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39 lines
1.4 KiB
Python
39 lines
1.4 KiB
Python
import json
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from pathlib import Path
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import pytest
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from akkudoktoreos.class_optimize import optimization_problem
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from akkudoktoreos.config import output_dir
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DIR_TESTDATA = Path(__file__).parent / "testdata"
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@pytest.mark.parametrize("fn_in, fn_out", [("optimize_input_1.json", "optimize_result_1.json")])
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def test_optimize(fn_in, fn_out):
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# Load input and output data
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with open(DIR_TESTDATA / fn_in, "r") as f_in:
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input_data = json.load(f_in)
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with open(DIR_TESTDATA / fn_out, "r") as f_out:
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expected_output_data = json.load(f_out)
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opt_class = optimization_problem(
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prediction_hours=48, strafe=10, optimization_hours=24, fixed_seed=42
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)
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start_hour = 10
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# Call the optimization function
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ergebnis = opt_class.optimierung_ems(parameter=input_data, start_hour=start_hour, ngen=3)
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# with open("new.json", "w") as f_out:
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# json.dump(ergebnis, f_out, indent=4)
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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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assert set(ergebnis) == set(expected_output_data)
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# The function creates a visualization result PDF as a side-effect.
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fp_viz = Path(output_dir) / "visualization_results.pdf"
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assert fp_viz.exists()
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