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8b37c3f | 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 | from __future__ import annotations
import numpy as np
import pandas as pd
from src.data.adapters import (
_calce_cycles_from_frame,
_matlab_datenum_to_elapsed_seconds,
_sanitize_temperature_channel,
cycle_inventory,
)
def test_calce_frame_normalizes_discharge_cycle():
frame = pd.DataFrame({
"Test_Time(s)": [0, 1, 2, 3, 4],
"Date_Time": pd.date_range("2026-01-01", periods=5, freq="s"),
"Cycle_Index": [1] * 5,
"Current(A)": [0, -1, -1, -1, 0],
"Voltage(V)": [4.2, 4.0, 3.8, 3.5, 3.4],
"Discharge_Capacity(Ah)": [0, 0.1, 0.5, 1.0, 1.0],
})
candidates = _calce_cycles_from_frame(frame, battery_id="CS2_35", source="fixture")
assert len(candidates) == 1
record = candidates[0][1]
assert record.capacity_ah == 1.0
assert list(record.measurements) == [
"Time", "Voltage_measured", "Current_measured", "Temperature_measured"
]
inventory = cycle_inventory([record])
assert inventory.loc[0, "dataset"] == "CALCE"
def test_matlab_datenum_is_converted_from_days_to_seconds():
observed = _matlab_datenum_to_elapsed_seconds([735954.0, 735954.5, 735955.0])
np.testing.assert_allclose(observed, [0.0, 43_200.0, 86_400.0])
def test_grossly_inconsistent_temperature_channel_is_marked_missing():
observed = _sanitize_temperature_channel([0.51, 0.52, 0.53], ambient_temperature_c=40.0)
assert np.isnan(observed).all()
valid = _sanitize_temperature_channel([39.8, 40.1, 41.0], ambient_temperature_c=40.0)
assert np.isfinite(valid).all()
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