Clean yaml converter test files #84
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| Original file line number | Diff line number | Diff line change | ||||
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| @@ -0,0 +1,191 @@ | ||||||
| from pathlib import Path | ||||||
| from typing import Callable, Literal | ||||||
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| import pandas as pd | ||||||
| import pytest | ||||||
| from antares.craft.model.study import Study | ||||||
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| from andromede.input_converter.src.converter import AntaresStudyConverter | ||||||
| from andromede.input_converter.src.data_preprocessing.thermal import ( | ||||||
| ThermalDataPreprocessing, | ||||||
| ) | ||||||
| from andromede.input_converter.src.logger import Logger | ||||||
| from andromede.study.parsing import InputComponentParameter | ||||||
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| def generate_tdp_instance_parameter( | ||||||
| areas, study_path: Path, create_dataframes: bool = True | ||||||
| ) -> ThermalDataPreprocessing: | ||||||
| if create_dataframes: | ||||||
| modulation_timeseries = str( | ||||||
| study_path | ||||||
| / "input" | ||||||
| / "thermal" | ||||||
| / "prepro" | ||||||
| / "fr" | ||||||
| / "gaz" | ||||||
| / "modulation.txt" | ||||||
| ) | ||||||
| series_path = ( | ||||||
| study_path / "input" / "thermal" / "series" / "fr" / "gaz" / "series.txt" | ||||||
| ) | ||||||
| data_p_max = [ | ||||||
| [1, 1, 1, 2], | ||||||
| [2, 2, 2, 6], | ||||||
| [3, 3, 3, 1], | ||||||
| ] | ||||||
| data_series = [ | ||||||
| [8], | ||||||
| [10], | ||||||
| [2], | ||||||
| ] | ||||||
| df = pd.DataFrame(data_p_max) | ||||||
| df.to_csv(modulation_timeseries, sep="\t", index=False, header=False) | ||||||
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| df = pd.DataFrame(data_series) | ||||||
| df.to_csv(series_path, sep="\t", index=False, header=False) | ||||||
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||||||
| for area in areas: | ||||||
| thermals = area.get_thermals() | ||||||
| for thermal in thermals.values(): | ||||||
| if thermal.area_id == "fr": | ||||||
| tdp = ThermalDataPreprocessing(thermal, study_path) | ||||||
| return tdp | ||||||
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| class TestPreprocessingThermal: | ||||||
| def _init_area_reading(self, local_study: Study): | ||||||
| logger = Logger(__name__, local_study.service.config.study_path) | ||||||
| converter = AntaresStudyConverter(study_input=local_study, logger=logger) | ||||||
| areas = converter.study.get_areas().values() | ||||||
| return areas, converter | ||||||
|
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| def _setup_test(self, local_study_w_thermal: Study, filename: Path): | ||||||
| """ | ||||||
| Initializes test parameters and returns the instance and expected file path. | ||||||
| """ | ||||||
| areas, converter = self._init_area_reading(local_study_w_thermal) | ||||||
| study_path = converter.study_path | ||||||
| instance = generate_tdp_instance_parameter(areas, study_path) | ||||||
| expected_path = ( | ||||||
| study_path / "input" / "thermal" / "series" / "fr" / "gaz" / filename | ||||||
| ) | ||||||
| return instance, expected_path | ||||||
|
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| def _validate_component( | ||||||
| self, | ||||||
| instance: ThermalDataPreprocessing, | ||||||
| process_method: str, | ||||||
| expected_path: Path, | ||||||
| expected_values: list, | ||||||
| ): | ||||||
| """ | ||||||
| Executes the given processing method, validates the component, and compares the output dataframe. | ||||||
| """ | ||||||
| component = getattr(instance, process_method)() | ||||||
| expected_component = InputComponentParameter( | ||||||
| id=process_method.split("process_")[1], | ||||||
|
There was a problem hiding this comment. Je trouve ça très dangereux parce que si on renomme la méthode dans la classe |
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| time_dependent=True, | ||||||
| scenario_dependent=True, | ||||||
| value=str(expected_path), | ||||||
| ) | ||||||
| current_df = pd.read_csv(expected_path.with_suffix(".txt"), header=None) | ||||||
| expected_df = pd.DataFrame(expected_values) | ||||||
| assert current_df.equals(expected_df) | ||||||
| assert component == expected_component | ||||||
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| def _test_p_min_cluster(self, local_study_w_thermal: Study): | ||||||
|
There was a problem hiding this comment.
Suggested change
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| """Tests the p_min_cluster parameter processing.""" | ||||||
| instance, expected_path = self._setup_test( | ||||||
| local_study_w_thermal, "p_min_cluster.txt" | ||||||
| ) | ||||||
| expected_values = [ | ||||||
| [6.0], | ||||||
| [10.0], | ||||||
| [2.0], | ||||||
| ] # min(min_gen_modulation * unit_count * nominal_capacity, p_max_cluster) | ||||||
| self._validate_component( | ||||||
| instance, "process_p_min_cluster", expected_path, expected_values | ||||||
| ) | ||||||
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| def test_nb_units_min(self, local_study_w_thermal: Study): | ||||||
| """Tests the nb_units_min parameter processing.""" | ||||||
| instance, expected_path = self._setup_test( | ||||||
| local_study_w_thermal, "nb_units_min" | ||||||
| ) | ||||||
| instance.process_p_min_cluster() | ||||||
|
There was a problem hiding this comment. Inutile ça se fait dans |
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| expected_values = [[2.0], [5.0], [1.0]] # ceil(p_min_cluster / p_max_unit) | ||||||
| self._validate_component( | ||||||
| instance, "process_nb_units_min", expected_path, expected_values | ||||||
| ) | ||||||
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| def test_nb_units_max(self, local_study_w_thermal: Study): | ||||||
|
There was a problem hiding this comment. Les tests |
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| """Tests the nb_units_max parameter processing.""" | ||||||
| instance, expected_path = self._setup_test( | ||||||
| local_study_w_thermal, "nb_units_max" | ||||||
| ) | ||||||
| instance.process_p_min_cluster() | ||||||
| expected_values = [[4.0], [5.0], [1.0]] # ceil(p_max_cluster / p_max_unit) | ||||||
| self._validate_component( | ||||||
| instance, "process_nb_units_max", expected_path, expected_values | ||||||
| ) | ||||||
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| @pytest.mark.parametrize("direction", ["forward", "backward"]) | ||||||
| def test_nb_units_max_variation( | ||||||
| self, | ||||||
| local_study_w_thermal: Study, | ||||||
| create_csv_from_constant_value: Callable[..., None], | ||||||
| direction: Literal["forward"] | Literal["backward"], | ||||||
| ): | ||||||
| """ | ||||||
| Tests nb_units_max_variation_forward and nb_units_max_variation_backward processing. | ||||||
| """ | ||||||
| instance, expected_path = self._setup_test( | ||||||
| local_study_w_thermal, f"nb_units_max_variation_{direction}" | ||||||
| ) | ||||||
| modulation_timeseries = ( | ||||||
| instance.study_path / "input" / "thermal" / "prepro" / "fr" / "gaz" | ||||||
| ) | ||||||
| series_path = ( | ||||||
| instance.study_path / "input" / "thermal" / "series" / "fr" / "gaz" | ||||||
| ) | ||||||
| create_csv_from_constant_value(modulation_timeseries, "modulation", 840, 4) | ||||||
| create_csv_from_constant_value(series_path, "series", 840) | ||||||
| instance.process_nb_units_max() | ||||||
| nb_units_max_output = pd.read_csv( | ||||||
| instance.series_path / "nb_units_max.txt", header=None | ||||||
| ) | ||||||
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| variation_component = getattr( | ||||||
| instance, f"process_nb_units_max_variation_{direction}" | ||||||
| )() | ||||||
| current_df = pd.read_csv(variation_component.value + ".txt", header=None) | ||||||
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| assert current_df[0][0] == max( | ||||||
| 0, nb_units_max_output[0][167] - nb_units_max_output[0][0] | ||||||
| ) | ||||||
| assert current_df[0][3] == max( | ||||||
| 0, nb_units_max_output[0][2] - nb_units_max_output[0][3] | ||||||
| ) | ||||||
| assert current_df[0][168] == max( | ||||||
| 0, nb_units_max_output[0][335] - nb_units_max_output[0][168] | ||||||
| ) | ||||||
| assert variation_component.value == str(expected_path) | ||||||
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| def test_nb_units_max_variation_forward( | ||||||
|
There was a problem hiding this comment. Inutile grâce au parametrize |
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| self, | ||||||
| local_study_w_thermal: Study, | ||||||
| create_csv_from_constant_value: Callable[..., None], | ||||||
| ): | ||||||
| self.test_nb_units_max_variation( | ||||||
| local_study_w_thermal, create_csv_from_constant_value, direction="forward" | ||||||
| ) | ||||||
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| def test_nb_units_max_variation_backward( | ||||||
|
There was a problem hiding this comment. Inutile grâce au parametrize |
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| self, | ||||||
| local_study_w_thermal: Study, | ||||||
| create_csv_from_constant_value: Callable[..., None], | ||||||
| ): | ||||||
| self.test_nb_units_max_variation( | ||||||
| local_study_w_thermal, create_csv_from_constant_value, direction="backward" | ||||||
| ) | ||||||
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Peux-tu le renommer
thermal_data_preprocessingdans tout le fichier pour plus de clarté ?