def test_consumption_data_filter_by_period_arbitrary(
consumption_data_kWh_arbitrary):
period = Period(datetime(2015,1,1), datetime(2015,1,3))
filtered_data = consumption_data_kWh_arbitrary.filter_by_period(period).data
assert_allclose(filtered_data, np.array([1,1,np.nan]),
rtol=RTOL, atol=ATOL)
assert filtered_data.index[0] == datetime(2015,1,1)
assert filtered_data.index[2] == datetime(2015,1,3)
period = Period(datetime(2014,1,1), datetime(2014,1,3,1))
filtered_data = consumption_data_kWh_arbitrary.filter_by_period(period).data
assert_allclose(filtered_data, [],
rtol=RTOL, atol=ATOL)
period = Period(None, datetime(2015,1,3))
filtered_data = consumption_data_kWh_arbitrary.filter_by_period(period).data
assert_allclose(filtered_data, np.array([1,1,np.nan]),
rtol=RTOL, atol=ATOL)
assert filtered_data.index[0] == datetime(2015,1,1)
assert filtered_data.index[2] == datetime(2015,1,3)
period = Period(datetime(2015,1,9),None)
filtered_data = consumption_data_kWh_arbitrary.filter_by_period(period).data
assert_allclose(filtered_data, np.array([1,1,np.nan]),
rtol=RTOL, atol=ATOL)
assert filtered_data.index[0] == datetime(2015,1,9)
assert filtered_data.index[2] == datetime(2015,1,11)
period = Period(None,None)
filtered_data = consumption_data_kWh_arbitrary.filter_by_period(period).data
assert_allclose(filtered_data, np.array([1,1,1,1,1,1,1,1,1,1,np.nan]),
rtol=RTOL, atol=ATOL)
assert filtered_data.index[0] == datetime(2015,1,1)
assert filtered_data.index[10] == datetime(2015,1,11)
def test_project_generator(gsod_722880_2012_2014_weather_source,
tmy3_722880_weather_source):
electricity_model = AverageDailyTemperatureSensitivityModel(cooling=True,
heating=True)
gas_model = AverageDailyTemperatureSensitivityModel(cooling=False,
heating=True)
electricity_param_distributions = {
"cooling_slope": uniform(loc=1, scale=.5),
"heating_slope": uniform(loc=1, scale=.5),
"base_daily_consumption": uniform(loc=5, scale=5),
"cooling_balance_temperature": uniform(loc=70, scale=5),
"heating_balance_temperature": uniform(loc=60, scale=5)
}
electricity_param_delta_distributions = {
"cooling_slope": uniform(loc=-.2, scale=.3),
"heating_slope": uniform(loc=-.2, scale=.3),
"base_daily_consumption": uniform(loc=-2, scale=3),
"cooling_balance_temperature": uniform(loc=0, scale=0),
"heating_balance_temperature": uniform(loc=0, scale=0)
}
gas_param_distributions = {
"heating_slope": uniform(loc=1, scale=.5),
"base_daily_consumption": uniform(loc=5, scale=5),
"heating_balance_temperature": uniform(loc=60, scale=5)
}
gas_param_delta_distributions = {
"heating_slope": uniform(loc=-.2, scale=.3),
"base_daily_consumption": uniform(loc=-2, scale=3),
"heating_balance_temperature": uniform(loc=0, scale=0)
}
generator = ProjectGenerator(electricity_model, gas_model,
electricity_param_distributions,
electricity_param_delta_distributions,
gas_param_distributions,
gas_param_delta_distributions)
location = Location(station="722880")
period = Period(datetime(2012, 1, 1), datetime(2013, 1, 1))
baseline_period = Period(datetime(2012, 1, 1), datetime(2012, 4, 1))
reporting_period = Period(datetime(2012, 5, 1), datetime(2013, 1, 1))
results = generator.generate(location, period, period, baseline_period,
reporting_period)
project = results["project"]
elec_data = project.consumption[0].data.values
gas_data = project.consumption[1].data.values
assert project.location == location
assert results.get("electricity_estimated_savings") is not None
assert results.get("natural_gas_estimated_savings") is not None
assert results.get("electricity_pre_params") is not None
assert results.get("natural_gas_pre_params") is not None
assert results.get("electricity_post_params") is not None
assert results.get("natural_gas_post_params") is not None
assert len(elec_data) in range(9, 16)
assert len(gas_data) in range(9, 16)
assert elec_data[0] < 750 # could probably lower this upper bound
assert gas_data[0] < 750 # could probably lower this upper bound
def test_consumption_data_filter_by_period_interval(
consumption_data_kWh_interval):
period = Period(datetime(2015, 1, 1), datetime(2015, 1, 3))
filtered_data = consumption_data_kWh_interval.filter_by_period(period).data
assert_allclose(filtered_data, np.array([1, 1, 1]), rtol=RTOL, atol=ATOL)
assert filtered_data.index[0] == datetime(2015, 1, 1)
assert filtered_data.index[2] == datetime(2015, 1, 3)
period = Period(datetime(2014, 1, 1), datetime(2014, 1, 3, 1))
filtered_data = consumption_data_kWh_interval.filter_by_period(period).data
assert_allclose(filtered_data, [], rtol=RTOL, atol=ATOL)
period = Period(None, datetime(2015, 1, 3))
filtered_data = consumption_data_kWh_interval.filter_by_period(period).data
assert_allclose(filtered_data, np.array([1, 1, 1]), rtol=RTOL, atol=ATOL)
assert filtered_data.index[0] == datetime(2015, 1, 1)
assert filtered_data.index[2] == datetime(2015, 1, 3)
period = Period(datetime(2015, 1, 9), None)
filtered_data = consumption_data_kWh_interval.filter_by_period(period).data
assert_allclose(filtered_data, np.array([1, 1]), rtol=RTOL, atol=ATOL)
assert filtered_data.index[0] == datetime(2015, 1, 9)
assert filtered_data.index[1] == datetime(2015, 1, 10)
period = Period(None, None)
filtered_data = consumption_data_kWh_interval.filter_by_period(period).data
assert_allclose(filtered_data,
np.array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1]),
rtol=RTOL,
atol=ATOL)
assert filtered_data.index[0] == datetime(2015, 1, 1)
assert filtered_data.index[9] == datetime(2015, 1, 10)
def test_period_both_open():
p = Period()
assert p.start is None
assert p.end is None
assert p.timedelta is None
assert not p.closed
assert datetime(2013,1,1) in p
assert datetime(2014,1,1) in p
assert datetime(2014,1,1,12) in p
assert datetime(2014,1,2) in p
assert datetime(2015,1,1) in p
assert p in p
assert Period(datetime(2014,1,1),datetime(2014,1,2)) in p
def test_project_consumption_baseline_reporting(generated_consumption_data_1):
cd, _ = generated_consumption_data_1
baseline_period = Period(datetime(2011,1,1),datetime(2013,6,1))
reporting_period = Period(datetime(2013,6,1),datetime(2016,1,1))
location = Location(zipcode="91104")
project = Project(location,[cd],baseline_period,reporting_period)
meter = ProjectConsumptionDataBaselineReporting()
result = meter.evaluate_raw(project=project)
assert result["consumption"][0]["value"].data.index[0] == datetime(2012,1,1)
assert result["consumption"][0]["value"].data.index[17] == datetime(2013,5,25)
assert result["consumption"][0]["tags"][0] == "electricity"
assert result["consumption"][0]["tags"][1] == "baseline"
assert result["consumption"][1]["value"].data.index[0] == datetime(2013,6,24)
assert result["consumption"][1]["value"].data.index[18] == datetime(2014,12,16)
assert result["consumption"][1]["tags"][0] == "electricity"
assert result["consumption"][1]["tags"][1] == "reporting"
def periods(self):
""" Converts DatetimeIndex (which is timestamp based) to an list of
Periods, which have associated start and endtimes.
Returns
-------
periods : list of eemeter.evaluation.Period
A list of consumption periods.
"""
if self.freq_timedelta is None:
# ignore last period which is NaN and acting as an end point
periods = [Period(start, end) for start, end in
zip(self.data.index,self.data.index[1:])]
return periods
else:
periods = [Period(dt, dt + self.freq_timedelta)
for dt in self.data.index]
return periods
def create_eemeter_project(project_row, consumption_data_rows):
"""
Given a row a pd.DataFrame for projects
and a set of rows for consumption data rows,
return eemeter project.
"""
location = Location(zipcode=project_row.zipcode,
lat_lng=(project_row.latitude, project_row.longitude),
station=project_row.weather_station)
baseline_period = Period(project_row.baseline_period_start,
project_row.baseline_period_end)
reporting_period = Period(project_row.reporting_period_start,
project_row.reporting_period_end)
consumptions = _create_eemeter_consumptions(consumption_data_rows)
project = Project(location, consumptions, baseline_period,
reporting_period)
return project
def default_residential_outputs_1(request, gsod_722880_2012_2014_weather_source):
elec_model_params, gas_model_params, \
elec_annualized_usage, gas_annualized_usage, \
elec_gross_savings, gas_gross_savings, \
elec_rmse, gas_rmse, elec_r_squared, gas_r_squared, \
temp_unit, cdd_tmy, hdd_tmy, total_cdd, total_hdd \
= request.param
period = Period(datetime(2012,1,1,tzinfo=pytz.utc),
datetime(2014,12,31,tzinfo=pytz.utc))
retrofit_start_date = datetime(2013,6,1,tzinfo=pytz.utc)
retrofit_completion_date = datetime(2013,8,1,tzinfo=pytz.utc)
datetimes = generate_monthly_billing_datetimes(period,randint(30,31))
# generate electricity consumption
elec_model = AverageDailyTemperatureSensitivityModel(cooling=True,heating=True)
elec_params = {
"base_daily_consumption": elec_model_params[0],
"heating_balance_temperature": elec_model_params[1],
"heating_slope": elec_model_params[2],
"cooling_balance_temperature": elec_model_params[3],
"cooling_slope": elec_model_params[4],
}
elec_gen = MonthlyBillingConsumptionGenerator("electricity", "kWh", temp_unit,
elec_model, elec_params)
elec_consumption_data = elec_gen.generate(gsod_722880_2012_2014_weather_source, datetimes)
elec_consumption_kWh_per_day, elec_consumption_n_days = \
elec_consumption_data.average_daily_consumptions()
elec_params = elec_model.param_type(elec_params)
# generate natural_gas consumption
gas_model = AverageDailyTemperatureSensitivityModel(cooling=False,heating=True)
gas_params = {
"base_daily_consumption": gas_model_params[0],
"heating_balance_temperature": gas_model_params[1],
"heating_slope": gas_model_params[2],
}
gas_gen = MonthlyBillingConsumptionGenerator("natural_gas", "therm", temp_unit,
gas_model, gas_params)
gas_consumption_data = gas_gen.generate(gsod_722880_2012_2014_weather_source, datetimes)
gas_consumption_kWh_per_day, gas_consumption_n_days = \
gas_consumption_data.average_daily_consumptions()
gas_params = gas_model.param_type(gas_params)
fixture = elec_consumption_data, gas_consumption_data, \
elec_params, gas_params, \
elec_annualized_usage, gas_annualized_usage, \
elec_gross_savings, gas_gross_savings, \
elec_rmse, gas_rmse, \
elec_r_squared, gas_r_squared, \
elec_consumption_kWh_per_day, gas_consumption_kWh_per_day, \
elec_consumption_n_days, gas_consumption_n_days, \
temp_unit, retrofit_start_date, retrofit_completion_date, \
cdd_tmy, hdd_tmy, total_cdd, total_hdd
return fixture
def create_project(params_e_pre, params_e_post, params_g_pre, params_g_post,
baseline_period_start_date, baseline_period_end_date,
reporting_period_start_date, reporting_period_end_date,
has_electricity, has_gas, weather_source, zipcode):
model_e = AverageDailyTemperatureSensitivityModel(heating=True,
cooling=True)
model_g = AverageDailyTemperatureSensitivityModel(heating=True,
cooling=False)
# generate consumption
baseline_period = Period(baseline_period_start_date,
reporting_period_start_date)
datetimes_pre = generate_monthly_billing_datetimes(baseline_period,
dist=randint(29, 31))
reporting_period = Period(datetimes_pre[-1], reporting_period_end_date)
datetimes_post = generate_monthly_billing_datetimes(reporting_period,
dist=randint(29, 31))
location = Location(zipcode=zipcode)
baseline_period = Period(baseline_period_start_date,
baseline_period_end_date)
reporting_period = Period(reporting_period_start_date,
reporting_period_end_date)
cds = []
if has_electricity:
cd_e = generate_consumption_records(model_e, params_e_pre,
params_e_post, datetimes_pre,
datetimes_post, "electricity",
"kWh", weather_source)
cds.append(cd_e)
if has_gas:
cd_g = generate_consumption_records(model_g, params_g_pre,
params_g_post, datetimes_pre,
datetimes_post, "natural_gas",
"therm", weather_source)
cds.append(cd_g)
return Project(location, cds, baseline_period, reporting_period)
def test_project_null_station():
location = Location(zipcode="INVALID")
with pytest.raises(ValueError):
baseline_period = Period(datetime(2014,1,1), datetime(2015,1,1))
reporting_period = None
project = Project(location, consumption=[],
baseline_period=baseline_period,
reporting_period=reporting_period,
other_periods=[],
weather_source=None,
weather_normal_source=None)
def test_project_attributes(generated_consumption_data_1):
cd,params = generated_consumption_data_1
baseline_period = Period(datetime(2014,1,1),datetime(2014,1,1))
location = Location(zipcode="91104")
project = Project(location,[cd,cd],baseline_period,None)
meter = ProjectFuelTypes(project)
result = meter.evaluate_raw(project=project)
assert len(result["fuel_types"]) == 2
assert result["fuel_types"][0]["value"] == "electricity"
assert result["fuel_types"][0]["tags"] == ["electricity"]
assert result["fuel_types"][1]["value"] == "electricity"
assert result["fuel_types"][1]["tags"] == ["electricity"]
def test_generate_monthly_billing_datetimes():
period = Period(datetime(2012, 1, 1), datetime(2013, 1, 1))
datetimes_30d = generate_monthly_billing_datetimes(period, randint(30, 31))
assert datetimes_30d[0] == datetime(2012, 1, 1)
assert datetimes_30d[1] == datetime(2012, 1, 31)
assert datetimes_30d[11] == datetime(2012, 11, 26)
assert datetimes_30d[12] == datetime(2012, 12, 26)
datetimes_1d = generate_monthly_billing_datetimes(period, randint(1, 2))
assert datetimes_1d[0] == datetime(2012, 1, 1)
assert datetimes_1d[1] == datetime(2012, 1, 2)
assert datetimes_1d[330] == datetime(2012, 11, 26)
assert datetimes_1d[331] == datetime(2012, 11, 27)
def test_project_attributes(generated_consumption_data_1):
cd,params = generated_consumption_data_1
baseline_period = Period(datetime(2014,1,1),datetime(2014,1,1))
location = Location(zipcode="91104")
project = Project(location,[cd],baseline_period,None)
meter = ProjectAttributes(project)
result = meter.evaluate_raw(project=project)
assert result["location"].zipcode == location.zipcode
assert result["consumption"][0] is not None
assert result["baseline_period"] is not None
assert result["reporting_period"] is None
assert result["other_periods"] == []
assert result["weather_source"].station_id == "722880"
assert result["weather_normal_source"].station_id == "722880"
def test_project_partial_period():
location = Location(zipcode="60604")
baseline_period = Period(None, datetime(2015,1,1))
reporting_period = Period(datetime(2015, 1,1), None)
project = Project(location, consumption=[],
baseline_period=baseline_period,
reporting_period=reporting_period,
other_periods=[],
weather_source=None,
weather_normal_source=None)
assert project.consumption == []
assert project.baseline_period.start is None
assert project.baseline_period.end == datetime(2015,1,1)
assert project.reporting_period.start == datetime(2015,1,1)
assert project.reporting_period.end is None
assert project.other_periods == []
assert project.weather_source.station_id == "725340"
assert project.weather_normal_source.station_id == "725340"
assert len(project.all_periods()) == 2
assert project._total_date_range()[0] == None
assert project._total_date_range()[1] == None
assert len(project.segmented_consumption_data()) == 0
def total_period(self):
""" The total period over which consumption data is recorded.
Returns
-------
period : eemeter.evaluation.Period
The total time span covered by this ConsumptionData instance.
"""
if self.data.shape[0] < 1:
return None
start_date = self.data.index[0]
end_date = self.data.index[-1]
if self.freq_timedelta is not None:
end_date += self.freq_timedelta
return Period(start_date, end_date)
def test_gross_savings_metric(
generated_consumption_data_pre_post_with_gross_savings_1,
gsod_722880_2012_2014_weather_source):
model = AverageDailyTemperatureSensitivityModel(heating=True, cooling=True)
meter = GrossSavingsMeter(temperature_unit_str="degF", model=model)
cd, params_pre, params_post, retrofit_date, savings = \
generated_consumption_data_pre_post_with_gross_savings_1
reporting_period = Period(retrofit_date, datetime(2015, 1, 1))
result = meter.evaluate_raw(
consumption_data_reporting=cd.filter_by_period(reporting_period),
model_params_baseline=params_pre,
weather_source=gsod_722880_2012_2014_weather_source,
energy_unit_str="kWh")
assert_allclose(result["gross_savings"], savings, rtol=RTOL, atol=ATOL)
def annual_daily_temperatures(self, unit):
"""Returns a list of daily temperature normals for a typical
meteorological year.
Parameters
----------
unit : {"degC", "degF"}
The unit in which temperatures should be returned.
Returns
-------
out : np.ndarray
List with single element which is an array of observed
daily temperatures.
"""
periods = [Period(start=datetime(1900,1,1), end=datetime(1901,1,1))]
return self.daily_temperatures(periods, unit)
def evaluate_raw(self, weather_normal_source, **kwargs):
"""Sums the total observed CDD in a normal year
Parameters
----------
weather_normal_source : eemeter.weather.WeatherSourceBase and eemeter.weather.WeatherNormalMixin
A weather data source from a location as geographically and
climatically close as possible to the target project.
Returns
-------
out : dict
- "normal_annual_hdd": the total cooling degree days observed
during a typical meteorological year
"""
annual_period = Period(datetime(2013, 1, 1), datetime(2014, 1, 1))
cdd = weather_normal_source.cdd(annual_period,
self.temperature_unit_str, self.base)
return {"normal_annual_cdd": cdd}
def _normalize_period(self, period):
start = self._normalize_datetime(period.start)
year_offset = period.end.year - period.start.year
end = self._normalize_datetime(period.end, year_offset)
return Period(start, end)
def test_period_name():
p = Period(name="baseline")
assert p.name == "baseline"
def test_period_end_closed():
p = Period(end=datetime(2014,1,2))
assert p.start is None
assert p.end == datetime(2014,1,2)
assert p.timedelta is None
assert not p.closed
assert datetime(2013,1,1) in p
assert datetime(2014,1,1) in p
assert datetime(2014,1,1,12) in p
assert datetime(2014,1,2) in p
assert datetime(2015,1,1) not in p
assert Period(datetime(2013,1,1),datetime(2013,1,2)) in p
assert Period(datetime(2013,1,1),datetime(2014,1,1)) in p
assert Period(datetime(2013,1,1),datetime(2014,1,1,12)) in p
assert Period(datetime(2013,1,1),datetime(2014,1,2)) in p
assert Period(datetime(2013,1,1),datetime(2014,1,3)) not in p
assert Period(datetime(2014,1,1),datetime(2014,1,1,12)) in p
assert Period(datetime(2014,1,1),datetime(2014,1,2)) in p
assert Period(datetime(2014,1,1),datetime(2014,1,3)) not in p
assert Period(datetime(2014,1,1,12),datetime(2014,1,1,13)) in p
assert Period(datetime(2014,1,1,12),datetime(2014,1,2)) in p
assert Period(datetime(2014,1,1,12),datetime(2014,1,3)) not in p
assert Period(datetime(2014,1,2),datetime(2014,1,3)) not in p
assert Period(datetime(2014,1,3),datetime(2014,1,4)) not in p
def test_default_residential_meter(default_residential_outputs_1,
gsod_722880_2012_2014_weather_source, tmy3_722880_weather_source):
elec_consumption_data, gas_consumption_data, \
elec_params, gas_params, \
elec_annualized_usage, gas_annualized_usage, \
elec_gross_savings, gas_gross_savings, \
elec_rmse, gas_rmse, \
elec_r_squared, gas_r_squared, \
elec_consumption_kWh_per_day, gas_consumption_kWh_per_day, \
elec_consumption_n_days, gas_consumption_n_days, \
temp_unit, retrofit_start_date, retrofit_completion_date, \
cdd_tmy, hdd_tmy, total_cdd, total_hdd = \
default_residential_outputs_1
meter = DefaultResidentialMeter(temperature_unit_str=temp_unit)
location = Location(station="722880")
baseline_period = Period(datetime(2012,1,1,tzinfo=pytz.utc),retrofit_start_date)
reporting_period = Period(retrofit_completion_date, datetime(2014,12,31,tzinfo=pytz.utc))
project = Project(location, [elec_consumption_data, gas_consumption_data], baseline_period,
reporting_period)
data_collection = DataCollection(project=project)
result = meter.evaluate(data_collection)
assert_allclose(result.get_data('annualized_usage',
tags=['electricity','baseline']).value, elec_annualized_usage,
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('annualized_usage',
tags=['natural_gas','baseline']).value, gas_annualized_usage,
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('annualized_usage',
tags=['electricity','reporting']).value, elec_annualized_usage,
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('annualized_usage',
tags=['natural_gas','reporting']).value, gas_annualized_usage,
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('gross_savings',
tags=['electricity']).value, elec_gross_savings,
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('gross_savings',
tags=['natural_gas']).value, gas_gross_savings,
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('average_daily_usages',
tags=['electricity', 'baseline']).value, elec_consumption_kWh_per_day[:17],
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('average_daily_usages',
tags=['natural_gas', 'baseline']).value, gas_consumption_kWh_per_day[:17],
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('average_daily_usages',
tags=['electricity', 'reporting']).value, elec_consumption_kWh_per_day[20:],
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('average_daily_usages',
tags=['natural_gas', 'reporting']).value, gas_consumption_kWh_per_day[20:],
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('cdd_tmy',
tags=['electricity', 'baseline']).value, cdd_tmy,
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('cdd_tmy',
tags=['natural_gas', 'baseline']).value, cdd_tmy,
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('cdd_tmy',
tags=['electricity', 'reporting']).value, cdd_tmy,
rtol=RTOL, atol=ATOL)
assert_allclose(result.get_data('cdd_tmy',
tags=['natural_gas', 'reporting']).value, cdd_tmy,
rtol=RTOL, atol=ATOL)
elec_rmse_results = result.search('rmse', ['electricity'])
assert elec_rmse_results.count() == 2
for data_container in elec_rmse_results.iteritems():
assert_allclose(data_container.value, elec_rmse, rtol=RTOL, atol=ATOL)
gas_rmse_results = result.search('rmse', ['natural_gas'])
assert gas_rmse_results.count() == 2
for data_container in gas_rmse_results.iteritems():
assert_allclose(data_container.value, gas_rmse, rtol=RTOL, atol=ATOL)
elec_r_squared_results = result.search('r_squared', ['electricity'])
assert elec_r_squared_results.count() == 2
for data_container in elec_r_squared_results.iteritems():
assert_allclose(data_container.value, elec_r_squared, rtol=RTOL, atol=ATOL)
gas_r_squared_results = result.search('r_squared', ['natural_gas'])
assert gas_r_squared_results.count() == 2
for data_container in gas_r_squared_results.iteritems():
assert_allclose(data_container.value, gas_r_squared, rtol=RTOL, atol=ATOL)
def get_example_project(zipcode):
# location
location = Location(zipcode=zipcode)
station = location.station
weather_source = GSODWeatherSource(station,2011,2015)
# model
model_e = AverageDailyTemperatureSensitivityModel(cooling=True, heating=True)
model_g = AverageDailyTemperatureSensitivityModel(cooling=False, heating=True)
# model params
params_e_b = {
"cooling_slope": 1,
"heating_slope": 1,
"base_daily_consumption": 30,
"cooling_balance_temperature": 73,
"heating_balance_temperature": 68,
}
params_e_r = {
"cooling_slope": .5,
"heating_slope": .5,
"base_daily_consumption": 15,
"cooling_balance_temperature": 73,
"heating_balance_temperature": 68,
}
params_g_b = {
"heating_slope": .2,
"base_daily_consumption": 2,
"heating_balance_temperature": 68,
}
params_g_r = {
"heating_slope": .1,
"base_daily_consumption": 1,
"heating_balance_temperature": 68,
}
#generators
gen_e_b = MonthlyBillingConsumptionGenerator("electricity", "kWh", "degF",
model_e, params_e_b)
gen_e_r = MonthlyBillingConsumptionGenerator("electricity", "kWh", "degF",
model_e, params_e_r)
gen_g_b = MonthlyBillingConsumptionGenerator("natural_gas", "therm", "degF",
model_g, params_g_b)
gen_g_r = MonthlyBillingConsumptionGenerator("natural_gas", "therm", "degF",
model_g, params_g_r)
# time periods
period = Period(datetime(2011,1,1,tzinfo=pytz.utc), datetime(2015,1,1,tzinfo=pytz.utc))
datetimes = generate_monthly_billing_datetimes(period, dist=randint(30,31))
# consumption data
cd_e_b = gen_e_b.generate(weather_source, datetimes, daily_noise_dist=None)
cd_e_r = gen_e_r.generate(weather_source, datetimes, daily_noise_dist=None)
cd_g_b = gen_g_b.generate(weather_source, datetimes, daily_noise_dist=None)
cd_g_r = gen_g_r.generate(weather_source, datetimes, daily_noise_dist=None)
# periods
periods = cd_e_b.periods()
reporting_period = Period(datetime(2013,1,1,tzinfo=pytz.utc), datetime(2015,1,1,tzinfo=pytz.utc))
baseline_period = Period(datetime(2011,1,1,tzinfo=pytz.utc), datetime(2013,1,1,tzinfo=pytz.utc))
# records
records_e = []
records_g = []
for e_b, e_r, g_b, g_r, p in zip(cd_e_b.data, cd_e_r.data, cd_g_b.data, cd_g_r.data, periods):
e = e_r if p in reporting_period else e_b
g = g_r if p in reporting_period else g_b
record_e = {"start": p.start, "end": p.end, "value": e}
record_g = {"start": p.start, "end": p.end, "value": g}
records_e.append(record_e)
records_g.append(record_g)
# consumption_data
cd_e = ConsumptionData(records_e, "electricity", "kWh",
record_type="arbitrary")
cd_g = ConsumptionData(records_g, "natural_gas", "therm",
record_type="arbitrary")
consumptions = [cd_e, cd_g]
# project
project = Project(location, consumptions, baseline_period, reporting_period)
return project
model_params, fuel_type, consumption_unit_name, temperature_unit_name = \
request.param
model = AverageDailyTemperatureSensitivityModel(cooling=True, heating=True)
params = {
"base_daily_consumption": model_params[0],
"heating_slope": model_params[1],
"heating_balance_temperature": model_params[2],
"cooling_slope": model_params[3],
"cooling_balance_temperature": model_params[4]
}
generator = MonthlyBillingConsumptionGenerator(fuel_type,
consumption_unit_name, temperature_unit_name, model, params)
params = model.param_type(params)
return generator, params
@pytest.fixture(params=[(Period(datetime(2012,1,1),datetime(2014,12,31)),
randint(30,31))])
def generated_consumption_data_1(request,
gsod_722880_2012_2014_weather_source, consumption_generator_1):
period, dist = request.param
generator, params = consumption_generator_1
datetimes = generate_monthly_billing_datetimes(period, dist)
consumption_data = generator.generate(
gsod_722880_2012_2014_weather_source, datetimes)
return consumption_data, params
@pytest.fixture(params=[(Period(datetime(2012,1,1),datetime(2014,12,31)),randint(30,31))])
def generated_consumption_data_2(request,
gsod_722880_2012_2014_weather_source, consumption_generator_2):
period, dist = request.param
generator, params = consumption_generator_2
def test_period_both_closed():
p = Period(datetime(2014,1,1),datetime(2014,1,2))
assert p.start == datetime(2014,1,1)
assert p.end == datetime(2014,1,2)
assert p.timedelta == timedelta(days=1)
assert p.closed
assert datetime(2013,1,1) not in p
assert datetime(2014,1,1) in p
assert datetime(2014,1,1,12) in p
assert datetime(2014,1,2) in p
assert datetime(2015,1,1) not in p
assert Period(datetime(2013,1,1),datetime(2013,1,2)) not in p
assert Period(datetime(2013,1,1),datetime(2014,1,1)) not in p
assert Period(datetime(2013,1,1),datetime(2014,1,1,12)) not in p
assert Period(datetime(2013,1,1),datetime(2014,1,2)) not in p
assert Period(datetime(2013,1,1),datetime(2014,1,3)) not in p
assert Period(datetime(2014,1,1),datetime(2014,1,1,12)) in p
assert Period(datetime(2014,1,1),datetime(2014,1,2)) in p
assert Period(datetime(2014,1,1),datetime(2014,1,3)) not in p
assert Period(datetime(2014,1,1,12),datetime(2014,1,1,13)) in p
assert Period(datetime(2014,1,1,12),datetime(2014,1,2)) in p
assert Period(datetime(2014,1,1,12),datetime(2014,1,3)) not in p
assert Period(datetime(2014,1,2),datetime(2014,1,3)) not in p
assert Period(datetime(2014,1,3),datetime(2014,1,4)) not in p
