def plot(files_list, name_files, path_out):
index_file = 0
directory_name = "sim_model_N_over_U/"
if not os.path.exists(path_out + directory_name):
os.makedirs(path_out + directory_name)
list_data_to_plot = []
for list_policy_files in files_list:
results_value_seeds = []
results_x_value = []
names = None
for path_file in list_policy_files:
file_name = "model_res.json"
file_json = open(path_file + file_name, "r")
json_data = json.load(file_json)
file_json.close()
file_name = "simulation_results.json"
file_json = open(path_file + file_name, "r")
sim_data = json.load(file_json)
file_json.close()
total_list_U = []
total_list_x = []
names = []
central_list, regionals_list, local_list, lan_list, actuator_list = divide_types(
json_data)
central_dict, regionals_dict, local_dict, lan_dict, actuator_dict = create_dicts(
sim_data)
central_group = get_type_groups(central_list)
sim_central_group = select_simulation_groups_dict(
central_group, central_dict)
U_central, x_value, name = group_node_computation(
sim_central_group, central_group, "central")
total_list_U += U_central
total_list_x += x_value
names += name
#print(U_central)
regional_group = get_type_groups(regionals_list)
sim_regional_group = select_simulation_groups_dict(
regional_group, regionals_dict)
U_regionals, x_value, name = group_node_computation(
sim_regional_group, regional_group, "regional")
total_list_U += U_regionals
total_list_x += x_value
names += name
#print(U_regionals)
local_group = get_type_groups(local_list)
sim_local_group = select_simulation_groups_dict(
local_group, local_dict)
U_locals, x_value, name = group_node_computation(
sim_local_group, local_group, "local")
total_list_U += U_locals
total_list_x += x_value
names += name
#print(U_locals)
actuator_group = get_type_groups(actuator_list)
sim_actuator_group = select_simulation_groups_dict(
actuator_group, actuator_dict)
U_actuactor, x_value, name = group_node_computation(
sim_actuator_group, actuator_group, "actuator")
total_list_U += U_actuactor
total_list_x += x_value
names += name
#print(U_actuactor)
lan_group = get_type_groups(lan_list)
sim_lan_group = select_simulation_groups_dict(lan_group, lan_dict)
U_lan, x_value, name = group_lan_computation(
sim_lan_group, lan_group, "lan")
total_list_U += U_lan
total_list_x += x_value
names += name
#print(U_lan)
results_value_seeds.append(total_list_U)
results_x_value.append(total_list_x)
array_np = np.array(results_value_seeds)
final_result = np.mean(array_np, axis=0)
array_np_x = np.array(results_x_value)
final_result_x = np.mean(array_np_x, axis=0)
#draw_histograms(list(final_result), names, "Utilization factor", "Element Type", "U", 0.0, np.amax(final_result))
#max_value = np.amax(final_result)
#max_value = 1.0
#PERCENTAGE = 0.0
max_value = np.amax(final_result)
PERCENTAGE = 0.1
#draw_histograms(list(final_result), names, "Utilization factor difference in percentage between model and simulation", "Element Type", "U", 0.0, max_value + PERCENTAGE*max_value, PATH=path_out + directory_name + name_files[index_file][0] + "_" + name_files[index_file][1])
list_data_to_plot.append((
list(final_result), list(final_result_x), [],
"Scatterplot utilization factor and difference in percentage for N between model and simulation",
"U", "Diff(N_m - N_s)", 0.0, max_value + PERCENTAGE * max_value,
path_out + directory_name + name_files[index_file][0] + "_" +
name_files[index_file][1]))
index_file += 1
max_value = 0
for data in list_data_to_plot:
if max_value < data[7]:
max_value = data[7]
for data in list_data_to_plot:
p0, p1, p2, p3, p4, p5, p6, p7, p8 = data
draw_scatterplot(p0, p1, p2, p3, p4, p5, p6, max_value, PATH=p8)
def plot(files_list, name_files, path_out):
index_file = 0
directory_name = "mean_number_queue_cat_histograms/"
if not os.path.exists(path_out + directory_name):
os.makedirs(path_out + directory_name)
list_data_to_plot = []
for list_policy_files in files_list:
results_value_seeds = []
names = None
for path_file in list_policy_files:
file_name = "model_res.json"
file_json = open(path_file + file_name, "r")
json_data = json.load(file_json)
file_json.close()
file_name = "simulation_results.json"
file_json = open(path_file + file_name, "r")
sim_data = json.load(file_json)
file_json.close()
total_list_U = []
names = []
central_list, regionals_list, local_list, lan_list, actuator_list = divide_types(json_data)
central_dict, regionals_dict, local_dict, lan_dict, actuator_dict = create_dicts(sim_data)
central_group = get_type_groups(central_list)
sim_central_group = select_simulation_groups_dict(central_group, central_dict)
U_central, name = group_node_computation(sim_central_group, "central")
total_list_U += U_central
names += name
#print(U_central)
regional_group = get_type_groups(regionals_list)
sim_regional_group = select_simulation_groups_dict(regional_group, regionals_dict)
U_regionals, name = group_node_computation(sim_regional_group, "regional")
total_list_U += U_regionals
names += name
#print(U_regionals)
local_group = get_type_groups(local_list)
sim_local_group = select_simulation_groups_dict(local_group, local_dict)
U_locals, name = group_node_computation(sim_local_group, "local")
total_list_U += U_locals
names += name
#print(U_locals)
actuator_group = get_type_groups(actuator_list)
sim_actuator_group = select_simulation_groups_dict(actuator_group, actuator_dict)
U_actuactor, name = group_node_computation(sim_actuator_group, "actuator")
total_list_U += U_actuactor
names += name
#print(U_actuactor)
lan_group = get_type_groups(lan_list)
sim_lan_group = select_simulation_groups_dict(lan_group, lan_dict)
U_lan, name = group_lan_computation(sim_lan_group, "lan")
total_list_U += U_lan
names += name
#print(U_lan)
results_value_seeds.append(total_list_U)
array_np = np.array(results_value_seeds)
final_result = np.mean(array_np, axis=0)
#draw_histograms(list(final_result), names, "Utilization factor", "Element Type", "U", 0.0, np.amax(final_result))
max_value = np.amax(final_result)
PERCENTAGE = 0.1
list_data_to_plot.append((np.transpose(final_result), names, "Mean number of jobs", "Element Type", "N", 0.0, max_value + max_value*PERCENTAGE, ["Telemetry", "Transition", "Command", "Batch"], path_out + directory_name + name_files[index_file][0] + "_" + name_files[index_file][1]))
index_file += 1
max_value = 0
for data in list_data_to_plot:
if max_value < data[6]:
max_value = data[6]
for data in list_data_to_plot:
p0, p1, p2, p3, p4, p5, p6, p7, p8 = data
draw_grouped_histograms(p0, p1, p2, p3, p4, p5, max_value, p7, PATH=p8)
