python3-chardet 2.0.1-1 / usr / lib / python3 / dist-packages / chardet / jpcntx.py

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######################## 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 #########################

from . 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 = False # If this flag is set to 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 = 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, aBuf):
        return -1, 1
        
class SJISContextAnalysis(JapaneseContextAnalysis):
    def get_order(self, aBuf):
        if not aBuf: return -1, 1
        # find out current char's byte length
        if ((aBuf[0] >= 0x81) and (aBuf[0] <= 0x9F)) or \
           ((aBuf[0] >= 0xE0) and (aBuf[0] <= 0xFC)):
            charLen = 2
        else:
            charLen = 1

        # return its order if it is hiragana
        if len(aBuf) > 1:
            if (aBuf[0] == 202) and \
               (aBuf[1] >= 0x9F) and \
               (aBuf[1] <= 0xF1):
                return aBuf[1] - 0x9F, charLen

        return -1, charLen

class EUCJPContextAnalysis(JapaneseContextAnalysis):
    def get_order(self, aBuf):
        if not aBuf: return -1, 1
        # find out current char's byte length
        if (aBuf[0] == 0x8E) or \
           ((aBuf[0] >= 0xA1) and (aBuf[0] <= 0xFE)):
            charLen = 2
        elif aBuf[0] == 0x8F:
            charLen = 3
        else:
            charLen = 1

        # return its order if it is hiragana
        if len(aBuf) > 1:
            if (aBuf[0] == 0xA4) and \
               (aBuf[1] >= 0xA1) and \
               (aBuf[1] <= 0xF3):
                return aBuf[1] - 0xA1, charLen

        return -1, charLen

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