Logo Search packages:      
Sourcecode: calibre version File versions  Download package

hebrewprober.py

######################## 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
import constants

# 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".

# windows-1255 / ISO-8859-8 code points of interest
FINAL_KAF = '\xea'
NORMAL_KAF = '\xeb'
FINAL_MEM = '\xed'
NORMAL_MEM = '\xee'
FINAL_NUN = '\xef'
NORMAL_NUN = '\xf0'
FINAL_PE = '\xf3'
NORMAL_PE = '\xf4'
FINAL_TSADI = '\xf5'
NORMAL_TSADI = '\xf6'

# 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"

class HebrewProber(CharSetProber):
    def __init__(self):
        CharSetProber.__init__(self)
        self._mLogicalProber = None
        self._mVisualProber = None
        self.reset()

    def reset(self):
        self._mFinalCharLogicalScore = 0
        self._mFinalCharVisualScore = 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._mPrev = ' '
        self._mBeforePrev = ' '
        # These probers are owned by the group prober.
        
    def set_model_probers(self, logicalProber, visualProber):
        self._mLogicalProber = logicalProber
        self._mVisualProber = visualProber

    def is_final(self, c):
        return c in [FINAL_KAF, FINAL_MEM, FINAL_NUN, FINAL_PE, 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 [NORMAL_KAF, NORMAL_MEM, NORMAL_NUN, NORMAL_PE]
    
    def feed(self, aBuf):
        # 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.get_state() == constants.eNotMe:
            # Both model probers say it's not them. No reason to continue.
            return constants.eNotMe

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

        # Forever detecting, till the end or until both model probers return eNotMe (handled above)
        return constants.eDetecting

    def get_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._mFinalCharLogicalScore - self._mFinalCharVisualScore
        if finalsub >= MIN_FINAL_CHAR_DISTANCE:
            return LOGICAL_HEBREW_NAME
        if finalsub <= -MIN_FINAL_CHAR_DISTANCE:
            return VISUAL_HEBREW_NAME

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

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

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

    def get_state(self):
        # Remain active as long as any of the model probers are active.
        if (self._mLogicalProber.get_state() == constants.eNotMe) and \
           (self._mVisualProber.get_state() == constants.eNotMe):
            return constants.eNotMe
        return constants.eDetecting

Generated by  Doxygen 1.6.0   Back to index