[135] | 1 | // This file is a part of the Framsticks GDK. |
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| 2 | // Copyright (C) 2002-2014 Maciej Komosinski and Szymon Ulatowski. See LICENSE.txt for details. |
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| 3 | // Refer to http://www.framsticks.com/ for further information. |
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| 4 | |
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| 5 | #include <frams/virtfile/stdiofile.h> |
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| 6 | #include <frams/util/sstringutils.h> |
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[145] | 7 | #include <frams/genetics/preconfigured.h> |
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[135] | 8 | #include <frams/model/model.h> |
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| 9 | #include <frams/errmgr/stdouterr.h> |
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| 10 | #include <frams/canvas/nn_layout_model.h> |
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| 11 | |
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| 12 | #include <algorithm> |
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| 13 | |
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| 14 | /** |
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| 15 | @file |
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| 16 | Sample code: Neuron layout tester |
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| 17 | |
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| 18 | Hint: Use loader_test to extract genotypes from framsticks *.gen files: |
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| 19 | loader_test "data/walking.gen" "Walking Lizard" | neuro_layout_test - |
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| 20 | */ |
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| 21 | |
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| 22 | // stl is fun? ;-) ForwardIterator implementation for element coordinates (required by min_element/max_element) |
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| 23 | template <int MEMBER> struct NNIter //MEMBER: 0..3=x/y/w/h |
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| 24 | { |
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| 25 | NNLayoutState *nn; int index; |
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| 26 | NNIter() {} |
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| 27 | NNIter(NNLayoutState *_nn, int _index):nn(_nn),index(_index) {} |
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| 28 | int operator*() {return nn->GetXYWH(index)[MEMBER];} |
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| 29 | NNIter& operator++() {index++; return *this;} |
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| 30 | bool operator!=(const NNIter& it) {return index!=it.index;} |
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| 31 | bool operator==(const NNIter& it) {return index==it.index;} |
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| 32 | |
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| 33 | static NNIter begin(NNLayoutState *_nn) {return NNIter(_nn,0);} |
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| 34 | static NNIter end(NNLayoutState *_nn) {return NNIter(_nn,_nn->GetElements());} |
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| 35 | }; |
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| 36 | |
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| 37 | class Screen |
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| 38 | { |
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| 39 | int min_x,max_x,min_y,max_y,scale_x,scale_y; |
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| 40 | int rows,columns; |
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| 41 | char* screen; |
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| 42 | |
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| 43 | public: |
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| 44 | |
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| 45 | Screen(int _min_x,int _max_x,int _min_y,int _max_y,int _scale_x,int _scale_y) |
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| 46 | :min_x(_min_x),max_x(_max_x),min_y(_min_y),max_y(_max_y),scale_x(_scale_x),scale_y(_scale_y) |
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| 47 | { |
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| 48 | columns=(max_x-min_x+scale_x-1)/scale_x; |
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| 49 | rows=(max_y-min_y+scale_y-1)/scale_y; |
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| 50 | screen=new char[rows*columns]; |
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| 51 | memset(screen,' ',rows*columns); |
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| 52 | } |
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| 53 | |
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| 54 | ~Screen() |
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| 55 | { |
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| 56 | delete[] screen; |
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| 57 | } |
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| 58 | |
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| 59 | void put(int x,int y,const char *str) |
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| 60 | { |
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| 61 | x=(x-min_x)/scale_x; |
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| 62 | y=(y-min_y)/scale_y; |
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| 63 | if (x<0) return; |
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| 64 | if (y<0) return; |
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| 65 | if (y>=rows) return; |
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| 66 | for(;*str;str++,x++) |
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| 67 | { |
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| 68 | if (x>=columns) return; |
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| 69 | screen[columns*y+x]=*str; |
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| 70 | } |
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| 71 | } |
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| 72 | |
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| 73 | void print() |
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| 74 | { |
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| 75 | for(int y=0;y<rows;y++) |
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| 76 | { |
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| 77 | fwrite(&screen[columns*y],1,columns,stdout); |
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| 78 | printf("\n"); |
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| 79 | } |
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| 80 | } |
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| 81 | }; |
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| 82 | |
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| 83 | int main(int argc,char*argv[]) |
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| 84 | { |
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[145] | 85 | StdoutErrorHandler err;//the default ErrorHandler constructor automatically registers this object to receive framsg messages (and in this case, redirect them to standard output) |
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| 86 | PreconfiguredGenetics genetics; |
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| 87 | |
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[135] | 88 | if (argc<=1) |
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| 89 | { |
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| 90 | puts("Parameters:\n" |
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| 91 | " 1. Genotype (or - character indicating the genotype will be read from stdin)\n" |
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| 92 | " 2. (Optional) layout type (the only useful layout is 2, which is the default, see nn_simple_layout.cpp"); |
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| 93 | return 10; |
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| 94 | } |
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| 95 | SString gen(argv[1]); |
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| 96 | if (!strcmp(gen,"-")) |
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| 97 | { |
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| 98 | gen=0; |
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| 99 | StdioFILEDontClose in(stdin); |
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| 100 | loadSString(&in,gen); |
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| 101 | } |
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| 102 | int layout_type=2; |
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| 103 | if (argc>2) layout_type=atol(argv[2]); |
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| 104 | Geno g(gen); |
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| 105 | if (!g.isValid()) {puts("invalid genotype");return 5;} |
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| 106 | Model m(g); |
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| 107 | if (!m.getNeuroCount()) {puts("no neural network");return 1;} |
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| 108 | printf("%d neurons,",m.getNeuroCount()); |
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| 109 | |
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| 110 | NNLayoutState_Model nn_layout(&m); |
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| 111 | struct NNLayoutFunction &nnfun=nn_layout_functions[layout_type]; |
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| 112 | printf(" using layout type=%d (%s)\n",layout_type,nnfun.name); |
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| 113 | nnfun.doLayout(&nn_layout); |
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| 114 | |
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| 115 | for(int i=0;i<nn_layout.GetElements();i++) |
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| 116 | { |
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| 117 | int *xywh=nn_layout.GetXYWH(i); |
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| 118 | printf("#%-3d %s\t%d,%d\t%dx%d\n",i,(const char*)m.getNeuro(i)->getClassName(), |
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| 119 | xywh[0],xywh[1],xywh[2],xywh[3]); |
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| 120 | } |
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| 121 | |
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| 122 | Screen screen(*std::min_element(NNIter<0>::begin(&nn_layout),NNIter<0>::end(&nn_layout))-30, |
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| 123 | *std::max_element(NNIter<0>::begin(&nn_layout),NNIter<0>::end(&nn_layout))+70, |
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| 124 | *std::min_element(NNIter<1>::begin(&nn_layout),NNIter<1>::end(&nn_layout)), |
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| 125 | *std::max_element(NNIter<1>::begin(&nn_layout),NNIter<1>::end(&nn_layout))+30, |
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| 126 | 10,35); |
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| 127 | |
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| 128 | printf("===========================================\n"); |
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| 129 | for(int i=0;i<nn_layout.GetElements();i++) |
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| 130 | { |
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| 131 | int *xywh=nn_layout.GetXYWH(i); |
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| 132 | SString label=SString::sprintf("%d:%s",i,(const char*)m.getNeuro(i)->getClassName()); |
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| 133 | screen.put(xywh[0],xywh[1],(const char*)label); |
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| 134 | } |
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| 135 | screen.print(); |
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| 136 | printf("===========================================\n"); |
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| 137 | |
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| 138 | } |
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