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 testVisualizeLocalOrderParameterNoFailures(self):
net = sync_network(10, ccore = False);
output_dynamic = net.simulate_static(20, 10, solution = solve_type.FAST, collect_dynamic = True);
sync_visualizer.show_local_order_parameter(output_dynamic, net);
sync_visualizer.show_local_order_parameter(output_dynamic, net, 0);
sync_visualizer.show_local_order_parameter(output_dynamic, net, 5);
sync_visualizer.show_local_order_parameter(output_dynamic, net, 5, 20);
def testVisualizeLocalOrderParameterNoFailures(self):
net = sync_network(10, ccore=False)
output_dynamic = net.simulate_static(20,
10,
solution=solve_type.FAST,
collect_dynamic=True)
sync_visualizer.show_local_order_parameter(output_dynamic, net)
sync_visualizer.show_local_order_parameter(output_dynamic, net, 0)
sync_visualizer.show_local_order_parameter(output_dynamic, net, 5)
sync_visualizer.show_local_order_parameter(output_dynamic, net, 5, 20)
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)
