How to use the eemeter.models.AverageDailyTemperatureSensitivityModel function in eemeter

def test_TemperatureSensitivityModel_with_heating():
    initial_params = {
        "base_daily_consumption": 0,
        "heating_slope": 0,
        "heating_balance_temperature": 55,
    }
    param_bounds = {
        "base_daily_consumption": [0,100],
        "heating_slope": [0,100],
        "heating_balance_temperature": [50,60],
    }
    model = AverageDailyTemperatureSensitivityModel(heating=True, cooling=False, initial_params=initial_params, param_bounds=param_bounds)
    params = model.param_type([1,60,1])
    observed_temps = np.array([[i] for i in range(50,70)])
    usages = model.transform(observed_temps,params)
    assert_allclose(usages[8:13],[3,2,1,1,1], rtol=1e-2, atol=1e-2)
    opt_params = model.fit(observed_temps, usages)
    assert_allclose(params.to_list(), opt_params.to_list(), rtol=1e-2, atol=1e-2)

def test_model_weather_input_not_np_array():
    model = AverageDailyTemperatureSensitivityModel(heating=False,cooling=False)
    params = model.param_type([1])
    observed_temps = [[70],[65,60]]
    usages = model.transform(observed_temps, params)
    assert_allclose(usages, [1,1], rtol=1e-2, atol=1e-2)

def consumption_generator_2(request):
    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.mark.slow
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)

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, \

@pytest.mark.slow
def test_annualized_gross_savings_metric(
        generated_consumption_data_pre_post_with_annualized_gross_savings_1,
        gsod_722880_2012_2014_weather_source, tmy3_722880_weather_source):

    model = AverageDailyTemperatureSensitivityModel(heating=True, cooling=True)
    meter = AnnualizedGrossSavingsMeter(temperature_unit_str="degF", model=model)

    cd, params_pre, params_post, retrofit_date, savings = \
            generated_consumption_data_pre_post_with_annualized_gross_savings_1

    reporting_period = Period(retrofit_date, datetime(2015,1,1))

    result = meter.evaluate_raw(
            model_params_baseline=params_pre,
            model_params_reporting=params_post,
            consumption_data_reporting=cd.filter_by_period(reporting_period),
            weather_normal_source=tmy3_722880_weather_source,
            energy_unit_str="kWh")

    assert_allclose(result["annualized_gross_savings"], savings,
            rtol=RTOL, atol=ATOL)

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)

def generated_consumption_data_with_hdd_1(request,
        gsod_722880_2012_2014_weather_source):
    model_params, period, total_hdd, base, temp_unit = 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]
    }
    gen = MonthlyBillingConsumptionGenerator("electricity", "kWh", "degF",
            model, params)

    datetimes = generate_monthly_billing_datetimes(period, dist=randint(30,31))
    consumption_data = gen.generate(gsod_722880_2012_2014_weather_source,
            datetimes)

    return consumption_data, total_hdd, base, temp_unit

def test_annualized_gross_savings_metric(
        generated_consumption_data_pre_post_with_annualized_gross_savings_1,
        gsod_722880_2012_2014_weather_source, tmy3_722880_weather_source):

    model = AverageDailyTemperatureSensitivityModel(heating=True, cooling=True)
    meter = AnnualizedGrossSavingsMeter(temperature_unit_str="degF", model=model)

    cd, params_pre, params_post, retrofit_date, savings = \
            generated_consumption_data_pre_post_with_annualized_gross_savings_1

    reporting_period = Period(retrofit_date, datetime(2015,1,1))

    result = meter.evaluate_raw(
            model_params_baseline=params_pre,
            model_params_reporting=params_post,
            consumption_data_reporting=cd.filter_by_period(reporting_period),
            weather_normal_source=tmy3_722880_weather_source,
            energy_unit_str="kWh")

    assert_allclose(result["annualized_gross_savings"], savings,
            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,