move normalization constant to base class

gtsam/inference/Conditional-inst.h

@@ -56,4 +56,27 @@ double Conditional<FACTOR, DERIVEDCONDITIONAL>::evaluate(
     const HybridValues& c) const {
   throw std::runtime_error("Conditional::evaluate is not implemented");
 }
+
+/* ************************************************************************* */
+template <class FACTOR, class DERIVEDCONDITIONAL>
+double Conditional<FACTOR, DERIVEDCONDITIONAL>::normalizationConstant() const {
+  return std::exp(logNormalizationConstant());
+}
+
+/* ************************************************************************* */
+template <class FACTOR, class DERIVEDCONDITIONAL>
+bool Conditional<FACTOR, DERIVEDCONDITIONAL>::checkInvariants(
+    const HybridValues& values) const {
+  const double probability = evaluate(values);
+  if (probability < 0.0 || probability > 1.0)
+    return false;  // probability is not in [0,1]
+  const double logProb = logProbability(values);
+  if (std::abs(probability - std::exp(logProb)) > 1e-9)
+    return false;  // logProb is not consistent with probability
+  const double expected =
+      this->logNormalizationConstant() - this->error(values);
+  if (std::abs(logProb - expected) > 1e-9)
+    return false;  // logProb is not consistent with error
+}
+
 }  // namespace gtsam

gtsam/inference/Conditional.h

@@ -141,6 +141,15 @@ namespace gtsam {
       return evaluate(x);
     }
 
+    /**
+     * By default, log normalization constant = 0.0.
+     * Override if this depends on the parameters.
+     */
+    virtual double logNormalizationConstant() const;
+
+    /** Non-virtual, exponentiate logNormalizationConstant. */
+    double normalizationConstant() const;
+
     /// @}
     /// @name Advanced Interface
     /// @{
@@ -172,7 +181,16 @@ namespace gtsam {
     /** Mutable iterator pointing past the last parent key. */
     typename FACTOR::iterator endParents() { return asFactor().end(); }
 
+    /** Check that the invariants hold for derived class at a given point. */
+    bool checkInvariants(const HybridValues& values) const;
+
+    /// @}
+
   private:
+
+    /// @name Serialization
+    /// @{
+
     // Cast to factor type (non-const) (casts down to derived conditional type, then up to factor type)
     FACTOR& asFactor() { return static_cast<FACTOR&>(static_cast<DERIVEDCONDITIONAL&>(*this)); }
 

gtsam/linear/GaussianConditional.h

@@ -136,14 +136,7 @@ namespace gtsam {
      * normalization constant = 1.0 / sqrt((2*pi)^n*det(Sigma))
      * log = - 0.5 * n*log(2*pi) - 0.5 * log det(Sigma)
      */
-    double logNormalizationConstant() const;
+    double logNormalizationConstant() const override;
-
-    /**
-     * normalization constant = 1.0 / sqrt((2*pi)^n*det(Sigma))
-     */
-    inline double normalizationConstant() const {
-      return exp(logNormalizationConstant());
-    }
 
     /**
      * Calculate log-probability log(evaluate(x)) for given values `x`: