mirror of
https://github.com/Akkudoktor-EOS/EOS.git
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aa334d0b61
* Update utilities in utils submodule. * Add base configuration modules. * Add server base configuration modules. * Add devices base configuration modules. * Add optimization base configuration modules. * Add utils base configuration modules. * Add prediction abstract and base classes plus tests. * Add PV forecast to prediction submodule. The PV forecast modules are adapted from the class_pvforecast module and replace it. * Add weather forecast to prediction submodule. The modules provide classes and methods to retrieve, manage, and process weather forecast data from various sources. Includes are structured representations of weather data and utilities for fetching forecasts for specific locations and time ranges. BrightSky and ClearOutside are currently supported. * Add electricity price forecast to prediction submodule. * Adapt fastapi server to base config and add fasthtml server. * Add ems to core submodule. * Adapt genetic to config. * Adapt visualize to config. * Adapt common test fixtures to config. * Add load forecast to prediction submodule. * Add core abstract and base classes. * Adapt single test optimization to config. * Adapt devices to config. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
100 lines
3.2 KiB
Python
100 lines
3.2 KiB
Python
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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from akkudoktoreos.config.config import get_config
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from akkudoktoreos.core.ems import get_ems
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from akkudoktoreos.prediction.loadakkudoktor import (
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LoadAkkudoktor,
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LoadAkkudoktorCommonSettings,
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)
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config_eos = get_config()
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ems_eos = get_ems()
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@pytest.fixture
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def load_provider(monkeypatch):
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"""Fixture to create a LoadAkkudoktor instance."""
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settings = {
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"load0_provider": "LoadAkkudoktor",
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"load0_name": "Akkudoktor Profile",
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"loadakkudoktor_year_energy": "1000",
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}
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config_eos.merge_settings_from_dict(settings)
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return LoadAkkudoktor()
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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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def test_loadakkudoktor_settings_validator():
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"""Test the field validator for `loadakkudoktor_year_energy`."""
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settings = LoadAkkudoktorCommonSettings(loadakkudoktor_year_energy=1234)
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assert isinstance(settings.loadakkudoktor_year_energy, float)
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assert settings.loadakkudoktor_year_energy == 1234.0
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settings = LoadAkkudoktorCommonSettings(loadakkudoktor_year_energy=1234.56)
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assert isinstance(settings.loadakkudoktor_year_energy, float)
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assert settings.loadakkudoktor_year_energy == 1234.56
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def test_loadakkudoktor_provider_id(load_provider):
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"""Test the `provider_id` class method."""
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assert load_provider.provider_id() == "LoadAkkudoktor"
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@patch("akkudoktoreos.prediction.loadakkudoktor.Path")
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@patch("akkudoktoreos.prediction.loadakkudoktor.np.load")
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def test_load_data_from_mock(mock_np_load, mock_path, mock_load_profiles_file, load_provider):
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"""Test the `load_data` method."""
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# Mock path behavior to return the test file
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mock_path.return_value.parent.parent.joinpath.return_value = mock_load_profiles_file
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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 = load_provider.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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def test_load_data_from_file(load_provider):
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"""Test `load_data` loads data from the profiles file."""
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data_year_energy = load_provider.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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def test_update_data(mock_load_data, load_provider):
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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.set_start_datetime(pendulum.datetime(2024, 1, 1))
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# Assure there are no prediction records
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load_provider.clear()
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assert len(load_provider) == 0
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# Execute the method
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load_provider._update_data()
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# Validate that update_value is called
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assert len(load_provider) > 0
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