From 3dbb16a114c56be87cf06c3a6c6603a9abce357e Mon Sep 17 00:00:00 2001
From: Varun Agrawal <varagrawal@gmail.com>
Date: Thu, 5 Sep 2024 15:51:37 -0400
Subject: [PATCH] remove const ref push_back

---
 gtsam/hybrid/HybridBayesNet.h                 | 20 +------------------
 .../tests/testGaussianMixtureFactor.cpp       | 11 +++++++---
 2 files changed, 9 insertions(+), 22 deletions(-)

diff --git a/gtsam/hybrid/HybridBayesNet.h b/gtsam/hybrid/HybridBayesNet.h
index 891be75da..f745b94c9 100644
--- a/gtsam/hybrid/HybridBayesNet.h
+++ b/gtsam/hybrid/HybridBayesNet.h
@@ -111,28 +111,10 @@ class GTSAM_EXPORT HybridBayesNet : public BayesNet<HybridConditional> {
    * @return IsSharedPtr<CONDITIONAL>
    */
   template <class CONDITIONAL>
-  IsSharedPtr<CONDITIONAL> push_back(const CONDITIONAL &conditional) {
+  void push_back(std::shared_ptr<CONDITIONAL> conditional) {
     factors_.push_back(std::make_shared<HybridConditional>(conditional));
   }
 
-  /**
-   * @brief Add a conditional to the Bayes net.
-   * Implicitly convert to a HybridConditional.
-   *
-   * E.g.
-   * hbn.push_back(DiscreteConditional(m, "1/1"));
-   * hbn.push_back(GaussianConditional(X(0), Vector1(0.0), I_1x1));
-   *
-   * @tparam CONDITIONAL Type of conditional. This is const ref version.
-   * @param conditional The conditional as a const reference.
-   * @return IsSharedPtr<CONDITIONAL>
-   */
-  template <class CONDITIONAL>
-  IsNotSharedPtr<CONDITIONAL> push_back(const CONDITIONAL &conditional) {
-    auto cond_shared_ptr = std::make_shared<CONDITIONAL>(conditional);
-    push_back(cond_shared_ptr);
-  }
-
   /**
    * Preferred: add a conditional directly using a pointer.
    *
diff --git a/gtsam/hybrid/tests/testGaussianMixtureFactor.cpp b/gtsam/hybrid/tests/testGaussianMixtureFactor.cpp
index 99814229e..20fb3266e 100644
--- a/gtsam/hybrid/tests/testGaussianMixtureFactor.cpp
+++ b/gtsam/hybrid/tests/testGaussianMixtureFactor.cpp
@@ -228,12 +228,17 @@ static HybridBayesNet GetGaussianMixtureModel(double mu0, double mu1,
   auto c0 = make_shared<GaussianConditional>(z, Vector1(mu0), I_1x1, model0),
        c1 = make_shared<GaussianConditional>(z, Vector1(mu1), I_1x1, model1);
 
-  GaussianMixture gm({z}, {}, {m}, {c0, c1});
-  DiscreteConditional mixing(m, "0.5/0.5");
+  KeyVector frontalKeys{z}, continuousParents;
+  DiscreteKeys discreteParents{m};
+  std::vector<GaussianConditional::shared_ptr> conditionals = {c0, c1};
+  auto gm = make_shared<GaussianMixture>(frontalKeys, continuousParents,
+                                         discreteParents, conditionals);
 
   HybridBayesNet hbn;
   hbn.push_back(gm);
-  hbn.push_back(mixing);
+
+  auto mixing = make_shared<DiscreteConditional>(m, "0.5/0.5");
+  hbn.emplace_shared<HybridConditional>(mixing);
 
   return hbn;
 }