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)