diff --git a/examples/Hybrid_City10000.cpp b/examples/Hybrid_City10000.cpp
index 8ba495940..e963e75e2 100644
--- a/examples/Hybrid_City10000.cpp
+++ b/examples/Hybrid_City10000.cpp
@@ -119,7 +119,6 @@ void SmootherUpdate(HybridSmoother& smoother, HybridNonlinearFactorGraph& graph,
                     const Values& initial, size_t maxNrHypotheses,
                     Values* result) {
   HybridGaussianFactorGraph linearized = *graph.linearize(initial);
-  // std::cout << "index: " << index << std::endl;
   smoother.update(linearized, maxNrHypotheses);
   graph.resize(0);
   // HybridValues delta = smoother.hybridBayesNet().optimize();
diff --git a/examples/plot_city10000.m b/examples/plot_city10000.m
index 6d6a4637c..3c6b1cfdd 100644
--- a/examples/plot_city10000.m
+++ b/examples/plot_city10000.m
@@ -2,8 +2,10 @@ clear;
 
 gt = dlmread('Data/ISAM2_GT_city10000.txt');
 
+% Generate by running `make ISAM2_City10000.run`
 eh_poses = dlmread('../build/examples/ISAM2_city10000.txt');
 
+% Generate by running `make Hybrid_City10000.run`
 h_poses = dlmread('../build/examples/HybridISAM_city10000.txt');
 
 % Plot the same number of GT poses as estimated ones
@@ -16,13 +18,18 @@ figure(1)
 hold on;
 axis equal;
 axis([-65 65 -75 60])
+title('City10000 result with Hybrid Factor Graphs');
 plot(gt(:,1), gt(:,2), '--', 'LineWidth', 4, 'color', [0.1 0.7 0.1 0.5]);
-% hold off;
-
-% figure(2)
-% hold on;
-% axis equal;
-% axis([-65 65 -75 60])
-plot(eh_poses(:,1), eh_poses(:,2), '-', 'LineWidth', 2, 'color', [0.9 0.1 0. 0.4]);
 plot(h_poses(:,1), h_poses(:,2), '-', 'LineWidth', 2, 'color', [0.1 0.1 0.9 0.4]);
+legend('Ground truth', 'Hybrid Factor Graphs');
+hold off;
+
+figure(2)
+hold on;
+axis equal;
+axis([-65 65 -75 60])
+title('City10000 result with ISAM2');
+plot(gt(:,1), gt(:,2), '--', 'LineWidth', 4, 'color', [0.1 0.7 0.1 0.5]);
+plot(eh_poses(:,1), eh_poses(:,2), '-', 'LineWidth', 2, 'color', [0.9 0.1 0. 0.4]);
+legend('Ground truth', 'ISAM2');
 hold off;