def runTest(self):
num_vars = 5
num_vals = 10
for x in xrange(num_runs):
vs = dict([('V'+str(i),range(num_vals)) for i in xrange(num_vars)])
# should get some random data with 0.
f = Factor(variables = vs.keys()
,data = [abs(randint(0,20)) for i in xrange(num_vals**num_vars)]
#,data = [5, 0, 1, 2]
#,data = [13,0,0,20]
#,data = [14,15,20,16]
,domain = Domain()
,new_domain_variables=vs
,check = True)
records = []
for inst in f.insts():
records.append(inst + (f[inst],))
rawdata = (vs.keys(), vs, vs.keys(), records)
#print records
cf = IncrementalCompactFactor(rawdata, rmin=0)
#print 'old tree:'
#print cf
# g = Factor(variables = vs.keys()
# #,data = [13,2,0,0]
# ,data = [14,15,0,0]
# ,domain = Domain()
# ,new_domain_variables=vs
# ,check = True)
g = f.copy(copy_domain=True)
def swap_some(x):
r = random()
if x == 0:
if r <= 0.5:
return randint(1,5)
return 0
elif r <= 0.5:
return 0
return x
def invert_some(x):
return 5-x
g.map(swap_some)
#print g
f += g
records = []
for inst in g.insts():
records.append(inst + (g[inst],))
rawdata = (vs.keys(), vs, vs.keys(), records)
cf.update(rawdata)
#print 'new tree:'
#print cf
for variables in powerset(vs.keys()):
g = f.copy(copy_domain=True)
g.marginalise_away(g.variables() - frozenset(variables))
self.assert_(same_factor(g,cf.makeFactor(variables),verbose=True))
def runTest(self):
num_vars = 5
num_vals = 10
for i in xrange(num_runs):
vs = dict([('V'+str(i),range(num_vals)) for i in xrange(num_vars)])
# should get some random data with 0.
f = Factor(variables = vs.keys()
,data = [abs(randint(0,5)) for i in xrange(num_vals**num_vars)]
,domain = Domain()
,new_domain_variables=vs
,check = True)
records = []
for inst in f.insts():
records.append(inst + (f[inst],))
rawdata = (vs.keys(), vs, vs.keys(), records)
cf = IncrementalCompactFactor(rawdata)
for variables in powerset(vs.keys()):
g = f.copy(copy_domain=True)
g.marginalise_away(g.variables() - frozenset(variables))
self.assert_(same_factor(g,cf.makeFactor(variables),verbose=True))
