void movimentaInimigos(){
for (int i = 0; i < inimigos.size(); i++) {
inimigo a = inimigos[i];
(rand()%10)/2 == 0 ? a.posX += randfrom(0, 10) : a.posX -= randfrom(0, 10);
(rand()%10)/2 == 0 ? a.posZ += randfrom(0, 10) : a.posZ -= randfrom(0, 10);
if(i == 0){
//printf("X: %f - Z: %f\n",a.posX,a.posZ);
}
}
}
void criaInimigos(int qtd){
if (inimigos.size() > 0) {
movimentaInimigos();
}else{
for (int i = 0; i < qtd; i++) {
inimigo aux;
aux.posX = (rand()%10)/2 == 0 ? randfrom(0, 300) : -randfrom(0, 300);
aux.posY = 400;
aux.posZ = (rand()%10)/2 == 0 ? randfrom(0, 300) : -randfrom(0, 300);
inimigos.push_back(aux);
}
criaInimigos(qtd);
}
}
int CreateDenseMatrixGeneral(char *fileName, unsigned long int numRows, unsigned long int numCols, unsigned int seed, double min, double max) {
//Options: numRows numCols fileName seed
FILE *output;
//long nz;
unsigned long int i, j;
MM_typecode outputmatcode;
mm_initialize_typecode(&outputmatcode);
mm_set_matrix(&outputmatcode);
mm_set_coordinate(&outputmatcode);
//mm_set_dense(&outputmatcode);
mm_set_real(&outputmatcode);
mm_set_general(&outputmatcode);
if(strcmp(fileName,"stdout")==0){
output = stdout;
}
else{
if ((output = fopen(fileName, "w")) == NULL){
fprintf(stderr,"[%s] Unable to open file for writing\n",__func__);
return 0;
}
}
double value = 0.0;
srand (seed);
mm_write_banner(output, outputmatcode);
mm_write_mtx_crd_size(output, numRows, numCols, numRows*numCols);
//ret_code = fprintf(output,"\%\%MatrixMarket matrix coordinate real symmetric\n");
//unsigned long long int val1 = 0;
//unsigned long long int val2 = 0;
for(i = 0;i < numRows; i++){
for(j = 0; j< numCols; j++){
value = randfrom(min, max);
fprintf(output, "%lu %lu %lg\n",i+1,j+1,value);
}
}
fclose(output);
return 1;
}
/**
* Initialize a neuron with random weights and tanh as transfer function.
* Has to be given the number of inputs.
*/
pNeuron create_random_neuron (neuron_head input_neuron_head) {
if (NULL == input_neuron_head) {
perror ("Empty list of input neurons. Can't create new neuron.");
exit (EXIT_FAILURE);
}
pNeuron cur_neuron = (pNeuron) malloc (sizeof(struct neuron));
if (NULL == cur_neuron) {
perror ("Not enough memory to create neuron.");
exit (EXIT_FAILURE);
}
// Init standard values.
cur_neuron->output = 0;
cur_neuron->net_sum = 0;
cur_neuron->transfer = &tanh;
// Init first weight. It's for the bias and therefore has no belonging neuron.
weight_head cur_weight_head = create_weight_node (randfrom(-0.5, 0.5), NULL);
weight_head weights = cur_weight_head, prev_weight_head = NULL;
unsigned int first_index = input_neuron_head->index;
// Loop through input neurons and create weights for every neuron.
do {
// Initialize the new current weight randomly, point it to the current neuron.
cur_weight_head = create_weight_node (randfrom(-0.5, 0.5), input_neuron_head->current_neuron);
// If we have a previous weight node, point it to the current weight node
if (NULL != prev_weight_head) {
prev_weight_head->next = cur_weight_head;
}
// Move to next element in input list.
prev_weight_head = cur_weight_head;
if (NULL != input_neuron_head->next) input_neuron_head = input_neuron_head->next;
} while (input_neuron_head->index != first_index);
cur_neuron->weights = weights;
return cur_neuron;
}
