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Merge branch 'feature/discrete_wrapper' into feature/discrete_wrapper_2

release/4.3a0
Varun Agrawal 2021-12-16 15:02:27 -05:00
parent 995e7a511f 6bcd1296c0
commit 7401b6e0c2
10 changed files with 70 additions and 42 deletions
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5
gtsam/discrete/DiscreteBayesNet.h
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@ -83,6 +83,11 @@ namespace gtsam {
//** evaluate for given DiscreteValues */
double evaluate(const DiscreteValues & values) const;
//** (Preferred) sugar for the above for given DiscreteValues */
double operator()(const DiscreteValues & values) const {
return evaluate(values);
}
/**
* Solve the DiscreteBayesNet by back-substitution
*/

6
gtsam/discrete/DiscreteBayesTree.h
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@ -80,6 +80,12 @@ class GTSAM_EXPORT DiscreteBayesTree
//** evaluate probability for given DiscreteValues */
double evaluate(const DiscreteValues& values) const;
//** (Preferred) sugar for the above for given DiscreteValues */
double operator()(const DiscreteValues & values) const {
return evaluate(values);
}
};
} // namespace gtsam

30
gtsam/discrete/DiscreteConditional.h
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@ -58,24 +58,28 @@ public:
DiscreteConditional(const Signature& signature);
/**
* Construct from key, parents, and a Table specifying the CPT.
*
* The first string is parsed to add a key and parents.
*
* Example: DiscreteConditional P(D, {B,E}, table);
*/
* Construct from key, parents, and a Signature::Table specifying the
* conditional probability table (CPT) in 00 01 10 11 order. For
* three-valued, it would be 00 01 02 10 11 12 20 21 22, etc....
*
* The first string is parsed to add a key and parents.
*
* Example: DiscreteConditional P(D, {B,E}, table);
*/
DiscreteConditional(const DiscreteKey& key, const DiscreteKeys& parents,
const Signature::Table& table)
: DiscreteConditional(Signature(key, parents, table)) {}
/**
* Construct from key, parents, and a string specifying the CPT.
*
* The first string is parsed to add a key and parents. The second string
* parses into a table.
*
* Example: DiscreteConditional P(D, {B,E}, "9/1 2/8 3/7 1/9");
*/
* Construct from key, parents, and a string specifying the conditional
* probability table (CPT) in 00 01 10 11 order. For three-valued, it would
* be 00 01 02 10 11 12 20 21 22, etc....
*
* The first string is parsed to add a key and parents. The second string
* parses into a table.
*
* Example: DiscreteConditional P(D, {B,E}, "9/1 2/8 3/7 1/9");
*/
DiscreteConditional(const DiscreteKey& key, const DiscreteKeys& parents,
const std::string& spec)
: DiscreteConditional(Signature(key, parents, spec)) {}

3
gtsam/discrete/DiscreteFactor.h
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@ -83,9 +83,6 @@ public:
/// Find value for given assignment of values to variables
virtual double operator()(const DiscreteValues&) const = 0;
/// Synonym for operator(), mostly for wrapper
double evaluate(const DiscreteValues& values) const { return operator()(values); }
/// Multiply in a DecisionTreeFactor and return the result as DecisionTreeFactor
virtual DecisionTreeFactor operator*(const DecisionTreeFactor&) const = 0;

3
gtsam/discrete/DiscreteFactorGraph.h
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@ -136,9 +136,6 @@ public:
*/
double operator()(const DiscreteValues& values) const;
/// Synonym for operator(), mostly for wrapper
double evaluate(const DiscreteValues& values) const { return operator()(values); }
/// print
void print(
const std::string& s = "DiscreteFactorGraph",

21
gtsam/discrete/Signature.h
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@ -30,7 +30,7 @@ namespace gtsam {
* The format is (Key % string) for nodes with no parents,
* and (Key | Key, Key = string) for nodes with parents.
*
* The string specifies a conditional probability spec in the 00 01 10 11 order.
* The string specifies a conditional probability table in 00 01 10 11 order.
* For three-valued, it would be 00 01 02 10 11 12 20 21 22, etc...
*
* For example, given the following keys
@ -73,22 +73,29 @@ namespace gtsam {
public:
/**
* Construct from key, parents, and a Table specifying the CPT.
* Construct from key, parents, and a Signature::Table specifying the
* conditional probability table (CPT) in 00 01 10 11 order. For
* three-valued, it would be 00 01 02 10 11 12 20 21 22, etc....
*
* The first string is parsed to add a key and parents.
*
* Example: Signature sig(D, {B,E}, table);
*
* Example:
* Signature::Table table{{0.9, 0.1}, {0.2, 0.8}, {0.3, 0.7}, {0.1, 0.9}};
* Signature sig(D, {E, B}, table);
*/
Signature(const DiscreteKey& key, const DiscreteKeys& parents,
const Table& table);
/**
* Construct from key, parents, and a string specifying the CPT.
* Construct from key, parents, and a string specifying the conditional
* probability table (CPT) in 00 01 10 11 order. For three-valued, it would
* be 00 01 02 10 11 12 20 21 22, etc....
*
* The first string is parsed to add a key and parents. The second string
* parses into a table.
*
* Example: Signature sig(D, {B,E}, "9/1 2/8 3/7 1/9");
*
* Example (same CPT as above):
* Signature sig(D, {B,E}, "9/1 2/8 3/7 1/9");
*/
Signature(const DiscreteKey& key, const DiscreteKeys& parents,
const std::string& spec);

14
gtsam/discrete/discrete.i
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@ -1,5 +1,5 @@
//*************************************************************************
// basis
// discrete
//*************************************************************************
namespace gtsam {
@ -26,7 +26,7 @@ class DiscreteFactor {
bool equals(const gtsam::DiscreteFactor& other, double tol = 1e-9) const;
bool empty() const;
size_t size() const;
double evaluate(const gtsam::DiscreteValues& values) const;
double operator()(const gtsam::DiscreteValues& values) const;
};
#include <gtsam/discrete/DecisionTreeFactor.h>
@ -38,7 +38,7 @@ virtual class DecisionTreeFactor: gtsam::DiscreteFactor {
const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
bool equals(const gtsam::DecisionTreeFactor& other, double tol = 1e-9) const;
double evaluate(const gtsam::DiscreteValues& values) const; // TODO(dellaert): why do I have to repeat???
double operator()(const gtsam::DiscreteValues& values) const; // TODO(dellaert): why do I have to repeat???
};
#include <gtsam/discrete/DiscreteConditional.h>
@ -53,7 +53,7 @@ virtual class DiscreteConditional : gtsam::DecisionTreeFactor {
const gtsam::DecisionTreeFactor& marginal,
const gtsam::Ordering& orderedKeys);
size_t size() const; // TODO(dellaert): why do I have to repeat???
double evaluate(const gtsam::DiscreteValues& values) const; // TODO(dellaert): why do I have to repeat???
double operator()(const gtsam::DiscreteValues& values) const; // TODO(dellaert): why do I have to repeat???
void print(string s = "Discrete Conditional\n",
const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
@ -86,7 +86,7 @@ class DiscreteBayesNet {
const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
void add(const gtsam::DiscreteConditional& s);
double evaluate(const gtsam::DiscreteValues& values) const;
double operator()(const gtsam::DiscreteValues& values) const;
gtsam::DiscreteValues optimize() const;
gtsam::DiscreteValues sample() const;
};
@ -98,7 +98,7 @@ class DiscreteBayesTree {
const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const;
bool equals(const gtsam::DiscreteBayesTree& other, double tol = 1e-9) const;
double evaluate(const gtsam::DiscreteValues& values) const;
double operator()(const gtsam::DiscreteValues& values) const;
};
#include <gtsam/discrete/DiscreteFactorGraph.h>
@ -119,7 +119,7 @@ class DiscreteFactorGraph {
bool equals(const gtsam::DiscreteFactorGraph& fg, double tol = 1e-9) const;
gtsam::DecisionTreeFactor product() const;
double evaluate(const gtsam::DiscreteValues& values) const;
double operator()(const gtsam::DiscreteValues& values) const;
gtsam::DiscreteValues optimize() const;
gtsam::DiscreteBayesNet eliminateSequential();

13
gtsam/discrete/tests/testSignature.cpp
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@ -92,7 +92,6 @@ TEST(testSignature, all_examples) {
Signature b(B, {S}, "70/30 40/60");
Signature e(E, {T, L}, "F F F 1");
Signature x(X, {E}, "95/5 2/98");
Signature d(D, {E, B}, "9/1 2/8 3/7 1/9");
}
// Make sure we can create all signatures for Asia network with operator magic.
@ -105,7 +104,17 @@ TEST(testSignature, all_examples_magic) {
Signature b(B | S = "70/30 40/60");
Signature e((E | T, L) = "F F F 1");
Signature x(X | E = "95/5 2/98");
Signature d((D | E, B) = "9/1 2/8 3/7 1/9");
}
// Check example from docs.
TEST(testSignature, doxygen_example) {
Signature::Table table{{0.9, 0.1}, {0.2, 0.8}, {0.3, 0.7}, {0.1, 0.9}};
Signature d1(D, {E, B}, table);
Signature d2((D | E, B) = "9/1 2/8 3/7 1/9");
Signature d3(D, {E, B}, "9/1 2/8 3/7 1/9");
EXPECT(*(d1.table()) == table);
EXPECT(*(d2.table()) == table);
EXPECT(*(d3.table()) == table);
}
/* ************************************************************************* */

3
python/gtsam/tests/test_DiscreteBayesNet.py
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@ -91,6 +91,9 @@ class TestDiscreteBayesNet(GtsamTestCase):
self.assertEqual(list(actualMPE.items()),
list(expectedMPE.items()))
# Check value for MPE is the same
self.assertAlmostEqual(asia(actualMPE), fg(actualMPE))
# add evidence, we were in Asia and we have dyspnea
fg.add(Asia, "0 1")
fg.add(Dyspnea, "0 1")

14
python/gtsam/tests/test_DiscreteFactorGraph.py
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@ -44,9 +44,9 @@ class TestDiscreteFactorGraph(GtsamTestCase):
assignment[1] = 1
# Check if graph evaluation works ( 0.3*0.6*4 )
self.assertAlmostEqual(.72, graph.evaluate(assignment))
self.assertAlmostEqual(.72, graph(assignment))
# Creating a new test with third node and adding unary and ternary factors on it
# Create a new test with third node and adding unary and ternary factor
graph.add(P3, "0.9 0.2 0.5")
keys = DiscreteKeys()
keys.push_back(P1)
@ -54,25 +54,25 @@ class TestDiscreteFactorGraph(GtsamTestCase):
keys.push_back(P3)
graph.add(keys, "1 2 3 4 5 6 7 8 9 10 11 12")
# Below assignment lead to selecting the 8th index in the ternary factor table
# Below assignment selects the 8th index in the ternary factor table
assignment[0] = 1
assignment[1] = 0
assignment[2] = 1
# Check if graph evaluation works (0.3*0.9*1*0.2*8)
self.assertAlmostEqual(4.32, graph.evaluate(assignment))
self.assertAlmostEqual(4.32, graph(assignment))
# Below assignment lead to selecting the 3rd index in the ternary factor table
# Below assignment selects the 3rd index in the ternary factor table
assignment[0] = 0
assignment[1] = 1
assignment[2] = 0
# Check if graph evaluation works (0.9*0.6*1*0.9*4)
self.assertAlmostEqual(1.944, graph.evaluate(assignment))
self.assertAlmostEqual(1.944, graph(assignment))
# Check if graph product works
product = graph.product()
self.assertAlmostEqual(1.944, product.evaluate(assignment))
self.assertAlmostEqual(1.944, product(assignment))
def test_optimize(self):
"""Test constructing and optizing a discrete factor graph."""