Download task/single-software-execution/cli/floris/task-09/eval.py from HongchengGao/EngiWorld-Tasks: direct link, hf CLI and curl.
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https://huggingface.co/datasets/HongchengGao/EngiWorld-Tasks/resolve/main/task/single-software-execution/cli/floris/task-09/eval.py
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hf download hf://datasets/HongchengGao/EngiWorld-Tasks/task/single-software-execution/cli/floris/task-09/eval.py
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curl -L -o eval.py https://huggingface.co/datasets/HongchengGao/EngiWorld-Tasks/resolve/main/task/single-software-execution/cli/floris/task-09/eval.py
2.54 kB
| #!/usr/bin/env python3 | |
| import math | |
| from pathlib import Path | |
| import floris | |
| from floris import FlorisModel, WindRose | |
| import numpy as np | |
| import yaml | |
| from eval_utils import ( | |
| desktop_root, | |
| parse_floats, | |
| print_result, | |
| read_numeric_csv, | |
| require_calls, | |
| require_source_tokens, | |
| run_submission, | |
| ) | |
| def configuration(): | |
| path = Path(floris.__file__).resolve().with_name("default_inputs.yaml") | |
| config = yaml.safe_load(path.read_text(encoding="utf-8")) | |
| config["logging"]["console"]["level"] = "ERROR" | |
| config["farm"]["layout_x"] = [0.0, 500.0, 0.0, 500.0] | |
| config["farm"]["layout_y"] = [0.0, 0.0, 500.0, 500.0] | |
| config["farm"]["turbine_type"] = ["nrel_5MW"] * 4 | |
| return config | |
| def compute_aep_gwh(x, y): | |
| rose = WindRose( | |
| np.array([270.0, 280.0, 290.0]), | |
| np.array([8.0]), | |
| 0.06, | |
| np.array([[0.5], [0.3], [0.2]]), | |
| ) | |
| model = FlorisModel(configuration()) | |
| model.set(layout_x=x, layout_y=y, wind_data=rose) | |
| model.run() | |
| return float(model.get_farm_AEP() / 1e9) | |
| def check() -> bool: | |
| root = desktop_root() | |
| tree = run_submission( | |
| root, | |
| "layout_opt.py", | |
| ["optimized_layout.csv", "summary.txt"], | |
| timeout=420, | |
| ) | |
| require_calls(tree, {"FlorisModel": 1, "WindRose": 1, "optimize": 1}) | |
| require_source_tokens(root / "layout_opt.py", ["LayoutOptimization", "378", "0.5", "0.3", "0.2"]) | |
| summary = parse_floats(root / "summary.txt", 3) | |
| layout = read_numeric_csv(root / "optimized_layout.csv", 4, 2, header=["x", "y"]) | |
| x = np.array([row[0] for row in layout]) | |
| y = np.array([row[1] for row in layout]) | |
| if np.any(x < -100.000001) or np.any(x > 600.000001): | |
| return False | |
| if np.any(y < -100.000001) or np.any(y > 600.000001): | |
| return False | |
| spacing = min( | |
| math.hypot(float(x[i] - x[j]), float(y[i] - y[j])) | |
| for i in range(4) | |
| for j in range(i + 1, 4) | |
| ) | |
| if spacing < 377.999: | |
| return False | |
| initial = compute_aep_gwh([0.0, 500.0, 0.0, 500.0], [0.0, 0.0, 500.0, 500.0]) | |
| optimized = compute_aep_gwh(x, y) | |
| return ( | |
| optimized >= initial * 1.02 | |
| and math.isclose(summary[0], initial, rel_tol=5e-4, abs_tol=1e-3) | |
| and math.isclose(summary[1], optimized, rel_tol=5e-4, abs_tol=1e-3) | |
| and math.isclose(summary[2], spacing, rel_tol=1e-5, abs_tol=1e-3) | |
| ) | |
| if __name__ == "__main__": | |
| try: | |
| result = check() | |
| except Exception: | |
| result = False | |
| raise SystemExit(print_result(result)) | |