######################## 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):
#   Jeff Hodges - port to Ruby
#   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 #########################

# 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
module CharDet
  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 initialize
      super()
      @_mLogicalProber = nil
      @_mVisualProber = nil
      reset()
    end

    def reset
      @_mFinalCharLogicalScore = 0
      @_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
      @_mPrev = ' '
      @_mBeforePrev = ' '
      # These probers are owned by the group prober.
    end

    def set_model_probers(logicalProber, visualProber)
      @_mLogicalProber = logicalProber
      @_mVisualProber = visualProber
    end

    def is_final(c)
      return [FINAL_KAF, FINAL_MEM, FINAL_NUN, FINAL_PE, FINAL_TSADI].include?(c)
    end

    def is_non_final(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 [NORMAL_KAF, NORMAL_MEM, NORMAL_NUN, NORMAL_PE].include?(c)
    end

    def feed(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 get_state() == ENotMe
        # Both model probers say it's not them. No reason to continue.
        return ENotMe
      end

      aBuf = filter_high_bit_only(aBuf)

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

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

    def get_charset_name
      # Make the decision: is it Logical or Visual?
      # If the final letter score distance is dominant enough, rely on it.
      finalsub = @_mFinalCharLogicalScore - @_mFinalCharVisualScore
      if finalsub >= MIN_FINAL_CHAR_DISTANCE
        return LOGICAL_HEBREW_NAME
      end
      if finalsub <= -MIN_FINAL_CHAR_DISTANCE
        return VISUAL_HEBREW_NAME
      end

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

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

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

    def get_state
      # Remain active as long as any of the model probers are active.
      if (@_mLogicalProber.get_state() == ENotMe) and (@_mVisualProber.get_state() == ENotMe)
        return ENotMe
      end
      return EDetecting
    end
  end
end
