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536ba3d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | from __future__ import annotations
import numpy as np
import pandas as pd
from src.data import features as feat
def test_compute_soc_and_soh():
df = pd.DataFrame({"Current_measured": [-1.0, -1.0], "Time": [0.0, 3600.0]})
soc = feat.compute_soc(df, nominal_capacity_ah=2.0)
assert soc.iloc[0] == 100.0
assert soc.iloc[-1] <= 100.0
assert feat.compute_soh(1.0, nominal_capacity_ah=2.0) == 50.0
def test_compute_rul_and_degradation_state():
cap = pd.Series([2.0, 1.8, 1.5, 1.3])
rul = feat.compute_rul_series(cap, eol_threshold=1.4)
assert rul.iloc[-1] == 0
labels = feat.classify_degradation_state(np.array([95.0, 85.0, 75.0, 60.0]))
assert labels.tolist() == [0, 1, 2, 3]
def test_extract_cycle_features():
df = pd.DataFrame(
{
"Voltage_measured": [4.2, 3.7],
"Current_measured": [-2.0, -1.0],
"Temperature_measured": [25.0, 30.0],
"Time": [0.0, 100.0],
}
)
out = feat.extract_cycle_features(df)
assert out["peak_voltage"] == 4.2
assert out["cycle_duration"] == 100.0
def test_add_v3_features_and_impute():
df = pd.DataFrame(
{
"battery_id": ["B1", "B1", "B2"],
"Capacity": [2.0, 1.9, 1.8],
"Re": [0.05, np.nan, 0.06],
"Rct": [0.08, 0.09, np.nan],
"SoH": [100.0, 95.0, 90.0],
"peak_voltage": [4.2, 4.1, 4.0],
"min_voltage": [2.5, 2.5, 2.5],
}
)
out = feat.add_v3_features(df)
assert "capacity_retention" in out.columns
fixed = feat.impute_features(out)
assert fixed["Re"].isna().sum() == 0
assert fixed["Rct"].isna().sum() == 0
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