def update_agent_log_action_graphs(study_agent, figure_sub, figure_switch_line,
scenario):
new_episode = make_episode(study_agent, scenario)
figure_sub["data"] = actions_model.get_action_per_sub(new_episode)
figure_switch_line["data"] = actions_model.get_action_per_line(new_episode)
figure_sub["layout"].update(
actions_model.update_layout(
len(figure_sub["data"][0]["x"]) == 0,
"No Actions on subs for this Agent"))
figure_switch_line["layout"].update(
actions_model.update_layout(
len(figure_switch_line["data"][0]["x"]) == 0,
"No Actions on lines for this Agent"))
return figure_sub, figure_switch_line
def update_action_repartition_pie(study_agent, figure, scenario):
new_episode = make_episode(study_agent, scenario)
figure['data'] = action_repartition_pie(new_episode)
figure['layout'].update(
actions_model.update_layout(figure["data"][0].values == (0, 0),
"No Actions for this Agent"))
return figure
def maintenance_duration_hist(study_agent, figure, scenario):
new_episode = make_episode(study_agent, scenario)
figure['data'] = [go.Histogram(x=hist_duration_maintenances(new_episode))]
figure["layout"].update(
actions_model.update_layout(
len(figure["data"][0]["x"]) == 0,
"No Maintenances for this scenario"))
figure["layout"]["xaxis"]["rangemode"] = "tozero"
return figure
def update_agent_log_action_graphs(study_agent, ref_agent, figure_sub,
figure_switch_line, figure_redisp,
scenario):
new_episode = make_episode(study_agent, scenario)
ref_episode = make_episode(ref_agent, scenario)
y_max = None
figure_sub["data"] = actions_model.get_action_per_sub(new_episode)
if len(figure_sub["data"][0]["x"]) != 0:
figure_sub["data"].append(
actions_model.get_action_per_sub(ref_episode)[0])
y_max = max(
map(max_or_zero, [trace.y
for trace in figure_sub["data"]])) + 1
figure_switch_line["data"] = actions_model.get_action_per_line(
new_episode)
if len(figure_switch_line["data"][0]["x"]) != 0:
figure_switch_line["data"].append(
actions_model.get_action_per_line(ref_episode)[0])
if y_max is None:
y_max = (max(
map(
max_or_zero,
[trace.y for trace in figure_switch_line["data"]],
)) + 1)
if (max(
map(max_or_zero,
[trace.y
for trace in figure_switch_line["data"]])) > y_max):
y_max = (max(
map(
max_or_zero,
[trace.y for trace in figure_switch_line["data"]],
)) + 1)
figure_redisp["data"] = actions_model.get_action_redispatch(
new_episode)
if len(figure_redisp["data"][0]["x"]) != 0:
figure_redisp["data"].append(
actions_model.get_action_redispatch(ref_episode)[0])
if y_max is None:
y_max = (max(
map(max_or_zero,
[trace.y for trace in figure_redisp["data"]])) + 1)
if (max(
map(max_or_zero,
[trace.y
for trace in figure_redisp["data"]])) > y_max):
y_max = (max(
map(max_or_zero,
[trace.y for trace in figure_redisp["data"]])) + 1)
figure_sub["layout"].update(
actions_model.update_layout(
len(figure_sub["data"][0]["x"]) == 0,
"No Actions on subs for this Agent",
))
figure_switch_line["layout"].update(
actions_model.update_layout(
len(figure_switch_line["data"][0]["x"]) == 0,
"No Actions on lines for this Agent",
))
figure_redisp["layout"].update(
actions_model.update_layout(
len(figure_redisp["data"][0]["x"]) == 0,
"No redispatching actions for this Agent",
))
if y_max:
figure_sub["layout"]["yaxis"].update(range=[0, y_max])
figure_switch_line["layout"]["yaxis"].update(range=[0, y_max])
figure_redisp["layout"]["yaxis"].update(range=[0, y_max])
return figure_sub, figure_switch_line, figure_redisp