Revert "turns out we can merge DiscreteConditional and DiscreteLookupTable"

This reverts commit f6449c0ad8.

gtsam/discrete/DiscreteConditional.cpp

@@ -236,10 +236,6 @@ DecisionTreeFactor::shared_ptr DiscreteConditional::likelihood(
 
 /* ************************************************************************** */
 size_t DiscreteConditional::argmax(const DiscreteValues& parentsValues) const {
-  ADT pFS = choose(parentsValues, true);  // P(F|S=parentsValues)
-
-  // Then, find the max over all remaining
-  // TODO(Duy): only works for one key now, seems horribly slow this way
   size_t maxValue = 0;
   double maxP = 0;
   DiscreteValues values = parentsValues;
@@ -258,33 +254,6 @@ size_t DiscreteConditional::argmax(const DiscreteValues& parentsValues) const {
   return maxValue;
 }
 
-/* ************************************************************************** */
-void DiscreteConditional::argmaxInPlace(DiscreteValues* values) const {
-  ADT pFS = choose(*values, true);  // P(F|S=parentsValues)
-
-  // Initialize
-  DiscreteValues mpe;
-  double maxP = 0;
-
-  // Get all Possible Configurations
-  const auto allPosbValues = frontalAssignments();
-
-  // Find the maximum
-  for (const auto& frontalVals : allPosbValues) {
-    double pValueS = pFS(frontalVals);  // P(F=value|S=parentsValues)
-    // Update maximum solution if better
-    if (pValueS > maxP) {
-      maxP = pValueS;
-      mpe = frontalVals;
-    }
-  }
-
-  // set values (inPlace) to maximum
-  for (Key j : frontals()) {
-    (*values)[j] = mpe[j];
-  }
-}
-
 /* ************************************************************************** */
 void DiscreteConditional::sampleInPlace(DiscreteValues* values) const {
   assert(nrFrontals() == 1);

gtsam/discrete/DiscreteConditional.h

@@ -18,9 +18,9 @@
 
 #pragma once
 
+#include <gtsam/inference/Conditional-inst.h>
 #include <gtsam/discrete/DecisionTreeFactor.h>
 #include <gtsam/discrete/Signature.h>
-#include <gtsam/inference/Conditional-inst.h>
 
 #include <memory>
 #include <string>
@@ -159,7 +159,9 @@ class GTSAM_EXPORT DiscreteConditional
   /// @{
 
   /// Log-probability is just -error(x).
-  double logProbability(const DiscreteValues& x) const { return -error(x); }
+  double logProbability(const DiscreteValues& x) const  {
+    return -error(x);
+  }
 
   /// print index signature only
   void printSignature(
@@ -212,18 +214,11 @@ class GTSAM_EXPORT DiscreteConditional
   size_t sample() const;
 
   /**
-   * @brief Return assignment for single frontal variable that maximizes value.
+   * @brief Return assignment that maximizes distribution.
-   * @param parentsValues Known assignments for the parents.
+   * @return Optimal assignment (1 frontal variable).
-   * @return maximizing assignment for the frontal variable.
    */
   size_t argmax(const DiscreteValues& parentsValues = DiscreteValues()) const;
 
-  /**
-   * @brief Calculate assignment for frontal variables that maximizes value.
-   * @param (in/out) parentsValues Known assignments for the parents.
-   */
-  void argmaxInPlace(DiscreteValues* parentsValues) const;
-
   /// @}
   /// @name Advanced Interface
   /// @{
@@ -249,6 +244,7 @@ class GTSAM_EXPORT DiscreteConditional
   std::string html(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
                    const Names& names = {}) const override;
 
+
   /// @}
   /// @name HybridValues methods.
   /// @{

gtsam/discrete/DiscreteLookupDAG.cpp

@@ -29,20 +29,97 @@ using std::vector;
 
 namespace gtsam {
 
+/* ************************************************************************** */
+// TODO(dellaert): copy/paste from DiscreteConditional.cpp :-(
+void DiscreteLookupTable::print(const std::string& s,
+                                const KeyFormatter& formatter) const {
+  using std::cout;
+  using std::endl;
+
+  cout << s << " g( ";
+  for (const_iterator it = beginFrontals(); it != endFrontals(); ++it) {
+    cout << formatter(*it) << " ";
+  }
+  if (nrParents()) {
+    cout << "; ";
+    for (const_iterator it = beginParents(); it != endParents(); ++it) {
+      cout << formatter(*it) << " ";
+    }
+  }
+  cout << "):\n";
+  ADT::print("", formatter);
+  cout << endl;
+}
+
+/* ************************************************************************** */
+void DiscreteLookupTable::argmaxInPlace(DiscreteValues* values) const {
+  ADT pFS = choose(*values, true);  // P(F|S=parentsValues)
+
+  // Initialize
+  DiscreteValues mpe;
+  double maxP = 0;
+
+  // Get all Possible Configurations
+  const auto allPosbValues = frontalAssignments();
+
+  // Find the maximum
+  for (const auto& frontalVals : allPosbValues) {
+    double pValueS = pFS(frontalVals);  // P(F=value|S=parentsValues)
+    // Update maximum solution if better
+    if (pValueS > maxP) {
+      maxP = pValueS;
+      mpe = frontalVals;
+    }
+  }
+
+  // set values (inPlace) to maximum
+  for (Key j : frontals()) {
+    (*values)[j] = mpe[j];
+  }
+}
+
+/* ************************************************************************** */
+size_t DiscreteLookupTable::argmax(const DiscreteValues& parentsValues) const {
+  ADT pFS = choose(parentsValues, true);  // P(F|S=parentsValues)
+
+  // Then, find the max over all remaining
+  // TODO(Duy): only works for one key now, seems horribly slow this way
+  size_t mpe = 0;
+  double maxP = 0;
+  DiscreteValues frontals;
+  assert(nrFrontals() == 1);
+  Key j = (firstFrontalKey());
+  for (size_t value = 0; value < cardinality(j); value++) {
+    frontals[j] = value;
+    double pValueS = pFS(frontals);  // P(F=value|S=parentsValues)
+    // Update MPE solution if better
+    if (pValueS > maxP) {
+      maxP = pValueS;
+      mpe = value;
+    }
+  }
+  return mpe;
+}
+
 /* ************************************************************************** */
 DiscreteLookupDAG DiscreteLookupDAG::FromBayesNet(
     const DiscreteBayesNet& bayesNet) {
   DiscreteLookupDAG dag;
   for (auto&& conditional : bayesNet) {
-    dag.push_back(conditional);
+    if (auto lookupTable =
+            std::dynamic_pointer_cast<DiscreteLookupTable>(conditional)) {
+      dag.push_back(lookupTable);
+    } else {
+      throw std::runtime_error(
+          "DiscreteFactorGraph::maxProduct: Expected look up table.");
+    }
   }
   return dag;
 }
 
 DiscreteValues DiscreteLookupDAG::argmax(DiscreteValues result) const {
   // Argmax each node in turn in topological sort order (parents first).
-  for (auto it = std::make_reverse_iterator(end());
+  for (auto it = std::make_reverse_iterator(end()); it != std::make_reverse_iterator(begin()); ++it) {
-       it != std::make_reverse_iterator(begin()); ++it) {
     // dereference to get the sharedFactor to the lookup table
     (*it)->argmaxInPlace(&result);
   }

gtsam/discrete/DiscreteLookupDAG.h

@@ -37,9 +37,41 @@ class DiscreteBayesNet;
  * Inherits from discrete conditional for convenience, but is not normalized.
  * Is used in the max-product algorithm.
  */
-// Typedef for backwards compatibility
+class GTSAM_EXPORT DiscreteLookupTable : public DiscreteConditional {
-// TODO(Varun): Remove
+ public:
-using DiscreteLookupTable = DiscreteConditional;
+  using This = DiscreteLookupTable;
+  using shared_ptr = std::shared_ptr<This>;
+  using BaseConditional = Conditional<DecisionTreeFactor, This>;
+
+  /**
+   * @brief Construct a new Discrete Lookup Table object
+   *
+   * @param nFrontals number of frontal variables
+   * @param keys a sorted list of gtsam::Keys
+   * @param potentials the algebraic decision tree with lookup values
+   */
+  DiscreteLookupTable(size_t nFrontals, const DiscreteKeys& keys,
+                      const ADT& potentials)
+      : DiscreteConditional(nFrontals, keys, potentials) {}
+
+  /// GTSAM-style print
+  void print(
+      const std::string& s = "Discrete Lookup Table: ",
+      const KeyFormatter& formatter = DefaultKeyFormatter) const override;
+
+  /**
+   * @brief return assignment for single frontal variable that maximizes value.
+   * @param parentsValues Known assignments for the parents.
+   * @return maximizing assignment for the frontal variable.
+   */
+  size_t argmax(const DiscreteValues& parentsValues) const;
+
+  /**
+   * @brief Calculate assignment for frontal variables that maximizes value.
+   * @param (in/out) parentsValues Known assignments for the parents.
+   */
+  void argmaxInPlace(DiscreteValues* parentsValues) const;
+};
 
 /** A DAG made from lookup tables, as defined above. */
 class GTSAM_EXPORT DiscreteLookupDAG : public BayesNet<DiscreteLookupTable> {