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Edit File : sbcharsetprober.py \| Size : 5.52 KB
######################## 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 ######################### from .charsetprober import CharSetProber from .enums import CharacterCategory, ProbingState, SequenceLikelihood class SingleByteCharSetProber(CharSetProber): SAMPLE_SIZE = 64 SB_ENOUGH_REL_THRESHOLD = 1024 # 0.25 * SAMPLE_SIZE^2 POSITIVE_SHORTCUT_THRESHOLD = 0.95 NEGATIVE_SHORTCUT_THRESHOLD = 0.05 def __init__(self, model, reversed=False, name_prober=None): super(SingleByteCharSetProber, self).__init__() self._model = model # TRUE if we need to reverse every pair in the model lookup self._reversed = reversed # Optional auxiliary prober for name decision self._name_prober = name_prober self._last_order = None self._seq_counters = None self._total_seqs = None self._total_char = None self._freq_char = None self.reset() def reset(self): super(SingleByteCharSetProber, self).reset() # char order of last character self._last_order = 255 self._seq_counters = [0] * SequenceLikelihood.get_num_categories() self._total_seqs = 0 self._total_char = 0 # characters that fall in our sampling range self._freq_char = 0 @property def charset_name(self): if self._name_prober: return self._name_prober.charset_name else: return self._model['charset_name'] @property def language(self): if self._name_prober: return self._name_prober.language else: return self._model.get('language') def feed(self, byte_str): if not self._model['keep_english_letter']: byte_str = self.filter_international_words(byte_str) if not byte_str: return self.state char_to_order_map = self._model['char_to_order_map'] for i, c in enumerate(byte_str): # XXX: Order is in range 1-64, so one would think we want 0-63 here, # but that leads to 27 more test failures than before. order = char_to_order_map[c] # XXX: This was SYMBOL_CAT_ORDER before, with a value of 250, but # CharacterCategory.SYMBOL is actually 253, so we use CONTROL # to make it closer to the original intent. The only difference # is whether or not we count digits and control characters for # _total_char purposes. if order < CharacterCategory.CONTROL: self._total_char += 1 if order < self.SAMPLE_SIZE: self._freq_char += 1 if self._last_order < self.SAMPLE_SIZE: self._total_seqs += 1 if not self._reversed: i = (self._last_order * self.SAMPLE_SIZE) + order model = self._model['precedence_matrix'][i] else: # reverse the order of the letters in the lookup i = (order * self.SAMPLE_SIZE) + self._last_order model = self._model['precedence_matrix'][i] self._seq_counters[model] += 1 self._last_order = order charset_name = self._model['charset_name'] if self.state == ProbingState.DETECTING: if self._total_seqs > self.SB_ENOUGH_REL_THRESHOLD: confidence = self.get_confidence() if confidence > self.POSITIVE_SHORTCUT_THRESHOLD: self.logger.debug('%s confidence = %s, we have a winner', charset_name, confidence) self._state = ProbingState.FOUND_IT elif confidence < self.NEGATIVE_SHORTCUT_THRESHOLD: self.logger.debug('%s confidence = %s, below negative ' 'shortcut threshhold %s', charset_name, confidence, self.NEGATIVE_SHORTCUT_THRESHOLD) self._state = ProbingState.NOT_ME return self.state def get_confidence(self): r = 0.01 if self._total_seqs > 0: r = ((1.0 * self._seq_counters[SequenceLikelihood.POSITIVE]) / self._total_seqs / self._model['typical_positive_ratio']) r = r * self._freq_char / self._total_char if r >= 1.0: r = 0.99 return r Back

Edit File : sbcharsetprober.py | Size : 5.52 KB

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

from .charsetprober import CharSetProber
from .enums import CharacterCategory, ProbingState, SequenceLikelihood

class SingleByteCharSetProber(CharSetProber):
    SAMPLE_SIZE = 64
    SB_ENOUGH_REL_THRESHOLD = 1024  #  0.25 * SAMPLE_SIZE^2
    POSITIVE_SHORTCUT_THRESHOLD = 0.95
    NEGATIVE_SHORTCUT_THRESHOLD = 0.05

def __init__(self, model, reversed=False, name_prober=None):
        super(SingleByteCharSetProber, self).__init__()
        self._model = model
        # TRUE if we need to reverse every pair in the model lookup
        self._reversed = reversed
        # Optional auxiliary prober for name decision
        self._name_prober = name_prober
        self._last_order = None
        self._seq_counters = None
        self._total_seqs = None
        self._total_char = None
        self._freq_char = None
        self.reset()

def reset(self):
        super(SingleByteCharSetProber, self).reset()
        # char order of last character
        self._last_order = 255
        self._seq_counters = [0] * SequenceLikelihood.get_num_categories()
        self._total_seqs = 0
        self._total_char = 0
        # characters that fall in our sampling range
        self._freq_char = 0

@property
    def charset_name(self):
        if self._name_prober:
            return self._name_prober.charset_name
        else:
            return self._model['charset_name']

@property
    def language(self):
        if self._name_prober:
            return self._name_prober.language
        else:
            return self._model.get('language')

def feed(self, byte_str):
        if not self._model['keep_english_letter']:
            byte_str = self.filter_international_words(byte_str)
        if not byte_str:
            return self.state
        char_to_order_map = self._model['char_to_order_map']
        for i, c in enumerate(byte_str):
            # XXX: Order is in range 1-64, so one would think we want 0-63 here,
            #      but that leads to 27 more test failures than before.
            order = char_to_order_map[c]
            # XXX: This was SYMBOL_CAT_ORDER before, with a value of 250, but
            #      CharacterCategory.SYMBOL is actually 253, so we use CONTROL
            #      to make it closer to the original intent. The only difference
            #      is whether or not we count digits and control characters for
            #      _total_char purposes.
            if order < CharacterCategory.CONTROL:
                self._total_char += 1
            if order < self.SAMPLE_SIZE:
                self._freq_char += 1
                if self._last_order < self.SAMPLE_SIZE:
                    self._total_seqs += 1
                    if not self._reversed:
                        i = (self._last_order * self.SAMPLE_SIZE) + order
                        model = self._model['precedence_matrix'][i]
                    else:  # reverse the order of the letters in the lookup
                        i = (order * self.SAMPLE_SIZE) + self._last_order
                        model = self._model['precedence_matrix'][i]
                    self._seq_counters[model] += 1
            self._last_order = order

charset_name = self._model['charset_name']
        if self.state == ProbingState.DETECTING:
            if self._total_seqs > self.SB_ENOUGH_REL_THRESHOLD:
                confidence = self.get_confidence()
                if confidence > self.POSITIVE_SHORTCUT_THRESHOLD:
                    self.logger.debug('%s confidence = %s, we have a winner',
                                      charset_name, confidence)
                    self._state = ProbingState.FOUND_IT
                elif confidence < self.NEGATIVE_SHORTCUT_THRESHOLD:
                    self.logger.debug('%s confidence = %s, below negative '
                                      'shortcut threshhold %s', charset_name,
                                      confidence,
                                      self.NEGATIVE_SHORTCUT_THRESHOLD)
                    self._state = ProbingState.NOT_ME

return self.state

def get_confidence(self):
        r = 0.01
        if self._total_seqs > 0:
            r = ((1.0 * self._seq_counters[SequenceLikelihood.POSITIVE]) /
                 self._total_seqs / self._model['typical_positive_ratio'])
            r = r * self._freq_char / self._total_char
            if r >= 1.0:
                r = 0.99
        return r

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