pyclustering/nnet/sync.py
def simulate_dynamic(self, order = 0.998, solution = solve_type.FAST, collect_dynamic = False, step = 0.1, int_step = 0.01, threshold_changes = 0.0000001):
        """!
        @brief Performs dynamic simulation of the network until stop condition is not reached. Stop condition is defined by input argument 'order'.
        
        @param[in] order (double): Order of process synchronization, distributed 0..1.
        @param[in] solution (solve_type): Type of solution.
        @param[in] collect_dynamic (bool): If True - returns whole dynamic of oscillatory network, otherwise returns only last values of dynamics.
        @param[in] step (double): Time step of one iteration of simulation.
        @param[in] int_step (double): Integration step, should be less than step.
        @param[in] threshold_changes (double): Additional stop condition that helps prevent infinite simulation, defines limit of changes of oscillators between current and previous steps.
        
        @return (list) Dynamic of oscillatory network. If argument 'collect_dynamic' = True, than return dynamic for the whole simulation time,
                otherwise returns only last values (last step of simulation) of dynamic.
        
        @see simulate()
        @see simulate_static()
        
        """
        
        if (self._ccore_network_pointer is not None):
            ccore_instance_dynamic = wrapper.sync_simulate_dynamic(self._ccore_network_pointer, order, solution, collect_dynamic, step, int_step, threshold_changes);
            return sync_dynamic(None, None, ccore_instance_dynamic);
        
        # For statistics and integration
        time_counter = 0;
        
        # Prevent infinite loop. It's possible when required state cannot be reached.
        previous_order = 0;
        current_order = self.sync_local_order();
        
        # If requested input dynamics
        dyn_phase = [];
        dyn_time = [];
        if (collect_dynamic == True):
            dyn_phase.append(self._phases);
            dyn_time.append(0);
        
        # Execute until sync state will be reached
        while (current_order < order):
            # update states of oscillators
            self._phases = self._calculate_phases(solution, time_counter, step, int_step);
            
            # update time
            time_counter += step;
            
            # if requested input dynamic
            if (collect_dynamic == True):
                dyn_phase.append(self._phases);
                dyn_time.append(time_counter);
                
            # update orders
            previous_order = current_order;
            current_order = self.sync_local_order();
            
            # hang prevention
            if (abs(current_order - previous_order) < threshold_changes):
                # print("Warning: sync_network::simulate_dynamic - simulation is aborted due to low level of convergence rate (order = " + str(current_order) + ").");
                break;
            
        if (collect_dynamic != True):
            dyn_phase.append(self._phases);
            dyn_time.append(time_counter);

        output_sync_dynamic = sync_dynamic(dyn_phase, dyn_time, None);
        return output_sync_dynamic;
def simulate_dynamic(self, order = 0.998, solution = solve_type.FAST, collect_dynamic = False, step = 0.1, int_step = 0.01, threshold_changes = 0.0000001):
        """!
        @brief Performs dynamic simulation of the network until stop condition is not reached. Stop condition is defined by input argument 'order'.
        
        @param[in] order (double): Order of process synchronization, distributed 0..1.
        @param[in] solution (solve_type): Type of solution.
        @param[in] collect_dynamic (bool): If True - returns whole dynamic of oscillatory network, otherwise returns only last values of dynamics.
        @param[in] step (double): Time step of one iteration of simulation.
        @param[in] int_step (double): Integration step, should be less than step.
        @param[in] threshold_changes (double): Additional stop condition that helps prevent infinite simulation, defines limit of changes of oscillators between current and previous steps.
        
        @return (list) Dynamic of oscillatory network. If argument 'collect_dynamic' = True, than return dynamic for the whole simulation time,
                otherwise returns only last values (last step of simulation) of dynamic.
        
        @see simulate()
        @see simulate_static()
        
        """
        
        if (self._ccore_network_pointer is not None):
            ccore_instance_dynamic = wrapper.sync_simulate_dynamic(self._ccore_network_pointer, order, solution, collect_dynamic, step, int_step, threshold_changes);
            return sync_dynamic(None, None, ccore_instance_dynamic);
        
        # For statistics and integration
        time_counter = 0;
        
        # Prevent infinite loop. It's possible when required state cannot be reached.
        previous_order = 0;
        current_order = self.sync_local_order();
        
        # If requested input dynamics
        dyn_phase = [];
        dyn_time = [];
        if (collect_dynamic == True):
            dyn_phase.append(self._phases);
            dyn_time.append(0);
        
        # Execute until sync state will be reached
        while (current_order < order):
            # update states of oscillators
            self._phases = self._calculate_phases(solution, time_counter, step, int_step);
            
            # update time
            time_counter += step;
            
            # if requested input dynamic
            if (collect_dynamic == True):
                dyn_phase.append(self._phases);
                dyn_time.append(time_counter);
                
            # update orders
            previous_order = current_order;
            current_order = self.sync_local_order();
            
            # hang prevention
            if (abs(current_order - previous_order) < threshold_changes):
                # print("Warning: sync_network::simulate_dynamic - simulation is aborted due to low level of convergence rate (order = " + str(current_order) + ").");
                break;
            
        if (collect_dynamic != True):
            dyn_phase.append(self._phases);
            dyn_time.append(time_counter);

        output_sync_dynamic = sync_dynamic(dyn_phase, dyn_time, None);
        return output_sync_dynamic;
!
        @brief Performs dynamic simulation of the network until stop condition is not reached. Stop condition is defined by input argument 'order'.
        
        @param[in] order (double): Order of process synchronization, distributed 0..1.
        @param[in] solution (solve_type): Type of solution.
        @param[in] collect_dynamic (bool): If True - returns whole dynamic of oscillatory network, otherwise returns only last values of dynamics.
        @param[in] step (double): Time step of one iteration of simulation.
        @param[in] int_step (double): Integration step, should be less than step.
        @param[in] threshold_changes (double): Additional stop condition that helps prevent infinite simulation, defines limit of changes of oscillators between current and previous steps.
        
        @return (list) Dynamic of oscillatory network. If argument 'collect_dynamic' = True, than return dynamic for the whole simulation time,
                otherwise returns only last values (last step of simulation) of dynamic.
        
        @see simulate()
        @see simulate_static()