Current File : //usr/lib/python2.7/site-packages/pip/_vendor/chardet/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
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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