mirror of
https://github.com/Akkudoktor-EOS/EOS.git
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99 lines
3.3 KiB
Python
99 lines
3.3 KiB
Python
import json
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from pathlib import Path
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from typing import Any
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from unittest.mock import patch
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import pytest
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from akkudoktoreos.config import AppConfig
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from akkudoktoreos.optimization.genetic import (
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OptimizationParameters,
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OptimizeResponse,
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optimization_problem,
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)
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DIR_TESTDATA = Path(__file__).parent / "testdata"
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def compare_dict(actual: dict[str, Any], expected: dict[str, Any]):
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assert set(actual) == set(expected)
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for key, value in expected.items():
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if isinstance(value, dict):
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assert isinstance(actual[key], dict)
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compare_dict(actual[key], value)
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elif isinstance(value, list):
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assert isinstance(actual[key], list)
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assert actual[key] == pytest.approx(value)
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else:
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assert actual[key] == pytest.approx(value)
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@pytest.mark.parametrize(
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"fn_in, fn_out, ngen",
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[
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("optimize_input_1.json", "optimize_result_1.json", 3),
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("optimize_input_2.json", "optimize_result_2.json", 3),
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("optimize_input_2.json", "optimize_result_2_full.json", 400),
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],
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)
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def test_optimize(
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fn_in: str,
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fn_out: str,
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ngen: int,
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is_full_run: bool,
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tmp_config: AppConfig,
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):
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"""Test optimierung_ems."""
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# Load input and output data
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file = DIR_TESTDATA / fn_in
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with file.open("r") as f_in:
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input_data = OptimizationParameters(**json.load(f_in))
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file = DIR_TESTDATA / fn_out
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# In case a new test case is added, we don't want to fail here, so the new output is written to disk before
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try:
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with file.open("r") as f_out:
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expected_result = OptimizeResponse(**json.load(f_out))
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except FileNotFoundError:
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pass
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opt_class = optimization_problem(tmp_config, fixed_seed=42)
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start_hour = 10
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# Activate with pytest --full-run
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if ngen > 10 and not is_full_run:
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pytest.skip()
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visualize_filename = str((DIR_TESTDATA / f"new_{fn_out}").with_suffix(".pdf"))
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def visualize_to_file(*args, **kwargs):
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from akkudoktoreos.visualize import visualisiere_ergebnisse
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# Write test output pdf to file, so we can look at it manually
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kwargs["filename"] = visualize_filename
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return visualisiere_ergebnisse(*args, **kwargs)
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with patch(
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"akkudoktoreos.optimization.genetic.visualisiere_ergebnisse", side_effect=visualize_to_file
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) as visualisiere_ergebnisse_patch:
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# Call the optimization function
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ergebnis = opt_class.optimierung_ems(
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parameters=input_data, start_hour=start_hour, ngen=ngen
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)
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# Write test output to file, so we can take it as new data on intended change
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with open(DIR_TESTDATA / f"new_{fn_out}", "w") as f_out:
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f_out.write(ergebnis.model_dump_json(indent=4, exclude_unset=True))
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assert ergebnis.result.Gesamtbilanz_Euro == pytest.approx(
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expected_result.result.Gesamtbilanz_Euro
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)
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# Assert that the output contains all expected entries.
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# This does not assert that the optimization always gives the same result!
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# Reproducibility and mathematical accuracy should be tested on the level of individual components.
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compare_dict(ergebnis.model_dump(), expected_result.model_dump())
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# The function creates a visualization result PDF as a side-effect.
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visualisiere_ergebnisse_patch.assert_called_once()
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