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
def update_agent_log_graph(study_agent, relayout_data_store, figure_overflow,
figure_usage, scenario):
if relayout_data_store is not None and relayout_data_store["relayout_data"]:
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
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])
figure_usage["data"] = new_episode.usage_rate_trace
return figure_overflow, figure_usage
def update_production_share_graph(scenario, figure):
"""Display best agent's production share when page load"""
best_agent_ep = make_episode(best_agents[scenario]['agent'], scenario)
share_prod = EpisodeTrace.get_prod_share_trace(best_agent_ep)
figure["data"] = share_prod
return figure
def load_scenario_cards(url):
"""
Create and display html cards with scenario's kpi for
the 15 first scenarios using cache file.
"""
cards_list = []
cards_count = 0
episode_graph_layout = {
'autosize': True,
'showlegend': False,
'xaxis': {'showticklabels': False},
'yaxis': {'showticklabels': False},
'margin': {'l': 0, 'r': 0, 't': 0, 'b': 0},
}
is_episode_page = (url == "/" or url == "" or url == "/episodes")
if cards_count < 15 and is_episode_page:
for scenario in sorted(scenarios):
best_agent_episode = make_episode(best_agents[scenario]['agent'], scenario)
prod_share = EpisodeTrace.get_prod_share_trace(best_agent_episode)
consumption = best_agent_episode.profile_traces
cards_list.append(
dbc.Col(lg=4, width=12, children=[
dbc.Card(className='mb-3', children=[
dbc.CardBody([
html.H5(className="card-title",
children="Scenario {0}".format(scenario)),
dbc.Row(children=[
dbc.Col(className="mb-4", children=[
html.P(className="border-bottom h3 mb-0 text-right",
children=best_agents[scenario]['out_of']),
html.P(className="text-muted", children="Agents on Scenario")
]),
dbc.Col(className="mb-4", children=[
html.P(className="border-bottom h3 mb-0 text-right",
children='{}/{}'.format(best_agents[scenario]['value'],
meta_json[scenario]['chronics_max_timestep'])),
html.P(className="text-muted", children="Agent's Survival")
]),
dbc.Col(className="mb-4", children=[
html.P(className="border-bottom h3 mb-0 text-right",
children=round(best_agents[scenario]['cum_reward'])),
html.P(className="text-muted", children="Cumulative Reward")
]),
dbc.Col(className="mb-4", children=[
html.P(className="border-bottom h3 mb-0 text-right",
children='{} min'.format(round(
best_agent_episode.total_maintenance_duration
))),
html.P(className="text-muted", children="Total Maintenance Duration")
]),
]),
dbc.Row(className="align-items-center", children=[
dbc.Col(lg=4, width=12, children=[
html.H5('Production Share', className='text-center'),
dcc.Graph(
style={'height': '150px'},
figure=go.Figure(
layout=episode_graph_layout,
data=prod_share,
)
)
]),
dbc.Col(lg=8, width=12, children=[
html.H5('Consumption Profile', className='text-center'),
dcc.Graph(
style={'height': '150px'},
figure=go.Figure(
layout=episode_graph_layout,
data=consumption
))
]
)
])
]),
dbc.CardFooter(dbc.Button(
"Open", id=scenario, key=scenario,
className="btn-block",
style={"background-color": "#2196F3"}))
])
])
)
cards_count += 1
return cards_list
def load_scenario_cards(url):
"""
Create and display html cards with scenario's kpi for
the 15 first scenarios using cache file.
"""
cards_list = []
cards_count = 0
episode_graph_layout = {
"autosize": True,
"showlegend": False,
"xaxis": {
"showticklabels": False
},
"yaxis": {
"showticklabels": False
},
"margin": {
"l": 0,
"r": 0,
"t": 0,
"b": 0
},
}
url_split = url.split("/")
url_split = url_split[len(url_split) - 1]
is_episode_page = url_split == "/" or url_split == "" or url_split == "episodes"
start_time = time.time()
if cards_count < 15 and is_episode_page:
sorted_scenarios = list(sorted(scenarios))
if not os.path.exists(cache_dir):
print(
"Starting Multiprocessing for reading the best agent of each scenario"
)
pool = ProcessPool(n_cores)
best_agents_data = list(
pool.imap(
make_episode_without_decorate,
[
best_agents[scenario]["agent"]
for scenario in sorted_scenarios
],
sorted_scenarios,
))
pool.close()
print("Multiprocessing done")
for i, scenario in enumerate(sorted_scenarios):
best_agent_episode = best_agents_data[i]
episode_data = retrieve_episode_from_disk(
best_agent_episode.episode_name,
best_agent_episode.agent)
best_agent_episode.decorate(episode_data)
save_in_ram_cache(
best_agent_episode.episode_name,
best_agent_episode.agent,
best_agent_episode,
)
for i, scenario in enumerate(sorted_scenarios):
best_agent_episode = make_episode(
best_agents[scenario]["agent"], scenario)
prod_share = EpisodeTrace.get_prod_share_trace(
best_agent_episode)
consumption = best_agent_episode.profile_traces
cards_list.append(
dbc.Col(
id=f"card_{scenario}",
lg=4,
width=12,
children=[
dbc.Card(
className="mb-3",
children=[
dbc.CardBody([
html.H5(
className="card-title",
children="Scenario {0}".format(
scenario),
),
dbc.Row(children=[
dbc.Col(
className="mb-4",
children=[
html.P(
className=
"border-bottom h3 mb-0 text-right",
children=best_agents[
scenario]
["out_of"],
),
html.P(
className="text-muted",
children=
"Agents on Scenario",
),
],
),
dbc.Col(
className="mb-4",
children=[
html.P(
className=
"border-bottom h3 mb-0 text-right",
children="{}/{}".
format(
best_agents[
scenario]
["value"],
meta_json[scenario]
["chronics_max_timestep"],
),
),
html.P(
className="text-muted",
children=
"Agent's Survival",
),
],
),
dbc.Col(
className="mb-4",
children=[
html.P(
className=
"border-bottom h3 mb-0 text-right",
children=
f'{round(best_agents[scenario]["cum_reward"]):,}',
),
html.P(
className="text-muted",
children=
"Cumulative Reward",
),
],
),
dbc.Col(
className="mb-4",
children=[
html.P(
className=
"border-bottom h3 mb-0 text-right",
children="{} min".
format(
round(
best_agent_episode
.
total_maintenance_duration
)),
),
html.P(
className="text-muted",
children=
"Total Maintenance Duration",
),
],
),
]),
dbc.Row(
className="align-items-center",
children=[
dbc.Col(
lg=4,
width=12,
children=[
html.H5(
"Production Share",
className=
"text-center",
),
dcc.Graph(
style={
"height":
"150px"
},
figure=go.Figure(
layout=
episode_graph_layout,
data=prod_share,
),
),
],
),
dbc.Col(
lg=8,
width=12,
children=[
html.H5(
"Consumption Profile",
className=
"text-center",
),
dcc.Graph(
style={
"height":
"150px"
},
figure=go.Figure(
layout=
episode_graph_layout,
data=
consumption,
),
),
],
),
],
),
]),
dbc.CardFooter(
dbc.Button(
"Open",
id=scenario,
key=scenario,
className="btn-block",
style={
"background-color": "#2196F3"
},
)),
],
)
],
))
cards_count += 1
print(
"Initial loading time for the best agent of all scenarios = {:.1f} seconds"
.format(time.time() - start_time))
return cards_list