From 27e786aae2b88162f3d88de2087468a8d5fb8943 Mon Sep 17 00:00:00 2001
From: Ankur Roy Chowdhury <ankur.roy@verdantrobotics.com>
Date: Thu, 2 Mar 2023 13:05:07 -0800
Subject: [PATCH] A few minor fixes to allow compiling 'boost-free' gtsam
 without compiling 'gtsam_unstable'.

---
 CMakeLists.txt                    | 5 +++--
 gtsam/base/Matrix.cpp             | 1 +
 gtsam/discrete/DecisionTree-inl.h | 1 +
 gtsam/hybrid/HybridSmoother.cpp   | 4 +++-
 4 files changed, 8 insertions(+), 3 deletions(-)

diff --git a/CMakeLists.txt b/CMakeLists.txt
index ebe27443a..eeaf05772 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -95,8 +95,6 @@ add_subdirectory(gtsam)
 # Build Tests
 add_subdirectory(tests)
 
-# Build examples
-add_subdirectory(examples)
 
 # Build timing
 add_subdirectory(timing)
@@ -104,6 +102,9 @@ add_subdirectory(timing)
 # Build gtsam_unstable
 if (GTSAM_BUILD_UNSTABLE)
   add_subdirectory(gtsam_unstable)
+  
+  # Build examples (Note: 'examples' require `gtsam_unstable` be built since it links against it.)
+  add_subdirectory(examples)
 endif()
 
 # This is the new wrapper
diff --git a/gtsam/base/Matrix.cpp b/gtsam/base/Matrix.cpp
index 3c6e64dbc..247c53cce 100644
--- a/gtsam/base/Matrix.cpp
+++ b/gtsam/base/Matrix.cpp
@@ -30,6 +30,7 @@
 #include <fstream>
 #include <limits>
 #include <iostream>
+#include <iterator>
 
 using namespace std;
 
diff --git a/gtsam/discrete/DecisionTree-inl.h b/gtsam/discrete/DecisionTree-inl.h
index cfaa806b8..9d618dea0 100644
--- a/gtsam/discrete/DecisionTree-inl.h
+++ b/gtsam/discrete/DecisionTree-inl.h
@@ -33,6 +33,7 @@
 #include <vector>
 #include <optional>
 #include <cassert>
+#include <iterator>
 
 namespace gtsam {
 
diff --git a/gtsam/hybrid/HybridSmoother.cpp b/gtsam/hybrid/HybridSmoother.cpp
index 549c71714..b06e4de4e 100644
--- a/gtsam/hybrid/HybridSmoother.cpp
+++ b/gtsam/hybrid/HybridSmoother.cpp
@@ -27,7 +27,9 @@ namespace gtsam {
 Ordering HybridSmoother::getOrdering(
     const HybridGaussianFactorGraph &newFactors) {
   HybridGaussianFactorGraph factors(hybridBayesNet());
-  factors += newFactors;
+  for(auto& factor: newFactors){
+    factors.push_back(factor);
+  }
   // Get all the discrete keys from the factors
   KeySet allDiscrete = factors.discreteKeySet();