def process_request(self, arg_set):
inst_args = ["load_data", "temp_data", "timezone", "temp_units", "sq_ft"]
inst_args = { a_name: arg_set[a_name] for a_name in inst_args if arg_set.get(a_name)}
sum_args = ["start_at", "end_at", "step_size"]
sum_args = { a_name: arg_set[a_name] for a_name in sum_args if arg_set.get(a_name)}
ls = Loadshape(**inst_args)
sum_series = ls.cumulative_sum(**sum_args)
response = {
"cumulative_kwh_diff": sum_series.data(),
}
return response
def process_request(self, arg_set):
inst_args = [
"load_data", "temp_data", "timezone", "temp_units", "sq_ft"
]
inst_args = {
a_name: arg_set[a_name]
for a_name in inst_args if arg_set.get(a_name)
}
sum_args = ["start_at", "end_at", "step_size"]
sum_args = {
a_name: arg_set[a_name]
for a_name in sum_args if arg_set.get(a_name)
}
ls = Loadshape(**inst_args)
sum_series = ls.cumulative_sum(**sum_args)
response = {
"cumulative_kwh_diff": sum_series.data(),
}
return response
my_load_shape.add_exclusion("2013-09-27 00:00:00", "2013-09-28 00:00:00")
my_load_shape.add_named_exclusion("US_HOLIDAYS")
# ----- generate the appropriate baseline ----- #
baseline = my_load_shape.baseline(weighting_days=CUMULATIVE_SUM_WEIGHTING_DAYS,
modeling_interval=900,
step_size=900)
# ----- set up the cumulative sum dates ----- #
tz = utils.get_timezone('America/Los_Angeles')
start_at = utils.str_to_datetime(CUMULATIVE_SUM_START, tz)
end_at = utils.int_to_datetime(my_load_shape.baseline_series.end_at(), tz)
# ----- calculate long term event performance and cumulative sum series ----- #
event_performance = my_load_shape.event_performance(start_at, end_at)
cumulative_sum_series = my_load_shape.cumulative_sum(start_at, end_at)
# ----- assemble a payload summarizng the cumulative sum ----- #
out = {}
out["building"] = BUILDING_NAME
out["event_name"] = CUMULATIVE_SUM_NAME
out["sum_start_at"] = start_at.strftime("%Y-%m-%d %H:%M:%S")
out["sum_end_at"] = end_at.strftime("%Y-%m-%d %H:%M:%S")
out["event_performance"] = event_performance
out["cumulative_sum_data"] = cumulative_sum_series.data()
# ----- write output to file ----- #
file_name = path.join(EXAMPLES_DIR, "output", "cumulative-sum-example.json")
write_json(data=out, file_name=file_name)
print "CUMULATIVE SUM EXAMPLE COMPLETE"
my_load_shape.add_exclusion("2013-09-27 00:00:00", "2013-09-28 00:00:00")
my_load_shape.add_named_exclusion("US_HOLIDAYS")
# ----- generate the appropriate baseline ----- #
baseline = my_load_shape.baseline(weighting_days=CUMULATIVE_SUM_WEIGHTING_DAYS,
modeling_interval=900,
step_size=900)
# ----- set up the cumulative sum dates ----- #
tz = utils.get_timezone('America/Los_Angeles')
start_at = utils.str_to_datetime(CUMULATIVE_SUM_START, tz)
end_at = utils.int_to_datetime(my_load_shape.baseline_series.end_at(), tz)
# ----- calculate long term event performance and cumulative sum series ----- #
event_performance = my_load_shape.event_performance(start_at, end_at)
cumulative_sum_series = my_load_shape.cumulative_sum(start_at, end_at)
# ----- assemble a payload summarizng the cumulative sum ----- #
out = {}
out["building"] = BUILDING_NAME
out["event_name"] = CUMULATIVE_SUM_NAME
out["sum_start_at"] = start_at.strftime("%Y-%m-%d %H:%M:%S")
out["sum_end_at"] = end_at.strftime("%Y-%m-%d %H:%M:%S")
out["event_performance"] = event_performance
out["cumulative_sum_data"] = cumulative_sum_series.data()
# ----- write output to file ----- #
file_name = path.join(EXAMPLES_DIR, "output", "cumulative-sum-example.json")
write_json(data=out, file_name=file_name)
print "CUMULATIVE SUM EXAMPLE COMPLETE"
