def run(self, request):
response = {'text': '', 'weight': 0, 'type': 'normal'}
js = json.loads(request, encoding = 'utf-8')
if len(js) == 0:
response['text'] = ''
response['weight'] = 0
res = json.dumps(response, ensure_ascii = False)
return res
candidates = {}
sym_list = js['Self Explaination'].split(' ')
for sym in sym_list:
if sym in self.disease_id:
id = self.disease_id[sym]
if not id in candidates:
candidates[id] = 0
candidates[id] += 1
if sym in self.ds_rind:
for id, rate in self.ds_rind[sym].items():
if not id in candidates:
candidates[id] = 0
candidates[id] += rate
ids = sorted(candidates.items(), key=lambda d:d[1], reverse=True)[:20]
print('candidates generated', file = sys.stderr)
dw = {}
deps = {}
for i, r in ids:
if r >= 1:
for d in self.disease_part[i]:
if not d in deps:
deps[d] = 0
deps[d] += 1
try:
model = BIFReader('models/model.bif.%s' % i).get_model()
except:
continue
infer = VariableElimination(model)
key = self.fea_map['D_' + self.disease_name[i]]
observed_info = {}
if '性别' in js['User Info']:
observed_info['SEX'] = js['User Info']['性别']
if '年龄' in js['User Info']:
observed_info['AGE'] = js['User Info']['年龄']
for sym in sym_list:
sym = 'S_' + sym
if not sym in model.nodes():
continue
if not sym in self.fea_map:
continue
observed_info[self.fea_map[sym]] = 0
score = infer.query(variables = [key], evidence = observed_info)[key].values[0]
dw[self.disease_name[i]] = score
#print('%s: %s = %.8f' % (i, self.disease_name[i], score))
for d in self.disease_part[i]:
if not d in deps:
deps[d] = 0
deps[d] += score
if len(deps) == 0:
print('unknown symptoms...', file = sys.stderr)
response['weight'] = 0
response['text'] = ''
res = json.dumps(response, ensure_ascii = False)
return res
for name, score in sorted(dw.items(), key=lambda d:d[1], reverse=True)[:10]:
print('%s\t%.8f' % (name, score), file = sys.stderr)
dep_list = sorted(deps.items(), key=lambda d:d[1], reverse=True)
print('department: ', file = sys.stderr)
for dep, wei in dep_list[:3]:
print(dep, file = sys.stderr)
response['text'] += dep
response['text'] += ' '
response['weight'] = (1000 * dep_list[0][1]) + 0.8
res = json.dumps(response, ensure_ascii = False)
return res
dw = {}
for i in ids:
try:
model = BIFReader('models/model.bif.%s' % i).get_model()
except:
continue
infer = VariableElimination(model)
key = fea_map['D_' + disease_name[i]]
observed_info = {}
for sym in a:
if sym.startswith('SEX_'):
observed_info['SEX'] = int(sym[len('SEX_'):])
if sym.startswith('AGE_'):
observed_info['AGE'] = int(sym[len('AGE_'):])
sym = 'S_' + sym
if not sym in model.nodes():
continue
if not sym in fea_map:
continue
observed_info[fea_map[sym]] = 0
score = infer.query(variables=[key],
evidence=observed_info)[key].values[0]
dw[disease_name[i]] = score
print('%s: %s = %.8f' % (i, disease_name[i], score))
for name, score in sorted(dw.items(), key=lambda d: d[1],
reverse=True)[:10]:
print('%s\t%.8f' % (name, score))
sys.stdout.flush()
