| from __future__ import annotations |
|
|
| import numpy as np |
| import pandas as pd |
|
|
| from src.data.adapters import DischargeCycle |
| from src.data.benchmark import build_benchmark_bundle |
| from src.utils.config import FEATURE_COLS_V3 |
|
|
|
|
| def _record(cycle_number: int, capacity: float) -> DischargeCycle: |
| return DischargeCycle( |
| dataset="fixture", |
| battery_id="B1", |
| cycle_number=cycle_number, |
| capacity_ah=capacity, |
| ambient_temperature_c=25.0, |
| source="fixture", |
| measurements=pd.DataFrame({ |
| "Time": np.arange(7, dtype=float), |
| "Voltage_measured": [4.1, 4.0, 3.9, 3.8, 3.7, 3.6, 3.5], |
| "Current_measured": [-2.0] * 7, |
| "Temperature_measured": np.linspace(25, 26, 7), |
| }), |
| ) |
|
|
|
|
| def test_bundle_aligns_features_sequences_and_targets(): |
| bundle = build_benchmark_bundle( |
| [_record(i, 2.0 - i * 0.05) for i in range(4)], |
| rated_capacity_by_dataset={"fixture": 2.0}, |
| ) |
| assert bundle.features.shape[0] == bundle.sequences.shape[0] == 4 |
| assert bundle.sequences.shape[1:] == (64, 5) |
| assert all(column in bundle.features for column in FEATURE_COLS_V3) |
| assert np.isclose(bundle.features.loc[0, "prior_equivalent_full_cycles"], 0.0) |
| assert bundle.features.loc[3, "prior_equivalent_full_cycles"] > 0 |
|
|
