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Align task taxonomy and IDs with the updated paper; main evaluation 306
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#!/usr/bin/env python3
from __future__ import annotations
import os
import re
from pathlib import Path
FLOAT_RE = re.compile(r"(?<![A-Za-z0-9_])[-+]?(?:\d+(?:\.\d*)?|\.\d+)(?:[eE][-+]?\d+)?(?![A-Za-z0-9_])")
REL_TOL = 1e-2
ABS_TOL = 1e-4
SPEEDS = (4, 8, 11, 15, 20)
REQUIRED_FILES = ['summary.txt', 'batch_run.py', 'batch_post.py'] + [
f'case_ws{speed}{suffix}' for speed in SPEEDS for suffix in ('.fst', '.out', '.log')
] + [f'NRELOffshrBsline5MW_InflowWind_{speed}.dat' for speed in SPEEDS]
EXPECTED_ROWS = [[4.0, 148.961900, 7.139225, 0.0], [8.0, 1615.091080, 8.922938, 0.0], [11.0, 4129.585700, 11.802750, 0.0], [15.0, 4999.824037, 12.098685, 9.619814], [20.0, 5000.103390, 12.100203, 16.936624]]
SUMMARY_FILE = 'summary.txt'
def parse_floats(text: str) -> list[float]:
values: list[float] = []
for token in FLOAT_RE.findall(text):
try:
values.append(float(token))
except ValueError:
continue
return values
def parse_numeric_rows(path: Path) -> list[list[float]]:
rows: list[list[float]] = []
for raw in path.read_text(encoding='utf-8', errors='ignore').splitlines():
line = raw.strip()
if (not line) or line.startswith('#'):
continue
vals = parse_floats(line)
if vals:
rows.append(vals)
return rows
def file_ok(path: Path) -> bool:
return path.exists() and path.is_file() and path.stat().st_size > 0
def close_enough(actual: float, expected: float) -> bool:
return abs(actual - expected) <= max(ABS_TOL, REL_TOL * max(1.0, abs(expected)))
def keyed_value(text: str, key: str) -> str:
for line in text.splitlines():
parts = line.split()
if len(parts) >= 2 and parts[1] == key:
return parts[0].strip('"')
raise KeyError(key)
def tail_means(path: Path) -> tuple[float, float, float]:
lines = path.read_text(encoding='utf-8', errors='ignore').splitlines()
header = next(i for i, line in enumerate(lines) if line.split() and line.split()[0] == 'Time')
names = lines[header].split()
indices = [names.index(name) for name in ('Time', 'GenPwr', 'RotSpeed', 'BldPitch1')]
rows = [[float(value) for value in line.split()] for line in lines[header + 2:] if line.split()]
if not rows or rows[-1][indices[0]] < 59.9:
raise ValueError('incomplete output')
tail = [row for row in rows if row[indices[0]] >= 50.0]
return tuple(sum(row[index] for row in tail) / len(tail) for index in indices[1:])
def check_task(root: Path) -> bool:
for rel in REQUIRED_FILES:
if not file_ok(root / rel):
return False
actual = parse_numeric_rows(root / SUMMARY_FILE)
if len(actual) != len(EXPECTED_ROWS):
return False
by_speed = {int(row[0]): row for row in actual if len(row) == 4}
for row_e in EXPECTED_ROWS:
speed = int(row_e[0])
row_a = by_speed.get(speed, [])
if len(row_a) != len(row_e):
return False
for a, e in zip(row_a, row_e):
if not close_enough(a, e):
return False
inflow_name = f'NRELOffshrBsline5MW_InflowWind_{speed}.dat'
inflow = (root / inflow_name).read_text(encoding='utf-8', errors='ignore')
if float(keyed_value(inflow, 'WindType')) != 1 or float(keyed_value(inflow, 'HWindSpeed')) != speed:
return False
if f'"{inflow_name}"' not in (root / f'case_ws{speed}.fst').read_text(errors='ignore'):
return False
if 'OpenFAST terminated normally' not in (root / f'case_ws{speed}.log').read_text(errors='ignore'):
return False
means = tail_means(root / f'case_ws{speed}.out')
if any(not close_enough(value, expected) for value, expected in zip(means, row_a[1:])):
return False
return True
def evaluate() -> int:
root = Path(os.environ.get('EVAL_OUTPUT_ROOT', '/home/user/Desktop'))
try:
ok = check_task(root)
except Exception:
ok = False
return 1 if ok else 0
def main() -> int:
result = evaluate()
print('True' if result == 1 else 'False')
return 0
if __name__ == '__main__':
raise SystemExit(main())