def test_graph_refutation(self, num_variables,num_samples):
data = dowhy.datasets.dataset_from_random_graph(num_vars = num_variables, num_samples= num_samples)
df = data["df"]
model = CausalModel(
data=df,
treatment=data["treatment_name"],
outcome=data["outcome_name"],
graph=data["gml_graph"],
)
graph_refutation_object = model.refute_graph(k = 1, independence_test =
{'test_for_continuous': 'partial_correlation',
'test_for_discrete' : 'conditional_mutual_information'})
assert graph_refutation_object.refutation_result == True
def test_graph_refutation2(self, num_variables,num_samples):
data = dowhy.datasets.dataset_from_random_graph(num_vars = num_variables, num_samples= num_samples)
df = data["df"]
gml_str = """
graph [
directed 1
node [
id 0
label "a"
]
node [
id 1
label "b"
]
node [
id 2
label "c"
]
node [
id 3
label "d"
]
node [
id 4
label "e"
]
node [
id 5
label "f"
]
node [
id 6
label "g"
]
node [
id 7
label "h"
]
node [
id 8
label "i"
]
node [
id 9
label "j"
]
edge [
source 0
target 1
]
edge [
source 0
target 3
]
edge [
source 3
target 2
]
edge [
source 7
target 4
]
edge [
source 6
target 5
]
edge [
source 7
target 8
]
edge [
source 9
target 2
]
edge [
source 9
target 8
]
]
"""
model = CausalModel(
data=df,
treatment=data["treatment_name"],
outcome=data["outcome_name"],
graph=gml_str,
)
graph_refutation_object = model.refute_graph(k = 2, independence_test =
{'test_for_continuous': 'partial_correlation',
'test_for_discrete' : 'conditional_mutual_information'})
assert graph_refutation_object.refutation_result == False