Get rid of (redundant and undocumented) FromFactors named constructor.

gtsam/hybrid/GaussianMixtureFactor.cpp

@@ -38,15 +38,6 @@ bool GaussianMixtureFactor::equals(const HybridFactor &lf, double tol) const {
   return e != nullptr && Base::equals(*e, tol);
 }
 
-/* *******************************************************************************/
-GaussianMixtureFactor GaussianMixtureFactor::FromFactors(
-    const KeyVector &continuousKeys, const DiscreteKeys &discreteKeys,
-    const std::vector<GaussianFactor::shared_ptr> &factors) {
-  Factors dt(discreteKeys, factors);
-
-  return GaussianMixtureFactor(continuousKeys, discreteKeys, dt);
-}
-
 /* *******************************************************************************/
 void GaussianMixtureFactor::print(const std::string &s,
                                   const KeyFormatter &formatter) const {

gtsam/hybrid/GaussianMixtureFactor.h

@@ -93,19 +93,16 @@ class GTSAM_EXPORT GaussianMixtureFactor : public HybridFactor {
    * @brief Construct a new GaussianMixtureFactor object using a vector of
    * GaussianFactor shared pointers.
    *
-   * @param keys Vector of keys for continuous factors.
+   * @param continuousKeys Vector of keys for continuous factors.
    * @param discreteKeys Vector of discrete keys.
    * @param factors Vector of gaussian factor shared pointers.
    */
-  GaussianMixtureFactor(const KeyVector &keys, const DiscreteKeys &discreteKeys,
+  GaussianMixtureFactor(const KeyVector &continuousKeys,
+                        const DiscreteKeys &discreteKeys,
                         const std::vector<GaussianFactor::shared_ptr> &factors)
-      : GaussianMixtureFactor(keys, discreteKeys,
+      : GaussianMixtureFactor(continuousKeys, discreteKeys,
                               Factors(discreteKeys, factors)) {}
 
-  static This FromFactors(
-      const KeyVector &continuousKeys, const DiscreteKeys &discreteKeys,
-      const std::vector<GaussianFactor::shared_ptr> &factors);
-
   /// @}
   /// @name Testable
   /// @{

gtsam/hybrid/hybrid.i

@@ -54,7 +54,7 @@ virtual class HybridDiscreteFactor {
 
 #include <gtsam/hybrid/GaussianMixtureFactor.h>
 class GaussianMixtureFactor : gtsam::HybridFactor {
-  static GaussianMixtureFactor FromFactors(
+  GaussianMixtureFactor(
       const gtsam::KeyVector& continuousKeys,
       const gtsam::DiscreteKeys& discreteKeys,
       const std::vector<gtsam::GaussianFactor::shared_ptr>& factorsList);

gtsam/hybrid/tests/Switching.h

@@ -57,7 +57,7 @@ inline HybridGaussianFactorGraph::shared_ptr makeSwitchingChain(
 
   // keyFunc(1) to keyFunc(n+1)
   for (size_t t = 1; t < n; t++) {
-    hfg.add(GaussianMixtureFactor::FromFactors(
+    hfg.add(GaussianMixtureFactor(
         {keyFunc(t), keyFunc(t + 1)}, {{dKeyFunc(t), 2}},
         {boost::make_shared<JacobianFactor>(keyFunc(t), I_3x3, keyFunc(t + 1),
                                             I_3x3, Z_3x1),

gtsam/hybrid/tests/testGaussianMixture.cpp

@@ -20,6 +20,8 @@
 
 #include <gtsam/discrete/DiscreteValues.h>
 #include <gtsam/hybrid/GaussianMixture.h>
+#include <gtsam/hybrid/GaussianMixtureFactor.h>
+#include <gtsam/hybrid/HybridValues.h>
 #include <gtsam/inference/Symbol.h>
 #include <gtsam/linear/GaussianConditional.h>
 
@@ -33,6 +35,7 @@ using namespace gtsam;
 using noiseModel::Isotropic;
 using symbol_shorthand::M;
 using symbol_shorthand::X;
+using symbol_shorthand::Z;
 
 /* ************************************************************************* */
 /* Check construction of GaussianMixture P(x1 | x2, m1) as well as accessing a
@@ -127,7 +130,43 @@ TEST(GaussianMixture, Error) {
   assignment[M(1)] = 0;
   EXPECT_DOUBLES_EQUAL(0.5, mixture.error(values, assignment), 1e-8);
   assignment[M(1)] = 1;
-  EXPECT_DOUBLES_EQUAL(4.3252595155709335, mixture.error(values, assignment), 1e-8);
+  EXPECT_DOUBLES_EQUAL(4.3252595155709335, mixture.error(values, assignment),
+                       1e-8);
+}
+
+/* ************************************************************************* */
+// Create a likelihood factor for a Gaussian mixture, return a Mixture factor on
+// the parents.
+GaussianMixtureFactor::shared_ptr likelihood(const HybridValues& values) {
+  GaussianMixtureFactor::shared_ptr factor;
+  return factor;
+}
+
+/// Check that likelihood returns a mixture factor on the parents.
+TEST(GaussianMixture, Likelihood) {
+  // Create mode key: 0 is low-noise, 1 is high-noise.
+  Key modeKey = M(0);
+  DiscreteKey mode(modeKey, 2);
+
+  // Create Gaussian mixture Z(0) = X(0) + noise.
+  // TODO(dellaert): making copies below is not ideal !
+  Matrix1 I = Matrix1::Identity();
+  const auto conditional0 = boost::make_shared<GaussianConditional>(
+      GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 0.5));
+  const auto conditional1 = boost::make_shared<GaussianConditional>(
+      GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 3));
+  const auto gm = GaussianMixture::FromConditionals(
+      {Z(0)}, {X(0)}, {mode}, {conditional0, conditional1});
+
+  // Call the likelihood function:
+  VectorValues measurements;
+  measurements.insert(Z(0), Vector1(0));
+  HybridValues values(DiscreteValues(), measurements);
+  const auto factor = likelihood(values);
+
+  // Check that the factor is a mixture factor on the parents.
+  const GaussianMixtureFactor expected = GaussianMixtureFactor();
+  EXPECT(assert_equal(*factor, expected));
 }
 
 /* ************************************************************************* */

gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp

@@ -176,7 +176,7 @@ TEST(HybridGaussianFactorGraph, eliminateFullMultifrontalSimple) {
   hfg.add(JacobianFactor(X(0), I_3x3, Z_3x1));
   hfg.add(JacobianFactor(X(0), I_3x3, X(1), -I_3x3, Z_3x1));
 
-  hfg.add(GaussianMixtureFactor::FromFactors(
+  hfg.add(GaussianMixtureFactor(
       {X(1)}, {{M(1), 2}},
       {boost::make_shared<JacobianFactor>(X(1), I_3x3, Z_3x1),
        boost::make_shared<JacobianFactor>(X(1), I_3x3, Vector3::Ones())}));
@@ -235,7 +235,7 @@ TEST(HybridGaussianFactorGraph, eliminateFullMultifrontalTwoClique) {
   hfg.add(JacobianFactor(X(1), I_3x3, X(2), -I_3x3, Z_3x1));
 
   {
-    hfg.add(GaussianMixtureFactor::FromFactors(
+    hfg.add(GaussianMixtureFactor(
         {X(0)}, {{M(0), 2}},
         {boost::make_shared<JacobianFactor>(X(0), I_3x3, Z_3x1),
          boost::make_shared<JacobianFactor>(X(0), I_3x3, Vector3::Ones())}));