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EOS/tests/test_genetic0_measured_soc.py
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"""GENETIC0 must use the SoC read during the run, not an older reading (#1447)."""
from unittest.mock import AsyncMock, Mock, patch
import numpy as np
import pandas as pd
import pytest
import pytest_asyncio
from akkudoktoreos.core.coreabc import get_ems, get_measurement
from akkudoktoreos.optimization.genetic0.genetic0params import (
Genetic0OptimizationParameters,
)
from akkudoktoreos.utils.datetimeutil import to_datetime
@pytest_asyncio.fixture
async def isolated_measurement(config_eos):
"""Keep synthetic records out of the process-wide measurement singleton."""
measurement = get_measurement()
await measurement.delete_by_datetime(None, None)
try:
yield measurement
finally:
await measurement.delete_by_datetime(None, None)
@pytest.mark.asyncio
async def test_soc_read_late_in_slot_beats_previous_reading(config_eos, isolated_measurement):
config_eos.merge_settings_from_dict(
{
"prediction": {"hours": 48},
"optimization": {"genetic0": {"horizon_hours": 24}},
"elecfee": {"provider": None},
"devices": {
"max_batteries": 1,
"max_electric_vehicles": 0,
"max_inverters": 1,
"max_home_appliances": 0,
"batteries": {"storage": {"capacity_wh": 2000, "max_charge_power_w": 1000}},
"inverters": {"inverter": {"battery_id": "storage", "max_power_w": 1000}},
},
}
)
# A run at 14:40 belongs to the 14:00 slot. The previous run (13:40) is closer
# to the slot start than the reading taken now.
run_time = to_datetime("2026-08-01T14:40:00+00:00")
get_ems().set_start_datetime(run_time)
measurement = isolated_measurement
await measurement.update_value(run_time.subtract(hours=1), "storage-soc-factor", 0.10)
await measurement.update_value(run_time, "storage-soc-factor", 0.42)
tariff = pd.Series(
0.00008, index=pd.date_range("2026-08-01T00:00:00Z", periods=72 * 4, freq="15min")
)
async def read_array(**kwargs):
return np.full(48, 0.0003)
prediction = Mock(
update_data=AsyncMock(),
key_to_array=AsyncMock(side_effect=read_array),
key_to_raw_series=AsyncMock(return_value=tariff),
)
with patch.object(Genetic0OptimizationParameters, "prediction", prediction):
parameters = await Genetic0OptimizationParameters.prepare()
assert parameters is not None
assert parameters.pv_battery is not None
assert parameters.pv_battery.initial_soc_percentage == 42
@pytest.mark.asyncio
async def test_meter_only_record_does_not_mask_soc(config_eos, isolated_measurement):
config_eos.merge_settings_from_dict(
{
"prediction": {"hours": 48},
"optimization": {"genetic0": {"horizon_hours": 24}},
"elecfee": {"provider": None},
"measurement": {"load_emr_keys": ["load_meter"]},
"devices": {
"max_batteries": 1,
"max_electric_vehicles": 0,
"max_inverters": 1,
"max_home_appliances": 0,
"batteries": {"storage": {"capacity_wh": 2000, "max_charge_power_w": 1000}},
"inverters": {"inverter": {"battery_id": "storage", "max_power_w": 1000}},
},
}
)
run_time = to_datetime("2026-08-01T14:40:00+00:00")
get_ems().set_start_datetime(run_time)
measurement = isolated_measurement
# SoC through the measurement API at 13:30, the adapter's meter reading at the
# slot start (14:00); the run at 14:40 must still find the SoC.
await measurement.update_value(run_time.subtract(minutes=70), "storage-soc-factor", 0.42)
await measurement.update_value(get_ems().start_datetime, "load_meter", 1234.5)
tariff = pd.Series(
0.00008, index=pd.date_range("2026-08-01T00:00:00Z", periods=72 * 4, freq="15min")
)
async def read_array(**kwargs):
return np.full(48, 0.0003)
prediction = Mock(
update_data=AsyncMock(),
key_to_array=AsyncMock(side_effect=read_array),
key_to_raw_series=AsyncMock(return_value=tariff),
)
with patch.object(Genetic0OptimizationParameters, "prediction", prediction):
parameters = await Genetic0OptimizationParameters.prepare()
assert parameters is not None
assert parameters.pv_battery is not None
assert parameters.pv_battery.initial_soc_percentage == 42
@pytest.mark.asyncio
async def test_older_missing_value_does_not_spoil_current_soc(config_eos, isolated_measurement):
config_eos.merge_settings_from_dict(
{
"prediction": {"hours": 48},
"optimization": {"genetic0": {"horizon_hours": 24}},
"elecfee": {"provider": None},
"devices": {
"max_batteries": 1,
"max_electric_vehicles": 0,
"max_inverters": 1,
"max_home_appliances": 0,
"batteries": {"storage": {"capacity_wh": 2000, "max_charge_power_w": 1000}},
"inverters": {"inverter": {"battery_id": "storage", "max_power_w": 1000}},
},
}
)
run_time = to_datetime("2026-08-01T14:40:00+00:00")
get_ems().set_start_datetime(run_time)
measurement = isolated_measurement
# An older reading stored as pandas NA (e.g. a JSON null in a Float64 series).
await measurement.update_value(run_time.subtract(hours=1), "storage-soc-factor", pd.NA)
await measurement.update_value(run_time, "storage-soc-factor", 0.42)
tariff = pd.Series(
0.00008, index=pd.date_range("2026-08-01T00:00:00Z", periods=72 * 4, freq="15min")
)
async def read_array(**kwargs):
return np.full(48, 0.0003)
prediction = Mock(
update_data=AsyncMock(),
key_to_array=AsyncMock(side_effect=read_array),
key_to_raw_series=AsyncMock(return_value=tariff),
)
with patch.object(Genetic0OptimizationParameters, "prediction", prediction):
parameters = await Genetic0OptimizationParameters.prepare()
assert parameters is not None
assert parameters.pv_battery is not None
assert parameters.pv_battery.initial_soc_percentage == 42