update random forest for faster, clean callbacks

pages/application/RandomForest/utils/options.py

-#!/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')

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)