def test_daily(trace4, mock_isd_weather_source):
mdbf = ModelDataBillingFormatter()
input_data = mdbf.create_input(
trace4, mock_isd_weather_source)
trace_data, temperature_data = input_data
assert trace_data.shape == (100,)
assert temperature_data.shape == (100,)
def test_basic_billing(input_billing_df, monkeypatch_temperature_data,
mock_isd_weather_source):
m = CaltrackMonthlyModel(fit_cdd=True)
assert str(m).startswith("Caltrack")
assert m.n is None
assert m.params is None
assert m.r2 is None
assert m.rmse is None
assert m.y is None
output = m.fit(input_billing_df)
assert "r2" in output
assert "rmse" in output
assert "cvrmse" in output
assert "model_params" in output
assert "n" in output
assert 'formula' in m.params
assert 'X_design_info' in m.params
assert 'coefficients' in m.params
index = pd.date_range('2011-01-01', freq='D', periods=365, tz=pytz.UTC)
formatter = ModelDataBillingFormatter()
formatted_predict_data = formatter.create_demand_fixture(
index, mock_isd_weather_source)
outputs, variance = m.predict(formatted_predict_data, summed=False)
assert outputs.shape == (365, )
assert all(variance > 0)
outputs, variance = m.predict(formatted_predict_data, summed=True)
assert outputs > 0
assert variance > 0
def test_empty(trace2, mock_isd_weather_source):
mdbf = ModelDataBillingFormatter()
input_data = mdbf.create_input(trace2, mock_isd_weather_source)
trace_data, temperature_data = input_data
assert trace_data.shape == (0, )
assert temperature_data.shape == (0, )
description = mdbf.describe_input(input_data)
assert description.get('start_date') is None
assert description.get('end_date') is None
assert description.get('n_rows') == 0
def test_empty(trace2, mock_isd_weather_source):
mdbf = ModelDataBillingFormatter()
input_data = mdbf.create_input(
trace2, mock_isd_weather_source)
trace_data, temperature_data = input_data
assert trace_data.shape == (0,)
assert temperature_data.shape == (0,)
description = mdbf.describe_input(input_data)
assert description.get('start_date') is None
assert description.get('end_date') is None
assert description.get('n_rows') == 0
def test_basic_daily(trace1, mock_isd_weather_source):
mdbf = ModelDataBillingFormatter()
input_data = mdbf.create_input(trace1, mock_isd_weather_source)
trace_data, temperature_data = input_data
assert trace_data.shape == (4, )
assert temperature_data.shape == (2832, 1)
description = mdbf.describe_input(input_data)
assert description.get('start_date') == \
datetime(2011, 1, 1, tzinfo=pytz.UTC)
assert description.get('end_date') == \
datetime(2011, 4, 29, tzinfo=pytz.UTC)
assert description.get('n_rows') == 4
def test_basic_daily(trace1, mock_isd_weather_source):
mdbf = ModelDataBillingFormatter()
input_data = mdbf.create_input(
trace1, mock_isd_weather_source)
trace_data, temperature_data = input_data
assert trace_data.shape == (4,)
assert temperature_data.shape == (2832, 1)
description = mdbf.describe_input(input_data)
assert description.get('start_date') == \
datetime(2011, 1, 1, tzinfo=pytz.UTC)
assert description.get('end_date') == \
datetime(2011, 4, 29, tzinfo=pytz.UTC)
assert description.get('n_rows') == 4
def test_basic_usage(trace, monkeypatch_temperature_data,
mock_isd_weather_source):
formatter = ModelDataBillingFormatter()
model = BillingElasticNetCVModel(65, 65)
formatted_input_data = formatter.create_input(trace,
mock_isd_weather_source)
outputs = model.fit(formatted_input_data)
assert 'upper' in outputs
assert 'lower' in outputs
assert 'n' in outputs
assert 'r2' in outputs
assert 'rmse' in outputs
assert 'cvrmse' in outputs
assert 'model_params' in outputs
index = pd.date_range('2011-01-01',
freq='H',
periods=365 * 24,
tz=pytz.UTC)
formatted_predict_data = formatter.create_demand_fixture(
index, mock_isd_weather_source)
outputs, variance = model.predict(formatted_predict_data, summed=False)
assert outputs.shape == (365, )
assert variance > 0
index = pd.date_range('2011-01-01', freq='D', periods=365, tz=pytz.UTC)
formatted_predict_data = formatter.create_demand_fixture(
index, mock_isd_weather_source)
outputs, variance = model.predict(formatted_predict_data, summed=False)
assert outputs.shape == (365, )
assert variance > 0
outputs, variance = model.predict(formatted_predict_data, summed=True)
assert outputs > 0
assert variance > 0
assert "ModelDataBillingFormatter" in str(ModelDataBillingFormatter)
def split_modeled_energy_trace_monthly(monthly_trace, modeling_period_set,
mock_isd_weather_source):
# create SplitModeledEnergyTrace
formatter = ModelDataBillingFormatter()
model_mapping = {
'modeling_period_1': BillingElasticNetCVModel(65, 65),
'modeling_period_2': BillingElasticNetCVModel(65, 65),
}
smet = SplitModeledEnergyTrace(monthly_trace, formatter, model_mapping,
modeling_period_set)
smet.fit(mock_isd_weather_source)
return smet
def test_basic_usage(trace, mock_isd_weather_source):
formatter = ModelDataBillingFormatter()
model = BillingElasticNetCVModel(65, 65)
formatted_input_data = formatter.create_input(
trace, mock_isd_weather_source)
outputs = model.fit(formatted_input_data)
assert 'upper' in outputs
assert 'lower' in outputs
assert 'n' in outputs
assert 'r2' in outputs
assert 'rmse' in outputs
assert 'cvrmse' in outputs
assert 'model_params' in outputs
index = pd.date_range('2011-01-01', freq='H', periods=365*24, tz=pytz.UTC)
formatted_predict_data = formatter.create_demand_fixture(
index, mock_isd_weather_source)
outputs = model.predict(formatted_predict_data)
assert outputs.shape == (365,)
assert "ModelDataBillingFormatter" in str(ModelDataBillingFormatter)
def test_empty(trace2, monkeypatch_temperature_data, mock_isd_weather_source):
mdbf = ModelDataBillingFormatter()
input_data = mdbf.create_input(trace2, mock_isd_weather_source)
trace_data, temperature_data = input_data
assert trace_data.shape == (0, )
assert temperature_data.shape == (0, )
description = mdbf.describe_input(input_data)
assert description.get('start_date') is None
assert description.get('end_date') is None
assert description.get('n_rows') == 0
missing = mdbf.get_input_data_mask(input_data)
assert missing.shape == (0, )
daily = mdbf.daily_trace_data(trace2)
assert daily.shape[0] == 1
assert_allclose(daily.sum(), trace2.data.value.sum())
def test_basic_monthly(trace1, monkeypatch_temperature_data,
mock_isd_weather_source):
mdbf = ModelDataBillingFormatter()
input_data = mdbf.create_input(trace1, mock_isd_weather_source)
trace_data, temperature_data = input_data
assert trace_data.shape == (4, )
assert temperature_data.shape == (2832, 1)
description = mdbf.describe_input(input_data)
assert description.get('start_date') == \
datetime(2011, 1, 1, tzinfo=pytz.UTC)
assert description.get('end_date') == \
datetime(2011, 4, 29, tzinfo=pytz.UTC)
assert description.get('n_rows') == 4
missing = mdbf.get_input_data_mask(input_data)
assert missing.shape == (118, )
assert sum(missing) == 0
daily = mdbf.daily_trace_data(trace1)
assert daily.shape[0] == 119
assert_allclose(daily.sum(), trace1.data.value.sum())
def test_small(trace3, monkeypatch_temperature_data, mock_isd_weather_source):
mdbf = ModelDataBillingFormatter()
with pytest.raises(ValueError):
mdbf.create_input(trace3, mock_isd_weather_source)
def input_billing_df(monkeypatch_temperature_data, billing_trace,
mock_isd_weather_source):
mdbf = ModelDataBillingFormatter()
return mdbf.create_input(billing_trace, mock_isd_weather_source)
def test_small(trace3, mock_isd_weather_source):
mdbf = ModelDataBillingFormatter()
with pytest.raises(ValueError):
mdbf.create_input(trace3, mock_isd_weather_source)
def input_billing_df(mock_isd_weather_source, billing_trace):
mdbf = ModelDataBillingFormatter()
return mdbf.create_input(billing_trace, mock_isd_weather_source)