[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 | #include "conv_f1.h" |
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| 6 | #include <common/nonstd_stl.h> |
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[375] | 7 | #include <common/log.h> |
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[109] | 8 | #include <frams/util/multirange.h> |
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| 9 | #include <frams/util/multimap.h> |
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| 10 | #include <ctype.h> |
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| 11 | |
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| 12 | //#define v1f1COMPATIBLE |
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| 13 | |
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| 14 | F1Props stdprops={1, 0, 1, 0.4, 0.25, 0.25, 0.25, 0.25, 0.0, 1.0, 1.0, 1, |
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| 15 | 0.2, 0.5,0.5,0.5 }; |
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| 16 | |
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| 17 | class Builder |
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| 18 | { |
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| 19 | public: |
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[319] | 20 | Builder(const char*g,int mapping=0):invalid(0),genbegin(g),usemapping(mapping),first_part_mapping(NULL),energ(0),energ_div(0) {} |
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[109] | 21 | ~Builder() {SAFEDELETE(first_part_mapping);} |
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| 22 | char tmp[222]; |
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| 23 | bool invalid; |
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| 24 | Model model; |
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| 25 | const char *genbegin; |
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| 26 | SList neuro_f1_to_f0; // neuro_f1_to_f0(f1_refno) = actual neuro pointer |
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| 27 | Neuro *last_f1_neuro; |
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| 28 | SyntParam *neuro_cls_param; |
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| 29 | |
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| 30 | struct Connection { int n1,n2; double w; |
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| 31 | Connection(int _n1,int _n2, double _w):n1(_n1),n2(_n2),w(_w) {} }; |
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| 32 | |
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| 33 | SListTempl<Connection> connections; |
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| 34 | int usemapping; |
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| 35 | MultiRange range; |
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| 36 | MultiRange *first_part_mapping; |
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| 37 | double lastjoint_muscle_power; |
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| 38 | double energ,energ_div; |
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| 39 | void grow(int part1,const char*g,Pt3D k,F1Props c); |
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| 40 | void setPartMapping(int p,const char* g); |
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| 41 | int growJoint(int part1,int part2,Pt3D &angle,F1Props &c,const char *g); |
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| 42 | int growPart(F1Props &c,const char *g); |
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| 43 | const char *skipNeuro(const char *z); |
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| 44 | const char* growNeuro(const char* t,F1Props &c,int&); |
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| 45 | void growConnection(const char* begin,const char* colon,const char* end,F1Props& props); |
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| 46 | int countBranches(const char*g,SList &out); |
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| 47 | SyntParam* lastNeuroClassParam(); |
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| 48 | void addClassParam(const char* name,double value); |
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| 49 | void addClassParam(const char* name,const char* value); |
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| 50 | |
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| 51 | const MultiRange* makeRange(const char*g) {return makeRange(g,g);} |
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| 52 | const MultiRange* makeRange(const char*g,const char*g2); |
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| 53 | Part *getLastPart() {return getLastJoint()->part2;} |
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| 54 | Neuro *getLastNeuro() {return model.getNeuro(model.getNeuroCount()-1);} |
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| 55 | Joint *getLastJoint() {return model.getJoint(model.getJointCount()-1);} |
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| 56 | void addOrRememberInput(int n1,int n2,double w) |
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| 57 | { |
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| 58 | //if (!addInput(n1,n2,w,false)) |
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| 59 | connections+=Connection(n1,n2,w); |
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| 60 | } |
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| 61 | bool addInput(int n1,int n2,double w,bool final) |
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| 62 | { |
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| 63 | if ((n1<0) || (n2<0) || (n1>=neuro_f1_to_f0.size()) || (n2>=neuro_f1_to_f0.size())) |
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| 64 | { |
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[375] | 65 | if (final) logPrintf("GenoConvF1","addInput",LOG_WARN, |
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[109] | 66 | "illegal neuron connection %d <- %d (ignored)",n1,n2); |
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| 67 | return 0; |
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| 68 | } |
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| 69 | Neuro *neuro=(Neuro*)neuro_f1_to_f0(n1); |
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| 70 | Neuro *input=(Neuro*)neuro_f1_to_f0(n2); |
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| 71 | neuro->addInput(input,w); |
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| 72 | return 1; |
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| 73 | } |
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| 74 | void addPendingInputs() |
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| 75 | { |
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| 76 | for(int i=0;i<connections.size();i++) |
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| 77 | { |
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| 78 | Connection *c=&connections(i); |
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| 79 | addInput(c->n1,c->n2,c->w,true); |
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| 80 | } |
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| 81 | } |
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| 82 | }; |
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| 83 | |
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| 84 | const MultiRange* Builder::makeRange(const char*g,const char*g2) |
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| 85 | { |
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| 86 | if (!usemapping) return 0; |
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| 87 | range.clear(); |
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| 88 | range.add(g-genbegin,g2-genbegin); |
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| 89 | return ⦥ |
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| 90 | } |
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| 91 | |
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| 92 | void F1Props::wykluczanie() |
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| 93 | { |
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| 94 | double s=ruch+asym+odpor+wchl; |
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| 95 | ruch=ruch/s; |
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| 96 | asym=asym/s; |
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| 97 | odpor=odpor/s; |
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| 98 | wchl=wchl/s; |
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| 99 | } |
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| 100 | |
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| 101 | /** main conversion function - with conversion map support */ |
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[139] | 102 | SString GenoConv_f1::convert(SString &i,MultiMap *map) |
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[109] | 103 | { |
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[348] | 104 | const char* g=i.c_str(); |
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[109] | 105 | Builder builder(g,map?1:0); |
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| 106 | builder.model.open(); |
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| 107 | builder.grow(-1,g,Pt3D_0,stdprops); // uses Model::singleStepBuild to create model elements |
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| 108 | if (builder.invalid) return SString(); |
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| 109 | builder.addPendingInputs(); |
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| 110 | builder.model.startenergy=(builder.energ_div>0)?(builder.energ/builder.energ_div):1.0; |
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| 111 | builder.model.close(); // model is ready to use now |
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| 112 | if (map) builder.model.getCurrentToF0Map(*map); // generate f1-to-f0 conversion map |
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| 113 | return builder.model.getF0Geno().getGene(); |
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| 114 | } |
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| 115 | |
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| 116 | void Builder::setPartMapping(int p,const char* g) |
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| 117 | { |
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| 118 | if (!usemapping) return; |
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| 119 | const MultiRange *r=makeRange(g); |
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| 120 | if (p<0) |
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| 121 | { //special case: mapping the part which is not yet created |
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| 122 | if (first_part_mapping) first_part_mapping->add(*r); |
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| 123 | else first_part_mapping=new MultiRange(*r); |
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| 124 | } |
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| 125 | else |
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| 126 | model.getPart(p)->addMapping(*r); |
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| 127 | } |
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| 128 | |
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| 129 | void Builder::grow(int part1,const char*g,Pt3D k,F1Props c) |
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| 130 | { |
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| 131 | int hasmuscles=0; |
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| 132 | k+=Pt3D(c.rot,0,c.skr); |
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| 133 | while(1) |
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| 134 | { |
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| 135 | switch(*g) |
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| 136 | { |
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| 137 | case 0: case ',': case ')': return; |
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| 138 | case 'R': k.x+=0.7853; setPartMapping(part1,g); break; |
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| 139 | case 'r': k.x-=0.7853; setPartMapping(part1,g); break; |
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| 140 | case 'Q': c.rot+=(1.58-c.rot)*0.3; setPartMapping(part1,g); break; |
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| 141 | case 'q': c.rot+=(-1.58-c.rot)*0.3; setPartMapping(part1,g); break; |
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| 142 | #ifdef v1f1COMPATIBLE |
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| 143 | case 'L': c.dlug+=(3.0-c.dlug)*0.3; setPartMapping(part1,g); break; |
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| 144 | #else |
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| 145 | case 'L': c.dlug+=(2.0-c.dlug)*0.3; setPartMapping(part1,g); break; |
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| 146 | #endif |
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| 147 | case 'l': c.dlug+=(0.33-c.dlug)*0.3; setPartMapping(part1,g); break; |
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| 148 | case 'A': c.asym+=(1-c.asym)*0.8; c.wykluczanie(); setPartMapping(part1,g); break; |
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| 149 | case 'a': c.asym-=c.asym*0.4; c.wykluczanie(); setPartMapping(part1,g); break; |
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| 150 | case 'I': c.wchl+=(1-c.wchl)*0.8; c.wykluczanie(); setPartMapping(part1,g); break; |
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| 151 | case 'i': c.wchl-=c.wchl*0.4; c.wykluczanie(); setPartMapping(part1,g); break; |
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| 152 | case 'S': c.odpor+=(1-c.odpor)*0.8; c.wykluczanie(); setPartMapping(part1,g); break; |
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| 153 | case 's': c.odpor-=c.odpor*0.4; c.wykluczanie(); setPartMapping(part1,g); break; |
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| 154 | case 'M': c.ruch+=(1-c.ruch)*0.8; c.wykluczanie(); setPartMapping(part1,g); break; |
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| 155 | case 'm': c.ruch-=c.ruch*0.4; c.wykluczanie(); setPartMapping(part1,g); break; |
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| 156 | case 'C': c.skr+=(2.0-c.skr)*0.25; setPartMapping(part1,g); break; |
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| 157 | case 'c': c.skr+=(-2.0-c.skr)*0.25; setPartMapping(part1,g); break; |
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| 158 | case 'F': c.tarcie+=(4-c.tarcie)*0.2; setPartMapping(part1,g); break; |
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| 159 | case 'f': c.tarcie-=c.tarcie*0.2; setPartMapping(part1,g); break; |
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| 160 | case 'W': c.masa+=(2.0-c.masa)*0.3; setPartMapping(part1,g); break; |
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| 161 | case 'w': c.masa+=(0.5-c.masa)*0.3; setPartMapping(part1,g); break; |
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| 162 | case 'E': c.energ+=(10.0-c.energ)*0.1; setPartMapping(part1,g); break; |
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| 163 | case 'e': c.energ-=c.energ*0.1; setPartMapping(part1,g); break; |
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| 164 | |
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| 165 | case 'D': c.cred+=(1.0-c.cred)*0.25; setPartMapping(part1,g); break; |
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| 166 | case 'd': c.cred+=(0.0-c.cred)*0.25; setPartMapping(part1,g); break; |
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| 167 | case 'G': c.cgreen+=(1.0-c.cgreen)*0.25; setPartMapping(part1,g); break; |
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| 168 | case 'g': c.cgreen+=(0.0-c.cgreen)*0.25; setPartMapping(part1,g); break; |
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| 169 | case 'B': c.cblue+=(1.0-c.cblue)*0.25; setPartMapping(part1,g); break; |
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| 170 | case 'b': c.cblue+=(0.0-c.cblue)*0.25; setPartMapping(part1,g); break; |
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| 171 | case 'H': c.grub+=(0.7-c.grub)*0.25; setPartMapping(part1,g); break; |
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| 172 | case 'h': c.grub+=(0.05-c.grub)*0.25; setPartMapping(part1,g); break; |
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| 173 | |
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| 174 | case '[': //neuron |
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| 175 | // setdebug(g-(char*)geny,DEBUGNEURO | !l_neu); |
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| 176 | if (model.getJointCount()) |
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| 177 | g=growNeuro(g+1,c,hasmuscles); |
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| 178 | else |
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| 179 | { |
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[375] | 180 | logMessage("GenoConv_F1","grow",1,"Illegal neuron position (ignored)"); |
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[109] | 181 | g=skipNeuro(g+1); |
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| 182 | } |
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| 183 | break; |
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| 184 | case 'X': |
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| 185 | { |
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| 186 | int freshpart=0; |
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| 187 | //setdebug(g-(char*)geny,DEBUGEST | !l_est); |
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| 188 | if (part1<0) //initial grow |
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| 189 | { |
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| 190 | if (model.getPartCount()>0) |
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| 191 | part1=0; |
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| 192 | else |
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| 193 | { |
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| 194 | part1=growPart(c,g); |
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| 195 | freshpart=1; |
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| 196 | if (first_part_mapping) |
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| 197 | model.getPart(part1)->setMapping(*first_part_mapping); |
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| 198 | } |
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| 199 | } |
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| 200 | if (!freshpart) |
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| 201 | { |
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| 202 | Part *part=model.getPart(part1); |
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| 203 | part->density=((part->mass*part->density)+1.0/c.masa)/(part->mass+1.0); // v=m*d |
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| 204 | // part->volume+=1.0/c.masa; |
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| 205 | part->mass+=1.0; |
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| 206 | } |
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| 207 | energ+=0.9*c.energ+0.1; |
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| 208 | energ_div+=1.0; |
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| 209 | |
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| 210 | int part2 = growPart(c,g); |
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| 211 | growJoint(part1,part2,k,c,g); |
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| 212 | // est* e = new est(*s,*s2,k,c,zz,this); |
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| 213 | |
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| 214 | // oslabianie cech wzdluz struktury |
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| 215 | c.dlug=0.5*c.dlug+0.5*stdprops.dlug; |
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| 216 | c.grub=0.5*c.grub+0.5*stdprops.grub; |
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| 217 | c.skr=0.66*c.skr; |
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| 218 | c.rot=0.66*c.rot; |
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| 219 | c.tarcie=0.8*c.tarcie+0.2*stdprops.tarcie; |
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| 220 | |
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| 221 | c.asym=0.8*c.asym+0.2*stdprops.asym; |
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| 222 | c.odpor=0.8*c.odpor+0.2*stdprops.odpor; |
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| 223 | c.ruch=0.8*c.ruch+0.2*stdprops.ruch; |
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| 224 | c.wchl=0.8*c.wchl+0.2*stdprops.wchl; |
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| 225 | c.masa+=(stdprops.masa-c.masa)*0.5; |
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| 226 | c.wykluczanie(); |
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| 227 | |
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| 228 | if (c.resetrange) c.bendrange=1.0; else c.resetrange=1; |
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| 229 | grow(part2,g+1,Pt3D_0,c); |
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| 230 | return; |
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| 231 | } |
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| 232 | case '(': |
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| 233 | { |
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| 234 | setPartMapping(part1,g); |
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| 235 | SList ga; |
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| 236 | int i,ile; |
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| 237 | ile=countBranches(g+1,ga); |
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| 238 | c.resetrange=0; |
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| 239 | c.bendrange=1.0/ile; |
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| 240 | for (i=0;i<ile;i++) |
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| 241 | grow(part1,(char*)ga(i),k+Pt3D(0,0,-3.141+(i+1)*(6.282/(ile+1))),c); |
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| 242 | return; |
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| 243 | } |
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| 244 | case ' ': case '\t': case '\n': case '\r': break; |
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| 245 | default: invalid=1; return; |
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| 246 | } |
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| 247 | g++; |
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| 248 | } |
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| 249 | } |
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| 250 | |
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| 251 | SyntParam* Builder::lastNeuroClassParam() |
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| 252 | { |
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| 253 | if (!neuro_cls_param) |
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| 254 | { |
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| 255 | NeuroClass *cls=last_f1_neuro->getClass(); |
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| 256 | if (cls) |
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| 257 | { |
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| 258 | neuro_cls_param=new SyntParam(last_f1_neuro->classProperties()); |
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| 259 | // this is equivalent to: |
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| 260 | // SyntParam tmp=last_f1_neuro->classProperties(); |
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| 261 | // neuro_cls_param=new SyntParam(tmp); |
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| 262 | // interestingly, some compilers eliminate the call to new SyntParam, |
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| 263 | // realizing that a copy constructor is redundant when the original object is |
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| 264 | // temporary. there are no side effect of such optimization, as long as the |
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| 265 | // copy-constructed object is exact equivalent of the original. |
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| 266 | } |
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| 267 | } |
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| 268 | return neuro_cls_param; |
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| 269 | } |
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| 270 | |
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| 271 | void Builder::addClassParam(const char* name,double value) |
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| 272 | { |
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| 273 | lastNeuroClassParam(); |
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| 274 | if (neuro_cls_param) |
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| 275 | neuro_cls_param->setDoubleById(name,value); |
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| 276 | } |
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| 277 | |
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| 278 | void Builder::addClassParam(const char* name,const char* value) |
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| 279 | { |
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| 280 | lastNeuroClassParam(); |
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| 281 | if (neuro_cls_param) |
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| 282 | { |
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| 283 | ExtValue e(value); |
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| 284 | const ExtValue &re(e); |
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| 285 | neuro_cls_param->setById(name,re); |
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| 286 | } |
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| 287 | } |
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| 288 | |
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| 289 | int Builder::countBranches(const char*g,SList &out) |
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| 290 | { |
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| 291 | int gl=0; |
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| 292 | out+=(void*)g; |
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| 293 | while (gl>=0) |
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| 294 | { |
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| 295 | switch(*g) |
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| 296 | { |
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| 297 | case 0: gl=-1; break; |
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| 298 | case '(': case '[': ++gl; break; |
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| 299 | case ')': case ']': --gl; break; |
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| 300 | case ',': if (!gl) out+=(void*)(g+1); |
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| 301 | } |
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| 302 | g++; |
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| 303 | } |
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[170] | 304 | return out.size(); |
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[109] | 305 | } |
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| 306 | |
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| 307 | int Builder::growJoint(int part1,int part2,Pt3D &angle,F1Props &c,const char *g) |
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| 308 | { |
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| 309 | double len=min(2.0,c.dlug); |
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| 310 | sprintf(tmp,"j:p1=%ld,p2=%ld,dx=%lg,rx=%lg,ry=%lg,rz=%lg,stam=%lg,vr=%g,vg=%g,vb=%g", |
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| 311 | part1,part2,len,angle.x,angle.y,angle.z,c.odpor, c.cred,c.cgreen,c.cblue); |
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| 312 | lastjoint_muscle_power=c.ruch; |
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| 313 | return model.singleStepBuild(tmp,makeRange(g)); |
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| 314 | } |
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| 315 | |
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| 316 | int Builder::growPart(F1Props &c,const char *g) |
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| 317 | { |
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[528] | 318 | sprintf(tmp,"p:dn=%lg,fr=%lg,ing=%lg,as=%lg,vs=%g,vr=%g,vg=%g,vb=%g", |
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[109] | 319 | 1.0/c.masa,c.tarcie,c.wchl,c.asym, c.grub, c.cred,c.cgreen,c.cblue); |
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| 320 | return model.singleStepBuild(tmp,makeRange(g)); |
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| 321 | } |
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| 322 | |
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| 323 | const char *Builder::skipNeuro(const char *z) |
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| 324 | { |
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| 325 | for (;*z;z++) if ((*z==']')||(*z==')')) break; |
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| 326 | return z-1; |
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| 327 | } |
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| 328 | |
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| 329 | const char* Builder::growNeuro(const char* t, F1Props& props,int &hasmuscles) |
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| 330 | { |
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| 331 | const char*neuroend=skipNeuro(t); |
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| 332 | last_f1_neuro=model.addNewNeuro(); |
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| 333 | neuro_cls_param=NULL; |
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| 334 | last_f1_neuro->attachToPart(getLastPart()); |
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| 335 | const MultiRange *mr=makeRange(t-1,neuroend+1); |
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| 336 | if (mr) last_f1_neuro->addMapping(*mr); |
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| 337 | neuro_f1_to_f0+=last_f1_neuro; |
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| 338 | |
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| 339 | SString clsname; |
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| 340 | bool haveclass=0; |
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| 341 | while(*t && *t<=' ') t++; |
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| 342 | const char* next=(*t)?(t+1):t; |
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| 343 | while(*next && *next<=' ') next++; |
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| 344 | if (*t && *next!=',' && *next!=']') // old style muscles [|rest] or [@rest] |
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| 345 | switch(*t) |
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| 346 | { |
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| 347 | case '@': if (t[1]==':') break; |
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| 348 | haveclass=1; |
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| 349 | // if (!(hasmuscles&1)) |
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| 350 | { |
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| 351 | hasmuscles|=1; |
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| 352 | Neuro *muscle=model.addNewNeuro(); |
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| 353 | sprintf(tmp,"@:p=%lg",lastjoint_muscle_power); |
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| 354 | muscle->addInput(last_f1_neuro); |
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| 355 | muscle->setDetails(tmp); |
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| 356 | muscle->attachToJoint(getLastJoint()); |
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| 357 | if (usemapping) muscle->addMapping(*makeRange(t)); |
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| 358 | } |
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| 359 | t++; |
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| 360 | break; |
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| 361 | case '|': if (t[1]==':') break; |
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| 362 | haveclass=1; |
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| 363 | // if (!(hasmuscles&2)) |
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| 364 | { |
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| 365 | hasmuscles|=2; |
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| 366 | Neuro *muscle=model.addNewNeuro(); |
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| 367 | sprintf(tmp,"|:p=%lg,r=%lg",lastjoint_muscle_power,props.bendrange); |
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| 368 | muscle->addInput(last_f1_neuro); |
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| 369 | muscle->setDetails(tmp); |
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| 370 | muscle->attachToJoint(getLastJoint()); |
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| 371 | if (usemapping) muscle->addMapping(*makeRange(t)); |
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| 372 | } |
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| 373 | t++; |
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| 374 | break; |
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| 375 | } |
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| 376 | while(*t && *t<=' ') t++; |
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| 377 | bool finished=0; |
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| 378 | const char *begin=t; |
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| 379 | const char* colon=0; |
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| 380 | SString classparams; |
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| 381 | while(!finished) |
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| 382 | { |
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| 383 | switch (*t) |
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| 384 | { |
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| 385 | case ':': colon=t; break; |
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| 386 | case 0: case ']': case ')': finished=1; |
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| 387 | // NO break! |
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| 388 | case ',': |
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| 389 | if ( !haveclass && !colon && t>begin ) |
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| 390 | { |
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| 391 | haveclass=1; |
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| 392 | SString clsname(begin,t-begin); |
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| 393 | clsname=trim(clsname); |
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| 394 | last_f1_neuro->setClassName(clsname); |
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| 395 | NeuroClass *cls=last_f1_neuro->getClass(); |
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| 396 | if (cls) |
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| 397 | { |
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| 398 | if (cls->getPreferredLocation()==2) |
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| 399 | last_f1_neuro->attachToJoint(getLastJoint()); |
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| 400 | else if (cls->getPreferredLocation()==1) |
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| 401 | last_f1_neuro->attachToPart(getLastPart()); |
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| 402 | |
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| 403 | lastNeuroClassParam(); |
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| 404 | //special handling: muscle properties (can be overwritten by subsequent property assignments) |
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[348] | 405 | if (!strcmp(cls->getName().c_str(),"|")) |
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[109] | 406 | { |
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| 407 | neuro_cls_param->setDoubleById("p",lastjoint_muscle_power); |
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| 408 | neuro_cls_param->setDoubleById("r",props.bendrange); |
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| 409 | } |
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[348] | 410 | else if (!strcmp(cls->getName().c_str(),"@")) |
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[109] | 411 | { |
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| 412 | neuro_cls_param->setDoubleById("p",lastjoint_muscle_power); |
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| 413 | } |
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| 414 | } |
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| 415 | } |
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| 416 | else if (colon && (colon>begin) && (t>colon)) |
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| 417 | growConnection(begin,colon,t,props); |
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| 418 | if (t[0]!=',') t--; |
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| 419 | begin=t+1; colon=0; |
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| 420 | break; |
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| 421 | } |
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| 422 | t++; |
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| 423 | } |
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| 424 | SAFEDELETE(neuro_cls_param); |
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| 425 | return t; |
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| 426 | } |
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| 427 | void Builder::growConnection(const char* begin, const char* colon,const char* end,F1Props& props) |
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| 428 | { |
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| 429 | while(*begin && *begin<=' ') begin++; |
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| 430 | int i; |
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| 431 | if (isdigit(begin[0]) || (begin[0]=='-')) |
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| 432 | { |
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[514] | 433 | double weight=ExtValue::getDouble(trim(SString(colon+1,end-(colon+1))).c_str()); |
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| 434 | paInt relative=ExtValue::getInt(trim(SString(begin,colon-begin)).c_str(),false); |
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[109] | 435 | int this_refno=neuro_f1_to_f0.size()-1; |
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| 436 | addOrRememberInput(this_refno,this_refno+relative,weight); |
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| 437 | } |
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| 438 | else if ((i=last_f1_neuro->extraProperties().findIdn(begin,colon-begin))>=0) |
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| 439 | { |
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| 440 | last_f1_neuro->extraProperties().set(i,colon+1); |
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| 441 | } |
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| 442 | else if (isupper(begin[0]) || strchr("*|@",begin[0])) |
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| 443 | { |
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| 444 | SString clsname(begin,colon-begin); |
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| 445 | trim(clsname); |
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| 446 | Neuro *receptor=model.addNewNeuro(); |
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| 447 | receptor->setClassName(clsname); |
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| 448 | NeuroClass *cls=receptor->getClass(); |
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| 449 | if (cls) |
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| 450 | { |
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| 451 | if (cls->getPreferredLocation()==2) receptor->attachToJoint(getLastJoint()); |
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| 452 | else if (cls->getPreferredLocation()==1) receptor->attachToPart(getLastPart()); |
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| 453 | } |
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[514] | 454 | last_f1_neuro->addInput(receptor,ExtValue::getDouble(trim(SString(colon+1,end-(colon+1))).c_str())); |
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[109] | 455 | if (usemapping) receptor->addMapping(*makeRange(begin,end-1)); |
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| 456 | } |
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| 457 | else if ((begin[0]=='>')&&(begin[1])) |
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| 458 | { |
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| 459 | Neuro *out=model.addNewNeuro(); |
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[514] | 460 | out->addInput(last_f1_neuro,ExtValue::getDouble(trim(SString(colon+1,end-(colon+1))).c_str())); |
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[109] | 461 | out->setClassName(SString(begin+1,end-colon-1)); |
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| 462 | if (begin[1]=='@') |
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| 463 | { |
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| 464 | sprintf(tmp,"p=%lg",lastjoint_muscle_power); |
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| 465 | out->setClassParams(tmp); |
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| 466 | } |
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| 467 | else if (begin[1]=='|') |
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| 468 | { |
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| 469 | sprintf(tmp,"p=%lg,r=%lg",lastjoint_muscle_power,props.bendrange); |
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| 470 | out->setClassParams(tmp); |
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| 471 | } |
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| 472 | NeuroClass *cls=out->getClass(); |
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| 473 | if (cls) |
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| 474 | { |
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| 475 | if (cls->getPreferredLocation()==2) out->attachToJoint(getLastJoint()); |
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| 476 | else if (cls->getPreferredLocation()==1) out->attachToPart(getLastPart()); |
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| 477 | } |
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| 478 | if (usemapping) out->addMapping(*makeRange(begin,end-1)); |
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| 479 | } |
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[514] | 480 | else if (*begin=='!') addClassParam("fo",ExtValue::getDouble(trim(SString(colon+1,end-(colon+1))).c_str())); |
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| 481 | else if (*begin=='=') addClassParam("in",ExtValue::getDouble(trim(SString(colon+1,end-(colon+1))).c_str())); |
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| 482 | else if (*begin=='/') addClassParam("si",ExtValue::getDouble(trim(SString(colon+1,end-(colon+1))).c_str())); |
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[109] | 483 | else if (islower(begin[0])) |
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| 484 | { |
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| 485 | SString name(begin,colon-begin); |
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| 486 | SString value(colon+1,end-(colon+1)); |
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[348] | 487 | addClassParam(name.c_str(),value.c_str()); |
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[109] | 488 | } |
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| 489 | } |
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