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;