/usr/share/pyshared/chardet/jpcntx.py is in python-chardet 2.0.1-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 | ######################## BEGIN LICENSE BLOCK ########################
# The Original Code is Mozilla Communicator client code.
#
# The Initial Developer of the Original Code is
# Netscape Communications Corporation.
# Portions created by the Initial Developer are Copyright (C) 1998
# the Initial Developer. All Rights Reserved.
#
# Contributor(s):
#   Mark Pilgrim - port to Python
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
# 
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
# Lesser General Public License for more details.
# 
# You should have received a copy of the GNU Lesser General Public
# License along with this library; if not, write to the Free Software
# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
# 02110-1301  USA
######################### END LICENSE BLOCK #########################
import constants
NUM_OF_CATEGORY = 6
DONT_KNOW = -1
ENOUGH_REL_THRESHOLD = 100
MAX_REL_THRESHOLD = 1000
MINIMUM_DATA_THRESHOLD = 4
# This is hiragana 2-char sequence table, the number in each cell represents its frequency category
jp2CharContext = ( \
(0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1),
(2,4,0,4,0,3,0,4,0,3,4,4,4,2,4,3,3,4,3,2,3,3,4,2,3,3,3,2,4,1,4,3,3,1,5,4,3,4,3,4,3,5,3,0,3,5,4,2,0,3,1,0,3,3,0,3,3,0,1,1,0,4,3,0,3,3,0,4,0,2,0,3,5,5,5,5,4,0,4,1,0,3,4),
(0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2),
(0,4,0,5,0,5,0,4,0,4,5,4,4,3,5,3,5,1,5,3,4,3,4,4,3,4,3,3,4,3,5,4,4,3,5,5,3,5,5,5,3,5,5,3,4,5,5,3,1,3,2,0,3,4,0,4,2,0,4,2,1,5,3,2,3,5,0,4,0,2,0,5,4,4,5,4,5,0,4,0,0,4,4),
(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,3,0,4,0,3,0,3,0,4,5,4,3,3,3,3,4,3,5,4,4,3,5,4,4,3,4,3,4,4,4,4,5,3,4,4,3,4,5,5,4,5,5,1,4,5,4,3,0,3,3,1,3,3,0,4,4,0,3,3,1,5,3,3,3,5,0,4,0,3,0,4,4,3,4,3,3,0,4,1,1,3,4),
(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,4,0,3,0,3,0,4,0,3,4,4,3,2,2,1,2,1,3,1,3,3,3,3,3,4,3,1,3,3,5,3,3,0,4,3,0,5,4,3,3,5,4,4,3,4,4,5,0,1,2,0,1,2,0,2,2,0,1,0,0,5,2,2,1,4,0,3,0,1,0,4,4,3,5,4,3,0,2,1,0,4,3),
(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,3,0,5,0,4,0,2,1,4,4,2,4,1,4,2,4,2,4,3,3,3,4,3,3,3,3,1,4,2,3,3,3,1,4,4,1,1,1,4,3,3,2,0,2,4,3,2,0,3,3,0,3,1,1,0,0,0,3,3,0,4,2,2,3,4,0,4,0,3,0,4,4,5,3,4,4,0,3,0,0,1,4),
(1,4,0,4,0,4,0,4,0,3,5,4,4,3,4,3,5,4,3,3,4,3,5,4,4,4,4,3,4,2,4,3,3,1,5,4,3,2,4,5,4,5,5,4,4,5,4,4,0,3,2,2,3,3,0,4,3,1,3,2,1,4,3,3,4,5,0,3,0,2,0,4,5,5,4,5,4,0,4,0,0,5,4),
(0,5,0,5,0,4,0,3,0,4,4,3,4,3,3,3,4,0,4,4,4,3,4,3,4,3,3,1,4,2,4,3,4,0,5,4,1,4,5,4,4,5,3,2,4,3,4,3,2,4,1,3,3,3,2,3,2,0,4,3,3,4,3,3,3,4,0,4,0,3,0,4,5,4,4,4,3,0,4,1,0,1,3),
(0,3,1,4,0,3,0,2,0,3,4,4,3,1,4,2,3,3,4,3,4,3,4,3,4,4,3,2,3,1,5,4,4,1,4,4,3,5,4,4,3,5,5,4,3,4,4,3,1,2,3,1,2,2,0,3,2,0,3,1,0,5,3,3,3,4,3,3,3,3,4,4,4,4,5,4,2,0,3,3,2,4,3),
(0,2,0,3,0,1,0,1,0,0,3,2,0,0,2,0,1,0,2,1,3,3,3,1,2,3,1,0,1,0,4,2,1,1,3,3,0,4,3,3,1,4,3,3,0,3,3,2,0,0,0,0,1,0,0,2,0,0,0,0,0,4,1,0,2,3,2,2,2,1,3,3,3,4,4,3,2,0,3,1,0,3,3),
(0,4,0,4,0,3,0,3,0,4,4,4,3,3,3,3,3,3,4,3,4,2,4,3,4,3,3,2,4,3,4,5,4,1,4,5,3,5,4,5,3,5,4,0,3,5,5,3,1,3,3,2,2,3,0,3,4,1,3,3,2,4,3,3,3,4,0,4,0,3,0,4,5,4,4,5,3,0,4,1,0,3,4),
(0,2,0,3,0,3,0,0,0,2,2,2,1,0,1,0,0,0,3,0,3,0,3,0,1,3,1,0,3,1,3,3,3,1,3,3,3,0,1,3,1,3,4,0,0,3,1,1,0,3,2,0,0,0,0,1,3,0,1,0,0,3,3,2,0,3,0,0,0,0,0,3,4,3,4,3,3,0,3,0,0,2,3),
(2,3,0,3,0,2,0,1,0,3,3,4,3,1,3,1,1,1,3,1,4,3,4,3,3,3,0,0,3,1,5,4,3,1,4,3,2,5,5,4,4,4,4,3,3,4,4,4,0,2,1,1,3,2,0,1,2,0,0,1,0,4,1,3,3,3,0,3,0,1,0,4,4,4,5,5,3,0,2,0,0,4,4),
(0,2,0,1,0,3,1,3,0,2,3,3,3,0,3,1,0,0,3,0,3,2,3,1,3,2,1,1,0,0,4,2,1,0,2,3,1,4,3,2,0,4,4,3,1,3,1,3,0,1,0,0,1,0,0,0,1,0,0,0,0,4,1,1,1,2,0,3,0,0,0,3,4,2,4,3,2,0,1,0,0,3,3),
(0,1,0,4,0,5,0,4,0,2,4,4,2,3,3,2,3,3,5,3,3,3,4,3,4,2,3,0,4,3,3,3,4,1,4,3,2,1,5,5,3,4,5,1,3,5,4,2,0,3,3,0,1,3,0,4,2,0,1,3,1,4,3,3,3,3,0,3,0,1,0,3,4,4,4,5,5,0,3,0,1,4,5),
(0,2,0,3,0,3,0,0,0,2,3,1,3,0,4,0,1,1,3,0,3,4,3,2,3,1,0,3,3,2,3,1,3,0,2,3,0,2,1,4,1,2,2,0,0,3,3,0,0,2,0,0,0,1,0,0,0,0,2,2,0,3,2,1,3,3,0,2,0,2,0,0,3,3,1,2,4,0,3,0,2,2,3),
(2,4,0,5,0,4,0,4,0,2,4,4,4,3,4,3,3,3,1,2,4,3,4,3,4,4,5,0,3,3,3,3,2,0,4,3,1,4,3,4,1,4,4,3,3,4,4,3,1,2,3,0,4,2,0,4,1,0,3,3,0,4,3,3,3,4,0,4,0,2,0,3,5,3,4,5,2,0,3,0,0,4,5),
(0,3,0,4,0,1,0,1,0,1,3,2,2,1,3,0,3,0,2,0,2,0,3,0,2,0,0,0,1,0,1,1,0,0,3,1,0,0,0,4,0,3,1,0,2,1,3,0,0,0,0,0,0,3,0,0,0,0,0,0,0,4,2,2,3,1,0,3,0,0,0,1,4,4,4,3,0,0,4,0,0,1,4),
(1,4,1,5,0,3,0,3,0,4,5,4,4,3,5,3,3,4,4,3,4,1,3,3,3,3,2,1,4,1,5,4,3,1,4,4,3,5,4,4,3,5,4,3,3,4,4,4,0,3,3,1,2,3,0,3,1,0,3,3,0,5,4,4,4,4,4,4,3,3,5,4,4,3,3,5,4,0,3,2,0,4,4),
(0,2,0,3,0,1,0,0,0,1,3,3,3,2,4,1,3,0,3,1,3,0,2,2,1,1,0,0,2,0,4,3,1,0,4,3,0,4,4,4,1,4,3,1,1,3,3,1,0,2,0,0,1,3,0,0,0,0,2,0,0,4,3,2,4,3,5,4,3,3,3,4,3,3,4,3,3,0,2,1,0,3,3),
(0,2,0,4,0,3,0,2,0,2,5,5,3,4,4,4,4,1,4,3,3,0,4,3,4,3,1,3,3,2,4,3,0,3,4,3,0,3,4,4,2,4,4,0,4,5,3,3,2,2,1,1,1,2,0,1,5,0,3,3,2,4,3,3,3,4,0,3,0,2,0,4,4,3,5,5,0,0,3,0,2,3,3),
(0,3,0,4,0,3,0,1,0,3,4,3,3,1,3,3,3,0,3,1,3,0,4,3,3,1,1,0,3,0,3,3,0,0,4,4,0,1,5,4,3,3,5,0,3,3,4,3,0,2,0,1,1,1,0,1,3,0,1,2,1,3,3,2,3,3,0,3,0,1,0,1,3,3,4,4,1,0,1,2,2,1,3),
(0,1,0,4,0,4,0,3,0,1,3,3,3,2,3,1,1,0,3,0,3,3,4,3,2,4,2,0,1,0,4,3,2,0,4,3,0,5,3,3,2,4,4,4,3,3,3,4,0,1,3,0,0,1,0,0,1,0,0,0,0,4,2,3,3,3,0,3,0,0,0,4,4,4,5,3,2,0,3,3,0,3,5),
(0,2,0,3,0,0,0,3,0,1,3,0,2,0,0,0,1,0,3,1,1,3,3,0,0,3,0,0,3,0,2,3,1,0,3,1,0,3,3,2,0,4,2,2,0,2,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,2,1,2,0,1,0,1,0,0,0,1,3,1,2,0,0,0,1,0,0,1,4),
(0,3,0,3,0,5,0,1,0,2,4,3,1,3,3,2,1,1,5,2,1,0,5,1,2,0,0,0,3,3,2,2,3,2,4,3,0,0,3,3,1,3,3,0,2,5,3,4,0,3,3,0,1,2,0,2,2,0,3,2,0,2,2,3,3,3,0,2,0,1,0,3,4,4,2,5,4,0,3,0,0,3,5),
(0,3,0,3,0,3,0,1,0,3,3,3,3,0,3,0,2,0,2,1,1,0,2,0,1,0,0,0,2,1,0,0,1,0,3,2,0,0,3,3,1,2,3,1,0,3,3,0,0,1,0,0,0,0,0,2,0,0,0,0,0,2,3,1,2,3,0,3,0,1,0,3,2,1,0,4,3,0,1,1,0,3,3),
(0,4,0,5,0,3,0,3,0,4,5,5,4,3,5,3,4,3,5,3,3,2,5,3,4,4,4,3,4,3,4,5,5,3,4,4,3,4,4,5,4,4,4,3,4,5,5,4,2,3,4,2,3,4,0,3,3,1,4,3,2,4,3,3,5,5,0,3,0,3,0,5,5,5,5,4,4,0,4,0,1,4,4),
(0,4,0,4,0,3,0,3,0,3,5,4,4,2,3,2,5,1,3,2,5,1,4,2,3,2,3,3,4,3,3,3,3,2,5,4,1,3,3,5,3,4,4,0,4,4,3,1,1,3,1,0,2,3,0,2,3,0,3,0,0,4,3,1,3,4,0,3,0,2,0,4,4,4,3,4,5,0,4,0,0,3,4),
(0,3,0,3,0,3,1,2,0,3,4,4,3,3,3,0,2,2,4,3,3,1,3,3,3,1,1,0,3,1,4,3,2,3,4,4,2,4,4,4,3,4,4,3,2,4,4,3,1,3,3,1,3,3,0,4,1,0,2,2,1,4,3,2,3,3,5,4,3,3,5,4,4,3,3,0,4,0,3,2,2,4,4),
(0,2,0,1,0,0,0,0,0,1,2,1,3,0,0,0,0,0,2,0,1,2,1,0,0,1,0,0,0,0,3,0,0,1,0,1,1,3,1,0,0,0,1,1,0,1,1,0,0,0,0,0,2,0,0,0,0,0,0,0,0,1,1,2,2,0,3,4,0,0,0,1,1,0,0,1,0,0,0,0,0,1,1),
(0,1,0,0,0,1,0,0,0,0,4,0,4,1,4,0,3,0,4,0,3,0,4,0,3,0,3,0,4,1,5,1,4,0,0,3,0,5,0,5,2,0,1,0,0,0,2,1,4,0,1,3,0,0,3,0,0,3,1,1,4,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0),
(1,4,0,5,0,3,0,2,0,3,5,4,4,3,4,3,5,3,4,3,3,0,4,3,3,3,3,3,3,2,4,4,3,1,3,4,4,5,4,4,3,4,4,1,3,5,4,3,3,3,1,2,2,3,3,1,3,1,3,3,3,5,3,3,4,5,0,3,0,3,0,3,4,3,4,4,3,0,3,0,2,4,3),
(0,1,0,4,0,0,0,0,0,1,4,0,4,1,4,2,4,0,3,0,1,0,1,0,0,0,0,0,2,0,3,1,1,1,0,3,0,0,0,1,2,1,0,0,1,1,1,1,0,1,0,0,0,1,0,0,3,0,0,0,0,3,2,0,2,2,0,1,0,0,0,2,3,2,3,3,0,0,0,0,2,1,0),
(0,5,1,5,0,3,0,3,0,5,4,4,5,1,5,3,3,0,4,3,4,3,5,3,4,3,3,2,4,3,4,3,3,0,3,3,1,4,4,3,4,4,4,3,4,5,5,3,2,3,1,1,3,3,1,3,1,1,3,3,2,4,5,3,3,5,0,4,0,3,0,4,4,3,5,3,3,0,3,4,0,4,3),
(0,5,0,5,0,3,0,2,0,4,4,3,5,2,4,3,3,3,4,4,4,3,5,3,5,3,3,1,4,0,4,3,3,0,3,3,0,4,4,4,4,5,4,3,3,5,5,3,2,3,1,2,3,2,0,1,0,0,3,2,2,4,4,3,1,5,0,4,0,3,0,4,3,1,3,2,1,0,3,3,0,3,3),
(0,4,0,5,0,5,0,4,0,4,5,5,5,3,4,3,3,2,5,4,4,3,5,3,5,3,4,0,4,3,4,4,3,2,4,4,3,4,5,4,4,5,5,0,3,5,5,4,1,3,3,2,3,3,1,3,1,0,4,3,1,4,4,3,4,5,0,4,0,2,0,4,3,4,4,3,3,0,4,0,0,5,5),
(0,4,0,4,0,5,0,1,1,3,3,4,4,3,4,1,3,0,5,1,3,0,3,1,3,1,1,0,3,0,3,3,4,0,4,3,0,4,4,4,3,4,4,0,3,5,4,1,0,3,0,0,2,3,0,3,1,0,3,1,0,3,2,1,3,5,0,3,0,1,0,3,2,3,3,4,4,0,2,2,0,4,4),
(2,4,0,5,0,4,0,3,0,4,5,5,4,3,5,3,5,3,5,3,5,2,5,3,4,3,3,4,3,4,5,3,2,1,5,4,3,2,3,4,5,3,4,1,2,5,4,3,0,3,3,0,3,2,0,2,3,0,4,1,0,3,4,3,3,5,0,3,0,1,0,4,5,5,5,4,3,0,4,2,0,3,5),
(0,5,0,4,0,4,0,2,0,5,4,3,4,3,4,3,3,3,4,3,4,2,5,3,5,3,4,1,4,3,4,4,4,0,3,5,0,4,4,4,4,5,3,1,3,4,5,3,3,3,3,3,3,3,0,2,2,0,3,3,2,4,3,3,3,5,3,4,1,3,3,5,3,2,0,0,0,0,4,3,1,3,3),
(0,1,0,3,0,3,0,1,0,1,3,3,3,2,3,3,3,0,3,0,0,0,3,1,3,0,0,0,2,2,2,3,0,0,3,2,0,1,2,4,1,3,3,0,0,3,3,3,0,1,0,0,2,1,0,0,3,0,3,1,0,3,0,0,1,3,0,2,0,1,0,3,3,1,3,3,0,0,1,1,0,3,3),
(0,2,0,3,0,2,1,4,0,2,2,3,1,1,3,1,1,0,2,0,3,1,2,3,1,3,0,0,1,0,4,3,2,3,3,3,1,4,2,3,3,3,3,1,0,3,1,4,0,1,1,0,1,2,0,1,1,0,1,1,0,3,1,3,2,2,0,1,0,0,0,2,3,3,3,1,0,0,0,0,0,2,3),
(0,5,0,4,0,5,0,2,0,4,5,5,3,3,4,3,3,1,5,4,4,2,4,4,4,3,4,2,4,3,5,5,4,3,3,4,3,3,5,5,4,5,5,1,3,4,5,3,1,4,3,1,3,3,0,3,3,1,4,3,1,4,5,3,3,5,0,4,0,3,0,5,3,3,1,4,3,0,4,0,1,5,3),
(0,5,0,5,0,4,0,2,0,4,4,3,4,3,3,3,3,3,5,4,4,4,4,4,4,5,3,3,5,2,4,4,4,3,4,4,3,3,4,4,5,5,3,3,4,3,4,3,3,4,3,3,3,3,1,2,2,1,4,3,3,5,4,4,3,4,0,4,0,3,0,4,4,4,4,4,1,0,4,2,0,2,4),
(0,4,0,4,0,3,0,1,0,3,5,2,3,0,3,0,2,1,4,2,3,3,4,1,4,3,3,2,4,1,3,3,3,0,3,3,0,0,3,3,3,5,3,3,3,3,3,2,0,2,0,0,2,0,0,2,0,0,1,0,0,3,1,2,2,3,0,3,0,2,0,4,4,3,3,4,1,0,3,0,0,2,4),
(0,0,0,4,0,0,0,0,0,0,1,0,1,0,2,0,0,0,0,0,1,0,2,0,1,0,0,0,0,0,3,1,3,0,3,2,0,0,0,1,0,3,2,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,4,0,2,0,0,0,0,0,0,2),
(0,2,1,3,0,2,0,2,0,3,3,3,3,1,3,1,3,3,3,3,3,3,4,2,2,1,2,1,4,0,4,3,1,3,3,3,2,4,3,5,4,3,3,3,3,3,3,3,0,1,3,0,2,0,0,1,0,0,1,0,0,4,2,0,2,3,0,3,3,0,3,3,4,2,3,1,4,0,1,2,0,2,3),
(0,3,0,3,0,1,0,3,0,2,3,3,3,0,3,1,2,0,3,3,2,3,3,2,3,2,3,1,3,0,4,3,2,0,3,3,1,4,3,3,2,3,4,3,1,3,3,1,1,0,1,1,0,1,0,1,0,1,0,0,0,4,1,1,0,3,0,3,1,0,2,3,3,3,3,3,1,0,0,2,0,3,3),
(0,0,0,0,0,0,0,0,0,0,3,0,2,0,3,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,3,0,3,0,3,1,0,1,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,2,0,2,3,0,0,0,0,0,0,0,0,3),
(0,2,0,3,1,3,0,3,0,2,3,3,3,1,3,1,3,1,3,1,3,3,3,1,3,0,2,3,1,1,4,3,3,2,3,3,1,2,2,4,1,3,3,0,1,4,2,3,0,1,3,0,3,0,0,1,3,0,2,0,0,3,3,2,1,3,0,3,0,2,0,3,4,4,4,3,1,0,3,0,0,3,3),
(0,2,0,1,0,2,0,0,0,1,3,2,2,1,3,0,1,1,3,0,3,2,3,1,2,0,2,0,1,1,3,3,3,0,3,3,1,1,2,3,2,3,3,1,2,3,2,0,0,1,0,0,0,0,0,0,3,0,1,0,0,2,1,2,1,3,0,3,0,0,0,3,4,4,4,3,2,0,2,0,0,2,4),
(0,0,0,1,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,2,2,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,3,1,0,0,0,0,0,0,0,3),
(0,3,0,3,0,2,0,3,0,3,3,3,2,3,2,2,2,0,3,1,3,3,3,2,3,3,0,0,3,0,3,2,2,0,2,3,1,4,3,4,3,3,2,3,1,5,4,4,0,3,1,2,1,3,0,3,1,1,2,0,2,3,1,3,1,3,0,3,0,1,0,3,3,4,4,2,1,0,2,1,0,2,4),
(0,1,0,3,0,1,0,2,0,1,4,2,5,1,4,0,2,0,2,1,3,1,4,0,2,1,0,0,2,1,4,1,1,0,3,3,0,5,1,3,2,3,3,1,0,3,2,3,0,1,0,0,0,0,0,0,1,0,0,0,0,4,0,1,0,3,0,2,0,1,0,3,3,3,4,3,3,0,0,0,0,2,3),
(0,0,0,1,0,0,0,0,0,0,2,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,0,0,1,0,0,0,0,0,3),
(0,1,0,3,0,4,0,3,0,2,4,3,1,0,3,2,2,1,3,1,2,2,3,1,1,1,2,1,3,0,1,2,0,1,3,2,1,3,0,5,5,1,0,0,1,3,2,1,0,3,0,0,1,0,0,0,0,0,3,4,0,1,1,1,3,2,0,2,0,1,0,2,3,3,1,2,3,0,1,0,1,0,4),
(0,0,0,1,0,3,0,3,0,2,2,1,0,0,4,0,3,0,3,1,3,0,3,0,3,0,1,0,3,0,3,1,3,0,3,3,0,0,1,2,1,1,1,0,1,2,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,2,2,1,2,0,0,2,0,0,0,0,2,3,3,3,3,0,0,0,0,1,4),
(0,0,0,3,0,3,0,0,0,0,3,1,1,0,3,0,1,0,2,0,1,0,0,0,0,0,0,0,1,0,3,0,2,0,2,3,0,0,2,2,3,1,2,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,2,0,0,0,0,2,3),
(2,4,0,5,0,5,0,4,0,3,4,3,3,3,4,3,3,3,4,3,4,4,5,4,5,5,5,2,3,0,5,5,4,1,5,4,3,1,5,4,3,4,4,3,3,4,3,3,0,3,2,0,2,3,0,3,0,0,3,3,0,5,3,2,3,3,0,3,0,3,0,3,4,5,4,5,3,0,4,3,0,3,4),
(0,3,0,3,0,3,0,3,0,3,3,4,3,2,3,2,3,0,4,3,3,3,3,3,3,3,3,0,3,2,4,3,3,1,3,4,3,4,4,4,3,4,4,3,2,4,4,1,0,2,0,0,1,1,0,2,0,0,3,1,0,5,3,2,1,3,0,3,0,1,2,4,3,2,4,3,3,0,3,2,0,4,4),
(0,3,0,3,0,1,0,0,0,1,4,3,3,2,3,1,3,1,4,2,3,2,4,2,3,4,3,0,2,2,3,3,3,0,3,3,3,0,3,4,1,3,3,0,3,4,3,3,0,1,1,0,1,0,0,0,4,0,3,0,0,3,1,2,1,3,0,4,0,1,0,4,3,3,4,3,3,0,2,0,0,3,3),
(0,3,0,4,0,1,0,3,0,3,4,3,3,0,3,3,3,1,3,1,3,3,4,3,3,3,0,0,3,1,5,3,3,1,3,3,2,5,4,3,3,4,5,3,2,5,3,4,0,1,0,0,0,0,0,2,0,0,1,1,0,4,2,2,1,3,0,3,0,2,0,4,4,3,5,3,2,0,1,1,0,3,4),
(0,5,0,4,0,5,0,2,0,4,4,3,3,2,3,3,3,1,4,3,4,1,5,3,4,3,4,0,4,2,4,3,4,1,5,4,0,4,4,4,4,5,4,1,3,5,4,2,1,4,1,1,3,2,0,3,1,0,3,2,1,4,3,3,3,4,0,4,0,3,0,4,4,4,3,3,3,0,4,2,0,3,4),
(1,4,0,4,0,3,0,1,0,3,3,3,1,1,3,3,2,2,3,3,1,0,3,2,2,1,2,0,3,1,2,1,2,0,3,2,0,2,2,3,3,4,3,0,3,3,1,2,0,1,1,3,1,2,0,0,3,0,1,1,0,3,2,2,3,3,0,3,0,0,0,2,3,3,4,3,3,0,1,0,0,1,4),
(0,4,0,4,0,4,0,0,0,3,4,4,3,1,4,2,3,2,3,3,3,1,4,3,4,0,3,0,4,2,3,3,2,2,5,4,2,1,3,4,3,4,3,1,3,3,4,2,0,2,1,0,3,3,0,0,2,0,3,1,0,4,4,3,4,3,0,4,0,1,0,2,4,4,4,4,4,0,3,2,0,3,3),
(0,0,0,1,0,4,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,3,2,0,0,1,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,2),
(0,2,0,3,0,4,0,4,0,1,3,3,3,0,4,0,2,1,2,1,1,1,2,0,3,1,1,0,1,0,3,1,0,0,3,3,2,0,1,1,0,0,0,0,0,1,0,2,0,2,2,0,3,1,0,0,1,0,1,1,0,1,2,0,3,0,0,0,0,1,0,0,3,3,4,3,1,0,1,0,3,0,2),
(0,0,0,3,0,5,0,0,0,0,1,0,2,0,3,1,0,1,3,0,0,0,2,0,0,0,1,0,0,0,1,1,0,0,4,0,0,0,2,3,0,1,4,1,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,1,0,0,0,0,0,0,0,2,0,0,3,0,0,0,0,0,3),
(0,2,0,5,0,5,0,1,0,2,4,3,3,2,5,1,3,2,3,3,3,0,4,1,2,0,3,0,4,0,2,2,1,1,5,3,0,0,1,4,2,3,2,0,3,3,3,2,0,2,4,1,1,2,0,1,1,0,3,1,0,1,3,1,2,3,0,2,0,0,0,1,3,5,4,4,4,0,3,0,0,1,3),
(0,4,0,5,0,4,0,4,0,4,5,4,3,3,4,3,3,3,4,3,4,4,5,3,4,5,4,2,4,2,3,4,3,1,4,4,1,3,5,4,4,5,5,4,4,5,5,5,2,3,3,1,4,3,1,3,3,0,3,3,1,4,3,4,4,4,0,3,0,4,0,3,3,4,4,5,0,0,4,3,0,4,5),
(0,4,0,4,0,3,0,3,0,3,4,4,4,3,3,2,4,3,4,3,4,3,5,3,4,3,2,1,4,2,4,4,3,1,3,4,2,4,5,5,3,4,5,4,1,5,4,3,0,3,2,2,3,2,1,3,1,0,3,3,3,5,3,3,3,5,4,4,2,3,3,4,3,3,3,2,1,0,3,2,1,4,3),
(0,4,0,5,0,4,0,3,0,3,5,5,3,2,4,3,4,0,5,4,4,1,4,4,4,3,3,3,4,3,5,5,2,3,3,4,1,2,5,5,3,5,5,2,3,5,5,4,0,3,2,0,3,3,1,1,5,1,4,1,0,4,3,2,3,5,0,4,0,3,0,5,4,3,4,3,0,0,4,1,0,4,4),
(1,3,0,4,0,2,0,2,0,2,5,5,3,3,3,3,3,0,4,2,3,4,4,4,3,4,0,0,3,4,5,4,3,3,3,3,2,5,5,4,5,5,5,4,3,5,5,5,1,3,1,0,1,0,0,3,2,0,4,2,0,5,2,3,2,4,1,3,0,3,0,4,5,4,5,4,3,0,4,2,0,5,4),
(0,3,0,4,0,5,0,3,0,3,4,4,3,2,3,2,3,3,3,3,3,2,4,3,3,2,2,0,3,3,3,3,3,1,3,3,3,0,4,4,3,4,4,1,1,4,4,2,0,3,1,0,1,1,0,4,1,0,2,3,1,3,3,1,3,4,0,3,0,1,0,3,1,3,0,0,1,0,2,0,0,4,4),
(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,3,0,3,0,2,0,3,0,1,5,4,3,3,3,1,4,2,1,2,3,4,4,2,4,4,5,0,3,1,4,3,4,0,4,3,3,3,2,3,2,5,3,4,3,2,2,3,0,0,3,0,2,1,0,1,2,0,0,0,0,2,1,1,3,1,0,2,0,4,0,3,4,4,4,5,2,0,2,0,0,1,3),
(0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,1,0,0,1,1,0,0,0,4,2,1,1,0,1,0,3,2,0,0,3,1,1,1,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,1,0,0,0,2,0,0,0,1,4,0,4,2,1,0,0,0,0,0,1),
(0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,1,0,0,0,0,0,0,1,0,1,0,0,0,0,3,1,0,0,0,2,0,2,1,0,0,1,2,1,0,1,1,0,0,3,0,0,0,0,0,0,0,0,0,0,0,1,3,1,0,0,0,0,0,1,0,0,2,1,0,0,0,0,0,0,0,0,2),
(0,4,0,4,0,4,0,3,0,4,4,3,4,2,4,3,2,0,4,4,4,3,5,3,5,3,3,2,4,2,4,3,4,3,1,4,0,2,3,4,4,4,3,3,3,4,4,4,3,4,1,3,4,3,2,1,2,1,3,3,3,4,4,3,3,5,0,4,0,3,0,4,3,3,3,2,1,0,3,0,0,3,3),
(0,4,0,3,0,3,0,3,0,3,5,5,3,3,3,3,4,3,4,3,3,3,4,4,4,3,3,3,3,4,3,5,3,3,1,3,2,4,5,5,5,5,4,3,4,5,5,3,2,2,3,3,3,3,2,3,3,1,2,3,2,4,3,3,3,4,0,4,0,2,0,4,3,2,2,1,2,0,3,0,0,4,1),
)
class JapaneseContextAnalysis:
    def __init__(self):
        self.reset()
        
    def reset(self):
        self._mTotalRel = 0 # total sequence received
        self._mRelSample = [0] * NUM_OF_CATEGORY # category counters, each interger counts sequence in its category
        self._mNeedToSkipCharNum = 0 # if last byte in current buffer is not the last byte of a character, we need to know how many bytes to skip in next buffer
        self._mLastCharOrder = -1 # The order of previous char
        self._mDone = constants.False # If this flag is set to constants.True, detection is done and conclusion has been made
    def feed(self, aBuf, aLen):
        if self._mDone: return
        
        # The buffer we got is byte oriented, and a character may span in more than one
        # buffers. In case the last one or two byte in last buffer is not complete, we 
        # record how many byte needed to complete that character and skip these bytes here.
        # We can choose to record those bytes as well and analyse the character once it 
        # is complete, but since a character will not make much difference, by simply skipping
        # this character will simply our logic and improve performance.
        i = self._mNeedToSkipCharNum
        while i < aLen:
            order, charLen = self.get_order(aBuf[i:i+2])
            i += charLen
            if i > aLen:
                self._mNeedToSkipCharNum = i - aLen
                self._mLastCharOrder = -1
            else:
                if (order != -1) and (self._mLastCharOrder != -1):
                    self._mTotalRel += 1
                    if self._mTotalRel > MAX_REL_THRESHOLD:
                        self._mDone = constants.True
                        break
                    self._mRelSample[jp2CharContext[self._mLastCharOrder][order]] += 1
                self._mLastCharOrder = order
    def got_enough_data(self):
        return self._mTotalRel > ENOUGH_REL_THRESHOLD
    
    def get_confidence(self):
        # This is just one way to calculate confidence. It works well for me.
        if self._mTotalRel > MINIMUM_DATA_THRESHOLD:
            return (self._mTotalRel - self._mRelSample[0]) / self._mTotalRel
        else:
            return DONT_KNOW
    def get_order(self, aStr):
        return -1, 1
        
class SJISContextAnalysis(JapaneseContextAnalysis):
    def get_order(self, aStr):
        if not aStr: return -1, 1
        # find out current char's byte length
        if ((aStr[0] >= '\x81') and (aStr[0] <= '\x9F')) or \
           ((aStr[0] >= '\xE0') and (aStr[0] <= '\xFC')):
            charLen = 2
        else:
            charLen = 1
        # return its order if it is hiragana
        if len(aStr) > 1:
            if (aStr[0] == '\202') and \
               (aStr[1] >= '\x9F') and \
               (aStr[1] <= '\xF1'):
                return ord(aStr[1]) - 0x9F, charLen
        return -1, charLen
class EUCJPContextAnalysis(JapaneseContextAnalysis):
    def get_order(self, aStr):
        if not aStr: return -1, 1
        # find out current char's byte length
        if (aStr[0] == '\x8E') or \
           ((aStr[0] >= '\xA1') and (aStr[0] <= '\xFE')):
            charLen = 2
        elif aStr[0] == '\x8F':
            charLen = 3
        else:
            charLen = 1
        # return its order if it is hiragana
        if len(aStr) > 1:
            if (aStr[0] == '\xA4') and \
               (aStr[1] >= '\xA1') and \
               (aStr[1] <= '\xF3'):
                return ord(aStr[1]) - 0xA1, charLen
        return -1, charLen
 |