def model_config(self,predicate,formula,database,mln_path,db_path):
"""
Returns the database and mln objects in MLN format
--Inputs--
predicate: predicate object with parsed predicates
formula: formula object with parsed predicates
database:.txt file containing the database(s)
mln_path: .mln file name to save the learned weights per formula
db_path: .db file to save the progress of the database learning
"""
base_path = os.getcwd()
mln = MLN(grammar='PRACGrammar',logic='FirstOrderLogic') #Parsing with PRACGrammar since we are using clusters
for i in predicate:
mln << i
print('input predicate successful:'+i)
for i in formula:
mln << i
print('input formula successful :'+i)
mln.write()
mln.tofile(base_path + '/'+ mln_path)
db = Database.load(mln,database)
#db.write()
#db.tofile(base_path + '/'+ db_path)
return (db,mln)
def model_config(predicate, formula, database, mln_path,
db_path): # mln_path,db_path 為string
base_path = os.getcwd()
mln = MLN(grammar='StandardGrammar', logic='FirstOrderLogic')
for i in predicate:
mln << i
print('input predicate successful:' + i)
for i in formula:
mln << i
print('input formula successful :' + i)
mln.write()
mln.tofile(base_path + '\\' + mln_path) #把谓语数据储存成 mln_path.mln 档案
db = Database(mln)
try:
for i in enumerate(database):
db << i[1][1]
print('input database successful : ' + i[1][0] + ' : ' +
i[1][1])
except:
for j in database[i[0]::]:
db << j[1]
db.write()
db.tofile(base_path + '\\' + db_path) #把证据数据储存成 db_path.db 档案
return (db, mln)
formulas = get_formulas(args.formula_file)
domains = get_domains(roles, instances)
# generates the markov logic network
mln = MLN(logic="FirstOrderLogic", grammar="PRACGrammar")
for domain, values in domains.items(): # domains
for value in values:
if len(value) > 1:
const = ''.join(value)
elif len(value) > 0:
const = value[0]
else:
const = "None"
mln.update_domain({domain: [const]})
for role in roles.keys(): # predicates
mln.predicate(Predicate(
role, [role + "_d!"])) # hard-functional constraints only
for formula in formulas: # formulas
formula_str = "0.0 "
for idx in range(len(formula)):
role = formula[idx]
if idx + 1 < len(formula):
formula_str += role + "(+?" + role[:2] + ")" + " ^ "
else:
formula_str += role + "(+?" + role[:2] + ")"
mln << formula_str
mln.write()
mln.tofile(args.output_mln)
print("The initial MLN has been written to '" + args.output_mln + "'.")
print("Verify the MLN using the print out above.")
print("NOTE: Weights of '" + args.output_mln + "' have NOT been learned.")
