def test_easy_shape(self):
n1 = DiscreteNode("Some Node", [True, False])
n2 = DiscreteNode("Second Node" , [True, False])
s = n1.get_cpd().multiplication(n2.get_cpd())
self.assertEqual(s.table.shape, (2,2));
s = n1.get_cpd().multiplication(n1.get_cpd())
self.assertEqual(s.table.shape,(2,))
def test_easy_shape(self):
n1 = DiscreteNode("Some Node", [True, False])
n2 = DiscreteNode("Second Node", [True, False])
s = n1.get_cpd().multiplication(n2.get_cpd())
self.assertEqual(s.table.shape, (2, 2))
s = n1.get_cpd().multiplication(n1.get_cpd())
self.assertEqual(s.table.shape, (2, ))
def test_complicated_multi(self):
n1 = DiscreteNode("Some Node", [True, False])
n2 = DiscreteNode("Second Node" , [True, False,"noIdea"])
cpt1 = numpy.array([2,3])
cpt2 = numpy.array([5,7,9])
n1.set_probability_table(cpt1,[n1])
n2.set_probability_table(cpt2,[n2])
c3 = n1.get_cpd().multiplication(n2.get_cpd())
c3 = n1.get_cpd().multiplication(c3)
cptN = numpy.array([[20, 28, 36],[45, 63, 81]])
numpy.testing.assert_array_equal(c3.table,cptN)
def test_complicated_multi(self):
n1 = DiscreteNode("Some Node", [True, False])
n2 = DiscreteNode("Second Node", [True, False, "noIdea"])
cpt1 = numpy.array([2, 3])
cpt2 = numpy.array([5, 7, 9])
n1.set_probability_table(cpt1, [n1])
n2.set_probability_table(cpt2, [n2])
c3 = n1.get_cpd().multiplication(n2.get_cpd())
c3 = n1.get_cpd().multiplication(c3)
cptN = numpy.array([[20, 28, 36], [45, 63, 81]])
numpy.testing.assert_array_equal(c3.table, cptN)
def test_easy_values(self):
n1 = DiscreteNode("Some Node", [True, False])
n2 = DiscreteNode("Second Node" , [True, False])
cpt1 = numpy.array([2,3])
cpt2 = numpy.array([5,7])
n1.set_probability_table(cpt1,[n1])
n2.set_probability_table(cpt2,[n2])
s = n1.get_cpd().multiplication(n2.get_cpd())
cptN = numpy.array([[10,14],[15,21]])
numpy.testing.assert_array_equal(s.table,cptN)
self.assertEqual(s.variables[0],n1)
def test_easy_values(self):
n1 = DiscreteNode("Some Node", [True, False])
n2 = DiscreteNode("Second Node", [True, False])
cpt1 = numpy.array([2, 3])
cpt2 = numpy.array([5, 7])
n1.set_probability_table(cpt1, [n1])
n2.set_probability_table(cpt2, [n2])
s = n1.get_cpd().multiplication(n2.get_cpd())
cptN = numpy.array([[10, 14], [15, 21]])
numpy.testing.assert_array_equal(s.table, cptN)
self.assertEqual(s.variables[0], n1)
def test_easy_marginalize(self):
n1 = DiscreteNode("Some Node", [True, False])
n2 = DiscreteNode("Second Node" , [True, False, "other"])
cpt1 = numpy.array([2,3])
cpt2 = numpy.array([5,7,3])
n1.set_probability_table(cpt1,[n1])
n2.set_probability_table(cpt2,[n2])
s = n1.get_cpd().multiplication(n2.get_cpd())
s =s.marginalization(n2)
print s.table
cptN = numpy.array([30,45])
numpy.testing.assert_array_equal(s.table,cptN)
self.assertEqual(s.variables[0],n1)
def test_easy_marginalize(self):
n1 = DiscreteNode("Some Node", [True, False])
n2 = DiscreteNode("Second Node", [True, False, "other"])
cpt1 = numpy.array([2, 3])
cpt2 = numpy.array([5, 7, 3])
n1.set_probability_table(cpt1, [n1])
n2.set_probability_table(cpt2, [n2])
s = n1.get_cpd().multiplication(n2.get_cpd())
s = s.marginalization(n2)
print s.table
cptN = numpy.array([30, 45])
numpy.testing.assert_array_equal(s.table, cptN)
self.assertEqual(s.variables[0], n1)
