source: cpp/frams/_demos/neuro_test.cpp @ 1302

// This file is a part of Framsticks SDK.  http://www.framsticks.com/
// Copyright (C) 1999-2020  Maciej Komosinski and Szymon Ulatowski.
// See LICENSE.txt for details.

#include <frams/genetics/geno.h>
#include <common/virtfile/stdiofile.h>
#include <frams/util/sstringutils.h>
#include <frams/genetics/preconfigured.h>
#include <frams/neuro/neuroimpl.h>
#include <frams/neuro/neurofactory.h>
#include <common/loggers/loggertostdout.h>

/**
 @file
 Sample code: Neural network tester (can run your custom neurons)
*/

#ifndef SDK_WITHOUT_FRAMS
#include <frams/mech/creatmechobj.h>
int CreatMechObject::modeltags_id = 0;
int CreatMechObject::mechtags_id = 0;
#endif

ParamEntry creature_paramtab[] = { 0 };

#ifdef VEYETEST
#include <frams/neuro/impl/neuroimpl-vectoreye.h>

#define N_VEye 0
#define N_VMotor 1
#define N_Mode 2
#define N_Fitness 3
#define LEARNINGSTEPS 50

void veyeStep(Model &m, int step)
{
        static float angle = 0;

        NeuroNetImpl::getImpl(m.getNeuro(N_Mode))->setState(step >= LEARNINGSTEPS); //0 (learning) or 1 (normal)

        NeuroImpl *ni = NeuroNetImpl::getImpl(m.getNeuro(N_VEye));
        ((NI_VectorEye*)ni)->relpos.y = 0;
        ((NI_VectorEye*)ni)->relpos.z = 0;
        if (NeuroNetImpl::getImpl(m.getNeuro(N_Mode))->getNewState() < 0.5)
        { //learning
                ((NI_VectorEye*)ni)->relpos.x = 5.0 * sin(2 * M_PI * step / LEARNINGSTEPS);
        }
        else
        { //VMotor controls location of VEye
                angle += NeuroNetImpl::getImpl(m.getNeuro(N_VMotor))->getState();
                angle = fmod((double)angle, M_PI * 2.0);
                ((NI_VectorEye*)ni)->relpos.x = 5 * sin(angle);
        }

        NeuroNetImpl::getImpl(m.getNeuro(N_Fitness))->setState(angle); //wymaga poprawy
        //oraz trzeba przemyslec kolejnosc get/set'ow neuronow zeby sygnal sie dobrze propagowal.
}
#endif

int main(int argc, char*argv[])
{
        LoggerToStdout messages_to_stdout(LoggerBase::Enable);
        PreconfiguredGenetics genetics;

        if (argc <= 1)
        {
                puts("Parameters: <genotype> [number of simulation steps]");
                return 10;
        }
        SString gen(argv[1]);
        if (!strcmp(gen.c_str(), "-"))
        {
                gen = 0;
                StdioFILEDontClose in(stdin);
                loadSString(&in, gen);
        }
        Geno g(gen);
        if (!g.isValid()) { puts("invalid genotype"); return 5; }
        Model m(g, Model::SHAPETYPE_UNKNOWN);
        if (!m.getNeuroCount()) { puts("no neural network"); return 1; }
        printf("%d neurons,", m.getNeuroCount());
        NeuroFactory neurofac;
        neurofac.setStandardImplementation();
        NeuroNetConfig nn_config(&neurofac);
        NeuroNetImpl *nn = new NeuroNetImpl(m, nn_config);
        int i; Neuro *n;
        if (!nn->getErrorCount()) printf(" no errors\n");
        else
        {
                printf(" %d errors:", nn->getErrorCount());
                int no_impl = 0; SString no_impl_names;
                int init_err = 0; SString init_err_names;
                for (i = 0; i < m.getNeuroCount(); i++)
                {
                        n = m.getNeuro(i);
                        NeuroImpl *ni = NeuroNetImpl::getImpl(n);
                        if (!ni)
                        {
                                if (no_impl) no_impl_names += ',';
                                no_impl_names += SString::sprintf("#%d.%s", i, n->getClassName().c_str());
                                no_impl++;
                        }
                        else if (ni->status == NeuroImpl::InitError)
                        {
                                if (init_err) init_err_names += ',';
                                init_err_names += SString::sprintf("#%d.%s", i, n->getClassName().c_str());
                                init_err++;
                        }
                }
                printf("\n");
                if (no_impl) printf("%d x missing implementation (%s)\n", no_impl, no_impl_names.c_str());
                if (init_err) printf("%d x failed initialization (%s)\n", init_err, init_err_names.c_str());
        }
        int steps = 1;
        if (argc > 2) steps = atol(argv[2]);
        int st;
        printf("step");
        for (i = 0; i < m.getNeuroCount(); i++)
        {
                n = m.getNeuro(i);
                printf("\t#%d.%s", i, n->getClassName().c_str());
        }
        printf("\n");
        for (st = 0; st <= steps; st++)
        {
#ifdef VEYETEST
                veyeStep(m, st);
#endif
                printf("%d", st);
                for (i = 0; i < m.getNeuroCount(); i++)
                {
                        n = m.getNeuro(i);
                        printf("\t%g", n->state);
                }
                printf("\n");
                nn->simulateNeuroNet();
        }
        neurofac.freeImplementation();
}