def go(self, obs, a, b, arr, ci):
# manipulate a and b
iic = InterventionalICPattern({obs: ci[obs], a | b: ci[a | b]})
self.assertEquals(iic.lines(), [arr[0]])
xs = [x for x, y in arr if y == 'c' or x == 'c']
if xs:
self.assertEquals(iic.arrows(), [arr[1]])
else:
self.assertEquals(iic.arrows(), [])
def go(self,obs,a,b,arr,ci):
# manipulate a and b
iic = InterventionalICPattern({obs:ci[obs], a|b:ci[a|b]})
self.assertEquals(iic.lines(), [arr[0]])
xs = [x for x, y in arr if y == 'c' or x == 'c']
if xs:
self.assertEquals(iic.arrows(),[arr[1]])
else:
self.assertEquals(iic.arrows(),[])
def tryModel(self, model):
model_do = CBN.from_bn(model.copy(copy_domain=True))
# perform every interventional query
ci = {}
for q in model_do.good_interventions():
# generate the model
model_do = CBN.from_bn(model.copy(copy_domain=True))
model_do.intervene(q)
ci[frozenset(q.keys())] = GraphCI(model_do.adg())
iic = InterventionalICPattern(ci)
self.assertEquals(iic.lines(), [])
self.assertEquals(iic.orient(), model.adg())
def tryModel(self, model):
model_do = CBN.from_bn(model.copy(copy_domain=True))
# perform every interventional query
ci = {}
for q in model_do.good_interventions():
# generate the model
model_do = CBN.from_bn(model.copy(copy_domain=True))
model_do.intervene(q)
ci[frozenset(q.keys())] = GraphCI(model_do.adg())
iic = InterventionalICPattern(ci)
self.assertEquals(iic.lines(), [])
self.assertEquals(iic.orient(), model.adg())
def tryModel(self, model):
# perform every interventional query
ci = {}
for xs in powerset(model.variables()):
# build the intervention q
q = {}
for x in xs:
q[x] = frozenset([set(model.values(x)).pop()])
# generate the model
model_do = CBN.from_bn(model.copy(copy_domain=True))
model_do.intervene(q)
ci[frozenset(q.keys())] = GraphCI(model_do.adg())
iic = InterventionalICPattern(ci)
self.assertEquals(iic.lines(), [])
self.assertEquals(iic.orient(), model.adg())
def tryModel(self, model):
# perform every interventional query
ci = {}
for xs in powerset(model.variables()):
# build the intervention q
q = {}
for x in xs:
q[x] = frozenset([set(model.values(x)).pop()])
# generate the model
model_do = CBN.from_bn(model.copy(copy_domain=True))
model_do.intervene(q)
ci[frozenset(q.keys())] = GraphCI(model_do.adg())
iic = InterventionalICPattern(ci)
self.assertEquals(iic.lines(), [])
self.assertEquals(iic.orient(), model.adg())
def go(self, obs, a, b, arr, ci):
# manipulate b
iic = InterventionalICPattern({obs: ci[obs], b: ci[b]})
self.assertEquals(iic.lines(), [])
self.assertEquals(iic.arrows(), arr)
def go(self, obs, a, b, arr, ci):
# observational
iic = InterventionalICPattern({obs: ci[obs]})
self.assertEquals(iic.arrows(), [])
self.assertEquals(iic.lines(), arr)
def go(self,obs,a,b,arr,ci):
# manipulate b
iic = InterventionalICPattern({obs:ci[obs], b:ci[b]})
self.assertEquals(iic.lines(), [])
self.assertEquals(iic.arrows(), arr)
def go(self,obs,a,b,arr,ci):
# observational
iic = InterventionalICPattern({obs:ci[obs]})
self.assertEquals(iic.arrows(), [])
self.assertEquals(iic.lines(), arr)
