNet& bayesNet, - const VectorValues& measurements) { +inline HybridGaussianFactorGraph convertBayesNet( + const HybridBayesNet& bayesNet, const VectorValues& measurements) { HybridGaussianFactorGraph fg; int num_measurements = bayesNet.size() - 2; for (int i = 0; i < num_measurements; i++) { @@ -81,7 +81,7 @@ HybridGaussianFactorGraph convertBayesNet(const HybridBayesNet& bayesNet, * continuous variable x0. If no measurements are given, they are sampled from * the generative Bayes net model HybridBayesNet::Example(num_measurements) */ -HybridGaussianFactorGraph createHybridGaussianFactorGraph( +inline HybridGaussianFactorGraph createHybridGaussianFactorGraph( int num_measurements = 1, boost::optional measurements = boost::none) { auto bayesNet = createHybridBayesNet(num_measurements);