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Edit File : hebrewprober.py \| Size : 13.51 KB
######################## BEGIN LICENSE BLOCK ######################## # The Original Code is Mozilla Universal charset detector code. # # The Initial Developer of the Original Code is # Shy Shalom # Portions created by the Initial Developer are Copyright (C) 2005 # 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 .charsetprober import CharSetProber from .enums import ProbingState # This prober doesn't actually recognize a language or a charset. # It is a helper prober for the use of the Hebrew model probers ### General ideas of the Hebrew charset recognition ### # # Four main charsets exist in Hebrew: # "ISO-8859-8" - Visual Hebrew # "windows-1255" - Logical Hebrew # "ISO-8859-8-I" - Logical Hebrew # "x-mac-hebrew" - ?? Logical Hebrew ?? # # Both "ISO" charsets use a completely identical set of code points, whereas # "windows-1255" and "x-mac-hebrew" are two different proper supersets of # these code points. windows-1255 defines additional characters in the range # 0x80-0x9F as some misc punctuation marks as well as some Hebrew-specific # diacritics and additional 'Yiddish' ligature letters in the range 0xc0-0xd6. # x-mac-hebrew defines similar additional code points but with a different # mapping. # # As far as an average Hebrew text with no diacritics is concerned, all four # charsets are identical with respect to code points. Meaning that for the # main Hebrew alphabet, all four map the same values to all 27 Hebrew letters # (including final letters). # # The dominant difference between these charsets is their directionality. # "Visual" directionality means that the text is ordered as if the renderer is # not aware of a BIDI rendering algorithm. The renderer sees the text and # draws it from left to right. The text itself when ordered naturally is read # backwards. A buffer of Visual Hebrew generally looks like so: # "[last word of first line spelled backwards] [whole line ordered backwards # and spelled backwards] [first word of first line spelled backwards] # [end of line] [last word of second line] ... etc' " # adding punctuation marks, numbers and English text to visual text is # naturally also "visual" and from left to right. # # "Logical" directionality means the text is ordered "naturally" according to # the order it is read. It is the responsibility of the renderer to display # the text from right to left. A BIDI algorithm is used to place general # punctuation marks, numbers and English text in the text. # # Texts in x-mac-hebrew are almost impossible to find on the Internet. From # what little evidence I could find, it seems that its general directionality # is Logical. # # To sum up all of the above, the Hebrew probing mechanism knows about two # charsets: # Visual Hebrew - "ISO-8859-8" - backwards text - Words and sentences are # backwards while line order is natural. For charset recognition purposes # the line order is unimportant (In fact, for this implementation, even # word order is unimportant). # Logical Hebrew - "windows-1255" - normal, naturally ordered text. # # "ISO-8859-8-I" is a subset of windows-1255 and doesn't need to be # specifically identified. # "x-mac-hebrew" is also identified as windows-1255. A text in x-mac-hebrew # that contain special punctuation marks or diacritics is displayed with # some unconverted characters showing as question marks. This problem might # be corrected using another model prober for x-mac-hebrew. Due to the fact # that x-mac-hebrew texts are so rare, writing another model prober isn't # worth the effort and performance hit. # #### The Prober #### # # The prober is divided between two SBCharSetProbers and a HebrewProber, # all of which are managed, created, fed data, inquired and deleted by the # SBCSGroupProber. The two SBCharSetProbers identify that the text is in # fact some kind of Hebrew, Logical or Visual. The final decision about which # one is it is made by the HebrewProber by combining final-letter scores # with the scores of the two SBCharSetProbers to produce a final answer. # # The SBCSGroupProber is responsible for stripping the original text of HTML # tags, English characters, numbers, low-ASCII punctuation characters, spaces # and new lines. It reduces any sequence of such characters to a single space. # The buffer fed to each prober in the SBCS group prober is pure text in # high-ASCII. # The two SBCharSetProbers (model probers) share the same language model: # Win1255Model. # The first SBCharSetProber uses the model normally as any other # SBCharSetProber does, to recognize windows-1255, upon which this model was # built. The second SBCharSetProber is told to make the pair-of-letter # lookup in the language model backwards. This in practice exactly simulates # a visual Hebrew model using the windows-1255 logical Hebrew model. # # The HebrewProber is not using any language model. All it does is look for # final-letter evidence suggesting the text is either logical Hebrew or visual # Hebrew. Disjointed from the model probers, the results of the HebrewProber # alone are meaningless. HebrewProber always returns 0.00 as confidence # since it never identifies a charset by itself. Instead, the pointer to the # HebrewProber is passed to the model probers as a helper "Name Prober". # When the Group prober receives a positive identification from any prober, # it asks for the name of the charset identified. If the prober queried is a # Hebrew model prober, the model prober forwards the call to the # HebrewProber to make the final decision. In the HebrewProber, the # decision is made according to the final-letters scores maintained and Both # model probers scores. The answer is returned in the form of the name of the # charset identified, either "windows-1255" or "ISO-8859-8". class HebrewProber(CharSetProber): # windows-1255 / ISO-8859-8 code points of interest FINAL_KAF = 0xea NORMAL_KAF = 0xeb FINAL_MEM = 0xed NORMAL_MEM = 0xee FINAL_NUN = 0xef NORMAL_NUN = 0xf0 FINAL_PE = 0xf3 NORMAL_PE = 0xf4 FINAL_TSADI = 0xf5 NORMAL_TSADI = 0xf6 # Minimum Visual vs Logical final letter score difference. # If the difference is below this, don't rely solely on the final letter score # distance. MIN_FINAL_CHAR_DISTANCE = 5 # Minimum Visual vs Logical model score difference. # If the difference is below this, don't rely at all on the model score # distance. MIN_MODEL_DISTANCE = 0.01 VISUAL_HEBREW_NAME = "ISO-8859-8" LOGICAL_HEBREW_NAME = "windows-1255" def __init__(self): super(HebrewProber, self).__init__() self._final_char_logical_score = None self._final_char_visual_score = None self._prev = None self._before_prev = None self._logical_prober = None self._visual_prober = None self.reset() def reset(self): self._final_char_logical_score = 0 self._final_char_visual_score = 0 # The two last characters seen in the previous buffer, # mPrev and mBeforePrev are initialized to space in order to simulate # a word delimiter at the beginning of the data self._prev = ' ' self._before_prev = ' ' # These probers are owned by the group prober. def set_model_probers(self, logicalProber, visualProber): self._logical_prober = logicalProber self._visual_prober = visualProber def is_final(self, c): return c in [self.FINAL_KAF, self.FINAL_MEM, self.FINAL_NUN, self.FINAL_PE, self.FINAL_TSADI] def is_non_final(self, c): # The normal Tsadi is not a good Non-Final letter due to words like # 'lechotet' (to chat) containing an apostrophe after the tsadi. This # apostrophe is converted to a space in FilterWithoutEnglishLetters # causing the Non-Final tsadi to appear at an end of a word even # though this is not the case in the original text. # The letters Pe and Kaf rarely display a related behavior of not being # a good Non-Final letter. Words like 'Pop', 'Winamp' and 'Mubarak' # for example legally end with a Non-Final Pe or Kaf. However, the # benefit of these letters as Non-Final letters outweighs the damage # since these words are quite rare. return c in [self.NORMAL_KAF, self.NORMAL_MEM, self.NORMAL_NUN, self.NORMAL_PE] def feed(self, byte_str): # Final letter analysis for logical-visual decision. # Look for evidence that the received buffer is either logical Hebrew # or visual Hebrew. # The following cases are checked: # 1) A word longer than 1 letter, ending with a final letter. This is # an indication that the text is laid out "naturally" since the # final letter really appears at the end. +1 for logical score. # 2) A word longer than 1 letter, ending with a Non-Final letter. In # normal Hebrew, words ending with Kaf, Mem, Nun, Pe or Tsadi, # should not end with the Non-Final form of that letter. Exceptions # to this rule are mentioned above in isNonFinal(). This is an # indication that the text is laid out backwards. +1 for visual # score # 3) A word longer than 1 letter, starting with a final letter. Final # letters should not appear at the beginning of a word. This is an # indication that the text is laid out backwards. +1 for visual # score. # # The visual score and logical score are accumulated throughout the # text and are finally checked against each other in GetCharSetName(). # No checking for final letters in the middle of words is done since # that case is not an indication for either Logical or Visual text. # # We automatically filter out all 7-bit characters (replace them with # spaces) so the word boundary detection works properly. [MAP] if self.state == ProbingState.NOT_ME: # Both model probers say it's not them. No reason to continue. return ProbingState.NOT_ME byte_str = self.filter_high_byte_only(byte_str) for cur in byte_str: if cur == ' ': # We stand on a space - a word just ended if self._before_prev != ' ': # next-to-last char was not a space so self._prev is not a # 1 letter word if self.is_final(self._prev): # case (1) [-2:not space][-1:final letter][cur:space] self._final_char_logical_score += 1 elif self.is_non_final(self._prev): # case (2) [-2:not space][-1:Non-Final letter][ # cur:space] self._final_char_visual_score += 1 else: # Not standing on a space if ((self._before_prev == ' ') and (self.is_final(self._prev)) and (cur != ' ')): # case (3) [-2:space][-1:final letter][cur:not space] self._final_char_visual_score += 1 self._before_prev = self._prev self._prev = cur # Forever detecting, till the end or until both model probers return # ProbingState.NOT_ME (handled above) return ProbingState.DETECTING @property def charset_name(self): # Make the decision: is it Logical or Visual? # If the final letter score distance is dominant enough, rely on it. finalsub = self._final_char_logical_score - self._final_char_visual_score if finalsub >= self.MIN_FINAL_CHAR_DISTANCE: return self.LOGICAL_HEBREW_NAME if finalsub <= -self.MIN_FINAL_CHAR_DISTANCE: return self.VISUAL_HEBREW_NAME # It's not dominant enough, try to rely on the model scores instead. modelsub = (self._logical_prober.get_confidence() - self._visual_prober.get_confidence()) if modelsub > self.MIN_MODEL_DISTANCE: return self.LOGICAL_HEBREW_NAME if modelsub < -self.MIN_MODEL_DISTANCE: return self.VISUAL_HEBREW_NAME # Still no good, back to final letter distance, maybe it'll save the # day. if finalsub < 0.0: return self.VISUAL_HEBREW_NAME # (finalsub > 0 - Logical) or (don't know what to do) default to # Logical. return self.LOGICAL_HEBREW_NAME @property def language(self): return 'Hebrew' @property def state(self): # Remain active as long as any of the model probers are active. if (self._logical_prober.state == ProbingState.NOT_ME) and \ (self._visual_prober.state == ProbingState.NOT_ME): return ProbingState.NOT_ME return ProbingState.DETECTING Back

Edit File : hebrewprober.py | Size : 13.51 KB

######################## BEGIN LICENSE BLOCK ########################
# The Original Code is Mozilla Universal charset detector code.
#
# The Initial Developer of the Original Code is
#          Shy Shalom
# Portions created by the Initial Developer are Copyright (C) 2005
# 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 .charsetprober import CharSetProber
from .enums import ProbingState

# This prober doesn't actually recognize a language or a charset.
# It is a helper prober for the use of the Hebrew model probers

### General ideas of the Hebrew charset recognition ###
#
# Four main charsets exist in Hebrew:
# "ISO-8859-8" - Visual Hebrew
# "windows-1255" - Logical Hebrew
# "ISO-8859-8-I" - Logical Hebrew
# "x-mac-hebrew" - ?? Logical Hebrew ??
#
# Both "ISO" charsets use a completely identical set of code points, whereas
# "windows-1255" and "x-mac-hebrew" are two different proper supersets of
# these code points. windows-1255 defines additional characters in the range
# 0x80-0x9F as some misc punctuation marks as well as some Hebrew-specific
# diacritics and additional 'Yiddish' ligature letters in the range 0xc0-0xd6.
# x-mac-hebrew defines similar additional code points but with a different
# mapping.
#
# As far as an average Hebrew text with no diacritics is concerned, all four
# charsets are identical with respect to code points. Meaning that for the
# main Hebrew alphabet, all four map the same values to all 27 Hebrew letters
# (including final letters).
#
# The dominant difference between these charsets is their directionality.
# "Visual" directionality means that the text is ordered as if the renderer is
# not aware of a BIDI rendering algorithm. The renderer sees the text and
# draws it from left to right. The text itself when ordered naturally is read
# backwards. A buffer of Visual Hebrew generally looks like so:
# "[last word of first line spelled backwards] [whole line ordered backwards
# and spelled backwards] [first word of first line spelled backwards]
# [end of line] [last word of second line] ... etc' "
# adding punctuation marks, numbers and English text to visual text is
# naturally also "visual" and from left to right.
#
# "Logical" directionality means the text is ordered "naturally" according to
# the order it is read. It is the responsibility of the renderer to display
# the text from right to left. A BIDI algorithm is used to place general
# punctuation marks, numbers and English text in the text.
#
# Texts in x-mac-hebrew are almost impossible to find on the Internet. From
# what little evidence I could find, it seems that its general directionality
# is Logical.
#
# To sum up all of the above, the Hebrew probing mechanism knows about two
# charsets:
# Visual Hebrew - "ISO-8859-8" - backwards text - Words and sentences are
#    backwards while line order is natural. For charset recognition purposes
#    the line order is unimportant (In fact, for this implementation, even
#    word order is unimportant).
# Logical Hebrew - "windows-1255" - normal, naturally ordered text.
#
# "ISO-8859-8-I" is a subset of windows-1255 and doesn't need to be
#    specifically identified.
# "x-mac-hebrew" is also identified as windows-1255. A text in x-mac-hebrew
#    that contain special punctuation marks or diacritics is displayed with
#    some unconverted characters showing as question marks. This problem might
#    be corrected using another model prober for x-mac-hebrew. Due to the fact
#    that x-mac-hebrew texts are so rare, writing another model prober isn't
#    worth the effort and performance hit.
#
#### The Prober ####
#
# The prober is divided between two SBCharSetProbers and a HebrewProber,
# all of which are managed, created, fed data, inquired and deleted by the
# SBCSGroupProber. The two SBCharSetProbers identify that the text is in
# fact some kind of Hebrew, Logical or Visual. The final decision about which
# one is it is made by the HebrewProber by combining final-letter scores
# with the scores of the two SBCharSetProbers to produce a final answer.
#
# The SBCSGroupProber is responsible for stripping the original text of HTML
# tags, English characters, numbers, low-ASCII punctuation characters, spaces
# and new lines. It reduces any sequence of such characters to a single space.
# The buffer fed to each prober in the SBCS group prober is pure text in
# high-ASCII.
# The two SBCharSetProbers (model probers) share the same language model:
# Win1255Model.
# The first SBCharSetProber uses the model normally as any other
# SBCharSetProber does, to recognize windows-1255, upon which this model was
# built. The second SBCharSetProber is told to make the pair-of-letter
# lookup in the language model backwards. This in practice exactly simulates
# a visual Hebrew model using the windows-1255 logical Hebrew model.
#
# The HebrewProber is not using any language model. All it does is look for
# final-letter evidence suggesting the text is either logical Hebrew or visual
# Hebrew. Disjointed from the model probers, the results of the HebrewProber
# alone are meaningless. HebrewProber always returns 0.00 as confidence
# since it never identifies a charset by itself. Instead, the pointer to the
# HebrewProber is passed to the model probers as a helper "Name Prober".
# When the Group prober receives a positive identification from any prober,
# it asks for the name of the charset identified. If the prober queried is a
# Hebrew model prober, the model prober forwards the call to the
# HebrewProber to make the final decision. In the HebrewProber, the
# decision is made according to the final-letters scores maintained and Both
# model probers scores. The answer is returned in the form of the name of the
# charset identified, either "windows-1255" or "ISO-8859-8".

class HebrewProber(CharSetProber):
    # windows-1255 / ISO-8859-8 code points of interest
    FINAL_KAF = 0xea
    NORMAL_KAF = 0xeb
    FINAL_MEM = 0xed
    NORMAL_MEM = 0xee
    FINAL_NUN = 0xef
    NORMAL_NUN = 0xf0
    FINAL_PE = 0xf3
    NORMAL_PE = 0xf4
    FINAL_TSADI = 0xf5
    NORMAL_TSADI = 0xf6

# Minimum Visual vs Logical final letter score difference.
    # If the difference is below this, don't rely solely on the final letter score
    # distance.
    MIN_FINAL_CHAR_DISTANCE = 5

# Minimum Visual vs Logical model score difference.
    # If the difference is below this, don't rely at all on the model score
    # distance.
    MIN_MODEL_DISTANCE = 0.01

VISUAL_HEBREW_NAME = "ISO-8859-8"
    LOGICAL_HEBREW_NAME = "windows-1255"

def __init__(self):
        super(HebrewProber, self).__init__()
        self._final_char_logical_score = None
        self._final_char_visual_score = None
        self._prev = None
        self._before_prev = None
        self._logical_prober = None
        self._visual_prober = None
        self.reset()

def reset(self):
        self._final_char_logical_score = 0
        self._final_char_visual_score = 0
        # The two last characters seen in the previous buffer,
        # mPrev and mBeforePrev are initialized to space in order to simulate
        # a word delimiter at the beginning of the data
        self._prev = ' '
        self._before_prev = ' '
        # These probers are owned by the group prober.

def set_model_probers(self, logicalProber, visualProber):
        self._logical_prober = logicalProber
        self._visual_prober = visualProber

def is_final(self, c):
        return c in [self.FINAL_KAF, self.FINAL_MEM, self.FINAL_NUN,
                     self.FINAL_PE, self.FINAL_TSADI]

def is_non_final(self, c):
        # The normal Tsadi is not a good Non-Final letter due to words like
        # 'lechotet' (to chat) containing an apostrophe after the tsadi. This
        # apostrophe is converted to a space in FilterWithoutEnglishLetters
        # causing the Non-Final tsadi to appear at an end of a word even
        # though this is not the case in the original text.
        # The letters Pe and Kaf rarely display a related behavior of not being
        # a good Non-Final letter. Words like 'Pop', 'Winamp' and 'Mubarak'
        # for example legally end with a Non-Final Pe or Kaf. However, the
        # benefit of these letters as Non-Final letters outweighs the damage
        # since these words are quite rare.
        return c in [self.NORMAL_KAF, self.NORMAL_MEM,
                     self.NORMAL_NUN, self.NORMAL_PE]

def feed(self, byte_str):
        # Final letter analysis for logical-visual decision.
        # Look for evidence that the received buffer is either logical Hebrew
        # or visual Hebrew.
        # The following cases are checked:
        # 1) A word longer than 1 letter, ending with a final letter. This is
        #    an indication that the text is laid out "naturally" since the
        #    final letter really appears at the end. +1 for logical score.
        # 2) A word longer than 1 letter, ending with a Non-Final letter. In
        #    normal Hebrew, words ending with Kaf, Mem, Nun, Pe or Tsadi,
        #    should not end with the Non-Final form of that letter. Exceptions
        #    to this rule are mentioned above in isNonFinal(). This is an
        #    indication that the text is laid out backwards. +1 for visual
        #    score
        # 3) A word longer than 1 letter, starting with a final letter. Final
        #    letters should not appear at the beginning of a word. This is an
        #    indication that the text is laid out backwards. +1 for visual
        #    score.
        #
        # The visual score and logical score are accumulated throughout the
        # text and are finally checked against each other in GetCharSetName().
        # No checking for final letters in the middle of words is done since
        # that case is not an indication for either Logical or Visual text.
        #
        # We automatically filter out all 7-bit characters (replace them with
        # spaces) so the word boundary detection works properly. [MAP]

if self.state == ProbingState.NOT_ME:
            # Both model probers say it's not them. No reason to continue.
            return ProbingState.NOT_ME

byte_str = self.filter_high_byte_only(byte_str)

for cur in byte_str:
            if cur == ' ':
                # We stand on a space - a word just ended
                if self._before_prev != ' ':
                    # next-to-last char was not a space so self._prev is not a
                    # 1 letter word
                    if self.is_final(self._prev):
                        # case (1) [-2:not space][-1:final letter][cur:space]
                        self._final_char_logical_score += 1
                    elif self.is_non_final(self._prev):
                        # case (2) [-2:not space][-1:Non-Final letter][
                        #  cur:space]
                        self._final_char_visual_score += 1
            else:
                # Not standing on a space
                if ((self._before_prev == ' ') and
                        (self.is_final(self._prev)) and (cur != ' ')):
                    # case (3) [-2:space][-1:final letter][cur:not space]
                    self._final_char_visual_score += 1
            self._before_prev = self._prev
            self._prev = cur

# Forever detecting, till the end or until both model probers return
        # ProbingState.NOT_ME (handled above)
        return ProbingState.DETECTING

@property
    def charset_name(self):
        # Make the decision: is it Logical or Visual?
        # If the final letter score distance is dominant enough, rely on it.
        finalsub = self._final_char_logical_score - self._final_char_visual_score
        if finalsub >= self.MIN_FINAL_CHAR_DISTANCE:
            return self.LOGICAL_HEBREW_NAME
        if finalsub <= -self.MIN_FINAL_CHAR_DISTANCE:
            return self.VISUAL_HEBREW_NAME

# It's not dominant enough, try to rely on the model scores instead.
        modelsub = (self._logical_prober.get_confidence()
                    - self._visual_prober.get_confidence())
        if modelsub > self.MIN_MODEL_DISTANCE:
            return self.LOGICAL_HEBREW_NAME
        if modelsub < -self.MIN_MODEL_DISTANCE:
            return self.VISUAL_HEBREW_NAME

# Still no good, back to final letter distance, maybe it'll save the
        # day.
        if finalsub < 0.0:
            return self.VISUAL_HEBREW_NAME

# (finalsub > 0 - Logical) or (don't know what to do) default to
        # Logical.
        return self.LOGICAL_HEBREW_NAME

@property
    def language(self):
        return 'Hebrew'

@property
    def state(self):
        # Remain active as long as any of the model probers are active.
        if (self._logical_prober.state == ProbingState.NOT_ME) and \
           (self._visual_prober.state == ProbingState.NOT_ME):
            return ProbingState.NOT_ME
        return ProbingState.DETECTING

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