boolean runServices(){
boolean OK = true;
for(int i=0; i<servicesN; i++){
int sleepPeriod = services[i]->getSleepPeriod();
if(sleepPeriod <=0){ //services with sleep period as 0 or <0 are always served
if(!services[i]->run()) OK = false;
}
else if((getSecs() - lastExecution[i]) >= sleepPeriod){
lastExecution[i] = getSecs();
if(!services[i]->run()) OK = false;
}
}
return OK;
}
void end_time()
{
getSecs();
secs = theseSecs - startSecs;
millisecs = (int)(1000.0 * secs);
return;
}
void start_time()
{
getSecs();
startSecs = theseSecs;
return;
}
void quality_benchmark_fann_som(unsigned int width,
unsigned int height,
char *topology,
char *neighborhood,
char *decay,
struct fann_train_data *train_data,
struct fann_train_data *test_data,
FILE * train_out,
unsigned int num_input,
unsigned int max_training_examples, double seconds_between_reports)
{
float test_error;
double elapsed = 0;
double total_elapsed = 0;
struct fann *ann;
unsigned int current_example = 0;
ann = fann_create_som(width, height, num_input);
/* Set the topology */
if (!strcmp(topology, "hexagonal"))
{
ann->som_params->som_topology = FANN_SOM_TOPOLOGY_HEXAGONAL;
}
else if (!strcmp(topology, "rectangular"))
{
ann->som_params->som_topology = FANN_SOM_TOPOLOGY_RECTANGULAR;
}
else
{
fprintf(stderr, "Error: Unknown topology: %s\n", topology);
exit(1);
}
/* Set the neighborhood */
if (!strcmp(neighborhood, "distance"))
{
ann->som_params->som_neighborhood = FANN_SOM_NEIGHBORHOOD_DISTANCE;
}
else if (!strcmp(neighborhood, "gaussian"))
{
ann->som_params->som_neighborhood = FANN_SOM_NEIGHBORHOOD_GAUSSIAN;
}
else
{
fprintf(stderr, "Error: Unknown neighborhood: %s\n", neighborhood);
exit(1);
}
/* Set the decay */
if (!strcmp(decay, "linear"))
{
ann->som_params->som_learning_decay = FANN_SOM_LEARNING_DECAY_LINEAR;
}
else if (!strcmp(decay, "inverse"))
{
ann->som_params->som_learning_decay = FANN_SOM_LEARNING_DECAY_INVERSE;
}
else
{
fprintf(stderr, "Error: Unknown decay type: %s\n", decay);
exit(1);
}
calibrate_timer();
while (current_example < max_training_examples)
{
/* train */
elapsed = 0;
start_timer();
while((elapsed < (double) seconds_between_reports) && (current_example < max_training_examples))
{
fann_train_example_som(ann, train_data, current_example, max_training_examples);
elapsed = time_elapsed();
current_example++;
}
stop_timer();
total_elapsed += getSecs();
/* make report */
test_error = fann_get_MSE_som(ann, test_data);
/* output the statistics */
fprintf(train_out, "%8.2f %8.6f %5d\n", total_elapsed, test_error, current_example);
fprintf(stderr, "secs: %8.2f, test_error: %8.6f training_examples: %5d\r",
total_elapsed, test_error, current_example);
}
fprintf(stdout, "\nTraining samples: %d, samples/sec: %f\n", max_training_examples, (float)max_training_examples / total_elapsed);
fann_destroy(ann);
}
void start_timer() {
startSecs = getSecs();
return;
}
double stop_timer() {
return getSecs() - startSecs;
}
