def get_best_global_scenarios(quantile_step):
db = DBAccess(env.DB_RESULT_NAME)
db.clear_collection(env.DB_DETAILED_BEST_RESULT_COLLECTION_NAME)
scenarios = db.get_records(env.DB_GLOBAL_RESULT_COLLECTION_NAME,
{}).sort([("Cost PV", DESCENDING)])
step = int(quantile_step * scenarios.count())
representative_scenarios = [
scenarios.skip(step * i)[0]
for i in range(0, int(scenarios.count() / step))
]
db.save_to_db_no_check(env.DB_GLOBAL_BEST_RESULT_COLLECTION_NAME,
representative_scenarios)
def get_best_detailed_scenarios(quantile_step):
db = DBAccess(env.DB_RESULT_NAME)
db.clear_collection(env.DB_DETAILED_BEST_RESULT_COLLECTION_NAME)
scenarios = db.get_fields(env.DB_GLOBAL_RESULT_COLLECTION_NAME, {
"Cost PV": 1,
"Scenario": 1
}, [("Cost PV", DESCENDING)])
step = int(quantile_step * scenarios.count())
points = [
scenarios.skip(step * i)[0]["Scenario"]
for i in range(0, int(scenarios.count() / step))
]
representative_scenarios = db.get_records(
env.DB_DETAILED_RESULT_COLLECTION_NAME, {"Scenario": {
"$in": points
}})
db.save_to_db_no_check(env.DB_DETAILED_BEST_RESULT_COLLECTION_NAME,
representative_scenarios)
def get_best_scenarios(quantile_step, db_name="mine2farm"):
update_cache(db_name, -1)
try:
time_start = datetime.datetime.now().strftime("%d/%m/%y %H:%M:%S")
# insert status of best scenarios "running"
db_history = DBAccess(env.MONITORING_DB_NAME)
query_insert = {
'time_start': time_start,
'db_name': db_name,
'quantile_step': quantile_step,
'status': -1
}
_id = db_history.save_to_db_no_check(
env.MONITORING_COLLECTION_HISTORY_BEST_NAME, query_insert)
# get best representative scenarios
quantile_step = quantile_step / 100.
reset_db_name(db_name)
db = DBAccess(env.DB_RESULT_NAME)
logger.info("Deleting best collections from DB")
db.clear_collection(env.DB_GLOBAL_BEST_RESULT_COLLECTION_NAME)
db.clear_collection(env.DB_DETAILED_BEST_RESULT_COLLECTION_NAME)
scenarios = db.get_records(env.DB_GLOBAL_RESULT_COLLECTION_NAME,
{}).sort([("Cost PV", DESCENDING)])
scenarios_count = scenarios.count()
step = int(quantile_step * scenarios_count)
# save to db
if step == 0:
# all scenarios are concerned
logger.info("Moving all scenarios to best collections")
db.copy_to_collection(env.DB_GLOBAL_RESULT_COLLECTION_NAME,
env.DB_GLOBAL_BEST_RESULT_COLLECTION_NAME)
db.copy_to_collection(env.DB_DETAILED_RESULT_COLLECTION_NAME,
env.DB_DETAILED_BEST_RESULT_COLLECTION_NAME)
details_count = db.count(
env.DB_DETAILED_BEST_RESULT_COLLECTION_NAME)
else:
# filter on specific scenarios
representative_scenario_ids = [
scenarios.skip(step * i)[0]["Scenario"]
for i in range(0, int(scenarios_count / step))
]
logger.info("List of selected best scenarios: %s" %
representative_scenario_ids)
# simulate
scenarios_global, scenarios_details = \
Simulator().simulate(scenarios_filter=representative_scenario_ids, logistics_lp=env.LOGISTICS_LP)
# save
for scenario in scenarios_global:
db.save_to_db_no_check(
env.DB_GLOBAL_BEST_RESULT_COLLECTION_NAME,
scenarios_global[scenario])
for scenario in scenarios_details:
json_data = json.dumps(NodeJSONEncoder().encode(
scenarios_details[scenario]))
data = json.loads(json.loads(json_data))
db.save_to_db_no_check(
env.DB_DETAILED_BEST_RESULT_COLLECTION_NAME, data)
details_count = len(scenarios_details)
# status update
query_insert['global_count'] = scenarios_count
query_insert['detailed_count'] = details_count
filter_ = {'_id': ObjectId(_id)}
db_history.update_record(
collection=env.MONITORING_COLLECTION_HISTORY_BEST_NAME,
filter_=filter_,
data=query_insert)
# raw materials sensitivities
logger.info("Running sensitivity over raw materials")
db.clear_collection(env.DB_SENSITIVITY_COLLECTION_NAME)
raw_materials_df = Driver().get_data("raw_materials")
shocks = {}
for raw_material in raw_materials_df:
item = raw_material["Item"]
shocks[item] = 1
scenarios_df = pd.DataFrame(Driver().get_results(
env.DB_GLOBAL_BEST_RESULT_COLLECTION_NAME))
scenarios_dic = Utils.get_scenario_from_df(scenarios_df)
risk_engine = RiskEngine()
for scenario_id in scenarios_dic:
deltas = risk_engine.compute_delta(scenarios_dic[scenario_id],
shocks,
with_logistics=env.LOGISTICS_LP)
deltas['Scenario'] = int(scenario_id)
db.save_to_db_no_check(env.DB_SENSITIVITY_COLLECTION_NAME, deltas)
# status update
query_insert['time_end'] = datetime.datetime.now().strftime(
"%d/%m/%y %H:%M:%S")
query_insert['status'] = 0
filter_ = {'_id': ObjectId(_id)}
db_history.update_record(
collection=env.MONITORING_COLLECTION_HISTORY_BEST_NAME,
filter_=filter_,
data=query_insert)
update_cache(db_name, 0)
except Exception as e:
logger.error("Best scenarios failed")
update_cache(db_name, 0)