replace error with errorTree

borglab · Jan 5, 2024 · 7ea1bbc · 7ea1bbc
1 parent ee5bda9
commit 7ea1bbc
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Showing 5 changed files with 13 additions and 12 deletions.
diff --git a/gtsam/hybrid/HybridBayesNet.cpp b/gtsam/hybrid/HybridBayesNet.cpp
@@ -282,15 +282,15 @@ HybridValues HybridBayesNet::sample() const {
 }
 
 /* ************************************************************************* */
-AlgebraicDecisionTree<Key> HybridBayesNet::error(
+AlgebraicDecisionTree<Key> HybridBayesNet::errorTree(
     const VectorValues &continuousValues) const {
   AlgebraicDecisionTree<Key> result(0.0);
 
   // Iterate over each conditional.
   for (auto &&conditional : *this) {
     if (auto gm = conditional->asMixture()) {
       // If conditional is hybrid, compute error for all assignments.
-      result = result + gm->error(continuousValues);
+      result = result + gm->errorTree(continuousValues);
 
     } else if (auto gc = conditional->asGaussian()) {
       // If continuous, get the error and add it to the result

diff --git a/gtsam/hybrid/HybridBayesNet.h b/gtsam/hybrid/HybridBayesNet.h
@@ -187,7 +187,8 @@ class GTSAM_EXPORT HybridBayesNet : public BayesNet<HybridConditional> {
    * @param continuousValues Continuous values at which to compute the error.
    * @return AlgebraicDecisionTree<Key>
    */
-  AlgebraicDecisionTree<Key> error(const VectorValues &continuousValues) const;
+  AlgebraicDecisionTree<Key> errorTree(
+      const VectorValues &continuousValues) const;
 
   /**
    * @brief Error method using HybridValues which returns specific error for

diff --git a/gtsam/hybrid/HybridGaussianFactorGraph.cpp b/gtsam/hybrid/HybridGaussianFactorGraph.cpp
@@ -99,7 +99,7 @@ void HybridGaussianFactorGraph::printErrors(
       } else {
         factor->print(ss.str(), keyFormatter);
         std::cout << "error = ";
-        gmf->error(values.continuous()).print("", keyFormatter);
+        gmf->errorTree(values.continuous()).print("", keyFormatter);
         std::cout << std::endl;
       }
     } else if (auto hc = std::dynamic_pointer_cast<HybridConditional>(factor)) {
@@ -113,12 +113,12 @@ void HybridGaussianFactorGraph::printErrors(
           std::cout << "error = " << hc->asGaussian()->error(values) << "\n";
         } else if (hc->isDiscrete()) {
           std::cout << "error = ";
-          hc->asDiscrete()->error().print("", keyFormatter);
+          hc->asDiscrete()->errorTree().print("", keyFormatter);
           std::cout << "\n";
         } else {
           // Is hybrid
           std::cout << "error = ";
-          hc->asMixture()->error(values.continuous()).print();
+          hc->asMixture()->errorTree(values.continuous()).print();
           std::cout << "\n";
         }
       }
@@ -141,7 +141,7 @@ void HybridGaussianFactorGraph::printErrors(
       } else {
         factor->print(ss.str(), keyFormatter);
         std::cout << "error = ";
-        df->error().print("", keyFormatter);
+        df->errorTree().print("", keyFormatter);
       }
 
     } else {

diff --git a/gtsam/hybrid/HybridNonlinearFactorGraph.cpp b/gtsam/hybrid/HybridNonlinearFactorGraph.cpp
@@ -66,7 +66,7 @@ void HybridNonlinearFactorGraph::printErrors(
       } else {
         factor->print(ss.str(), keyFormatter);
         std::cout << "error = ";
-        mf->error(values.nonlinear()).print("", keyFormatter);
+        mf->errorTree(values.nonlinear()).print("", keyFormatter);
         std::cout << std::endl;
       }
     } else if (auto gmf =
@@ -77,7 +77,7 @@ void HybridNonlinearFactorGraph::printErrors(
       } else {
         factor->print(ss.str(), keyFormatter);
         std::cout << "error = ";
-        gmf->error(values.continuous()).print("", keyFormatter);
+        gmf->errorTree(values.continuous()).print("", keyFormatter);
         std::cout << std::endl;
       }
     } else if (auto gm = std::dynamic_pointer_cast<GaussianMixture>(factor)) {
@@ -87,7 +87,7 @@ void HybridNonlinearFactorGraph::printErrors(
       } else {
         factor->print(ss.str(), keyFormatter);
         std::cout << "error = ";
-        gm->error(values.continuous()).print("", keyFormatter);
+        gm->errorTree(values.continuous()).print("", keyFormatter);
         std::cout << std::endl;
       }
     } else if (auto nf = std::dynamic_pointer_cast<NonlinearFactor>(factor)) {
@@ -121,7 +121,7 @@ void HybridNonlinearFactorGraph::printErrors(
       } else {
         factor->print(ss.str(), keyFormatter);
         std::cout << "error = ";
-        df->error().print("", keyFormatter);
+        df->errorTree().print("", keyFormatter);
         std::cout << std::endl;
       }
 

diff --git a/gtsam/hybrid/tests/testHybridBayesNet.cpp b/gtsam/hybrid/tests/testHybridBayesNet.cpp
@@ -182,7 +182,7 @@ TEST(HybridBayesNet, Error) {
   values.insert(X(1), Vector1(1));
 
   AlgebraicDecisionTree<Key> actual_errors =
-      bayesNet.error(values.continuous());
+      bayesNet.errorTree(values.continuous());
 
   // Regression.
   // Manually added all the error values from the 3 conditional types.