def update_actions_graph(study_agent, relayout_data_store, figure, agent_ref,
scenario):
if relayout_data_store is not None and relayout_data_store["relayout_data"]:
relayout_data = relayout_data_store["relayout_data"]
layout = figure["layout"]
new_axis_layout = get_axis_relayout(figure, relayout_data)
if new_axis_layout is not None:
layout.update(new_axis_layout)
return figure
return make_action_ts(study_agent, agent_ref, scenario, figure['layout'])
def load_ts(
relayout_data_store,
window,
study_agent,
rew_figure,
cumrew_figure,
actions_figure,
agent_ref,
scenario,
):
figures = [rew_figure, cumrew_figure, actions_figure]
condition = (relayout_data_store is not None
and relayout_data_store["relayout_data"])
if condition:
relayout_data = relayout_data_store["relayout_data"]
relayouted = False
for figure in figures:
axis_layout = get_axis_relayout(figure, relayout_data)
if axis_layout is not None:
figure["layout"].update(axis_layout)
relayouted = True
if relayouted:
return figures
rew_figure, cumrew_figure = common_graph.make_rewards_ts(
study_agent, agent_ref, scenario, rew_figure, cumrew_figure)
actions_figure = common_graph.make_action_ts(study_agent, agent_ref,
scenario,
actions_figure["layout"])
figures = [rew_figure, cumrew_figure, actions_figure]
if window is not None:
start_datetime = dt.datetime.strptime(window[0],
"%Y-%m-%dT%H:%M:%S")
end_datetime = dt.datetime.strptime(window[-1],
"%Y-%m-%dT%H:%M:%S")
for figure in figures:
figure["layout"].update(xaxis=dict(
range=[start_datetime, end_datetime], autorange=False))
return figures
def load_actions_ts(relayout_data_store, window, figure, selected_timestamp,
study_agent, agent_ref, scenario):
layout = figure["layout"]
if relayout_data_store is not None and relayout_data_store["relayout_data"]:
relayout_data = relayout_data_store["relayout_data"]
new_axis_layout = get_axis_relayout(figure, relayout_data)
if new_axis_layout is not None:
layout.update(new_axis_layout)
return figure
figure = common_graph.make_action_ts(study_agent, agent_ref, scenario,
layout)
if window is not None:
figure["layout"].update(xaxis=dict(range=window, autorange=False))
return figure
def update_actions_graph(study_agent, relayout_data_store, figure,
agent_ref, 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 = figure["layout"]
new_axis_layout = get_axis_relayout(figure, relayout_data)
if new_axis_layout is not None:
layout.update(new_axis_layout)
return figure
return make_action_ts(study_agent, agent_ref, scenario,
figure['layout'])
def update_synchronized_figures(
agent_study_ts,
ref_agent,
relayout_data_store,
rew_figure,
cumrew_figure,
overflow_figure,
usage_rate_figure,
actions_figure,
scenario,
study_agent,
relayoutStoreMacro_ts,
):
figures = [
rew_figure,
cumrew_figure,
overflow_figure,
usage_rate_figure,
actions_figure,
]
episode = make_episode(study_agent, scenario)
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"]
relayouted = False
for figure in figures:
axis_layout = get_axis_relayout(figure, relayout_data)
if axis_layout is not None:
figure["layout"].update(axis_layout)
relayouted = True
if relayouted:
return figures
new_reward_fig, new_cumreward_fig = make_rewards_ts(
study_agent, ref_agent, scenario, rew_figure, cumrew_figure)
overflow_figure["data"] = episode.total_overflow_trace.copy()
for event in ["maintenance", "hazard", "attacks"]:
func = getattr(EpisodeTrace, f"get_{event}_trace")
traces = func(episode, ["total"])
if len(traces) > 0:
traces[0].update({"name": event.capitalize()})
overflow_figure["data"].append(traces[0])
usage_rate_figure["data"] = episode.usage_rate_trace
new_action_fig = make_action_ts(study_agent, ref_agent, scenario,
actions_figure["layout"])
return (
new_reward_fig,
new_cumreward_fig,
overflow_figure,
usage_rate_figure,
new_action_fig,
)