// 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::SHAPE_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();
}