上传PythonModels文件

PythonModels/scripts/run_testmodel.py

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+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from datetime import UTC, datetime
+from pathlib import Path
+
+from PythonModels.reporting import (
+    COMPARISON_KEYS,
+    PRIMARY_KEYS,
+    TestModelArtifacts,
+    export_testmodel_artifacts,
+    format_testmodel_run_report,
+    load_modelica_series,
+    write_testmodel_run_report,
+)
+from PythonModels.core.solver import SolveIVPConfig
+from PythonModels.systems.testmodel import (
+    InitializationDiagnostics,
+    TestModelConfig,
+    TestModelSystem,
+)
+from PythonModels.systems.testmodel_closure import TestModelSolveDiagnostics
+
+
+@dataclass(frozen=True)
+class TestModelSamplingConfig:
+    step: float = 0.1
+
+
+@dataclass(frozen=True)
+class TestModelPathConfig:
+    output_dir: Path | None = None
+    modelica_result_path: Path | None = None
+
+
+@dataclass(frozen=True)
+class TestModelExecutionConfig:
+    use_modelica_reference_if_available: bool = True
+
+
+@dataclass(frozen=True)
+class TestModelRunConfig:
+    model: TestModelConfig = field(default_factory=TestModelConfig)
+    solver: SolveIVPConfig = field(default_factory=SolveIVPConfig)
+    sampling: TestModelSamplingConfig = field(default_factory=TestModelSamplingConfig)
+    paths: TestModelPathConfig = field(default_factory=TestModelPathConfig)
+    execution: TestModelExecutionConfig = field(default_factory=TestModelExecutionConfig)
+
+    @property
+    def sample_step(self) -> float:
+        return self.sampling.step
+
+    def sample_times(self) -> list[float]:
+        return _sample_times(
+            self.solver.t_start,
+            self.solver.t_stop,
+            step=self.sampling.step,
+        )
+
+
+@dataclass(frozen=True)
+class PreparedTestModelRun:
+    run_config: TestModelRunConfig
+    repo_root: Path
+    output_dir: Path
+    modelica_result_path: Path
+    t_eval: tuple[float, ...]
+    use_modelica_reference_if_available: bool
+    modelica_reference_exists: bool
+
+
+@dataclass(frozen=True)
+class TestModelRunResult:
+    run_config: TestModelRunConfig
+    prepared_run: PreparedTestModelRun
+    system: TestModelSystem
+    initialization: InitializationDiagnostics
+    raw_initial_state: tuple[float, ...]
+    consistent_initial_state: tuple[float, ...]
+    solution: object
+    series: dict[str, list[float]]
+    solve_diagnostics: TestModelSolveDiagnostics | None
+    artifacts: TestModelArtifacts
+    comparison_summary: dict[str, tuple[float, float]] | None
+    used_modelica_reference: bool
+
+
+def _sample_times(t_start: float, t_stop: float, step: float) -> list[float]:
+    point_count = int(round((t_stop - t_start) / step))
+    return [t_start + index * step for index in range(point_count + 1)]
+
+
+def _default_run_output_dir(pythonmodels_root: Path) -> Path:
+    timestamp = datetime.now(UTC).strftime("testmodel_%Y%m%d_%H%M%S_%f")
+    return pythonmodels_root / "runs" / timestamp
+
+
+def prepare_testmodel_run(
+    *,
+    run_config: TestModelRunConfig | None = None,
+    output_dir: Path | None = None,
+    modelica_result_path: Path | None = None,
+) -> PreparedTestModelRun:
+    run_config = run_config or TestModelRunConfig()
+    repo_root = Path(__file__).resolve().parents[2]
+    pythonmodels_root = Path(__file__).resolve().parents[1]
+    resolved_output_dir = (
+        output_dir
+        or run_config.paths.output_dir
+        or _default_run_output_dir(pythonmodels_root)
+    )
+    resolved_modelica_result_path = (
+        modelica_result_path
+        or run_config.paths.modelica_result_path
+        or repo_root / "ModelicaModels" / "Simulation" / "Testmodel_res.csv"
+    )
+    t_eval = tuple(run_config.sample_times())
+    return PreparedTestModelRun(
+        run_config=run_config,
+        repo_root=repo_root,
+        output_dir=resolved_output_dir,
+        modelica_result_path=resolved_modelica_result_path,
+        t_eval=t_eval,
+        use_modelica_reference_if_available=run_config.execution.use_modelica_reference_if_available,
+        modelica_reference_exists=resolved_modelica_result_path.exists(),
+    )
+
+
+def run_prepared_testmodel(prepared_run: PreparedTestModelRun) -> TestModelRunResult:
+    run_config = prepared_run.run_config
+    system = TestModelSystem(config=run_config.model)
+    raw_initial_state = tuple(system.initial_state_vector())
+    initialization = system.initialize_consistent_state()
+    consistent_initial_state = tuple(initialization.state_vector)
+    solution = system.simulate(config=run_config.solver, t_eval=list(prepared_run.t_eval))
+    series = system.evaluate_solution(solution)
+    solve_diagnostics = system.last_solve_diagnostics
+
+    modelica_series = None
+    used_modelica_reference = False
+    if (
+        prepared_run.use_modelica_reference_if_available
+        and prepared_run.modelica_reference_exists
+    ):
+        modelica_series = load_modelica_series(
+            prepared_run.modelica_result_path,
+            COMPARISON_KEYS,
+        )
+        used_modelica_reference = True
+
+    artifacts, comparison_summary = export_testmodel_artifacts(
+        output_dir=prepared_run.output_dir,
+        series=series,
+        modelica_series=modelica_series,
+    )
+    report_text = format_testmodel_run_report(
+        network_summary=system.network.summary(),
+        initialization=initialization,
+        raw_initial_state=raw_initial_state,
+        consistent_initial_state=consistent_initial_state,
+        solution=solution,
+        series=series,
+        solve_diagnostics=solve_diagnostics,
+        artifacts=artifacts,
+        comparison_summary=comparison_summary,
+    )
+    write_testmodel_run_report(prepared_run.output_dir, report_text)
+
+    return TestModelRunResult(
+        run_config=run_config,
+        prepared_run=prepared_run,
+        system=system,
+        initialization=initialization,
+        raw_initial_state=raw_initial_state,
+        consistent_initial_state=consistent_initial_state,
+        solution=solution,
+        series=series,
+        solve_diagnostics=solve_diagnostics,
+        artifacts=artifacts,
+        comparison_summary=comparison_summary,
+        used_modelica_reference=used_modelica_reference,
+    )
+
+
+def run_testmodel(
+    *,
+    run_config: TestModelRunConfig | None = None,
+    output_dir: Path | None = None,
+    modelica_result_path: Path | None = None,
+) -> TestModelRunResult:
+    prepared_run = prepare_testmodel_run(
+        run_config=run_config,
+        output_dir=output_dir,
+        modelica_result_path=modelica_result_path,
+    )
+    return run_prepared_testmodel(prepared_run)
+
+
+def main() -> None:
+    run_config = TestModelRunConfig()
+    result = run_testmodel(run_config=run_config)
+    print(
+        format_testmodel_run_report(
+            network_summary=result.system.network.summary(),
+            initialization=result.initialization,
+            raw_initial_state=result.raw_initial_state,
+            consistent_initial_state=result.consistent_initial_state,
+            solution=result.solution,
+            series=result.series,
+            solve_diagnostics=result.solve_diagnostics,
+            artifacts=result.artifacts,
+            comparison_summary=result.comparison_summary,
+        ),
+        end="",
+    )
+
+
+if __name__ == "__main__":
+    main()