def main(filename, examplefile):
try:
examples = list(lfi.read_examples(examplefile))
program = PrologFile(filename)
score, weights, names, iterations = lfi.run_lfi(program, examples)
new_names = []
for n in names:
new_names.append((str(n.with_probability()), ) +
program.lineno(n.location)[1:])
return True, (score, weights, new_names, iterations)
except Exception as err:
return False, {"err": process_error(err)}
def main(argv, result_handler=None):
parser = argparser()
args = parser.parse_args(argv)
if result_handler is None:
if args.web:
result_handler = print_result_json
else:
result_handler = print_result
knowledge = get_evaluatable(args.koption)
if args.output is None:
outf = sys.stdout
else:
outf = open(args.output, 'w')
create_logger('problog_lfi', args.verbose)
create_logger('problog', args.verbose - 1)
program = PrologFile(args.model)
examples = list(read_examples(*args.examples))
if len(examples) == 0:
logging.getLogger('problog_lfi').warn('no examples specified')
else:
logging.getLogger('problog_lfi').info('Number of examples: %s' %
len(examples))
options = vars(args)
del options['examples']
try:
results = run_lfi(program, examples, knowledge=knowledge, **options)
for n in results[2]:
n.loc = program.lineno(n.location)
retcode = result_handler((True, results), output=outf)
except Exception as err:
trace = traceback.format_exc()
err.trace = trace
retcode = result_handler((False, err), output=outf)
if args.output is not None:
outf.close()
if retcode:
sys.exit(retcode)