likelihood

gtsam/discrete/DiscreteConditional.cpp

@@ -97,45 +97,90 @@ bool DiscreteConditional::equals(const DiscreteFactor& other,
 }
 
 /* ******************************************************************************** */
-Potentials::ADT DiscreteConditional::choose(
-    const DiscreteValues& parentsValues) const {
+static DiscreteConditional::ADT Choose(const DiscreteConditional& conditional,
+                                       const DiscreteValues& parentsValues) {
   // Get the big decision tree with all the levels, and then go down the
   // branches based on the value of the parent variables.
-  ADT pFS(*this);
+  DiscreteConditional::ADT adt(conditional);
   size_t value;
-  for (Key j : parents()) {
+  for (Key j : conditional.parents()) {
     try {
       value = parentsValues.at(j);
-      pFS = pFS.choose(j, value);  // ADT keeps getting smaller.
+      adt = adt.choose(j, value);  // ADT keeps getting smaller.
     } catch (exception&) {
-      cout << "Key: " << j << "  Value: " << value << endl;
       parentsValues.print("parentsValues: ");
       throw runtime_error("DiscreteConditional::choose: parent value missing");
     };
   }
-  return pFS;
+  return adt;
 }
 
 /* ******************************************************************************** */
-DecisionTreeFactor::shared_ptr DiscreteConditional::chooseAsFactor(
+DecisionTreeFactor::shared_ptr DiscreteConditional::choose(
     const DiscreteValues& parentsValues) const {
-  ADT pFS = choose(parentsValues);
+  // Get the big decision tree with all the levels, and then go down the
+  // branches based on the value of the parent variables.
+  ADT adt(*this);
+  size_t value;
+  for (Key j : parents()) {
+    try {
+      value = parentsValues.at(j);
+      adt = adt.choose(j, value);  // ADT keeps getting smaller.
+    } catch (exception&) {
+      parentsValues.print("parentsValues: ");
+      throw runtime_error("DiscreteConditional::choose: parent value missing");
+    };
+  }
 
   // Convert ADT to factor.
-  if (nrFrontals() != 1) {
-    throw std::runtime_error("Expected only one frontal variable in choose.");
+  DiscreteKeys discreteKeys;
+  for (Key j : frontals()) {
+    discreteKeys.emplace_back(j, this->cardinality(j));
   }
-  DiscreteKeys keys;
-  const Key frontalKey = keys_[0];
-  size_t frontalCardinality = this->cardinality(frontalKey);
-  keys.push_back(DiscreteKey(frontalKey, frontalCardinality));
-  return boost::make_shared<DecisionTreeFactor>(keys, pFS);
+  return boost::make_shared<DecisionTreeFactor>(discreteKeys, adt);
+}
+
+/* ******************************************************************************** */
+DecisionTreeFactor::shared_ptr DiscreteConditional::likelihood(
+    const DiscreteValues& frontalValues) const {
+  // Get the big decision tree with all the levels, and then go down the
+  // branches based on the value of the frontal variables.
+  ADT adt(*this);
+  size_t value;
+  for (Key j : frontals()) {
+    try {
+      value = frontalValues.at(j);
+      adt = adt.choose(j, value);  // ADT keeps getting smaller.
+    } catch (exception&) {
+      frontalValues.print("frontalValues: ");
+      throw runtime_error("DiscreteConditional::choose: frontal value missing");
+    };
+  }
+
+  // Convert ADT to factor.
+  DiscreteKeys discreteKeys;
+  for (Key j : parents()) {
+    discreteKeys.emplace_back(j, this->cardinality(j));
+  }
+  return boost::make_shared<DecisionTreeFactor>(discreteKeys, adt);
+}
+
+/* ******************************************************************************** */
+DecisionTreeFactor::shared_ptr DiscreteConditional::likelihood(
+    size_t value) const {
+  if (nrFrontals() != 1)
+    throw std::invalid_argument(
+        "Single value likelihood can only be invoked on single-variable "
+        "conditional");
+  DiscreteValues values;
+  values.emplace(keys_[0], value);
+  return likelihood(values);
 }
 
 /* ******************************************************************************** */
 void DiscreteConditional::solveInPlace(DiscreteValues* values) const {
   // TODO: Abhijit asks: is this really the fastest way? He thinks it is.
-  ADT pFS = choose(*values); // P(F|S=parentsValues)
+  ADT pFS = Choose(*this, *values); // P(F|S=parentsValues)
 
   // Initialize
   DiscreteValues mpe;
@@ -177,7 +222,7 @@ void DiscreteConditional::sampleInPlace(DiscreteValues* values) const {
 size_t DiscreteConditional::solve(const DiscreteValues& parentsValues) const {
 
   // TODO: is this really the fastest way? I think it is.
-  ADT pFS = choose(parentsValues); // P(F|S=parentsValues)
+  ADT pFS = Choose(*this, parentsValues); // P(F|S=parentsValues)
 
   // Then, find the max over all remaining
   // TODO, only works for one key now, seems horribly slow this way
@@ -203,7 +248,7 @@ size_t DiscreteConditional::sample(const DiscreteValues& parentsValues) const {
   static mt19937 rng(2);  // random number generator
 
   // Get the correct conditional density
-  ADT pFS = choose(parentsValues);  // P(F|S=parentsValues)
+  ADT pFS = Choose(*this, parentsValues);  // P(F|S=parentsValues)
 
   // TODO(Duy): only works for one key now, seems horribly slow this way
   assert(nrFrontals() == 1);

gtsam/discrete/DiscreteConditional.h

@@ -146,13 +146,17 @@ public:
     return DecisionTreeFactor::shared_ptr(new DecisionTreeFactor(*this));
   }
 
-  /** Restrict to given parent values, returns AlgebraicDecisionDiagram */
-  ADT choose(const DiscreteValues& parentsValues) const;
-
   /** Restrict to given parent values, returns DecisionTreeFactor */
-  DecisionTreeFactor::shared_ptr chooseAsFactor(
+  DecisionTreeFactor::shared_ptr choose(
       const DiscreteValues& parentsValues) const;
 
+  /** Convert to a likelihood factor by providing value before bar. */
+  DecisionTreeFactor::shared_ptr likelihood(
+      const DiscreteValues& frontalValues) const;
+
+  /** Single variable version of likelihood. */
+  DecisionTreeFactor::shared_ptr likelihood(size_t value) const;
+
   /**
    * solve a conditional
    * @param parentsValues Known values of the parents

gtsam/discrete/discrete.i

@@ -76,8 +76,11 @@ virtual class DiscreteConditional : gtsam::DecisionTreeFactor {
       string s = "Discrete Conditional: ",
       const gtsam::KeyFormatter& formatter = gtsam::DefaultKeyFormatter) const;
   gtsam::DecisionTreeFactor* toFactor() const;
-  gtsam::DecisionTreeFactor* chooseAsFactor(
+  gtsam::DecisionTreeFactor* choose(
       const gtsam::DiscreteValues& parentsValues) const;
+  gtsam::DecisionTreeFactor* likelihood(
+      const gtsam::DiscreteValues& frontalValues) const;
+  gtsam::DecisionTreeFactor* likelihood(size_t value) const;
   size_t solve(const gtsam::DiscreteValues& parentsValues) const;
   size_t sample(const gtsam::DiscreteValues& parentsValues) const;
   void solveInPlace(gtsam::DiscreteValues @parentsValues) const;

gtsam/discrete/tests/testDiscreteConditional.cpp

@@ -31,24 +31,21 @@ using namespace std;
 using namespace gtsam;
 
 /* ************************************************************************* */
-TEST( DiscreteConditional, constructors)
-{
-  DiscreteKey X(0, 2), Y(2, 3), Z(1, 2); // watch ordering !
+TEST(DiscreteConditional, constructors) {
+  DiscreteKey X(0, 2), Y(2, 3), Z(1, 2);  // watch ordering !
+
+  DiscreteConditional expected(X | Y = "1/1 2/3 1/4");
+  EXPECT_LONGS_EQUAL(0, *(expected.beginFrontals()));
+  EXPECT_LONGS_EQUAL(2, *(expected.beginParents()));
+  EXPECT(expected.endParents() == expected.end());
+  EXPECT(expected.endFrontals() == expected.beginParents());
 
-  DiscreteConditional::shared_ptr expected1 = //
-      boost::make_shared<DiscreteConditional>(X | Y = "1/1 2/3 1/4");
-  EXPECT(expected1);
-  EXPECT_LONGS_EQUAL(0, *(expected1->beginFrontals()));
-  EXPECT_LONGS_EQUAL(2, *(expected1->beginParents()));
-  EXPECT(expected1->endParents() == expected1->end());
-  EXPECT(expected1->endFrontals() == expected1->beginParents());
-  
   DecisionTreeFactor f1(X & Y, "0.5 0.4 0.2 0.5 0.6 0.8");
   DiscreteConditional actual1(1, f1);
-  EXPECT(assert_equal(*expected1, actual1, 1e-9));
+  EXPECT(assert_equal(expected, actual1, 1e-9));
 
-  DecisionTreeFactor f2(X & Y & Z,
-      "0.2 0.5 0.3 0.6 0.4 0.7 0.25 0.55 0.35 0.65 0.45 0.75");
+  DecisionTreeFactor f2(
+      X & Y & Z, "0.2 0.5 0.3 0.6 0.4 0.7 0.25 0.55 0.35 0.65 0.45 0.75");
   DiscreteConditional actual2(1, f2);
   EXPECT(assert_equal(f2 / *f2.sum(1), *actual2.toFactor(), 1e-9));
 }
@@ -108,6 +105,20 @@ TEST(DiscreteConditional, Combine) {
   EXPECT(assert_equal(expected, *actual, 1e-5));
 }
 
+/* ************************************************************************* */
+TEST(DiscreteConditional, likelihood) {
+  DiscreteKey X(0, 2), Y(1, 3);
+  DiscreteConditional conditional(X | Y = "2/8 4/6 5/5");
+
+  auto actual0 = conditional.likelihood(0);
+  DecisionTreeFactor expected0(Y, "0.2 0.4 0.5");
+  EXPECT(assert_equal(expected0, *actual0, 1e-9));
+
+  auto actual1 = conditional.likelihood(1);
+  DecisionTreeFactor expected1(Y, "0.8 0.6 0.5");
+  EXPECT(assert_equal(expected1, *actual1, 1e-9));
+}
+
 /* ************************************************************************* */
 // Check markdown representation looks as expected, no parents.
 TEST(DiscreteConditional, markdown_prior) {

python/gtsam/tests/test_DiscreteConditional.py

@@ -13,12 +13,26 @@ Author: Varun Agrawal
 
 import unittest
 
-from gtsam import DiscreteConditional, DiscreteKeys
+from gtsam import DecisionTreeFactor, DiscreteConditional, DiscreteKeys
 from gtsam.utils.test_case import GtsamTestCase
 
 
 class TestDiscreteConditional(GtsamTestCase):
     """Tests for Discrete Conditionals."""
+
+    def test_likelihood(self):
+        X = (0, 2)
+        Y = (1, 3)
+        conditional = DiscreteConditional(X, "2/8 4/6 5/5", Y)
+
+        actual0 = conditional.likelihood(0)
+        expected0 = DecisionTreeFactor(Y, "0.2 0.4 0.5")
+        self.gtsamAssertEquals(actual0, expected0, 1e-9)
+
+        actual1 = conditional.likelihood(1)
+        expected1 = DecisionTreeFactor(Y, "0.8 0.6 0.5")
+        self.gtsamAssertEquals(actual1, expected1, 1e-9)
+
     def test_markdown(self):
         """Test whether the _repr_markdown_ method."""
 
@@ -32,7 +46,7 @@ class TestDiscreteConditional(GtsamTestCase):
         conditional = DiscreteConditional(A, parents,
                                           "0/1 1/3  1/1 3/1  0/1 1/0")
         expected = \
-            " $P(A|B,C)$:\n" \
+            " *P(A|B,C)*:\n\n" \
             "|B|C|0|1|\n" \
             "|:-:|:-:|:-:|:-:|\n" \
             "|0|0|0|1|\n" \