Merge pull request #985 from borglab/featue/wrap_discrete_BT
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fb3f00d656
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@ -92,12 +92,28 @@ class DiscreteBayesNet {
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};
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#include <gtsam/discrete/DiscreteBayesTree.h>
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class DiscreteBayesTreeClique {
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DiscreteBayesTreeClique();
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DiscreteBayesTreeClique(const gtsam::DiscreteConditional* conditional);
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const gtsam::DiscreteConditional* conditional() const;
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bool isRoot() const;
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void printSignature(
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const string& s = "Clique: ",
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const gtsam::KeyFormatter& formatter = gtsam::DefaultKeyFormatter) const;
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double evaluate(const gtsam::DiscreteValues& values) const;
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};
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class DiscreteBayesTree {
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DiscreteBayesTree();
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void print(string s = "DiscreteBayesTree\n",
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const gtsam::KeyFormatter& keyFormatter =
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gtsam::DefaultKeyFormatter) const;
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bool equals(const gtsam::DiscreteBayesTree& other, double tol = 1e-9) const;
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size_t size() const;
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bool empty() const;
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const DiscreteBayesTreeClique* operator[](size_t j) const;
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string dot(const gtsam::KeyFormatter& keyFormatter =
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gtsam::DefaultKeyFormatter) const;
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void saveGraph(string s,
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@ -0,0 +1,25 @@
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digraph G{
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0[label="8,12,14"];
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0->1
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1[label="0 : 8,12"];
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0->2
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2[label="1 : 8,12"];
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0->3
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3[label="9 : 12,14"];
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3->4
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4[label="2 : 9,12"];
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3->5
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5[label="3 : 9,12"];
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0->6
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6[label="10,13 : 14"];
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6->7
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7[label="4 : 10,13"];
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6->8
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8[label="5 : 10,13"];
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6->9
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9[label="11 : 13,14"];
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9->10
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10[label="6 : 11,13"];
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9->11
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11[label="7 : 11,13"];
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}
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@ -0,0 +1,89 @@
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"""
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GTSAM Copyright 2010-2021, Georgia Tech Research Corporation,
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Atlanta, Georgia 30332-0415
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All Rights Reserved
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See LICENSE for the license information
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Unit tests for Discrete Bayes trees.
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Author: Frank Dellaert
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"""
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# pylint: disable=no-name-in-module, invalid-name
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import unittest
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from gtsam import (DiscreteBayesNet, DiscreteBayesTreeClique,
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DiscreteConditional, DiscreteFactorGraph, DiscreteKeys,
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Ordering)
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from gtsam.utils.test_case import GtsamTestCase
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def P(*args):
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""" Create a DiscreteKeys instances from a variable number of DiscreteKey pairs."""
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# TODO: We can make life easier by providing variable argument functions in C++ itself.
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dks = DiscreteKeys()
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for key in args:
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dks.push_back(key)
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return dks
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class TestDiscreteBayesNet(GtsamTestCase):
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"""Tests for Discrete Bayes Nets."""
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def test_elimination(self):
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"""Test Multifrontal elimination."""
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# Define DiscreteKey pairs.
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keys = [(j, 2) for j in range(15)]
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# Create thin-tree Bayesnet.
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bayesNet = DiscreteBayesNet()
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bayesNet.add(keys[0], P(keys[8], keys[12]), "2/3 1/4 3/2 4/1")
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bayesNet.add(keys[1], P(keys[8], keys[12]), "4/1 2/3 3/2 1/4")
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bayesNet.add(keys[2], P(keys[9], keys[12]), "1/4 8/2 2/3 4/1")
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bayesNet.add(keys[3], P(keys[9], keys[12]), "1/4 2/3 3/2 4/1")
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bayesNet.add(keys[4], P(keys[10], keys[13]), "2/3 1/4 3/2 4/1")
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bayesNet.add(keys[5], P(keys[10], keys[13]), "4/1 2/3 3/2 1/4")
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bayesNet.add(keys[6], P(keys[11], keys[13]), "1/4 3/2 2/3 4/1")
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bayesNet.add(keys[7], P(keys[11], keys[13]), "1/4 2/3 3/2 4/1")
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bayesNet.add(keys[8], P(keys[12], keys[14]), "T 1/4 3/2 4/1")
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bayesNet.add(keys[9], P(keys[12], keys[14]), "4/1 2/3 F 1/4")
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bayesNet.add(keys[10], P(keys[13], keys[14]), "1/4 3/2 2/3 4/1")
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bayesNet.add(keys[11], P(keys[13], keys[14]), "1/4 2/3 3/2 4/1")
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bayesNet.add(keys[12], P(keys[14]), "3/1 3/1")
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bayesNet.add(keys[13], P(keys[14]), "1/3 3/1")
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bayesNet.add(keys[14], P(), "1/3")
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# Create a factor graph out of the Bayes net.
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factorGraph = DiscreteFactorGraph(bayesNet)
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# Create a BayesTree out of the factor graph.
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ordering = Ordering()
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for j in range(15):
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ordering.push_back(j)
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bayesTree = factorGraph.eliminateMultifrontal(ordering)
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# Uncomment these for visualization:
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# print(bayesTree)
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# for key in range(15):
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# bayesTree[key].printSignature()
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# bayesTree.saveGraph("test_DiscreteBayesTree.dot")
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self.assertFalse(bayesTree.empty())
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self.assertEqual(12, bayesTree.size())
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# The root is P( 8 12 14), we can retrieve it by key:
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root = bayesTree[8]
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self.assertIsInstance(root, DiscreteBayesTreeClique)
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self.assertTrue(root.isRoot())
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self.assertIsInstance(root.conditional(), DiscreteConditional)
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if __name__ == "__main__":
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unittest.main()
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