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eb9e966de9
FAstAPI is an async framework. Data may be imported and exported, load and save, set and get asynchronously. Prevent interleaving data operations to corrupt the data. In the previous design sync and async data access was intermixed leading to data corruption. The basic data classes DataSequence and DataContainer and the derived classes like Provider and Measurement now are async. Data access is protected by several async locks. To support the async design of the data classes the database interface became async. The energy management is also adapted to the new async design. Optimization is still off-loaded to another thread, but the prepration for the optimization and the post optimization actions now follow the async design. Adapter operations are now also protected by async locks. Tests were adapted to the async design and new tests were created. Besides this major fix several other improvements and fixes are included in this PR. * fix: key_to_dict/list/array only regard data records with key value set. Before the exclusion of no value data records was only done if the dropna flag was set. * fix: test for visual result pdf generation Due to updates in the library the generated charts text was a little bit different. Adapt the test to create the comaprison pdf in the test data durectory and update the reference pdf. * chore: Remove MutableMapping from DataSequence and DataContainer. Mutable Mapping does not fit to the now async design. * chore: Add NoDB database backend This backend implements the full database backend interface but performs no actual persistence. It is intended for configurations where database persistence is disabled (`provider=None`). * chore: Improve measurement data import testing with real world scenarios. Added two new endpoints to support testing. * chore: Add mermaid to supported documentation tools * chore: Add documentation about async design * chore: Add documentation about generic data handling Covers the basics of measurement and prediction time series data handling. * chore: Add empty lines around markdown lists. * chore: sync pre-commit config to updated package versions Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
257 lines
8.8 KiB
Python
257 lines
8.8 KiB
Python
import asyncio
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from unittest.mock import patch
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import numpy as np
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import pendulum
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import pytest
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import pytest_asyncio
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from akkudoktoreos.core.coreabc import get_ems, get_measurement
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from akkudoktoreos.measurement.measurement import MeasurementDataRecord
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from akkudoktoreos.prediction.loadakkudoktor import (
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LoadAkkudoktor,
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LoadAkkudoktorAdjusted,
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LoadAkkudoktorCommonSettings,
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)
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from akkudoktoreos.utils.datetimeutil import compare_datetimes, to_datetime, to_duration
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@pytest.fixture
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def loadakkudoktor(config_eos):
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"""Fixture to initialise the LoadAkkudoktor instance."""
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settings = {
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"load": {
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"provider": "LoadAkkudoktor",
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"loadakkudoktor": {
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"loadakkudoktor_year_energy_kwh": "1000",
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},
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},
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}
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config_eos.merge_settings_from_dict(settings)
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assert config_eos.load.provider == "LoadAkkudoktor"
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assert config_eos.load.loadakkudoktor.loadakkudoktor_year_energy_kwh == 1000
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return LoadAkkudoktor()
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@pytest.fixture
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def loadakkudoktoradjusted(config_eos):
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"""Fixture to initialise the LoadAkkudoktorAdjusted instance."""
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settings = {
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"load": {
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"provider": "LoadAkkudoktorAdjusted",
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"loadakkudoktor": {
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"loadakkudoktor_year_energy_kwh": "1000",
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},
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},
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"measurement": {
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"load_emr_keys": ["load0_mr", "load1_mr"]
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}
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}
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config_eos.merge_settings_from_dict(settings)
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assert config_eos.load.provider == "LoadAkkudoktorAdjusted"
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assert config_eos.load.loadakkudoktor.loadakkudoktor_year_energy_kwh == 1000
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return LoadAkkudoktorAdjusted()
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@pytest_asyncio.fixture
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async def measurement_eos():
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"""Fixture to initialise the Measurement instance."""
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# Load meter readings are in kWh
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measurement = get_measurement()
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load0_mr = 500.0
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load1_mr = 500.0
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dt = to_datetime("2024-01-01T00:00:00")
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interval = to_duration("1 hour")
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for i in range(25):
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await measurement.insert_by_datetime(
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MeasurementDataRecord(
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date_time=dt,
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load0_mr=load0_mr,
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load1_mr=load1_mr,
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)
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)
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dt += interval
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# 0.05 kWh = 50 Wh
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load0_mr += 0.05
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load1_mr += 0.05
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min_dt = await measurement.min_datetime()
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max_dt = await measurement.max_datetime()
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assert compare_datetimes(min_dt, to_datetime("2024-01-01T00:00:00")).equal
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assert compare_datetimes(max_dt, to_datetime("2024-01-02T00:00:00")).equal
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return measurement
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@pytest.fixture
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def mock_load_profiles_file(tmp_path):
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"""Fixture to create a mock load profiles file."""
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load_profiles_path = tmp_path / "load_profiles.npz"
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np.savez(
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load_profiles_path,
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yearly_profiles=np.random.rand(365, 24), # Random load profiles
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yearly_profiles_std=np.random.rand(365, 24), # Random standard deviation
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)
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return load_profiles_path
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@pytest.mark.asyncio
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class TestLoadAkkudoktor:
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async def test_loadakkudoktor_settings_validator(self):
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"""Test the field validator for `loadakkudoktor_year_energy_kwh`."""
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settings = LoadAkkudoktorCommonSettings(loadakkudoktor_year_energy_kwh=1234)
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assert isinstance(settings.loadakkudoktor_year_energy_kwh, float)
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assert settings.loadakkudoktor_year_energy_kwh == 1234.0
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settings = LoadAkkudoktorCommonSettings(loadakkudoktor_year_energy_kwh=1234.56)
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assert isinstance(settings.loadakkudoktor_year_energy_kwh, float)
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assert settings.loadakkudoktor_year_energy_kwh == 1234.56
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async def test_loadakkudoktor_provider_id(self, loadakkudoktor):
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"""Test the `provider_id` class method."""
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assert loadakkudoktor.provider_id() == "LoadAkkudoktor"
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@patch("akkudoktoreos.prediction.loadakkudoktor.np.load")
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async def test_load_data_from_mock(self, mock_np_load, mock_load_profiles_file, loadakkudoktor):
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"""Test the `load_data` method."""
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# Mock numpy load to return data similar to what would be in the file
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mock_np_load.return_value = {
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"yearly_profiles": np.ones((365, 24)),
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"yearly_profiles_std": np.zeros((365, 24)),
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}
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# Test data loading
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data_year_energy = loadakkudoktor.load_data()
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assert data_year_energy is not None
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assert data_year_energy.shape == (365, 2, 24)
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async def test_load_data_from_file(self, loadakkudoktor):
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"""Test `load_data` loads data from the profiles file."""
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data_year_energy = loadakkudoktor.load_data()
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assert data_year_energy is not None
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@patch("akkudoktoreos.prediction.loadakkudoktor.LoadAkkudoktor.load_data")
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async def test_update_data(self, mock_load_data, loadakkudoktor):
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"""Test the `_update` method."""
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mock_load_data.return_value = np.random.rand(365, 2, 24)
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# Mock methods for updating values
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ems_eos = get_ems()
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ems_eos.set_start_datetime(pendulum.datetime(2024, 1, 1))
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# Assure there are no prediction records
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await loadakkudoktor.delete_by_datetime(start_datetime=None, end_datetime=None)
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assert len(loadakkudoktor) == 0
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# Execute the method
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await loadakkudoktor._update_data()
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# Validate that update_value is called
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assert len(loadakkudoktor) > 0
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@pytest.mark.asyncio
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class TestLoadAkkudoktorAdjusted:
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async def test_calculate_adjustment(self, loadakkudoktoradjusted, measurement_eos):
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"""Test `_calculate_adjustment` for various scenarios."""
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data_year_energy = np.random.rand(365, 2, 24)
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# Check the test setup
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assert loadakkudoktoradjusted.measurement is measurement_eos
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min_dt = await measurement_eos.min_datetime()
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assert min_dt == to_datetime("2024-01-01T00:00:00")
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max_dt = await measurement_eos.max_datetime()
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assert max_dt == to_datetime("2024-01-02T00:00:00")
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# Use same calculation as in _calculate_adjustment
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compare_start = max_dt - to_duration("7 days")
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if compare_datetimes(compare_start, min_dt).lt:
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# Not enough measurements for 7 days - use what is available
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compare_start = min_dt
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compare_end = max_dt
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compare_interval = to_duration("1 hour")
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load_total_kwh_array = await measurement_eos.load_total_kwh(
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start_datetime=compare_start,
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end_datetime=compare_end,
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interval=compare_interval,
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)
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np.testing.assert_allclose(load_total_kwh_array, [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1])
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# Call the method and validate results
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weekday_adjust, weekend_adjust = await loadakkudoktoradjusted._calculate_adjustment(data_year_energy)
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assert weekday_adjust.shape == (24,)
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assert weekend_adjust.shape == (24,)
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data_year_energy = np.zeros((365, 2, 24))
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weekday_adjust, weekend_adjust = await loadakkudoktoradjusted._calculate_adjustment(data_year_energy)
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assert weekday_adjust.shape == (24,)
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expected = np.array(
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[
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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100.0,
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]
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)
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np.testing.assert_allclose(weekday_adjust, expected)
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assert weekend_adjust.shape == (24,)
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expected = np.array(
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[
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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]
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)
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np.testing.assert_array_equal(weekend_adjust, expected)
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async def test_provider_adjustments_with_mock_data(self, loadakkudoktoradjusted):
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"""Test full integration of adjustments with mock data."""
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with patch(
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"akkudoktoreos.prediction.loadakkudoktor.LoadAkkudoktorAdjusted._calculate_adjustment"
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) as mock_adjust:
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mock_adjust.return_value = (np.zeros(24), np.zeros(24))
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# Test execution
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await loadakkudoktoradjusted._update_data()
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assert mock_adjust.called
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