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				|  | @ -76,7 +76,7 @@ GTSAM_CONCEPT_TESTABLE_INST(CrazyDecisionTree) | |||
| /* ************************************************************************** */ | ||||
| 
 | ||||
| // Create a decision stump one one variable 'a' with values 10 and 20.
 | ||||
| TEST(DecisionTree, constructor) { | ||||
| TEST(DecisionTree, Constructor) { | ||||
|   DecisionTree<char, int> tree('a', 10, 20); | ||||
| 
 | ||||
|   // Evaluate the tree on an assignment to the variable.
 | ||||
|  | @ -129,7 +129,7 @@ struct Ring { | |||
| 
 | ||||
| /* ************************************************************************** */ | ||||
| // Check that creating decision trees respects key order.
 | ||||
| TEST(DecisionTree, constructor_order) { | ||||
| TEST(DecisionTree, ConstructorOrder) { | ||||
|   // Create labels
 | ||||
|   string A("A"), B("B"); | ||||
| 
 | ||||
|  | @ -159,7 +159,7 @@ TEST(DecisionTree, constructor_order) { | |||
| 
 | ||||
| /* ************************************************************************** */ | ||||
| // test DT
 | ||||
| TEST(DecisionTree, example) { | ||||
| TEST(DecisionTree, Example) { | ||||
|   // Create labels
 | ||||
|   string A("A"), B("B"), C("C"); | ||||
| 
 | ||||
|  |  | |||
|  | @ -28,7 +28,7 @@ using namespace std; | |||
| using namespace gtsam; | ||||
| 
 | ||||
| /* ************************************************************************* */ | ||||
| TEST(DecisionTreeFactor, constructors_match) { | ||||
| TEST(DecisionTreeFactor, ConstructorsMatch) { | ||||
|   // Declare two keys
 | ||||
|   DiscreteKey X(0, 2), Y(1, 3); | ||||
| 
 | ||||
|  |  | |||
|  | @ -140,7 +140,7 @@ namespace gtsam { | |||
|     /** Access the conditional */ | ||||
|     const sharedConditional& conditional() const { return conditional_; } | ||||
| 
 | ||||
|     /// Is this the root of a Bayes tree? 
 | ||||
|     /// Return true if this clique is the root of a Bayes tree. 
 | ||||
|     inline bool isRoot() const { return parent_.expired(); } | ||||
| 
 | ||||
|     /// Return the number of children.
 | ||||
|  |  | |||
|  | @ -20,7 +20,7 @@ from gtsam.utils.test_case import GtsamTestCase | |||
| import gtsam | ||||
| from gtsam import (DiscreteBayesNet, DiscreteBayesTreeClique, | ||||
|                    DiscreteConditional, DiscreteFactorGraph, | ||||
|                    DiscreteKeys, DiscreteValues, Ordering) | ||||
|                    DiscreteValues, Ordering) | ||||
| 
 | ||||
| 
 | ||||
| class TestDiscreteBayesNet(GtsamTestCase): | ||||
|  | @ -32,7 +32,7 @@ class TestDiscreteBayesNet(GtsamTestCase): | |||
|         # Define DiscreteKey pairs. | ||||
|         keys = [(j, 2) for j in range(15)] | ||||
| 
 | ||||
|         # Create thin-tree Bayesnet. | ||||
|         # Create thin-tree Bayes net. | ||||
|         bayesNet = DiscreteBayesNet() | ||||
| 
 | ||||
|         bayesNet.add(keys[0], [keys[8], keys[12]], "2/3 1/4 3/2 4/1") | ||||
|  | @ -121,7 +121,7 @@ class TestDiscreteBayesNet(GtsamTestCase): | |||
|         graph.add([x2, a2, x3], table) | ||||
| 
 | ||||
|         # Eliminate for MPE (maximum probable explanation). | ||||
|         ordering = Ordering([A(2), X(3), X(1), A(1), X(2)]) | ||||
|         ordering = Ordering(keys=[A(2), X(3), X(1), A(1), X(2)]) | ||||
|         lookup = graph.eliminateMultifrontal(ordering, gtsam.EliminateForMPE) | ||||
| 
 | ||||
|         # Check that the lookup table is correct | ||||
|  |  | |||
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