1 | // This file is a part of Framsticks SDK. http://www.framsticks.com/ |
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2 | // Copyright (C) 1999-2020 Maciej Komosinski and Szymon Ulatowski. |
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3 | // See LICENSE.txt for details. |
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4 | |
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5 | #ifndef _NEUROIMPL_H_ |
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6 | #define _NEUROIMPL_H_ |
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7 | |
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8 | #include <frams/model/model.h> |
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9 | #include <frams/param/param.h> |
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10 | #include <common/log.h> |
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11 | #ifdef NEURO_SIGNALS |
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12 | #include <frams/simul/signals.h> |
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13 | #endif |
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14 | |
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15 | class NeuroImpl; |
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16 | extern ParamEntry neuroimpl_tab[]; |
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17 | |
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18 | class Creature; |
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19 | class NeuroLibrary; |
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20 | class NeuroFactory; |
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21 | |
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22 | class NeuroNetConfig |
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23 | { |
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24 | public: |
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25 | NeuroNetConfig(NeuroFactory *fac); |
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26 | |
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27 | Param par; |
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28 | double randominit; |
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29 | double nnoise; |
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30 | double touchrange; |
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31 | |
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32 | NeuroFactory *factory; |
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33 | //static NeuroNetConfig& getGlobalConfig(); |
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34 | }; |
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35 | |
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36 | #ifdef NEURO_SIGNALS |
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37 | class NeuroSignals : public SignalSet |
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38 | { |
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39 | protected: |
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40 | Creature *cr; |
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41 | NeuroImpl *owner; |
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42 | Creature *getCreature(); |
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43 | public: |
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44 | |
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45 | NeuroSignals(NeuroImpl *n) :cr(0), owner(n) {} |
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46 | |
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47 | #define STATRICKCLASS NeuroSignals |
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48 | PARAMPROCDEF(p_add); |
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49 | PARAMPROCDEF(p_get); |
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50 | PARAMGETDEF(size); |
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51 | PARAMPROCDEF(p_receive); |
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52 | PARAMPROCDEF(p_receiveSet); |
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53 | PARAMPROCDEF(p_receiveFilter); |
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54 | PARAMPROCDEF(p_receiveSingle); |
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55 | #undef STATRICKCLASS |
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56 | |
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57 | static Param& getStaticParam(); |
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58 | }; |
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59 | #endif |
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60 | |
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61 | /// Neuro net implementation |
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62 | class NeuroNetImpl |
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63 | { |
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64 | CallbackNode *cnode; |
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65 | Model &mod; |
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66 | SList neurons[4]; |
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67 | NeuroNetConfig& config; |
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68 | int isbuilt, errorcount; |
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69 | STCALLBACKDEFC(NeuroNetImpl, destroyNN); |
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70 | int minorder, maxorder; |
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71 | |
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72 | public: |
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73 | #ifdef NEURO_SIGNALS |
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74 | ChannelSpace *channels; |
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75 | #endif |
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76 | static int mytags_id; |
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77 | static double getStateFromNeuro(Neuro *n); |
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78 | int getErrorCount() { return errorcount; } |
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79 | NeuroNetConfig &getConfig() { return config; } |
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80 | NeuroNetImpl(Model& model, NeuroNetConfig& conf |
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81 | #ifdef NEURO_SIGNALS |
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82 | , ChannelSpace *ch = 0 |
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83 | #endif |
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84 | ); |
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85 | ~NeuroNetImpl(); |
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86 | void simulateNeuroNet(); |
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87 | void simulateNeuroPhysics(); |
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88 | |
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89 | static NeuroImpl *getImpl(Neuro* n) { return (NeuroImpl*)n->userdata[mytags_id]; } |
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90 | static void getLiveNeuroObject(Neuro *n, ExtValue *ret); |
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91 | }; |
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92 | |
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93 | |
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94 | /** |
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95 | Neuro implementation - this object calculates the Neuron's state |
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96 | (Neuro::state) in each simulation step. |
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97 | |
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98 | SUBCLASSING TUTORIAL |
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99 | ==================== |
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100 | |
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101 | 1.Derive your custom neuron from NeuroImpl class. The name must be prefixed with NI_ |
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102 | |
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103 | class NI_MyNeuron: public NeuroImpl |
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104 | { ... }; |
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105 | |
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106 | 2.Public parameters |
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107 | Create any number of public fields, they will be adjustable from the genotype level. |
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108 | 3 datatypes are supported: long, double and SString |
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109 | |
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110 | public: |
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111 | paInt intParameter; |
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112 | double fpParameter; |
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113 | SString txtParameter; |
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114 | |
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115 | |
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116 | 3.Required method: "instantiator". |
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117 | It is always the same, just create a new instance of your neuron. |
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118 | public: |
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119 | NeuroImpl* makeNew() { return new NI_MyNeuron(); }; |
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120 | |
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121 | |
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122 | 4.Required method: default constructor |
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123 | Set the "paramentries" variable if you need public parameters in your neuron. |
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124 | NI_..._tab is created automatically and should be declared as: extern ParamEntry NI_..._tab[]; |
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125 | At this stage the parameter values are not yet available. |
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126 | |
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127 | public: |
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128 | NI_MyNeuron() // no parameters! |
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129 | { |
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130 | paramentries=NI_MyNeuron_tab; |
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131 | // you add here: some general initialization |
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132 | } |
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133 | |
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134 | |
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135 | 5.Optional method: initialization |
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136 | This method is called once before the neuron is actually used in the simulation. |
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137 | The parameter values are already initialized (according to the genotype) and the neuron is bound to the creature (i.e. this->neuro is valid). |
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138 | Return 0 if the neuron cannot be initialized. |
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139 | |
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140 | int lateinit() |
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141 | { |
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142 | // you add here: initialization using full neuron context |
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143 | // example: if (!neuro->joint) return 0; //this neuron must be attached to joint |
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144 | return 1;//OK |
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145 | } |
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146 | |
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147 | |
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148 | 6.Required method: simulation step |
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149 | If it has output: calculate the next neuron state and call setState() |
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150 | If it is an effector: do anything else |
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151 | |
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152 | void go() |
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153 | { |
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154 | // you add here: things called every simulation step |
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155 | } |
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156 | |
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157 | Note: You can make your neuron fire before or after "regular" neurons by changing its "simorder" property (during initialization). The default value is 1, whereas receptors have simorder=0 and effectors have simorder=2. |
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158 | |
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159 | |
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160 | 7.Neuron definition |
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161 | In order to incorporate the new neuron into Framsticks you need to provide some additional information (to be added to "f0.def" file). |
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162 | |
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163 | NEUROCLASS(MyNeuron,MN,This is the name,`Neuron description',-1,1,0) |
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164 | NEUROPROP(int,0,0,name of the int,d,,,,intParameter) |
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165 | NEUROPROP(fp,0,0,name of the floating point,f,,,,fpParameter) |
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166 | NEUROPROP(txt,0,0,name of the text,s,,,,txtParameter) |
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167 | ENDNEUROCLASS |
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168 | |
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169 | NEUROCLASS: |
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170 | - MyNeuron: neuron class name (without the NI_ prefix) |
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171 | - MN: neuron symbol (used in genotypes) |
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172 | - full name and description |
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173 | - -1: preferred number of inputs (special case: -1=any) |
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174 | - 1: provides output: 1=yes/0=no |
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175 | - 0: preferred location: 0=none, 1=part, 2=joint |
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176 | |
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177 | NEUROPROP: |
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178 | - int/fp/txt: parameter names as visible in genotypes and scripting |
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179 | - "name of the ...": descriptive name |
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180 | - d/f/s: type (int/floating point/string) |
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181 | - intParameter/fpParameter/txtParameter: C++ field names |
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182 | |
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183 | |
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184 | */ |
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185 | class NeuroImpl |
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186 | { |
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187 | protected: |
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188 | int simorder; |
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189 | int channels; |
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190 | SListTempl<double> chstate; |
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191 | SListTempl<double> chnewstate; |
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192 | Param *fields_param; |
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193 | ExtObject *fields_object; |
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194 | public: |
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195 | static const int ENDDRAWING; |
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196 | static const int MAXDRAWINGXY; |
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197 | |
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198 | enum NeuroImplStats { BeforeInit = 0, InitError = 1, InitOk = 2 }; |
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199 | NeuroImplStats status; |
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200 | /** originating neuron object (from the model) */ |
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201 | Neuro *neuro; |
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202 | NeuroClass *neuroclass; |
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203 | /** don't access directly */ |
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204 | double newstate; |
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205 | NeuroNetImpl *owner; |
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206 | /** will be used by readParam() method, if not null */ |
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207 | ParamEntry *paramentries; // no extra properties if ==0 |
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208 | |
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209 | #ifdef NEURO_SIGNALS |
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210 | NeuroSignals sigs; |
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211 | ExtObject sigs_obj; |
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212 | #endif |
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213 | |
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214 | /** "virtual constructor" - NeuroFactory uses this method to create the proper implementation object. |
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215 | subclasses must return new object here. */ |
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216 | virtual NeuroImpl* makeNew() { return 0; } // |
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217 | /** read additional properties from "moredata" field of the originating Neuro */ |
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218 | void readParam(); |
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219 | /** called when all other neuro objects were already created and "moredata" transferred to |
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220 | object fields. |
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221 | useful for initialization that cannot be performed in the constructor. |
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222 | @return 1=ok 0=failure |
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223 | */ |
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224 | virtual int lateinit() { return 1; } |
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225 | /** calculate 'newstate - implementation dependent */ |
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226 | virtual void go() {} |
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227 | /** for neurons doing some physical actions (called each simulation step when nnspeed!=1.0) */ |
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228 | virtual void goPhysics() {} |
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229 | |
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230 | int getSimOrder() { return simorder; } |
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231 | virtual int getNeedPhysics() { return 0; } |
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232 | |
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233 | void setChannelCount(int c); |
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234 | int getChannelCount() { return channels; } |
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235 | |
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236 | int getInputCount() { return neuro->getInputCount(); } |
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237 | int getInputChannelCount(int i); |
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238 | double getInputState(int i, int channel = 0); |
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239 | double getWeightedInputState(int i, int channel = 0); |
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240 | double getInputSum(int startwith = 0); |
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241 | double getWeightedInputSum(int startwith = 0); |
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242 | double getInputWeight(int i) { return neuro->getInputWeight(i); } |
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243 | void setState(double st, int channel); |
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244 | void setState(double st) { validateNeuroState(st); newstate = st; } |
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245 | double getState(int channel); |
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246 | double getState() { return neuro->state; } |
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247 | |
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248 | virtual int getDrawingCount() { return 0; } |
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249 | virtual int* getDrawing(int i) { return 0; } |
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250 | |
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251 | /** is this implementation current? script neurons retain their original implementation when reloading *.neuro */ |
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252 | virtual bool isCurrent() { return true; } |
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253 | |
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254 | void commit(); |
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255 | void validateNeuroState(double& st) { if (st <= -1e10) st = -1e10; else if (st > 1e10) st = 1e10; } |
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256 | |
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257 | NeuroImpl() :simorder(1), channels(1), fields_param(0), fields_object(0), status(BeforeInit), neuro(0), newstate(0), owner(0), paramentries(0) |
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258 | #ifdef NEURO_SIGNALS |
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259 | , sigs(this), sigs_obj(&NeuroSignals::getStaticParam(), &sigs) |
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260 | #endif |
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261 | {} |
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262 | virtual ~NeuroImpl(); |
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263 | virtual void createFieldsObject(); |
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264 | |
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265 | /** usually == "newstate" but will obey the "hold state" */ |
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266 | double getNewState(int channel = 0); |
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267 | |
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268 | /** don't use! */ |
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269 | void setCurrentState(double st, int channel = 0); |
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270 | |
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271 | bool getPosition(Pt3D &pos); |
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272 | Creature* getCreature(); |
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273 | |
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274 | virtual Pt3D getRelativePosition() { return Pt3D_0; } |
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275 | virtual Orient getRelativeOrientation() { return Orient_1; } |
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276 | |
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277 | #define STATRICKCLASS NeuroImpl |
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278 | PARAMGETDEF(count) { arg1->setInt(getInputCount()); } |
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279 | PARAMPROCDEF(p_get) { arg2->setDouble(getInputState(arg1->getInt())); } |
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280 | PARAMPROCDEF(p_getweight) { arg2->setDouble(getInputWeight(arg1->getInt())); } |
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281 | PARAMPROCDEF(p_getw) { arg2->setDouble(getWeightedInputState(arg1->getInt())); } |
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282 | PARAMPROCDEF(p_getsum) { arg2->setDouble(getInputSum(arg1->getInt())); } |
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283 | PARAMPROCDEF(p_getwsum) { arg2->setDouble(getWeightedInputSum(arg1->getInt())); } |
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284 | PARAMGETDEF(sum) { arg1->setDouble(getInputSum(0)); } |
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285 | PARAMGETDEF(wsum) { arg1->setDouble(getWeightedInputSum(0)); } |
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286 | PARAMPROCDEF(p_getchancount) { arg2->setInt(getInputChannelCount(arg1->getInt())); } |
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287 | PARAMPROCDEF(p_getchan) { arg2->setDouble(getInputState(arg1[1].getInt(), arg1[0].getInt())); } |
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288 | PARAMPROCDEF(p_getwchan) { arg2->setDouble(getWeightedInputState(arg1[1].getInt(), arg1[0].getInt())); } |
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289 | PARAMGETDEF(state) { arg1->setDouble(getState()); } |
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290 | PARAMSETDEF(state) { setState(arg1->getDouble()); return 0; } |
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291 | PARAMGETDEF(cstate) { arg1->setDouble(neuro->state); } |
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292 | PARAMSETDEF(cstate) { setCurrentState(arg1->getDouble()); return 0; } |
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293 | PARAMGETDEF(hold) { arg1->setInt((neuro->flags & (Neuro::HoldState)) ? 1 : 0); } |
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294 | PARAMSETDEF(hold) { neuro->flags = (neuro->flags & ~Neuro::HoldState) | (arg1->getInt() ? Neuro::HoldState : 0); return 0; } |
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295 | PARAMGETDEF(channels) { arg1->setInt(getChannelCount()); } |
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296 | PARAMSETDEF(channels) { setChannelCount(arg1->getInt()); return 0; } |
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297 | PARAMPROCDEF(p_getstate) { arg2->setDouble(getState(arg1->getInt())); } |
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298 | PARAMPROCDEF(p_setstate) { setState(arg1[0].getDouble(), arg1[1].getInt()); } |
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299 | PARAMPROCDEF(p_setcstate) { setCurrentState(arg1[0].getDouble(), arg1[1].getInt()); } |
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300 | PARAMGETDEF(creature); |
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301 | PARAMGETDEF(part); |
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302 | PARAMGETDEF(joint); |
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303 | PARAMGETDEF(position_x); |
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304 | PARAMGETDEF(position_y); |
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305 | PARAMGETDEF(position_z); |
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306 | PARAMGETDEF(relative_pos); |
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307 | PARAMGETDEF(relative_orient); |
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308 | PARAMGETDEF(fields); |
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309 | PARAMGETDEF(neurodef); |
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310 | PARAMGETDEF(classObject); |
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311 | #undef STATRICKCLASS |
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312 | |
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313 | static Param& getStaticParam(); |
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314 | }; |
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315 | |
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316 | #endif |
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