annotate characterstatistics.py @ 189:4381be70e1bb tip

Fixed incompatibility with latest changes to bgrease.
author Beliar <KarstenBock@gmx.net>
date Sun, 08 Apr 2012 20:30:43 +0200
parents 741d7d193bad
children
rev   line source
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1 # This program is free software: you can redistribute it and/or modify
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2 # it under the terms of the GNU General Public License as published by
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3 # the Free Software Foundation, either version 3 of the License, or
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4 # (at your option) any later version.
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5
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6 # This program is distributed in the hope that it will be useful,
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7 # but WITHOUT ANY WARRANTY; without even the implied warranty of
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8 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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9 # GNU General Public License for more details.
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10
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11 # You should have received a copy of the GNU General Public License
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12 # along with this program. If not, see <http://www.gnu.org/licenses/>.
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13 """
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14 Provides classes that define character stats and traits.
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15 """
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16
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17 from abc import ABCMeta, abstractmethod
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18 from weakref import ref as weakref
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19
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20 from .serializers import SerializableRegistry
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21
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22 from components import character_statistics
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23
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24 class AbstractCharacterStatistic(object):
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25 __metaclass__ = ABCMeta
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26
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27 @abstractmethod
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28 def __init__(self, description, minimum, maximum):
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29 self.description = description
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30 self.minimum = minimum
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31 self.maximum = maximum
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32
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33
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34 class PrimaryCharacterStatistic(AbstractCharacterStatistic):
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35 def __init__(self, long_name, short_name, description, minimum=0,
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36 maximum=100):
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37 AbstractCharacterStatistic.__init__(self, description=description,
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38 minimum=minimum, maximum=maximum)
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39 self.long_name = long_name
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40 self.short_name = short_name
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41
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42 SerializableRegistry.registerClass(
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43 'PrimaryCharacterStatistic',
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44 PrimaryCharacterStatistic,
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45 init_args=[
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46 ('long_name', unicode),
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47 ('short_name', unicode),
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48 ('description', unicode),
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49 ('minimum', int),
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50 ('maximum', int),
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51 ],
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52 )
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53
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54
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55 class SecondaryCharacterStatistic(AbstractCharacterStatistic):
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56 def __init__(self, name, description, unit, mean, sd, stat_modifiers,
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57 minimum=None, maximum=None):
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58 AbstractCharacterStatistic.__init__(self, description=description,
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59 minimum=minimum, maximum=maximum)
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60 self.name = name
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61 self.unit = unit
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62 self.mean = mean
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63 self.sd = sd
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64 self.stat_modifiers = stat_modifiers
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65
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66 SerializableRegistry.registerClass(
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67 'SecondaryCharacterStatistic',
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68 SecondaryCharacterStatistic,
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69 init_args=[
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70 ('name', unicode),
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71 ('description', unicode),
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72 ('unit', unicode),
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73 ('mean', float),
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74 ('sd', float),
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75 ('stat_modifiers', dict),
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76 ('minimum', float),
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77 ('maximum', float),
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78 ],
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79 )
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80
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81
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82 class AbstractStatisticValue(object):
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83 __metaclass__ = ABCMeta
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84
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85 @abstractmethod
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86 def __init__(self, statistic_type, character):
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87 self.statistic_type = statistic_type
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88 self.character = weakref(character)
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89
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90
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91 class PrimaryStatisticValue(AbstractStatisticValue):
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92 def value():
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93 def fget(self):
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94 return self._value
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95 def fset(self, new_value):
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96 assert 0 <= new_value <= 100
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97 self._value = new_value
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98
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99 def __init__(self, statistic_type, character, value):
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100 AbstractStatisticValue.__init__(self, statistic_type=statistic_type,
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101 character=character)
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102 self._value = None
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103 self.value = value
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104
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105
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106 class SecondaryStatisticValue(AbstractStatisticValue):
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107 def normalized_value():
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108 def fget(self):
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109 return self._normalized_value
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110 def fset(self, new_value):
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111 self._normalized_value = new_value
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112 statistic_type = self.statistic_type
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113 mean = statistic_type.mean
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114 sd = statistic_type.sd
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115 self._value = self.calculate_value(mean, sd, new_value)
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116 return locals()
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117 normalized_value = property(**normalized_value())
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118
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119 def value():
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120 def fget(self):
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121 return self._value
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122 def fset(self, new_value):
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123 self._value = new_value
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124 statistic_type = self.statistic_type
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125 mean = statistic_type.mean
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126 sd = statistic_type.sd
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127 self._normalized_value = self.calculate_value(mean, sd, new_value)
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128 return locals()
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129 value = property(**value())
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130
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131 def __init__(self, statistic_type, character):
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132 AbstractStatisticValue.__init__(self, statistic_type=statistic_type,
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133 character=character)
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134 mean = statistic_type.mean
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135 sd = statistic_type.sd
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136 normalized_value = self.derive_value(normalized=True)
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137 self._normalized_value = normalized_value
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138 self._value = self.calculate_value(mean, sd, normalized_value)
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139
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140 def derive_value(self, normalized=True):
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141 """
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142 Derive the current value
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143 """
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144 statistic_type = self.statistic_type
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145 stat_modifiers = statistic_type.stat_modifiers
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146 character = self.character()
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147
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148 value = sum(
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149 character_statistics.get_statistic(character, name).value *
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150 modifier for name, modifier in
0
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151 stat_modifiers.items()
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152 )
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153 assert 0 <= value <= 100
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154 if not normalized:
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155 mean = statistic_type.mean
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156 sd = statistic_type.sd
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157 value = self.calculate_value(mean, sd, value)
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158 return value
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159
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160 @staticmethod
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161 def calculate_value(mean, sd, normalized_value):
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162 value = sd * (normalized_value - 50) + mean
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163 return value
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164
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165 @staticmethod
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166 def calculate_normalized_value(mean, sd, value):
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167 normalized_value = ((value - mean) / sd) + 50
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168 return normalized_value