Python HyBayesianNetworkの例

コード例 #1

ファイル: run_unit_tests.py プロジェクト: Anaphory/libpgm

 def setUp(self):
     self.nd = HybridNodeData.load("unittesthdict.txt")
     self.nd.entriestoinstances()
     self.skel = GraphSkeleton()
     self.skel.load("unittestdict.txt")
     self.skel.toporder()
     self.hybn = HyBayesianNetwork(self.skel, self.nd)

コード例 #2

ファイル: run_unit_tests.py プロジェクト: Anaphory/libpgm

 def setUp(self):
     self.nd = HybridNodeData.load("unittesthdict.txt")
     self.nd.entriestoinstances()
     self.skel = GraphSkeleton()
     self.skel.load("unittestdict.txt")
     self.skel.toporder()
     self.hybn = HyBayesianNetwork(self.skel, self.nd)

コード例 #3

ファイル: run_unit_tests.py プロジェクト: Anaphory/libpgm

class TestHyBayesianNetwork(unittest.TestCase):
    def setUp(self):
        self.nd = HybridNodeData.load("unittesthdict.txt")
        self.nd.entriestoinstances()
        self.skel = GraphSkeleton()
        self.skel.load("unittestdict.txt")
        self.skel.toporder()
        self.hybn = HyBayesianNetwork(self.skel, self.nd)

    def test_randomsample(self):
        sample = self.hybn.randomsample(1)[0]
        self.assertTrue(isinstance(sample['Grade'], float))
        self.assertTrue(isinstance(sample['Intelligence'], str))
        self.assertEqual(sample["SAT"][-12:], 'blueberries!')

コード例 #4

ファイル: run_unit_tests.py プロジェクト: Anaphory/libpgm

class TestHyBayesianNetwork(unittest.TestCase):

    def setUp(self):
        self.nd = HybridNodeData.load("unittesthdict.txt")
        self.nd.entriestoinstances()
        self.skel = GraphSkeleton()
        self.skel.load("unittestdict.txt")
        self.skel.toporder()
        self.hybn = HyBayesianNetwork(self.skel, self.nd)

    def test_randomsample(self):
        sample = self.hybn.randomsample(1)[0]
        self.assertTrue(isinstance(sample['Grade'], float))
        self.assertTrue(isinstance(sample['Intelligence'], str))
        self.assertEqual(sample["SAT"][-12:], 'blueberries!')

コード例 #5

# Generate a sequence of samples from a hybrid (any CPD type) Bayesian network.

# load nodedata and graphskeleton
nd = NodeData()
skel = GraphSkeleton()
nd.load("../tests/unittesthdict.txt")
skel.load("../tests/unittestdict.txt")

# topologically order graphskeleton
skel.toporder()

# convert nodes to class instances
nd.entriestoinstances()

# load bayesian network
hybn = HyBayesianNetwork(skel, nd)

# sample
result = hybn.randomsample(10)

# output - toggle comment to see
#print json.dumps(result, indent=2)

# (4) ------------------------------------------------------------------------
# Generate a sequence of samples from a discrete-CPD Bayesian network, given evidence

# load nodedata and graphskeleton
nd = NodeData()
skel = GraphSkeleton()
nd.load("../tests/unittestdict.txt")
skel.load("../tests/unittestdict.txt")

コード例 #6

ファイル: examples.py プロジェクト: Anaphory/libpgm

# Generate a sequence of samples from a hybrid (any CPD type) Bayesian network.

# load nodedata and graphskeleton
nd = NodeData()
skel = GraphSkeleton()
nd.load("../tests/unittesthdict.txt")
skel.load("../tests/unittestdict.txt")

# topologically order graphskeleton
skel.toporder()

# convert nodes to class instances
nd.entriestoinstances()

# load bayesian network
hybn = HyBayesianNetwork(skel, nd)

# sample 
result = hybn.randomsample(10)

# output - toggle comment to see
#print json.dumps(result, indent=2)

# (4) ------------------------------------------------------------------------
# Generate a sequence of samples from a discrete-CPD Bayesian network, given evidence

# load nodedata and graphskeleton
nd = NodeData()
skel = GraphSkeleton()
nd.load("../tests/unittestdict.txt")
skel.load("../tests/unittestdict.txt")