diff --git a/pages/application/RandomForest/utils/options.py b/pages/application/RandomForest/utils/options.py
deleted file mode 100644
index 446eb71702f91876d0f8bef64fd90d048dd95282..0000000000000000000000000000000000000000
--- a/pages/application/RandomForest/utils/options.py
+++ /dev/null
@@ -1,154 +0,0 @@
-#!/usr/bin/env python
-#-*- coding:utf-8 -*-
-##
-## options.py
-##
-## Created on: Dec 7, 2018
-## Author: Alexey Ignatiev, Nina Narodytska
-## E-mail: aignatiev@ciencias.ulisboa.pt, narodytska@vmware.com
-##
-
-#
-#==============================================================================
-from __future__ import print_function
-import getopt
-import math
-import os
-import sys
-
-
-#
-#==============================================================================
-class Options(object):
- """
- Class for representing command-line options.
- """
-
- def __init__(self, command):
- """
- Constructor.
- """
-
- # actions
- self.train = False
- self.encode = 'none'
- self.explain = ''
- self.xtype = 'abd'
- self.use_categorical = False
-
- # training options
- self.accmin = 0.95
- self.n_estimators = 100
- self.maxdepth = 3
- self.testsplit = 0.2
- self.seed = 7
-
- # other options
- self.files = None
- self.output = 'Classifiers'
- self.mapfile = None
- self.separator = ','
- self.smallest = False
- self.solver = 'g3'
- self.verb = 0
-
-
- if command:
- self.parse(command)
-
- def parse(self, command):
- """
- Parser.
- """
-
- self.command = command
-
- try:
- opts, args = getopt.getopt(command[1:],
- 'e:hc:d:Mn:o:s:tvx:X:',
- ['encode=', 'help', 'use-categorical=',
- 'maxdepth=', 'minimum', 'nbestims=',
- 'output=', 'seed=', 'solver=', 'testsplit=',
- 'train', 'verbose', 'explain=', 'xtype=' ])
- except getopt.GetoptError as err:
- sys.stderr.write(str(err).capitalize())
- self.usage()
- sys.exit(1)
-
- for opt, arg in opts:
- if opt in ('-a', '--accmin'):
- self.accmin = float(arg)
- elif opt in ('-c', '--use-categorical'):
- self.use_categorical = True
- elif opt in ('-d', '--maxdepth'):
- self.maxdepth = int(arg)
- elif opt in ('-e', '--encode'):
- self.encode = str(arg)
- elif opt in ('-h', '--help'):
- self.usage()
- sys.exit(0)
-
- elif opt in ('-M', '--minimum'):
- self.smallest = True
- elif opt in ('-n', '--nbestims'):
- self.n_estimators = int(arg)
- elif opt in ('-o', '--output'):
- self.output = str(arg)
-
- elif opt == '--seed':
- self.seed = int(arg)
- elif opt == '--sep':
- self.separator = str(arg)
- elif opt in ('-s', '--solver'):
- self.solver = str(arg)
- elif opt == '--testsplit':
- self.testsplit = float(arg)
- elif opt in ('-t', '--train'):
- self.train = True
- elif opt in ('-v', '--verbose'):
- self.verb += 1
- elif opt in ('-x', '--explain'):
- self.explain = str(arg)
- elif opt in ('-X', '--xtype'):
- self.xtype = str(arg)
- else:
- assert False, 'Unhandled option: {0} {1}'.format(opt, arg)
-
- if self.encode == 'none':
- self.encode = None
-
- self.files = args
-
- def usage(self):
- """
- Print usage message.
- """
-
- print('Usage: ' + os.path.basename(self.command[0]) + ' [options] input-file')
- print('Options:')
- #print(' -a, --accmin=<float> Minimal accuracy')
- #print(' Available values: [0.0, 1.0] (default = 0.95)')
- #print(' -c, --use-categorical Treat categorical features as categorical (with categorical features info if available)')
- print(' -d, --maxdepth=<int> Maximal depth of a tree')
- print(' Available values: [1, INT_MAX] (default = 3)')
- #print(' -e, --encode=<smt> Encode a previously trained model')
- #print(' Available values: sat, maxsat, none (default = none)')
- print(' -h, --help Show this message')
-
- #print(' -m, --map-file=<string> Path to a file containing a mapping to original feature values. (default: none)')
- #print(' -M, --minimum Compute a smallest size explanation (instead of a subset-minimal one)')
- print(' -n, --nbestims=<int> Number of trees in the ensemble')
- print(' Available values: [1, INT_MAX] (default = 100)')
- print(' -o, --output=<string> Directory where output files will be stored (default: \'temp\')')
-
- print(' --seed=<int> Seed for random splitting')
- print(' Available values: [1, INT_MAX] (default = 7)')
- print(' --sep=<string> Field separator used in input file (default = \',\')')
- print(' -s, --solver=<string> A SAT oracle to use')
- print(' Available values: glucose3, minisat (default = g3)')
- print(' -t, --train Train a model of a given dataset')
- print(' --testsplit=<float> Training and test sets split')
- print(' Available values: [0.0, 1.0] (default = 0.2)')
- print(' -v, --verbose Increase verbosity level')
- print(' -x, --explain=<string> Explain a decision for a given comma-separated sample (default: none)')
- print(' -X, --xtype=<string> Type of explanation to compute: abductive or contrastive')
diff --git a/utils.py b/utils.py
index fc6dfe1a5ce67a3a9e1f5092745f9b7529e7e39b..d171f1b1a02928f3a631e47a6972ba220088d20b 100644
--- a/utils.py
+++ b/utils.py
@@ -10,10 +10,6 @@ from pages.application.RandomForest.utils import xrf
from pages.application.RandomForest.utils.xrf import *
sys.modules['xrf'] = xrf
-from pages.application.RandomForest.utils import options
-sys.modules['options'] = options
-
-
def parse_contents_graph(contents, filename):
content_type, content_string = contents.split(',')
decoded = base64.b64decode(content_string)