1 | // This file is a part of Framsticks SDK. http://www.framsticks.com/ |
---|
2 | // Copyright (C) 1999-2020 Maciej Komosinski and Szymon Ulatowski. |
---|
3 | // See LICENSE.txt for details. |
---|
4 | |
---|
5 | #include <frams/genetics/geno.h> |
---|
6 | #include <common/virtfile/stdiofile.h> |
---|
7 | #include <frams/util/sstringutils.h> |
---|
8 | #include <frams/genetics/preconfigured.h> |
---|
9 | #include <frams/neuro/neuroimpl.h> |
---|
10 | #include <frams/neuro/neurofactory.h> |
---|
11 | #include <common/loggers/loggertostdout.h> |
---|
12 | |
---|
13 | /** |
---|
14 | @file |
---|
15 | Sample code: Neural network tester (can run your custom neurons) |
---|
16 | */ |
---|
17 | |
---|
18 | #ifndef SDK_WITHOUT_FRAMS |
---|
19 | #include <frams/mech/creatmechobj.h> |
---|
20 | int CreatMechObject::modeltags_id = 0; |
---|
21 | int CreatMechObject::mechtags_id = 0; |
---|
22 | #endif |
---|
23 | |
---|
24 | ParamEntry creature_paramtab[] = { 0 }; |
---|
25 | |
---|
26 | #ifdef VEYETEST |
---|
27 | #include <frams/neuro/impl/neuroimpl-vectoreye.h> |
---|
28 | |
---|
29 | #define N_VEye 0 |
---|
30 | #define N_VMotor 1 |
---|
31 | #define N_Mode 2 |
---|
32 | #define N_Fitness 3 |
---|
33 | #define LEARNINGSTEPS 50 |
---|
34 | |
---|
35 | void veyeStep(Model &m, int step) |
---|
36 | { |
---|
37 | static float angle = 0; |
---|
38 | |
---|
39 | NeuroNetImpl::getImpl(m.getNeuro(N_Mode))->setState(step >= LEARNINGSTEPS); //0 (learning) or 1 (normal) |
---|
40 | |
---|
41 | NeuroImpl *ni = NeuroNetImpl::getImpl(m.getNeuro(N_VEye)); |
---|
42 | ((NI_VectorEye*)ni)->relpos.y = 0; |
---|
43 | ((NI_VectorEye*)ni)->relpos.z = 0; |
---|
44 | if (NeuroNetImpl::getImpl(m.getNeuro(N_Mode))->getNewState() < 0.5) |
---|
45 | { //learning |
---|
46 | ((NI_VectorEye*)ni)->relpos.x = 5.0 * sin(2 * M_PI * step / LEARNINGSTEPS); |
---|
47 | } |
---|
48 | else |
---|
49 | { //VMotor controls location of VEye |
---|
50 | angle += NeuroNetImpl::getImpl(m.getNeuro(N_VMotor))->getState(); |
---|
51 | angle = fmod((double)angle, M_PI * 2.0); |
---|
52 | ((NI_VectorEye*)ni)->relpos.x = 5 * sin(angle); |
---|
53 | } |
---|
54 | |
---|
55 | NeuroNetImpl::getImpl(m.getNeuro(N_Fitness))->setState(angle); //wymaga poprawy |
---|
56 | //oraz trzeba przemyslec kolejnosc get/set'ow neuronow zeby sygnal sie dobrze propagowal. |
---|
57 | } |
---|
58 | #endif |
---|
59 | |
---|
60 | int main(int argc, char*argv[]) |
---|
61 | { |
---|
62 | LoggerToStdout messages_to_stdout(LoggerBase::Enable); |
---|
63 | PreconfiguredGenetics genetics; |
---|
64 | |
---|
65 | if (argc <= 1) |
---|
66 | { |
---|
67 | puts("Parameters: <genotype> [number of simulation steps]"); |
---|
68 | return 10; |
---|
69 | } |
---|
70 | SString gen(argv[1]); |
---|
71 | if (!strcmp(gen.c_str(), "-")) |
---|
72 | { |
---|
73 | gen = 0; |
---|
74 | StdioFILEDontClose in(stdin); |
---|
75 | loadSString(&in, gen); |
---|
76 | } |
---|
77 | Geno g(gen); |
---|
78 | if (!g.isValid()) { puts("invalid genotype"); return 5; } |
---|
79 | Model m(g, Model::SHAPE_UNKNOWN); |
---|
80 | if (!m.getNeuroCount()) { puts("no neural network"); return 1; } |
---|
81 | printf("%d neurons,", m.getNeuroCount()); |
---|
82 | NeuroFactory neurofac; |
---|
83 | neurofac.setStandardImplementation(); |
---|
84 | NeuroNetConfig nn_config(&neurofac); |
---|
85 | NeuroNetImpl *nn = new NeuroNetImpl(m, nn_config); |
---|
86 | int i; Neuro *n; |
---|
87 | if (!nn->getErrorCount()) printf(" no errors\n"); |
---|
88 | else |
---|
89 | { |
---|
90 | printf(" %d errors:", nn->getErrorCount()); |
---|
91 | int no_impl = 0; SString no_impl_names; |
---|
92 | int init_err = 0; SString init_err_names; |
---|
93 | for (i = 0; i < m.getNeuroCount(); i++) |
---|
94 | { |
---|
95 | n = m.getNeuro(i); |
---|
96 | NeuroImpl *ni = NeuroNetImpl::getImpl(n); |
---|
97 | if (!ni) |
---|
98 | { |
---|
99 | if (no_impl) no_impl_names += ','; |
---|
100 | no_impl_names += SString::sprintf("#%d.%s", i, n->getClassName().c_str()); |
---|
101 | no_impl++; |
---|
102 | } |
---|
103 | else if (ni->status == NeuroImpl::InitError) |
---|
104 | { |
---|
105 | if (init_err) init_err_names += ','; |
---|
106 | init_err_names += SString::sprintf("#%d.%s", i, n->getClassName().c_str()); |
---|
107 | init_err++; |
---|
108 | } |
---|
109 | } |
---|
110 | printf("\n"); |
---|
111 | if (no_impl) printf("%d x missing implementation (%s)\n", no_impl, no_impl_names.c_str()); |
---|
112 | if (init_err) printf("%d x failed initialization (%s)\n", init_err, init_err_names.c_str()); |
---|
113 | } |
---|
114 | int steps = 1; |
---|
115 | if (argc > 2) steps = atol(argv[2]); |
---|
116 | int st; |
---|
117 | printf("step"); |
---|
118 | for (i = 0; i < m.getNeuroCount(); i++) |
---|
119 | { |
---|
120 | n = m.getNeuro(i); |
---|
121 | printf("\t#%d.%s", i, n->getClassName().c_str()); |
---|
122 | } |
---|
123 | printf("\n"); |
---|
124 | for (st = 0; st <= steps; st++) |
---|
125 | { |
---|
126 | #ifdef VEYETEST |
---|
127 | veyeStep(m, st); |
---|
128 | #endif |
---|
129 | printf("%d", st); |
---|
130 | for (i = 0; i < m.getNeuroCount(); i++) |
---|
131 | { |
---|
132 | n = m.getNeuro(i); |
---|
133 | printf("\t%g", n->state); |
---|
134 | } |
---|
135 | printf("\n"); |
---|
136 | nn->simulateNeuroNet(); |
---|
137 | } |
---|
138 | neurofac.freeImplementation(); |
---|
139 | } |
---|