def environment_ts_data(kind, episode, equipments):
"""
Get the selected kind of timeserie trace for an equipment used in episode.
There's four kind of trace possible:
- Load
- Production
- Hazards
- Maintenances
:param kind: Type of trace
:param episode: Episode studied
:param equipments: A equipment to analyze like substation etc.
:param prod_types: Different types of production
:return: A list of plotly object corresponding to a trace
"""
if kind == "Load":
return EpisodeTrace.get_load_trace_per_equipment(episode, equipments)
if kind == "Production":
prod_types = episode.get_prod_types()
return EpisodeTrace.get_all_prod_trace(episode, prod_types, equipments)
if kind == "Hazards":
return EpisodeTrace.get_hazard_trace(episode, equipments)
if kind == "Maintenances":
return EpisodeTrace.get_maintenance_trace(episode, equipments)
def update_agent_log_graph(study_agent, relayout_data_store,
figure_overflow, figure_usage, scenario,
agent_study_ts, relayoutStoreMacro_ts):
if agent_study_ts is not None and relayoutStoreMacro_ts is not None:
condition = (relayout_data_store is not None
and relayout_data_store["relayout_data"]
and relayoutStoreMacro_ts > agent_study_ts)
else:
condition = (relayout_data_store is not None
and relayout_data_store["relayout_data"])
if condition:
relayout_data = relayout_data_store["relayout_data"]
layout_usage = figure_usage["layout"]
new_axis_layout = get_axis_relayout(figure_usage, relayout_data)
if new_axis_layout is not None:
layout_usage.update(new_axis_layout)
figure_overflow["layout"].update(new_axis_layout)
return figure_overflow, figure_usage
new_episode = make_episode(study_agent, scenario)
figure_overflow["data"] = new_episode.total_overflow_trace.copy()
maintenance_traces = EpisodeTrace.get_maintenance_trace(
new_episode, ["total"])
if len(maintenance_traces) != 0:
maintenance_traces[0].update({"name": "Nb of maintenances"})
figure_overflow["data"].append(maintenance_traces[0])
hazard_traces = EpisodeTrace.get_hazard_trace(new_episode,
["total"]).copy()
if len(hazard_traces) != 0:
hazard_traces[0].update({"name": "Nb of hazards"})
figure_overflow["data"].append(hazard_traces[0])
attacks_trace = EpisodeTrace.get_attacks_trace(new_episode).copy()
if len(attacks_trace) != 0:
attacks_trace[0].update({"name": "Attacks"})
figure_overflow["data"].append(attacks_trace[0])
figure_usage["data"] = new_episode.usage_rate_trace
return figure_overflow, figure_usage