From c6e9bfc8241c715f08afb8db9542acee79a9a7c0 Mon Sep 17 00:00:00 2001
From: Varun Agrawal <varagrawal@gmail.com>
Date: Tue, 31 Dec 2024 14:08:25 -0500
Subject: [PATCH] remove unused methods

---
 gtsam/discrete/DiscreteTableConditional.cpp | 34 ---------------
 gtsam/discrete/DiscreteTableConditional.h   | 47 +--------------------
 2 files changed, 2 insertions(+), 79 deletions(-)

diff --git a/gtsam/discrete/DiscreteTableConditional.cpp b/gtsam/discrete/DiscreteTableConditional.cpp
index f50d7fbebc..bcb65628a5 100644
--- a/gtsam/discrete/DiscreteTableConditional.cpp
+++ b/gtsam/discrete/DiscreteTableConditional.cpp
@@ -141,18 +141,6 @@ bool DiscreteTableConditional::equals(const DiscreteFactor& other,
   }
 }
 
-/* ************************************************************************** */
-TableFactor::shared_ptr DiscreteTableConditional::likelihood(
-    const DiscreteValues& frontalValues) const {
-  throw std::runtime_error("Likelihood not implemented");
-}
-
-/* ****************************************************************************/
-TableFactor::shared_ptr DiscreteTableConditional::likelihood(
-    size_t frontal) const {
-  throw std::runtime_error("Likelihood not implemented");
-}
-
 /* ****************************************************************************/
 DiscreteConditional::shared_ptr DiscreteTableConditional::max(
     const Ordering& keys) const {
@@ -180,26 +168,4 @@ DiscreteConditional::shared_ptr DiscreteTableConditional::prune(
       this->nrFrontals(), this->discreteKeys(), pruned.sparseTable());
 }
 
-/* ************************************************************************** */
-size_t DiscreteTableConditional::argmax(
-    const DiscreteValues& parentsValues) const {
-  // Initialize
-  size_t maxValue = 0;
-  double maxP = 0;
-  DiscreteValues values = parentsValues;
-
-  assert(nrFrontals() == 1);
-  Key j = firstFrontalKey();
-  for (size_t value = 0; value < cardinality(j); value++) {
-    values[j] = value;
-    double pValueS = (*this)(values);
-    // Update MPE solution if better
-    if (pValueS > maxP) {
-      maxP = pValueS;
-      maxValue = value;
-    }
-  }
-  return maxValue;
-}
-
 }  // namespace gtsam
diff --git a/gtsam/discrete/DiscreteTableConditional.h b/gtsam/discrete/DiscreteTableConditional.h
index f34cad2a30..7bd419f7b7 100644
--- a/gtsam/discrete/DiscreteTableConditional.h
+++ b/gtsam/discrete/DiscreteTableConditional.h
@@ -158,28 +158,8 @@ class GTSAM_EXPORT DiscreteTableConditional : public DiscreteConditional {
   /// @name Standard Interface
   /// @{
 
-  /// Log-probability is just -error(x).
-  double logProbability(const DiscreteValues& x) const { return -error(x); }
-
-  /// print index signature only
-  void printSignature(
-      const std::string& s = "Discrete Conditional: ",
-      const KeyFormatter& formatter = DefaultKeyFormatter) const {
-    static_cast<const BaseConditional*>(this)->print(s, formatter);
-  }
-
-  /** Convert to a likelihood factor by providing value before bar. */
-  TableFactor::shared_ptr likelihood(const DiscreteValues& frontalValues) const;
-
-  /** Single variable version of likelihood. */
-  TableFactor::shared_ptr likelihood(size_t frontal) const;
-
-  /**
-   * @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 = DiscreteValues()) const;
+  /// Return the underlying TableFactor
+  TableFactor table() const { return table_; }
 
   /**
    * @brief Create new conditional by maximizing over all
@@ -195,29 +175,6 @@ class GTSAM_EXPORT DiscreteTableConditional : public DiscreteConditional {
   /// @name Advanced Interface
   /// @{
 
-  /// Return all assignments for frontal variables.
-  std::vector<DiscreteValues> frontalAssignments() const;
-
-  /// Return all assignments for frontal *and* parent variables.
-  std::vector<DiscreteValues> allAssignments() const;
-
-  /// @}
-  /// @name HybridValues methods.
-  /// @{
-
-  using BaseConditional::operator();  ///< HybridValues version
-
-  /**
-   * Calculate log-probability log(evaluate(x)) for HybridValues `x`.
-   * This is actually just -error(x).
-   */
-  double logProbability(const HybridValues& x) const override {
-    return -error(x);
-  }
-
-  /// Return the underlying TableFactor
-  TableFactor table() const { return table_; }
-
   /// Evaluate the conditional given the values.
   virtual double evaluate(const Assignment<Key>& values) const override {
     return table_.evaluate(values);