import sys
import re
import string
from pylib_discretize import *
import pylib_io
import pylib_eprots
ed_opt = "--equidist"
ed_optspc = ed_opt+"="
ed_spclen = len(ed_optspc);
round_fun = equidist_round(10)
options = pylib_io.get_options()
files = pylib_io.get_args()
for opt in options:
if opt == "--constant":
round_fun = const_round
elif opt == "--prop":
round_fun = prop_round
elif opt == "--none":
round_fun = no_round
elif opt == ed_opt:
round_fun = equidist_round(10)
elif opt[0:ed_spclen] == ed_optspc:
try:
round_fun = equidist_round(int(opt[ed_spclen:]))
except ValueError:
elif option.startswith("-b"):
batch_app = option[2:]
if batch_app == "":
sys.exit("-b needs non-empty argument")
else:
sys.exit("Unknown option " + option)
if outfile and batch_app:
sys.exit("Options -o and -b are incompatible")
if not outfile:
outfile = "-"
if not batch_app:
out_fp = pylib_io.flexopen(outfile, "w")
files = pylib_io.get_args()
if len(files) == 0:
files.append("-")
for file in files:
formula = prop_formula()
formula.dimacs_parse(file)
if batch_app:
out_fp = pylib_io.flexopen(file + "." + batch_app, "w")
if format == "mathsat":
out_fp.write(formula.mathsat_str())
out_fp.write("\n")
elif format == "tptp2":
out_fp.write(formula.tptp2_str())
import pylib_dectrees
relgain_limit = 0.5
entropy_compare_fun = cmp
max_split = 10
crossval = 0
eval_tree = False
classify = False
printtree = True
seed = None
stratified = True
feature_selection = "R"
dectree_constructor = pylib_dectrees.global_decision_tree
options = pylib_io.get_options()
args = pylib_io.get_args()
for o in options:
if o[0:2] == "-g":
relgain_limit = float(o[2:])
if o == "-a":
entropy_compare_fun = pylib_basics.rl_lex_compare
feature_selection = "A"
if o[0:2] == "-s":
max_split = int(float(o[2:]))
if o[0:2] == "-x":
try:
crossval = int(float(o[2:]))
except ValueError:
crossval = 10
if o[0:2] == "-X":
import pylib_dectrees
relgain_limit = 0.5
entropy_compare_fun = cmp
max_split = 10
crossval = 0
eval_tree = False
classify = False
printtree = True
seed = None
stratified = True
feature_selection = "R"
dectree_constructor = pylib_dectrees.global_decision_tree
options = pylib_io.get_options()
args = pylib_io.get_args()
for o in options:
if o[0:2] == "-g":
relgain_limit = float(o[2:])
if o == "-a":
entropy_compare_fun = pylib_basics.rl_lex_compare
feature_selection = "A"
if o[0:2] == "-s":
max_split = int(float(o[2:]))
if o[0:2] == "-x":
try:
crossval = int(float(o[2:]))
except ValueError:
crossval = 10
if o[0:2] == "-X":
