import numpy as np
import pandas as pd
from prereise.gather.demanddata.transportation_electrification.immediate import ( # adjust_bev,
apply_annual_scaling,
apply_daily_adjustments,
)
[docs]def test_apply_daily_adjustments():
hourly_profile = np.array([60, 180, 120, 120, 240, 60, 180, 220, 200, 20, 50, 30])
adjustment_values = pd.DataFrame([0.6, 0.7, 0.3, 0.5])
num_days_per_year = 4
num_segments_per_day = 3
adjustment_result = apply_daily_adjustments(
hourly_profile, adjustment_values, num_days_per_year, num_segments_per_day
)
correct_adjustment = np.array(
[
0.1,
0.3,
0.2,
0.2,
0.4,
0.1,
0.09,
0.11,
0.1,
0.1,
0.25,
0.15,
]
)
print(adjustment_result)
np.testing.assert_almost_equal(adjustment_result, correct_adjustment)
[docs]def test_apply_annual_scaling():
hourly_profile = np.array(
[
0.1,
0.3,
0.2,
0.2,
0.4,
0.1,
0.09,
0.11,
0.1,
0.1,
0.25,
0.15,
]
)
bev_vmt = 10
charging_efficiency = 0.9
kwhmi = 18
scaling_result = apply_annual_scaling(
hourly_profile,
bev_vmt,
charging_efficiency,
kwhmi,
)
correct_annual_scaling = np.array([20, 60, 40, 40, 80, 20, 18, 22, 20, 20, 50, 30])
assert np.array_equal(scaling_result, correct_annual_scaling)
