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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 #########################
+
+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