def template_clustering(file,
radius,
order,
show_dyn=False,
show_conn=False,
show_clusters=True,
ena_conn_weight=False,
ccore_flag=True,
tolerance=0.1):
sample = read_sample(file)
network = syncnet(sample,
radius,
enable_conn_weight=ena_conn_weight,
ccore=ccore_flag)
(ticks, analyser) = timedcall(network.process, order, solve_type.FAST,
show_dyn)
print("Sample: ", file, "\t\tExecution time: ", ticks, "\n")
if (show_dyn == True):
sync_visualizer.show_output_dynamic(analyser)
sync_visualizer.animate(analyser)
#sync_visualizer.animate_output_dynamic(analyser);
#sync_visualizer.animate_correlation_matrix(analyser, colormap = 'hsv');
if ((show_conn == True) and (ccore_flag == False)):
network.show_network()
if (show_clusters == True):
clusters = analyser.allocate_clusters(tolerance)
print("amout of clusters: ", len(clusters))
draw_clusters(sample, clusters)
def templateVisualizerNoFailures(self, size, velocity, ccore_flag):
net = sync_network(size, ccore=ccore_flag)
output_dynamic = net.simulate_dynamic(solution=solve_type.FAST,
collect_dynamic=True)
sync_visualizer.animate(output_dynamic)
sync_visualizer.animate_correlation_matrix(output_dynamic, velocity)
sync_visualizer.animate_output_dynamic(output_dynamic, velocity)
sync_visualizer.show_correlation_matrix(output_dynamic)
sync_visualizer.show_output_dynamic(output_dynamic)
def template_animate_output_dynamic(title, amount_oscillators,
coupling_stregth, frequency, order):
network = sync_network(amount_oscillators,
coupling_stregth,
frequency,
ccore=True)
sync_output_dynamic = network.simulate_dynamic(order,
solution=solve_type.RK4,
collect_dynamic=True)
sync_visualizer.animate(sync_output_dynamic, title)
def templateVisualizerNoFailures(size, velocity, ccore_flag):
net = sync_network(size, ccore = ccore_flag);
output_dynamic = net.simulate_dynamic(solution = solve_type.FAST, collect_dynamic = True);
sync_visualizer.animate(output_dynamic);
sync_visualizer.animate_correlation_matrix(output_dynamic, velocity);
sync_visualizer.animate_output_dynamic(output_dynamic, velocity);
sync_visualizer.animate_phase_matrix(output_dynamic, 1, size, velocity);
sync_visualizer.show_correlation_matrix(output_dynamic);
sync_visualizer.show_output_dynamic(output_dynamic);
sync_visualizer.show_phase_matrix(output_dynamic, 1, size);
sync_visualizer.show_order_parameter(output_dynamic);
sync_visualizer.show_local_order_parameter(output_dynamic, net);
def template_clustering(file, radius, order, show_dyn = False, show_conn = False, show_clusters = True, ena_conn_weight = False, ccore_flag = True, tolerance = 0.1):
sample = read_sample(file)
syncnet_instance = syncnet(sample, radius, enable_conn_weight = ena_conn_weight, ccore = ccore_flag)
(ticks, analyser) = timedcall(syncnet_instance.process, order, solve_type.FAST, show_dyn)
print("Sample: ", file, "\t\tExecution time: ", ticks)
if show_dyn == True:
sync_visualizer.show_output_dynamic(analyser)
sync_visualizer.animate(analyser)
sync_visualizer.show_local_order_parameter(analyser, syncnet_instance)
#sync_visualizer.animate_output_dynamic(analyser);
#sync_visualizer.animate_correlation_matrix(analyser, colormap = 'hsv')
if show_conn == True:
syncnet_instance.show_network()
if show_clusters == True:
clusters = analyser.allocate_clusters(tolerance)
print("Amount of allocated clusters: ", len(clusters))
draw_clusters(sample, clusters)
print("----------------------------\n")
return (sample, clusters)
def template_clustering(file, radius, order, show_dyn = False, show_conn = False, show_clusters = True, ena_conn_weight = False, ccore_flag = True, tolerance = 0.1):
sample = read_sample(file)
syncnet_instance = syncnet(sample, radius, enable_conn_weight = ena_conn_weight, ccore = ccore_flag)
(ticks, analyser) = timedcall(syncnet_instance.process, order, solve_type.FAST, show_dyn)
print("Sample: ", file, "\t\tExecution time: ", ticks)
if show_dyn == True:
sync_visualizer.show_output_dynamic(analyser)
sync_visualizer.animate(analyser)
sync_visualizer.show_local_order_parameter(analyser, syncnet_instance)
#sync_visualizer.animate_output_dynamic(analyser);
#sync_visualizer.animate_correlation_matrix(analyser, colormap = 'hsv')
if show_conn == True:
syncnet_instance.show_network()
if show_clusters == True:
clusters = analyser.allocate_clusters(tolerance)
print("Amount of allocated clusters: ", len(clusters))
draw_clusters(sample, clusters)
print("----------------------------\n")
return (sample, clusters)
def template_animate_output_dynamic(title, amount_oscillators, coupling_stregth, frequency, order):
network = sync_network(amount_oscillators, coupling_stregth, frequency, ccore = True);
sync_output_dynamic = network.simulate_dynamic(order, solution = solve_type.RK4, collect_dynamic = True);
sync_visualizer.animate(sync_output_dynamic, title);
