Vector<double> BoundingLayer::calculate_second_derivative(const Vector<double>& inputs) const
{
std::ostringstream buffer;
const size_t bounding_neurons_number = get_bounding_neurons_number();
const Vector<double> outputs = calculate_outputs(inputs);
for(size_t i = 0; i < bounding_neurons_number; i++)
{
if(outputs[i] == lower_bounds[i])
{
buffer << "OpenNN Exception: BoundingLayer class.\n"
<< "Vector<double> calculate_outputs(const Vector<double>&) const method.\n"
<< "Output is equal to lower bound. The bounding function is not differentiable at this point.\n";
throw std::logic_error(buffer.str());
}
else if(outputs[i] == upper_bounds[i])
{
buffer << "OpenNN Exception: BoundingLayer class.\n"
<< "Vector<double> calculate_outputs(const Vector<double>&) const method.\n"
<< "Output is equal to upper bound. The bounding function is not differentiable at this point.\n";
throw std::logic_error(buffer.str());
}
}
Vector<double> second_derivative(bounding_neurons_number, 0.0);
return(second_derivative);
}
void Petri_Conveyor::execute(void* arg) {
struct _pulse pulse;
init_places();
while (!isStopped()) {
if (-1 == MsgReceivePulse(conveyor_dispatcher_Chid, &pulse,
sizeof(pulse), NULL)) {
if (isStopped()) {
break; // channel destroyed, Thread ending
}
perror("Petri_Motor: MsgReceivePulse");
exit(EXIT_FAILURE);
}
conveyor_tmpArr = conveyor_dispatcher->get_conveyor_inputs();
set_conveyor_inputs();
process_transitions();
calculate_outputs();
NotifyReactor();
//conveyor_dispatcher->set_disp_Outputs(conveyor_lokal_outputs);
}
}
Vector<double> BoundingLayer::calculate_derivative(const Vector<double>& inputs) const
{
const size_t bounding_neurons_number = get_bounding_neurons_number();
const Vector<double> outputs = calculate_outputs(inputs);
Vector<double> derivatives(bounding_neurons_number);
for(size_t i = 0; i < bounding_neurons_number; i++)
{
if(outputs[i] <= lower_bounds[i] || outputs[i] >= upper_bounds[i])
{
derivatives[i] = 0.0;
}
else
{
derivatives[i] = 1.0;
}
}
return(derivatives);
}
