# -*- coding: utf-8 -*-
"""
Created on Thu Feb 20 10:36:01 2014
@author: Huang,Zheng
A command line wrapper to use LinearCRF class to Test.
"""
import argparse
import LinearCRF2
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("datafile", help="data file for Testing input")
parser.add_argument("modelfile",
help="the learnt model file to load. ")
parser.add_argument("resultfile",
help="the output file name.")
#parser.add_argument("-s", "--sigma", type=float,
# default=1,
# help="sigma")
args = parser.parse_args()
LinearCRF2.crfpredict(args.datafile, args.modelfile, args.resultfile)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("datafile", help="data file for training input")
parser.add_argument("templatefile",
help="template file for generate feature functions.")
parser.add_argument("modelfile",
help="the learnt model file. (output)")
parser.add_argument("-r", "--regularity", type=int,
default=2, choices=[0, 1, 2],
help="regularity: 0:none; 1:first order; 2:square.")
parser.add_argument("-s", "--sigma", type=float,
default=1,
help="sigma")
parser.add_argument("-m", "--multiproc", type=int,
default=1, choices=[0,1],
help="multiprocessing: 1:use multiprocessing; 0:only single core.")
parser.add_argument("-f", "--fd", type=int,
default=1,
help="feature reduction: the number of observed x under this value is ignored.")
args = parser.parse_args()
#print args.sigma
LinearCRF2.train(args.datafile,args.templatefile,args.modelfile,
regtype=args.regularity,sigma=args.sigma,mp=args.multiproc, fd=args.fd)
choices=[0, 1, 2],
help="regularity: 0:none; 1:first order; 2:square.")
parser.add_argument("-s", "--sigma", type=float, default=1, help="sigma")
parser.add_argument(
"-m",
"--multiproc",
type=int,
default=1,
choices=[0, 1],
help="multiprocessing: 1:use multiprocessing; 0:only single core.")
parser.add_argument(
"-f",
"--fd",
type=int,
default=1,
help=
"feature reduction: the number of observed x under this value is ignored."
)
args = parser.parse_args()
#print args.sigma
LinearCRF2.train(args.datafile,
args.templatefile,
args.modelfile,
regtype=args.regularity,
sigma=args.sigma,
mp=args.multiproc,
fd=args.fd)
