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10/02/2024 07:52:55 PM
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__init__.py
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__pycache__
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big5freq.py
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big5prober.py
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chardetect.py
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chardistribution.py
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charsetgroupprober.py
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charsetprober.py
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codingstatemachine.py
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compat.py
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constants.py
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cp949prober.py
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escprober.py
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escsm.py
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eucjpprober.py
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euckrfreq.py
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euckrprober.py
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euctwfreq.py
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euctwprober.py
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gb2312freq.py
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gb2312prober.py
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hebrewprober.py
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jisfreq.py
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jpcntx.py
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langbulgarianmodel.py
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langcyrillicmodel.py
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langgreekmodel.py
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langhebrewmodel.py
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langhungarianmodel.py
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langthaimodel.py
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latin1prober.py
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mbcharsetprober.py
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mbcsgroupprober.py
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mbcssm.py
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sbcharsetprober.py
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sbcsgroupprober.py
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sjisprober.py
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universaldetector.py
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utf8prober.py
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Editing: sbcharsetprober.py
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######################## BEGIN LICENSE BLOCK ######################## # The Original Code is Mozilla Universal charset detector code. # # The Initial Developer of the Original Code is # Netscape Communications Corporation. # Portions created by the Initial Developer are Copyright (C) 2001 # the Initial Developer. All Rights Reserved. # # Contributor(s): # Mark Pilgrim - port to Python # Shy Shalom - original C code # # 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 sys from . import constants from .charsetprober import CharSetProber from .compat import wrap_ord SAMPLE_SIZE = 64 SB_ENOUGH_REL_THRESHOLD = 1024 POSITIVE_SHORTCUT_THRESHOLD = 0.95 NEGATIVE_SHORTCUT_THRESHOLD = 0.05 SYMBOL_CAT_ORDER = 250 NUMBER_OF_SEQ_CAT = 4 POSITIVE_CAT = NUMBER_OF_SEQ_CAT - 1 #NEGATIVE_CAT = 0 class SingleByteCharSetProber(CharSetProber): def __init__(self, model, reversed=False, nameProber=None): CharSetProber.__init__(self) self._mModel = model # TRUE if we need to reverse every pair in the model lookup self._mReversed = reversed # Optional auxiliary prober for name decision self._mNameProber = nameProber self.reset() def reset(self): CharSetProber.reset(self) # char order of last character self._mLastOrder = 255 self._mSeqCounters = [0] * NUMBER_OF_SEQ_CAT self._mTotalSeqs = 0 self._mTotalChar = 0 # characters that fall in our sampling range self._mFreqChar = 0 def get_charset_name(self): if self._mNameProber: return self._mNameProber.get_charset_name() else: return self._mModel['charsetName'] def feed(self, aBuf): if not self._mModel['keepEnglishLetter']: aBuf = self.filter_without_english_letters(aBuf) aLen = len(aBuf) if not aLen: return self.get_state() for c in aBuf: order = self._mModel['charToOrderMap'][wrap_ord(c)] if order < SYMBOL_CAT_ORDER: self._mTotalChar += 1 if order < SAMPLE_SIZE: self._mFreqChar += 1 if self._mLastOrder < SAMPLE_SIZE: self._mTotalSeqs += 1 if not self._mReversed: i = (self._mLastOrder * SAMPLE_SIZE) + order model = self._mModel['precedenceMatrix'][i] else: # reverse the order of the letters in the lookup i = (order * SAMPLE_SIZE) + self._mLastOrder model = self._mModel['precedenceMatrix'][i] self._mSeqCounters[model] += 1 self._mLastOrder = order if self.get_state() == constants.eDetecting: if self._mTotalSeqs > SB_ENOUGH_REL_THRESHOLD: cf = self.get_confidence() if cf > POSITIVE_SHORTCUT_THRESHOLD: if constants._debug: sys.stderr.write('%s confidence = %s, we have a' 'winner\n' % (self._mModel['charsetName'], cf)) self._mState = constants.eFoundIt elif cf < NEGATIVE_SHORTCUT_THRESHOLD: if constants._debug: sys.stderr.write('%s confidence = %s, below negative' 'shortcut threshhold %s\n' % (self._mModel['charsetName'], cf, NEGATIVE_SHORTCUT_THRESHOLD)) self._mState = constants.eNotMe return self.get_state() def get_confidence(self): r = 0.01 if self._mTotalSeqs > 0: r = ((1.0 * self._mSeqCounters[POSITIVE_CAT]) / self._mTotalSeqs / self._mModel['mTypicalPositiveRatio']) r = r * self._mFreqChar / self._mTotalChar if r >= 1.0: r = 0.99 return r