[286] | 1 | // This file is a part of Framsticks SDK. http://www.framsticks.com/ |
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| 2 | // Copyright (C) 1999-2015 Maciej Komosinski and Szymon Ulatowski. |
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| 3 | // See LICENSE.txt for details. |
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[109] | 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/framsg.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 | }; |
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| 91 | |
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| 92 | |
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| 93 | /** |
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| 94 | Neuro implementation - this object calculates the Neuron's state |
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| 95 | (Neuro::state) in each simulation step. |
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| 96 | |
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| 97 | SUBCLASSING TUTORIAL |
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| 98 | ==================== |
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| 99 | |
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| 100 | 1.Derive your custom neuron from NeuroImpl class. The name must be prefixed with NI_ |
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| 101 | |
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| 102 | class NI_MyNeuron: public NeuroImpl |
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| 103 | { ... }; |
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| 104 | |
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| 105 | 2.Public parameters |
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| 106 | Create any number of public fields, they will be adjustable from the genotype level. |
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| 107 | 3 datatypes are supported: long, double and SString |
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| 108 | |
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| 109 | public: |
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[247] | 110 | paInt intParameter; |
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[109] | 111 | double fpParameter; |
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| 112 | SString txtParameter; |
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| 113 | |
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| 114 | |
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| 115 | 3.Required method: "instantiator". |
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| 116 | It is always the same, just create a new instance of your neuron. |
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| 117 | public: |
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| 118 | NeuroImpl* makeNew() { return new NI_MyNeuron(); }; |
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| 119 | |
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| 120 | |
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| 121 | 4.Required method: default constructor |
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| 122 | Set the "paramentries" variable if you need public parameters in your neuron. |
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| 123 | NI_..._tab is created automatically and should be declared as: extern ParamEntry NI_..._tab[]; |
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| 124 | At this stage the parameter values are not yet available. |
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| 125 | |
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| 126 | public: |
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| 127 | NI_MyNeuron() // no parameters! |
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| 128 | { |
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| 129 | paramentries=NI_MyNeuron_tab; |
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| 130 | // you add here: some general initialization |
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| 131 | } |
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| 132 | |
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| 133 | |
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| 134 | 5.Optional method: initialization |
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| 135 | This method is called once before the neuron is actually used in the simulation. |
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| 136 | 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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| 137 | Return 0 if the neuron cannot be initialized. |
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| 138 | |
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| 139 | int lateinit() |
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| 140 | { |
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| 141 | // you add here: initialization using full neuron context |
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| 142 | // example: if (!neuro->joint) return 0; //this neuron must be attached to joint |
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| 143 | return 1;//OK |
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| 144 | } |
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| 145 | |
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| 146 | |
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| 147 | 6.Required method: simulation step |
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| 148 | If it has output: calculate the next neuron state and call setState() |
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| 149 | If it is an effector: do anything else |
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| 150 | |
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| 151 | void go() |
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| 152 | { |
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| 153 | // you add here: things called every simulation step |
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| 154 | } |
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| 155 | |
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| 156 | 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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| 157 | |
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| 158 | |
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| 159 | 7.Neuron definition |
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| 160 | 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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| 161 | |
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| 162 | NEUROCLASS(MyNeuron,MN,This is the name,`Neuron description',-1,1,0) |
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| 163 | NEUROPROP(int,0,0,name of the int,d,,,,intParameter) |
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| 164 | NEUROPROP(fp,0,0,name of the floating point,f,,,,fpParameter) |
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| 165 | NEUROPROP(txt,0,0,name of the text,s,,,,txtParameter) |
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| 166 | ENDNEUROCLASS |
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| 167 | |
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| 168 | NEUROCLASS: |
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| 169 | - MyNeuron: neuron class name (without the NI_ prefix) |
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| 170 | - MN: neuron symbol (used in genotypes) |
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| 171 | - full name and description |
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| 172 | - -1: preferred number of inputs (special case: -1=any) |
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| 173 | - 1: provides output: 1=yes/0=no |
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| 174 | - 0: preferred location: 0=none, 1=part, 2=joint |
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| 175 | |
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| 176 | NEUROPROP: |
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| 177 | - int/fp/txt: parameter names as visible in genotypes and scripting |
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| 178 | - "name of the ...": descriptive name |
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| 179 | - d/f/s: type (int/floating point/string) |
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| 180 | - intParameter/fpParameter/txtParameter: C++ field names |
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| 181 | |
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| 182 | |
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| 183 | */ |
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| 184 | class NeuroImpl |
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| 185 | { |
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| 186 | protected: |
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| 187 | int simorder; |
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| 188 | int channels; |
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| 189 | SListTempl<double> chstate; |
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| 190 | SListTempl<double> chnewstate; |
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| 191 | Param *fields_param; |
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| 192 | ExtObject *fields_object; |
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| 193 | public: |
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| 194 | static const int ENDDRAWING; |
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| 195 | static const int MAXDRAWINGXY; |
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| 196 | |
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| 197 | enum NeuroImplStats { BeforeInit=0, InitError=1, InitOk=2 }; |
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| 198 | NeuroImplStats status; |
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| 199 | /** originating neuron object (from the model) */ |
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| 200 | Neuro *neuro; |
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| 201 | NeuroClass *neuroclass; |
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| 202 | /** don't access directly */ |
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| 203 | double newstate; |
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| 204 | NeuroNetImpl *owner; |
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| 205 | /** will be used by readParam() method, if not null */ |
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| 206 | ParamEntry *paramentries; // no extra properties if ==0 |
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| 207 | |
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| 208 | #ifdef NEURO_SIGNALS |
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| 209 | NeuroSignals sigs; |
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| 210 | ExtObject sigs_obj; |
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| 211 | #endif |
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| 212 | |
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| 213 | /** "virtual constructor" - NeuroFactory uses this method to create the proper implementation object. |
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| 214 | subclasses must return new object here. */ |
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| 215 | virtual NeuroImpl* makeNew() {return 0;} // |
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| 216 | /** read additional properties from "moredata" field of the originating Neuro */ |
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| 217 | void readParam(); |
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| 218 | /** called when all other neuro objects were already created and "moredata" transferred to |
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| 219 | object fields. |
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| 220 | useful for initialization that cannot be performed in the constructor. |
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| 221 | @return 1=ok 0=failure |
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| 222 | */ |
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| 223 | virtual int lateinit() {return 1;} |
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| 224 | /** calculate 'newstate - implementation dependent */ |
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| 225 | virtual void go(){} |
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| 226 | /** for neurons doing some physical actions (called each simulation step when nnspeed!=1.0) */ |
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| 227 | virtual void goPhysics(){} |
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| 228 | |
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| 229 | int getSimOrder() {return simorder;} |
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| 230 | virtual int getNeedPhysics() {return 0;} |
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| 231 | |
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| 232 | void setChannelCount(int c); |
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| 233 | int getChannelCount() {return channels;} |
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| 234 | |
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| 235 | int getInputCount() {return neuro->getInputCount();} |
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| 236 | int getInputChannelCount(int i); |
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| 237 | double getInputState(int i,int channel=0); |
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| 238 | double getWeightedInputState(int i,int channel=0); |
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| 239 | double getInputSum(int startwith=0); |
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| 240 | double getWeightedInputSum(int startwith=0); |
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| 241 | double getInputWeight(int i) {return neuro->getInputWeight(i);} |
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| 242 | void setState(double st,int channel); |
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| 243 | void setState(double st) {validateNeuroState(st); newstate=st;} |
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| 244 | double getState(int channel); |
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| 245 | double getState() {return neuro->state;} |
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| 246 | |
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| 247 | virtual int getDrawingCount() {return 0;} |
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| 248 | virtual int* getDrawing(int i) {return 0;} |
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| 249 | |
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| 250 | void commit(); |
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| 251 | void validateNeuroState(double& st) {if (st<=-1e10) st=-1e10; else if (st>1e10) st=1e10;} |
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| 252 | |
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| 253 | 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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| 254 | #ifdef NEURO_SIGNALS |
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| 255 | ,sigs(this),sigs_obj(&NeuroSignals::getStaticParam(),&sigs) |
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| 256 | #endif |
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| 257 | {} |
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| 258 | virtual ~NeuroImpl(); |
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| 259 | virtual void createFieldsObject(); |
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| 260 | |
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| 261 | /** usually == "newstate" but will obey the "hold state" */ |
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| 262 | double getNewState(int channel=0); |
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| 263 | |
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| 264 | /** don't use! */ |
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| 265 | void setCurrentState(double st,int channel=0); |
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| 266 | |
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| 267 | bool getPosition(Pt3D &pos); |
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| 268 | Creature* getCreature(); |
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| 269 | |
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| 270 | #define STATRICKCLASS NeuroImpl |
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| 271 | PARAMGETDEF(count) {arg1->setInt(getInputCount());} |
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| 272 | PARAMPROCDEF(p_get) {arg2->setDouble(getInputState(arg1->getInt()));} |
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| 273 | PARAMPROCDEF(p_getweight) {arg2->setDouble(getInputWeight(arg1->getInt()));} |
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| 274 | PARAMPROCDEF(p_getw) {arg2->setDouble(getWeightedInputState(arg1->getInt()));} |
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| 275 | PARAMPROCDEF(p_getsum) {arg2->setDouble(getInputSum(arg1->getInt()));} |
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| 276 | PARAMPROCDEF(p_getwsum) {arg2->setDouble(getWeightedInputSum(arg1->getInt()));} |
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| 277 | PARAMGETDEF(sum) {arg1->setDouble(getInputSum(0));} |
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| 278 | PARAMGETDEF(wsum) {arg1->setDouble(getWeightedInputSum(0));} |
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| 279 | PARAMPROCDEF(p_getchancount) {arg2->setInt(getInputChannelCount(arg1->getInt()));} |
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| 280 | PARAMPROCDEF(p_getchan) {arg2->setDouble(getInputState(arg1[1].getInt(),arg1[0].getInt()));} |
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| 281 | PARAMPROCDEF(p_getwchan) {arg2->setDouble(getWeightedInputState(arg1[1].getInt(),arg1[0].getInt()));} |
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| 282 | PARAMGETDEF(state) {arg1->setDouble(getState());} |
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| 283 | PARAMSETDEF(state) {setState(arg1->getDouble()); return 0;} |
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| 284 | PARAMGETDEF(cstate) {arg1->setDouble(neuro->state);} |
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| 285 | PARAMSETDEF(cstate) {setCurrentState(arg1->getDouble()); return 0;} |
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| 286 | PARAMGETDEF(hold) {arg1->setInt((neuro->flags&(Neuro::HoldState))?1:0);} |
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| 287 | PARAMSETDEF(hold) {neuro->flags=(neuro->flags&~Neuro::HoldState)|(arg1->getInt()?Neuro::HoldState:0); return 0;} |
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| 288 | PARAMGETDEF(channels) {arg1->setInt(getChannelCount());} |
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| 289 | PARAMSETDEF(channels) {setChannelCount(arg1->getInt()); return 0;} |
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| 290 | PARAMPROCDEF(p_getstate) {arg2->setDouble(getState(arg1->getInt()));} |
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| 291 | PARAMPROCDEF(p_setstate) {setState(arg1[0].getDouble(),arg1[1].getInt());} |
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| 292 | PARAMPROCDEF(p_setcstate) {setCurrentState(arg1[0].getDouble(),arg1[1].getInt());} |
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| 293 | PARAMGETDEF(creature); |
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| 294 | PARAMGETDEF(part); |
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| 295 | PARAMGETDEF(joint); |
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| 296 | PARAMGETDEF(position_x); |
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| 297 | PARAMGETDEF(position_y); |
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| 298 | PARAMGETDEF(position_z); |
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| 299 | PARAMGETDEF(fields); |
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| 300 | PARAMGETDEF(neurodef); |
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| 301 | PARAMGETDEF(classObject); |
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| 302 | #undef STATRICKCLASS |
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| 303 | |
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| 304 | static Param& getStaticParam(); |
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| 305 | }; |
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| 306 | |
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| 307 | #endif |
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