Mercurial > repos > guerler > springsuite
annotate planemo/lib/python3.7/site-packages/chardet/sbcharsetprober.py @ 0:d30785e31577 draft
"planemo upload commit 6eee67778febed82ddd413c3ca40b3183a3898f1"
author | guerler |
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date | Fri, 31 Jul 2020 00:18:57 -0400 |
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0
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1 ######################## BEGIN LICENSE BLOCK ######################## |
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2 # The Original Code is Mozilla Universal charset detector code. |
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3 # |
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4 # The Initial Developer of the Original Code is |
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5 # Netscape Communications Corporation. |
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6 # Portions created by the Initial Developer are Copyright (C) 2001 |
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7 # the Initial Developer. All Rights Reserved. |
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8 # |
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9 # Contributor(s): |
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10 # Mark Pilgrim - port to Python |
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11 # Shy Shalom - original C code |
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12 # |
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13 # This library is free software; you can redistribute it and/or |
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14 # modify it under the terms of the GNU Lesser General Public |
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15 # License as published by the Free Software Foundation; either |
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16 # version 2.1 of the License, or (at your option) any later version. |
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17 # |
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18 # This library is distributed in the hope that it will be useful, |
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19 # but WITHOUT ANY WARRANTY; without even the implied warranty of |
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20 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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21 # Lesser General Public License for more details. |
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22 # |
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23 # You should have received a copy of the GNU Lesser General Public |
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24 # License along with this library; if not, write to the Free Software |
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25 # Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA |
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26 # 02110-1301 USA |
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27 ######################### END LICENSE BLOCK ######################### |
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28 |
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29 from .charsetprober import CharSetProber |
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30 from .enums import CharacterCategory, ProbingState, SequenceLikelihood |
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31 |
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32 |
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33 class SingleByteCharSetProber(CharSetProber): |
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34 SAMPLE_SIZE = 64 |
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35 SB_ENOUGH_REL_THRESHOLD = 1024 # 0.25 * SAMPLE_SIZE^2 |
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36 POSITIVE_SHORTCUT_THRESHOLD = 0.95 |
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37 NEGATIVE_SHORTCUT_THRESHOLD = 0.05 |
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38 |
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39 def __init__(self, model, reversed=False, name_prober=None): |
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40 super(SingleByteCharSetProber, self).__init__() |
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41 self._model = model |
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42 # TRUE if we need to reverse every pair in the model lookup |
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43 self._reversed = reversed |
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44 # Optional auxiliary prober for name decision |
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45 self._name_prober = name_prober |
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46 self._last_order = None |
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47 self._seq_counters = None |
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48 self._total_seqs = None |
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49 self._total_char = None |
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50 self._freq_char = None |
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51 self.reset() |
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52 |
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53 def reset(self): |
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54 super(SingleByteCharSetProber, self).reset() |
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55 # char order of last character |
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56 self._last_order = 255 |
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57 self._seq_counters = [0] * SequenceLikelihood.get_num_categories() |
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58 self._total_seqs = 0 |
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59 self._total_char = 0 |
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60 # characters that fall in our sampling range |
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61 self._freq_char = 0 |
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62 |
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63 @property |
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64 def charset_name(self): |
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65 if self._name_prober: |
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66 return self._name_prober.charset_name |
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67 else: |
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68 return self._model['charset_name'] |
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69 |
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70 @property |
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71 def language(self): |
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72 if self._name_prober: |
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73 return self._name_prober.language |
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74 else: |
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75 return self._model.get('language') |
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76 |
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77 def feed(self, byte_str): |
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78 if not self._model['keep_english_letter']: |
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79 byte_str = self.filter_international_words(byte_str) |
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80 if not byte_str: |
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81 return self.state |
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82 char_to_order_map = self._model['char_to_order_map'] |
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83 for i, c in enumerate(byte_str): |
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84 # XXX: Order is in range 1-64, so one would think we want 0-63 here, |
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85 # but that leads to 27 more test failures than before. |
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86 order = char_to_order_map[c] |
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87 # XXX: This was SYMBOL_CAT_ORDER before, with a value of 250, but |
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88 # CharacterCategory.SYMBOL is actually 253, so we use CONTROL |
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89 # to make it closer to the original intent. The only difference |
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90 # is whether or not we count digits and control characters for |
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91 # _total_char purposes. |
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92 if order < CharacterCategory.CONTROL: |
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93 self._total_char += 1 |
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94 if order < self.SAMPLE_SIZE: |
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95 self._freq_char += 1 |
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96 if self._last_order < self.SAMPLE_SIZE: |
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97 self._total_seqs += 1 |
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98 if not self._reversed: |
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99 i = (self._last_order * self.SAMPLE_SIZE) + order |
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100 model = self._model['precedence_matrix'][i] |
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101 else: # reverse the order of the letters in the lookup |
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102 i = (order * self.SAMPLE_SIZE) + self._last_order |
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103 model = self._model['precedence_matrix'][i] |
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104 self._seq_counters[model] += 1 |
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105 self._last_order = order |
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106 |
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107 charset_name = self._model['charset_name'] |
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108 if self.state == ProbingState.DETECTING: |
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109 if self._total_seqs > self.SB_ENOUGH_REL_THRESHOLD: |
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110 confidence = self.get_confidence() |
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111 if confidence > self.POSITIVE_SHORTCUT_THRESHOLD: |
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112 self.logger.debug('%s confidence = %s, we have a winner', |
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113 charset_name, confidence) |
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114 self._state = ProbingState.FOUND_IT |
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115 elif confidence < self.NEGATIVE_SHORTCUT_THRESHOLD: |
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116 self.logger.debug('%s confidence = %s, below negative ' |
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117 'shortcut threshhold %s', charset_name, |
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118 confidence, |
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119 self.NEGATIVE_SHORTCUT_THRESHOLD) |
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120 self._state = ProbingState.NOT_ME |
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121 |
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122 return self.state |
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123 |
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124 def get_confidence(self): |
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125 r = 0.01 |
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126 if self._total_seqs > 0: |
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127 r = ((1.0 * self._seq_counters[SequenceLikelihood.POSITIVE]) / |
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128 self._total_seqs / self._model['typical_positive_ratio']) |
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129 r = r * self._freq_char / self._total_char |
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130 if r >= 1.0: |
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131 r = 0.99 |
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132 return r |