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| 1 ######################## BEGIN LICENSE BLOCK ######################## |
| 2 # The Original Code is Mozilla Universal charset detector code. |
| 3 # |
| 4 # The Initial Developer of the Original Code is |
| 5 # Netscape Communications Corporation. |
| 6 # Portions created by the Initial Developer are Copyright (C) 2001 |
| 7 # the Initial Developer. All Rights Reserved. |
| 8 # |
| 9 # Contributor(s): |
| 10 # Mark Pilgrim - port to Python |
| 11 # Shy Shalom - original C code |
| 12 # |
| 13 # This library is free software; you can redistribute it and/or |
| 14 # modify it under the terms of the GNU Lesser General Public |
| 15 # License as published by the Free Software Foundation; either |
| 16 # version 2.1 of the License, or (at your option) any later version. |
| 17 # |
| 18 # This library is distributed in the hope that it will be useful, |
| 19 # but WITHOUT ANY WARRANTY; without even the implied warranty of |
| 20 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
| 21 # Lesser General Public License for more details. |
| 22 # |
| 23 # You should have received a copy of the GNU Lesser General Public |
| 24 # License along with this library; if not, write to the Free Software |
| 25 # Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA |
| 26 # 02110-1301 USA |
| 27 ######################### END LICENSE BLOCK ######################### |
| 28 |
| 29 import sys |
| 30 from . import constants |
| 31 from .charsetprober import CharSetProber |
| 32 from .compat import wrap_ord |
| 33 |
| 34 SAMPLE_SIZE = 64 |
| 35 SB_ENOUGH_REL_THRESHOLD = 1024 |
| 36 POSITIVE_SHORTCUT_THRESHOLD = 0.95 |
| 37 NEGATIVE_SHORTCUT_THRESHOLD = 0.05 |
| 38 SYMBOL_CAT_ORDER = 250 |
| 39 NUMBER_OF_SEQ_CAT = 4 |
| 40 POSITIVE_CAT = NUMBER_OF_SEQ_CAT - 1 |
| 41 #NEGATIVE_CAT = 0 |
| 42 |
| 43 |
| 44 class SingleByteCharSetProber(CharSetProber): |
| 45 def __init__(self, model, reversed=False, nameProber=None): |
| 46 CharSetProber.__init__(self) |
| 47 self._mModel = model |
| 48 # TRUE if we need to reverse every pair in the model lookup |
| 49 self._mReversed = reversed |
| 50 # Optional auxiliary prober for name decision |
| 51 self._mNameProber = nameProber |
| 52 self.reset() |
| 53 |
| 54 def reset(self): |
| 55 CharSetProber.reset(self) |
| 56 # char order of last character |
| 57 self._mLastOrder = 255 |
| 58 self._mSeqCounters = [0] * NUMBER_OF_SEQ_CAT |
| 59 self._mTotalSeqs = 0 |
| 60 self._mTotalChar = 0 |
| 61 # characters that fall in our sampling range |
| 62 self._mFreqChar = 0 |
| 63 |
| 64 def get_charset_name(self): |
| 65 if self._mNameProber: |
| 66 return self._mNameProber.get_charset_name() |
| 67 else: |
| 68 return self._mModel['charsetName'] |
| 69 |
| 70 def feed(self, aBuf): |
| 71 if not self._mModel['keepEnglishLetter']: |
| 72 aBuf = self.filter_without_english_letters(aBuf) |
| 73 aLen = len(aBuf) |
| 74 if not aLen: |
| 75 return self.get_state() |
| 76 for c in aBuf: |
| 77 order = self._mModel['charToOrderMap'][wrap_ord(c)] |
| 78 if order < SYMBOL_CAT_ORDER: |
| 79 self._mTotalChar += 1 |
| 80 if order < SAMPLE_SIZE: |
| 81 self._mFreqChar += 1 |
| 82 if self._mLastOrder < SAMPLE_SIZE: |
| 83 self._mTotalSeqs += 1 |
| 84 if not self._mReversed: |
| 85 i = (self._mLastOrder * SAMPLE_SIZE) + order |
| 86 model = self._mModel['precedenceMatrix'][i] |
| 87 else: # reverse the order of the letters in the lookup |
| 88 i = (order * SAMPLE_SIZE) + self._mLastOrder |
| 89 model = self._mModel['precedenceMatrix'][i] |
| 90 self._mSeqCounters[model] += 1 |
| 91 self._mLastOrder = order |
| 92 |
| 93 if self.get_state() == constants.eDetecting: |
| 94 if self._mTotalSeqs > SB_ENOUGH_REL_THRESHOLD: |
| 95 cf = self.get_confidence() |
| 96 if cf > POSITIVE_SHORTCUT_THRESHOLD: |
| 97 if constants._debug: |
| 98 sys.stderr.write('%s confidence = %s, we have a' |
| 99 'winner\n' % |
| 100 (self._mModel['charsetName'], cf)) |
| 101 self._mState = constants.eFoundIt |
| 102 elif cf < NEGATIVE_SHORTCUT_THRESHOLD: |
| 103 if constants._debug: |
| 104 sys.stderr.write('%s confidence = %s, below negative' |
| 105 'shortcut threshhold %s\n' % |
| 106 (self._mModel['charsetName'], cf, |
| 107 NEGATIVE_SHORTCUT_THRESHOLD)) |
| 108 self._mState = constants.eNotMe |
| 109 |
| 110 return self.get_state() |
| 111 |
| 112 def get_confidence(self): |
| 113 r = 0.01 |
| 114 if self._mTotalSeqs > 0: |
| 115 r = ((1.0 * self._mSeqCounters[POSITIVE_CAT]) / self._mTotalSeqs |
| 116 / self._mModel['mTypicalPositiveRatio']) |
| 117 r = r * self._mFreqChar / self._mTotalChar |
| 118 if r >= 1.0: |
| 119 r = 0.99 |
| 120 return r |
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