source_names = [str(hash(patient)) for patient in PATIENTS] + PATHWAYS
#-- Fuse patients together.
fused_bkb = fuse(bkfs, [1 for _ in range(len(source_names))],
source_names,
working_dir=os.getcwd())
#fused_bkb.makeGraph(layout='neato')
print(counts)
for gene in GENES:
print('=' * 20 + str(' No Connection:'))
#-- Instantiate Reasoner
fused_bkb_ = copy.deepcopy(fused_bkb)
reasoner = Reasoner(fused_bkb_, None)
reasoner.metadata = patient_data_hash
#-- Make query
query1 = Query(evidence={gene_: 'True'
for gene_ in [GENES[0], GENES[2]]},
targets=['_Source_[{}]_'.format(gene) for gene in GENES],
type='updating')
query1 = reasoner.analyze_query(query1)
query1.getReport()
query1.bkb._name = 'No Connection'
#query1.bkb.makeGraph(layout='neato')
#-- Structure Learn
fused_bkb_1 = copy.deepcopy(fused_bkb_)
gene0Comp_idx = fused_bkb_1.getComponentIndex('Gene0')
}
for patient in PATIENTS
}
patient_data_hash = dict()
for patient, dict_ in patient_data.items():
patient_data_hash[hash(patient)] = dict_
print(patient_data)
#-- Denote Demographic evidence.
demo_ev = [('Age', '>=', 50), ('Gender', '==', 'Male')]
demo_tar = [('Survival', '>=', 2)]
reasoner1 = Reasoner(fused_bkb, None)
reasoner1.metadata = patient_data_hash
reasoner1.cpp_reasoning = True
reasoner2 = Reasoner(fused_bkb_wStruct, None)
reasoner2.metadata = patient_data_hash
reasoner2.cpp_reasoning = True
query0 = Query(
evidence={'Gene{}_mutated'.format(i): 'True'
for i in range(NUM_GENES)},
targets=list(),
meta_evidence=demo_ev,
meta_targets=demo_tar,
type='updating')
query01 = reasoner1.analyze_query(copy.deepcopy(query0))
