Exemple #1
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    def generate_BayesNet(root):
        '''
        Generate a BayesNet from a XMLBIF.

        This method is used internally. Do not call it outside this class.
        '''
        network = BayesNet()
        bif_nodes = root.getElementsByTagName("BIF")
        if len(bif_nodes) != 1:
            raise Exception("More than one or none <BIF>-tag in document.")
        network_nodes = bif_nodes[0].getElementsByTagName("NETWORK")
        if len(network_nodes) != 1:
            raise Exception("More than one or none <NETWORK>-tag in document.")
        variable_nodes = network_nodes[0].getElementsByTagName("VARIABLE")
        for variable_node in variable_nodes:
            name = "Unnamed node"
            value_range = []
            position = (0, 0)
            for name_node in variable_node.getElementsByTagName("NAME"):
                name = XMLBIF.get_node_text(name_node.childNodes)
                break
            for output_node in variable_node.getElementsByTagName("OUTCOME"):
                value_range.append(XMLBIF.get_node_text(output_node.childNodes))
            for position_node in variable_node.getElementsByTagName("PROPERTY"):
                position = XMLBIF.get_node_position_from_text(position_node.childNodes)
                break
            new_node = DiscreteNode(name, value_range)
            new_node.position = position
            network.add_node(new_node)
        definition_nodes = network_nodes[0].getElementsByTagName("DEFINITION")
        for definition_node in definition_nodes:
            node = None
            for for_node in definition_node.getElementsByTagName("FOR"):
                name = XMLBIF.get_node_text(for_node.childNodes)
                node = network.get_node(name)
                break
            if node == None:
                continue
            for given_node in definition_node.getElementsByTagName("GIVEN"):
                parent_name = XMLBIF.get_node_text(given_node.childNodes)
                parent_node = network.get_node(parent_name)
                node.announce_parent(parent_node)
            for table_node in definition_node.getElementsByTagName("TABLE"):
                table = XMLBIF.get_node_table_from_text(table_node.childNodes)
                node.get_cpd().get_table().T.flat = table
                break

        return network
Exemple #2
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class ImportExportTest(unittest.TestCase):
    def setUp(self):
        # Create BayesNet
        self.bn = BayesNet();
        # Create Nodes
        weather0 = DiscreteNode("Weather0", ["Sun", "Rain"])
        weather = DiscreteNode("Weather", ["Sun", "Rain"])
        ice_cream_eaten = DiscreteNode("Ice Cream Eaten", [True, False])
        # Add nodes
        self.bn.add_node(weather0)
        self.bn.add_node(weather)
        self.bn.add_node(ice_cream_eaten)
        # Add edges
        self.bn.add_edge(weather, ice_cream_eaten)
        self.bn.add_edge(weather0, weather);
        # Set probabilities
        cpt_weather0 = numpy.array([.6, .4])
        weather0.set_probability_table(cpt_weather0, [weather0])
        cpt_weather = numpy.array([[.7, .5],
                                   [.3, .5]])
        weather.set_probability_table(cpt_weather, [weather0, weather])
        ice_cream_eaten.set_probability(.9, [(ice_cream_eaten, True), (weather, "Sun")])
        ice_cream_eaten.set_probability(.1, [(ice_cream_eaten, False), (weather, "Sun")])
        ice_cream_eaten.set_probability(.2, [(ice_cream_eaten, True), (weather, "Rain")])
        ice_cream_eaten.set_probability(.8, [(ice_cream_eaten, False), (weather, "Rain")])
    
    def test_import_export(self):
        # write BN 
        xmlbif = XMLBIF(self.bn, "Test Net")
        xmlbif.write("test_out.xmlbif")
        # read BN
        bn2 = XMLBIF.read("test_out.xmlbif")
        for node1 in self.bn.get_nodes():
            
            name_found = False
            cpd_equal = False
            value_range_equal = False
            str_equal = False
            pos_equal = False
            for node2 in bn2.get_nodes():
                # Test node names
                if node1.name == node2.name:
                    name_found = True
                    cpd_equal = node1.get_cpd == node2.get_cpd
                    value_range_equal = node1.get_value_range() == node2.get_value_range()
                    str_equal = str(node1) == str(node2)
                    pos_equal = node1.pos == node2.pos
            self.assertTrue(name_found)
            self.assertTrue(cpd_equal)
            self.assertTrue(value_range_equal)
            self.assertTrue(str_equal)
            self.assertTrue(pos_equal)
        # remove file
        os.remove("test_out.xmlbif")
Exemple #3
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class NodeAddAndRemoveTestCase(unittest.TestCase):
    def setUp(self):
        self.bn = BayesNet()

    def tearDown(self):
        self.bn = None

    def test_clear_and_len(self):
        self.assertFalse(0 == len(self.bn))
        self.assertFalse(0 == self.bn.number_of_nodes())
        self.bn.clear()
        self.assertEqual(0, len(self.bn))
        self.assertEqual(0, self.bn.number_of_nodes())

    def test_add_node(self):
        self.bn.clear()
        n = DiscreteNode("Some Node", [True, False])
        self.bn.add_node(n)
        self.assertEqual(n, self.bn.get_node("Some Node"))
        self.assertTrue(n in self.bn.get_nodes(["Some Node"]))
        node_with_same_name = DiscreteNode("Some Node", [True, False])
        self.assertRaises(Exception, self.bn.add_node, node_with_same_name)

    def test_remove_node(self):
        self.bn.clear()
        n = DiscreteNode("Some Node to remove", [True, False])
        self.bn.add_node(n)
        self.bn.remove_node(n)
        self.assertFalse(n in self.bn.get_nodes([]))

    def test_add_edge(self):
        self.bn.clear()
        n1 = DiscreteNode("1", [True, False])
        n2 = DiscreteNode("2", [True, False])
        self.bn.add_node(n1)
        self.bn.add_node(n2)
        self.bn.add_edge(n1, n2)
        self.assertTrue(n1 in self.bn.get_parents(n2))
        self.assertTrue(n2 in self.bn.get_children(n1))

    def test_remove_edge(self):
        self.bn.clear()
        n1 = DiscreteNode("1", [True, False])
        n2 = DiscreteNode("2", [True, False])
        self.bn.add_node(n1)
        self.bn.add_node(n2)
        self.bn.add_edge(n1, n2)
        self.assertEqual([n1], self.bn.get_parents(n2))
        self.bn.remove_edge(n1, n2)
        self.assertEqual([], self.bn.get_parents(n2))

    def test_is_valid(self):
        self.bn.clear()
        n1 = DiscreteNode("1", [True, False])
        n2 = DiscreteNode("2", [True, False])
        self.bn.add_node(n1)
        self.bn.add_node(n2)
        self.bn.add_edge(n1, n2)
        self.assertTrue(self.bn.is_valid())
        self.bn.add_edge(n1, n1)
        self.assertFalse(self.bn.is_valid())
        self.bn.remove_edge(n1, n1)
        self.assertTrue(self.bn.is_valid())
        n3 = DiscreteNode("3", [True, False])
        n4 = DiscreteNode("4", [True, False])
        self.bn.add_node(n3)
        self.bn.add_node(n4)
        self.assertTrue(self.bn.is_valid())
        self.bn.add_edge(n2, n3)
        self.assertTrue(self.bn.is_valid())
        self.bn.add_edge(n3, n4)
        self.assertTrue(self.bn.is_valid())
        self.bn.add_edge(n4, n1)
        self.assertFalse(self.bn.is_valid())
Exemple #4
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from primo.core import BayesNet
from primo.reasoning import DiscreteNode
import numpy

bn = BayesNet()
burglary = DiscreteNode("Burglary", ["Intruder", "Safe"])
alarm = DiscreteNode("Alarm", ["Ringing", "Silent", "Kaputt"])
earthquake = DiscreteNode("Earthquake", ["Shaking", "Calm"])
john_calls = DiscreteNode("John calls", ["Calling", "Not Calling"])
mary_calls = DiscreteNode("Mary calls", ["Calling", "Not Calling"])


bn.add_node(burglary)
bn.add_node(alarm)
bn.add_node(earthquake)
bn.add_node(john_calls)
bn.add_node(mary_calls)


bn.add_edge(burglary, alarm)
bn.add_edge(earthquake, alarm)
bn.add_edge(alarm, john_calls)
bn.add_edge(alarm, mary_calls)


burglary.set_probability(0.2, [(burglary, "Intruder")])

alarm.set_probability(0.1, [(alarm, "Ringing"), (burglary, "Safe"), (earthquake, "Calm")])
Exemple #5
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from primo.core import BayesNet
from primo.reasoning import DiscreteNode
from primo.reasoning import MarkovChainSampler
from primo.reasoning import GibbsTransitionModel
from primo.reasoning.density import ProbabilityTable
import numpy

#Construct some simple BayesianNetwork
bn = BayesNet()
burglary = DiscreteNode("Burglary", ["Intruder","Safe"])
alarm = DiscreteNode("Alarm", ["Ringing", "Silent","Kaputt"])

bn.add_node(burglary)


bn.add_node(alarm)

bn.add_edge(burglary,alarm)

burglary_cpt=numpy.array([0.2,0.8])
burglary.set_probability_table(burglary_cpt, [burglary])

alarm_cpt=numpy.array([[0.8,0.15,0.05],[0.05,0.9,0.05]])
alarm.set_probability_table(alarm_cpt, [burglary,alarm])

#Construct a Markov Chain by sampling states from this Network

transition_model = GibbsTransitionModel()
from primo.reasoning import DiscreteNode
import primo.reasoning.particlebased.ParticleFilterDBN as pf
import numpy


#Construct some simple DynmaicBayesianNetwork
B0 = BayesNet()
dbn = DynamicBayesNet()
twoTBN = TwoTBN()

weather0_init = DiscreteNode("Weather0", ["Sun", "Rain"])
weather0 = DiscreteNode("Weather0", ["Sun", "Rain"])
weather = DiscreteNode("Weather", ["Sun", "Rain"])
ice_cream_eaten = DiscreteNode("Ice Cream Eaten", [True, False])

B0.add_node(weather0_init)
twoTBN.add_node(weather0, True)
twoTBN.add_node(weather)
twoTBN.add_node(ice_cream_eaten)

twoTBN.add_edge(weather, ice_cream_eaten)
twoTBN.add_edge(weather0, weather);

cpt_weather0_init = numpy.array([.6, .4])
weather0_init.set_probability_table(cpt_weather0_init, [weather0_init])

cpt_weather0 = numpy.array([.6, .4])
weather0.set_probability_table(cpt_weather0, [weather0])

cpt_weather = numpy.array([[.7, .5],
                           [.3, .5]])