|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
import time |
|
|
import numpy as np |
|
|
import sys |
|
|
import os |
|
|
from importlib import __import__ |
|
|
import itertools |
|
|
|
|
|
BENCHMARK = 0.036529889880030156 |
|
|
TOL = 1e-6 |
|
|
NUM_POINTS = 11 |
|
|
|
|
|
|
|
|
def check_inside_triangle_wtol(points: np.ndarray, tol: float = 1e-6): |
|
|
"""Checks that all points are inside the triangle with vertices (0,0), (1,0), (0.5, sqrt(3)/2). |
|
|
|
|
|
Args: |
|
|
points: Array of 2D points to check |
|
|
tol: Tolerance for numerical errors |
|
|
""" |
|
|
for x, y in points: |
|
|
cond1 = y >= -tol |
|
|
cond2 = np.sqrt(3) * x <= np.sqrt(3) - y + tol |
|
|
cond3 = y <= np.sqrt(3) * x + tol |
|
|
|
|
|
if not (cond1 and cond2 and cond3): |
|
|
raise ValueError( |
|
|
f"Point ({x}, {y}) is outside the equilateral triangle (tolerance: {tol})." |
|
|
) |
|
|
|
|
|
|
|
|
def triangle_area(a: np.array, b: np.array, c: np.array) -> float: |
|
|
return np.abs(a[0] * (b[1] - c[1]) + b[0] * (c[1] - a[1]) + c[0] * (a[1] - b[1])) / 2 |
|
|
|
|
|
|
|
|
def evaluate(program_path: str): |
|
|
try: |
|
|
abs_program_path = os.path.abspath(program_path) |
|
|
program_dir = os.path.dirname(abs_program_path) |
|
|
module_name = os.path.splitext(os.path.basename(program_path))[0] |
|
|
|
|
|
points = None |
|
|
try: |
|
|
sys.path.insert(0, program_dir) |
|
|
program = __import__(module_name) |
|
|
|
|
|
start_time = time.time() |
|
|
points = program.heilbronn_triangle11() |
|
|
end_time = time.time() |
|
|
eval_time = end_time - start_time |
|
|
except Exception as err: |
|
|
raise err |
|
|
finally: |
|
|
if program_dir in sys.path: |
|
|
sys.path.remove(program_dir) |
|
|
|
|
|
if not isinstance(points, np.ndarray): |
|
|
points = np.array(points) |
|
|
|
|
|
if points.shape != (NUM_POINTS, 2): |
|
|
raise ValueError(f"Invalid shapes: points = {points.shape}, expected {(NUM_POINTS,2)}") |
|
|
|
|
|
check_inside_triangle_wtol(points, TOL) |
|
|
|
|
|
a = np.array([0, 0]) |
|
|
b = np.array([1, 0]) |
|
|
c = np.array([0.5, np.sqrt(3) / 2]) |
|
|
min_triangle_area = min( |
|
|
[triangle_area(p1, p2, p3) for p1, p2, p3 in itertools.combinations(points, 3)] |
|
|
) |
|
|
min_area_normalized = min_triangle_area / triangle_area(a, b, c) |
|
|
|
|
|
return { |
|
|
"min_area_normalized": float(min_area_normalized), |
|
|
"combined_score": float(min_area_normalized / BENCHMARK), |
|
|
"eval_time": float(eval_time), |
|
|
} |
|
|
except Exception as e: |
|
|
return {"combined_score": 0.0, "error": str(e)} |
|
|
|