def testdnet(self):
from gPy.IO import read_dnet
from gPy.Models import BN
from gPy.Variables import Domain
bnm = BN(domain=Domain())
bnm.from_dnet(read_dnet('Asia.dnet'))
self.samegraph(bnm.adg(),self.asia_adg)
for name, cpt_in_file in self.asia_cpts.items():
cpt = bnm[name]
self.samecpt(cpt,cpt_in_file,cpt.child())
def testdnet(self):
from gPy.IO import read_dnet
from gPy.Models import BN
from gPy.Variables import Domain
bnm = BN(domain=Domain())
bnm.from_dnet(read_dnet('Asia.dnet'))
self.samegraph(bnm.adg(), self.asia_adg)
for name, cpt_in_file in self.asia_cpts.items():
cpt = bnm[name]
self.samecpt(cpt, cpt_in_file, cpt.child())
def setUp(self):
from gPy.Variables import Domain
bnm = BN(domain=Domain())
bnm.from_dnet(read_dnet('Asia.dnet'))
self.hypergraph = bnm._hypergraph
self.adg = bnm._adg
self.tarjan = UGraph(range(1,11),
((1,2),(1,3),(2,3),(2,10),(3,10),(4,5),
(4,7),(5,6),(5,9),(5,7),(6,7),(6,9),
(7,8),(7,9),(8,9),(8,10),(9,10)))
self.tarjan2 = UGraph(range(1,10),
((1,4),(1,3),(2,3),(2,7),(3,5),(3,6),
(4,5),(4,8),(5,6),(5,8),(6,7),(6,9),
(7,9),(8,9)))
self.tarjan3 = UGraph(range(1,10),
((1,4),(1,3),(2,3),(2,7),(3,5),(3,6),
(4,5),(4,8),(5,6),(5,8),(6,7),(6,9),
(7,9),(8,9),
(3,4),(3,7),(4,6),(4,7),(5,7),(6,8),(7,8)))
self.tarjanh1 = Hypergraph([[3,4],[2,4],[1,2,3]])
self.tarjanh2 = Hypergraph([[3,4],[2,4],[1,2,3],[2,3,4]])
self.graph1 = UGraph('ABCDEF',('AB','AC','BD','CE','EF'))
self.graph2 = UGraph('ABCDEF',('AB','AC','BD','CE','EF','BC','CD','DE'))
class TestParameters(unittest.TestCase):
def setUp(self):
from gPy.Variables import Domain
self.domain = Domain()
self.bnm = BN(domain=self.domain)
self.bnm.from_dnet(read_dnet('Asia.dnet'))
self.cptdict = {}
# taken directly from Netica output
self.marginals = [
Factor((('VisitAsia'),),
[0.99,0.01]),
Factor((('Tuberculosis'),),
[0.9896,0.0104]),
Factor((('Smoking'),),
[0.5,0.5]),
Factor((('Cancer'),),
[0.945,0.055]),
Factor((('TbOrCa'),),
[0.93517, 0.064828]),
Factor((('XRay'),),
[0.11029, 0.88971]),
Factor((('Bronchitis'),),
[0.55,0.45]),
Factor((('Dyspnea'),),
[0.56403,0.43597])
]
# taken directly from Netica output
self.cond_marginals = [
Factor((('VisitAsia'),),
[0.95192,0.048077]),
Factor((('Tuberculosis'),),
[0,1]),
Factor((('Smoking'),),
[0.52381,0.47619]),
#other marginals are conditional on these values
#Factor((('Cancer'),),
# [1,0]),
#Factor((('TbOrCa'),),
# [0,1]),
Factor((('XRay'),),
[0.98, 0.02]),
Factor((('Bronchitis'),),
[0.55714,0.44286]),
Factor((('Dyspnea'),),
[0.21143,0.78857])
]
for cpt in self.bnm:
self.cptdict[cpt.child()] = cpt
self.rawdata = read_csv(open('alarm_1K.dat'))
def test_str(self):
out = ''
for node in ['VisitAsia','Tuberculosis','Smoking','Cancer',
'TbOrCa','XRay','Bronchitis','Dyspnea']:
out += str(self.cptdict[node])
self.assertEqual(out,open('Asia.cpts').read())
def test_cptcheck(self):
# be nice to check that this is printed out
errmsg = """
For child: Dyspnea
For row: Bronchitis=Absent, Dyspnea=Absent, TbOrCa=True
Sum was: 0.90 (should be 1.0)
"""
def bnfromfile(filename): x= BN(domain=self.domain); x.from_dnet(read_dnet(filename)); return x
self.assertRaises(CPTError,bnfromfile,open('Asia_wrong.dnet'))
def test_multinplace(self):
factor = self.cptdict['VisitAsia'] * self.cptdict['Tuberculosis']
fid = id(factor)
factor *= self.cptdict['Bronchitis']
self.assertEqual(fid,id(factor))
factor2 = self.cptdict['VisitAsia'] * \
self.cptdict['Tuberculosis'] * self.cptdict['Bronchitis']
self.samefactor(factor,factor2)
def test_scalarprod(self):
for factor in self.bnm:
for scalar in 0,0.3,7:
tf1 = scalar * factor
tf2 = factor * scalar
self.samefactor(tf1,tf2)
for i, val in enumerate(tf1._data):
self.assertAlmostEqual(val,scalar * factor._data[i],places)
def test_instbyname(self):
dyspnea = self.cptdict['Dyspnea']
datum = dyspnea[{'Dyspnea':'Present',
'Bronchitis':'Present',
'TbOrCa':'False'}]
self.assertAlmostEqual(datum,0.8,places)
def test_getitem(self):
dyspnea = self.cptdict['Dyspnea']
datum = dyspnea['Present','Present','False']
self.assertAlmostEqual(datum,0.8,places)
def test_z(self):
factor = 1
order = ['VisitAsia','Tuberculosis','Smoking',
'Cancer','TbOrCa','XRay','Bronchitis',
'Dyspnea']
for name in order:
newfactor = factor * self.cptdict[name]
factor *= self.cptdict[name]
self.samefactor(factor,newfactor)
self.assertAlmostEqual(factor.z(),1,places)
self.assertEqual(str(factor),open('Asia.joint').read())
factor = 1
for cpt in self.cptdict.values():
factor *= cpt
self.assertAlmostEqual(factor.z(),1,places)
def test_marginals(self):
joint = 1
for cpt in self.bnm:
joint *= cpt
order = ['VisitAsia','Tuberculosis','Smoking',
'Cancer','TbOrCa','XRay','Bronchitis',
'Dyspnea']
varset = set(order)
for i, var in enumerate(order):
tmp = varset.copy()
tmp.remove(var)
self.samefactor(self.marginals[i],joint.sumout(tmp))
def test_factorprodcommute(self):
for f1 in self.bnm:
for f2 in self.bnm:
tf1 = f1 * f2
tf2 = f2 * f1
self.samefactor(tf1,tf2)
def test_restrict(self):
bnm = self.bnm.copy(copy_domain=True)
given = {'Cancer':['Absent'],'TbOrCa':['True']}
bnm.condition(given)
joint = 1
for cpt in bnm:
joint *= cpt
order = ['VisitAsia','Tuberculosis','Smoking',
'XRay','Bronchitis','Dyspnea']
varset = set(order)
varset.update(['Cancer','TbOrCa'])
for i, var in enumerate(order):
marginal = joint.sumout(varset - set([var]))
marginal /= marginal.z()
self.samefactor(self.cond_marginals[i],marginal)
def samefactor(self,tf1,tf2):
self.assertEqual(tf1.variables(),tf2.variables())
tf2data = tf2.data()
for i, val in enumerate(tf1.data()):
self.assertAlmostEqual(val,tf2data[i],places)
def bnfromfile(filename): x= BN(domain=self.domain); x.from_dnet(read_dnet(filename)); return x
self.assertRaises(CPTError,bnfromfile,open('Asia_wrong.dnet'))
def bnfromfile(filename):
x = BN(domain=self.domain)
x.from_dnet(read_dnet(filename))
return x
class TestParameters(unittest.TestCase):
def setUp(self):
from gPy.Variables import Domain
self.domain = Domain()
self.bnm = BN(domain=self.domain)
self.bnm.from_dnet(read_dnet('Asia.dnet'))
self.cptdict = {}
# taken directly from Netica output
self.marginals = [
Factor((('VisitAsia'), ), [0.99, 0.01]),
Factor((('Tuberculosis'), ), [0.9896, 0.0104]),
Factor((('Smoking'), ), [0.5, 0.5]),
Factor((('Cancer'), ), [0.945, 0.055]),
Factor((('TbOrCa'), ), [0.93517, 0.064828]),
Factor((('XRay'), ), [0.11029, 0.88971]),
Factor((('Bronchitis'), ), [0.55, 0.45]),
Factor((('Dyspnea'), ), [0.56403, 0.43597])
]
# taken directly from Netica output
self.cond_marginals = [
Factor((('VisitAsia'), ), [0.95192, 0.048077]),
Factor((('Tuberculosis'), ), [0, 1]),
Factor((('Smoking'), ), [0.52381, 0.47619]),
#other marginals are conditional on these values
#Factor((('Cancer'),),
# [1,0]),
#Factor((('TbOrCa'),),
# [0,1]),
Factor((('XRay'), ), [0.98, 0.02]),
Factor((('Bronchitis'), ), [0.55714, 0.44286]),
Factor((('Dyspnea'), ), [0.21143, 0.78857])
]
for cpt in self.bnm:
self.cptdict[cpt.child()] = cpt
self.rawdata = read_csv(open('alarm_1K.dat'))
def test_str(self):
out = ''
for node in [
'VisitAsia', 'Tuberculosis', 'Smoking', 'Cancer', 'TbOrCa',
'XRay', 'Bronchitis', 'Dyspnea'
]:
out += str(self.cptdict[node])
self.assertEqual(out, open('Asia.cpts').read())
def test_cptcheck(self):
# be nice to check that this is printed out
errmsg = """
For child: Dyspnea
For row: Bronchitis=Absent, Dyspnea=Absent, TbOrCa=True
Sum was: 0.90 (should be 1.0)
"""
def bnfromfile(filename):
x = BN(domain=self.domain)
x.from_dnet(read_dnet(filename))
return x
self.assertRaises(CPTError, bnfromfile, open('Asia_wrong.dnet'))
def test_multinplace(self):
factor = self.cptdict['VisitAsia'] * self.cptdict['Tuberculosis']
fid = id(factor)
factor *= self.cptdict['Bronchitis']
self.assertEqual(fid, id(factor))
factor2 = self.cptdict['VisitAsia'] * \
self.cptdict['Tuberculosis'] * self.cptdict['Bronchitis']
self.samefactor(factor, factor2)
def test_scalarprod(self):
for factor in self.bnm:
for scalar in 0, 0.3, 7:
tf1 = scalar * factor
tf2 = factor * scalar
self.samefactor(tf1, tf2)
for i, val in enumerate(tf1._data):
self.assertAlmostEqual(val, scalar * factor._data[i],
places)
def test_instbyname(self):
dyspnea = self.cptdict['Dyspnea']
datum = dyspnea[{
'Dyspnea': 'Present',
'Bronchitis': 'Present',
'TbOrCa': 'False'
}]
self.assertAlmostEqual(datum, 0.8, places)
def test_getitem(self):
dyspnea = self.cptdict['Dyspnea']
datum = dyspnea['Present', 'Present', 'False']
self.assertAlmostEqual(datum, 0.8, places)
def test_z(self):
factor = 1
order = [
'VisitAsia', 'Tuberculosis', 'Smoking', 'Cancer', 'TbOrCa', 'XRay',
'Bronchitis', 'Dyspnea'
]
for name in order:
newfactor = factor * self.cptdict[name]
factor *= self.cptdict[name]
self.samefactor(factor, newfactor)
self.assertAlmostEqual(factor.z(), 1, places)
self.assertEqual(str(factor), open('Asia.joint').read())
factor = 1
for cpt in self.cptdict.values():
factor *= cpt
self.assertAlmostEqual(factor.z(), 1, places)
def test_marginals(self):
joint = 1
for cpt in self.bnm:
joint *= cpt
order = [
'VisitAsia', 'Tuberculosis', 'Smoking', 'Cancer', 'TbOrCa', 'XRay',
'Bronchitis', 'Dyspnea'
]
varset = set(order)
for i, var in enumerate(order):
tmp = varset.copy()
tmp.remove(var)
self.samefactor(self.marginals[i], joint.sumout(tmp))
def test_factorprodcommute(self):
for f1 in self.bnm:
for f2 in self.bnm:
tf1 = f1 * f2
tf2 = f2 * f1
self.samefactor(tf1, tf2)
def test_restrict(self):
bnm = self.bnm.copy(copy_domain=True)
given = {'Cancer': ['Absent'], 'TbOrCa': ['True']}
bnm.condition(given)
joint = 1
for cpt in bnm:
joint *= cpt
order = [
'VisitAsia', 'Tuberculosis', 'Smoking', 'XRay', 'Bronchitis',
'Dyspnea'
]
varset = set(order)
varset.update(['Cancer', 'TbOrCa'])
for i, var in enumerate(order):
marginal = joint.sumout(varset - set([var]))
marginal /= marginal.z()
self.samefactor(self.cond_marginals[i], marginal)
def samefactor(self, tf1, tf2):
self.assertEqual(tf1.variables(), tf2.variables())
tf2data = tf2.data()
for i, val in enumerate(tf1.data()):
self.assertAlmostEqual(val, tf2data[i], places)
