separate DiscreteMarginals into .h and .cpp

gtsam/discrete/DiscreteMarginals.cpp

@@ -0,0 +1,58 @@
+/* ----------------------------------------------------------------------------
+
+ * GTSAM Copyright 2010, Georgia Tech Research Corporation,
+ * Atlanta, Georgia 30332-0415
+ * All Rights Reserved
+ * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
+
+ * See LICENSE for the license information
+
+ * -------------------------------------------------------------------------- */
+
+/**
+ * @file DiscreteMarginals.cpp
+ * @brief A class for computing marginals in a DiscreteFactorGraph
+ * @author Abhijit Kundu
+ * @author Richard Roberts
+ * @author Varun Agrawal
+ * @author Frank Dellaert
+ * @date June 4, 2012
+ */
+
+#pragma once
+
+#include <gtsam/base/Vector.h>
+#include <gtsam/discrete/DiscreteBayesTree.h>
+#include <gtsam/discrete/DiscreteFactorGraph.h>
+
+namespace gtsam {
+
+/* ************************************************************************* */
+DiscreteMarginals::DiscreteMarginals(const DiscreteFactorGraph& graph) {
+  bayesTree_ = graph.eliminateMultifrontal();
+}
+
+/* ************************************************************************* */
+DiscreteFactor::shared_ptr DiscreteMarginals::operator()(Key variable) const {
+  // Compute marginal
+  DiscreteFactor::shared_ptr marginalFactor =
+      bayesTree_->marginalFactor(variable, &EliminateDiscrete);
+  return marginalFactor;
+}
+
+/* ************************************************************************* */
+Vector DiscreteMarginals::marginalProbabilities(const DiscreteKey& key) const {
+  // Compute marginal
+  DiscreteFactor::shared_ptr marginalFactor = this->operator()(key.first);
+
+  // Create result
+  Vector vResult(key.second);
+  for (size_t state = 0; state < key.second; ++state) {
+    DiscreteValues values;
+    values[key.first] = state;
+    vResult(state) = (*marginalFactor)(values);
+  }
+  return vResult;
+}
+
+} /* namespace gtsam */

gtsam/discrete/DiscreteMarginals.h

@@ -14,6 +14,7 @@
  * @brief A class for computing marginals in a DiscreteFactorGraph
  * @author Abhijit Kundu
  * @author Richard Roberts
+ * @author Varun Agrawal
  * @author Frank Dellaert
  * @date June 4, 2012
  */
@@ -38,38 +39,19 @@ class DiscreteMarginals {
   DiscreteMarginals() {}
 
   /** Construct a marginals class.
-   * @param graph The factor graph defining the full joint 
+   * @param graph The factor graph defining the full joint
    * distribution on all variables.
    */
-  DiscreteMarginals(const DiscreteFactorGraph& graph) {
-    bayesTree_ = graph.eliminateMultifrontal();
-  }
+  DiscreteMarginals(const DiscreteFactorGraph& graph);
 
   /** Compute the marginal of a single variable */
-  DiscreteFactor::shared_ptr operator()(Key variable) const {
-    // Compute marginal
-    DiscreteFactor::shared_ptr marginalFactor =
-        bayesTree_->marginalFactor(variable, &EliminateDiscrete);
-    return marginalFactor;
-  }
+  DiscreteFactor::shared_ptr operator()(Key variable) const;
 
   /** Compute the marginal of a single variable
    *   @param key DiscreteKey of the Variable
    *   @return Vector of marginal probabilities
    */
-  Vector marginalProbabilities(const DiscreteKey& key) const {
-    // Compute marginal
-    DiscreteFactor::shared_ptr marginalFactor = this->operator()(key.first);
-
-    // Create result
-    Vector vResult(key.second);
-    for (size_t state = 0; state < key.second; ++state) {
-      DiscreteValues values;
-      values[key.first] = state;
-      vResult(state) = (*marginalFactor)(values);
-    }
-    return vResult;
-  }
+  Vector marginalProbabilities(const DiscreteKey& key) const;
 };
 
 } /* namespace gtsam */