def present_token_and_token_after_termination(configurations, algorithm):
data = []
for fault_group, configurations_sorted in configurations.items():
for i, c in enumerate(configurations_sorted):
data.append(
graphing.get_box_trace(
c.get_tokens(),
'T %s %i' % (fault_group, c.number_of_nodes)))
data.append(
graphing.get_box_trace(
c.get_tokens_after_termination(),
'T %s %i' % (fault_group, c.number_of_nodes),
'rgb(255,140,0)'))
if fault_group == '90':
data.append(
graphing.get_box_trace(
c.get_backup_tokens(),
'T %s %i' % (fault_group, c.number_of_nodes),
'rgb(140,255,0)'))
plotly.offline.plot(
graphing.hide_layout(data),
filename='../graphs/tokens_and_tokens_after_faulty-%s.html' %
algorithm)
def present_token_and_token_after_termination(configurations):
data = []
network_sizes = 4
for i in range(network_sizes):
fs_configuration = configurations['0 fs'][i]
ft_configuration = configurations['0'][i]
data.append(graphing.get_box_trace(fs_configuration.get_tokens(), 'FS %i' % fs_configuration.number_of_nodes))
data.append(graphing.get_box_trace(fs_configuration.get_tokens_after_termination(),
'FS %i' % fs_configuration.number_of_nodes, 'rgb(255,140,0)'))
data.append(graphing.get_box_trace(ft_configuration.get_tokens(), 'FT %i' % ft_configuration.number_of_nodes))
data.append(graphing.get_box_trace(ft_configuration.get_tokens_after_termination(),
'FT %i' % ft_configuration.number_of_nodes, 'rgb(255,140,0'))
plotly.offline.plot(graphing.hide_layout(data), filename='../graphs/tokens_and_token_after_termination_box_plot.html')
def present_total_times(configurations, algorithm):
data = []
for fault_group, configurations_sorted in configurations.items():
for i, c in enumerate(configurations_sorted):
data.append(
graphing.get_box_trace(
c.get_average_total_times(),
'T %s %i' % (fault_group, c.number_of_nodes)))
data.append(
graphing.get_box_trace(
c.get_total_times_after_termination(),
'T %s %i' % (fault_group, c.number_of_nodes),
'rgb(255,140,0)'))
plotly.offline.plot(data,
filename='../graphs/total_times-%s.html' % algorithm)
print("Estimated ratio of repetition with early official termination: %f" % (
repetitions_with_rea_warnings / repetitions_with_crashes))
pprint(expected_configurations, indent=2)
compare_safra_versions(configurations, algorithm)
analyse_influence_of_network_size(configurations)
analyse_influence_of_faults(configurations, algorithm)
fields = ['tokens', 'tokens_after_termination', 'number_of_nodes_crashed', 'safra_times', 'basic_times',
'safra_times_after_termination', 'total_times', 'token_bytes', 'backup_tokens']
data = defaultdict(lambda: list())
for f in fields:
for c in configurations:
data[f].append(get_box_trace(getattr(c, 'get_' + f)(),
"%i-%f-%r" % (c.number_of_nodes, c.fault_percentage, c.fault_sensitive)))
# for plot_name, plot_data in data.items():
# plotly.offline.plot(plot_data, filename='../graphs/%s.html' % plot_name)
# for configuration in merged_configurations:
# data = get_scatter_graph_with_mean_and_confidence_interval(list(range(len(configuration.repetitions))), configuration.get_tokens(), "tokens")
# data += get_scatter_graph_with_mean_and_confidence_interval(list(range(len(configuration.repetitions))), configuration.get_number_of_nodes_crashed(), "faults")
# data += get_scatter_graph_with_mean_and_confidence_interval(list(range(len(configuration.repetitions))), configuration.get_backup_tokens(), "backup")
# data += get_scatter_graph_with_mean_and_confidence_interval(list(range(len(configuration.repetitions))), configuration.get_tokens_after_termination(), "afterTermination")
# data += get_scatter_graph_with_mean_and_confidence_interval(list(range(len(configuration.repetitions))), configuration.get_safra_time(), "times")
# plotly.offline.plot(data, filename='../graphs/graph.html')