iomgaa
cf6bc4c844
runner 用 Docker 跑一条命令并交回结局和资源用量；tasks 读 task.json、准备运行目录、给出正式运行/校验器/轻量检查的运行定义，并从原始产物独立判分。任务目录从参考项目搬到 tasks/circle_packing/，新增 task.json；vocab 的 VERDICTS 删掉"判不了"，ProcessResult 的 cancelled 改为"容器从外面被杀了"。 全新上下文审阅后的两处修复：计量 shell 以容器内 root 运行，命令经 setpriv 降权，结果写在容器自己的文件层、结束后 docker cp 取出，并加 no-new-privileges，候选无法伪造计量结果把超时记成正常退出；harness 开跑前删掉旧的 solution.json、metrics.json，旧产物不会被当成本次的值。 Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
101 lines
3.1 KiB
Python
101 lines
3.1 KiB
Python
# EVOLVE-BLOCK-START
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"""Constructor-based circle packing for n=26 circles"""
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import numpy as np
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def construct_packing():
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"""
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Construct a specific arrangement of 26 circles in a unit square
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that attempts to maximize the sum of their radii.
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Returns:
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Tuple of (centers, radii, sum_of_radii)
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centers: np.array of shape (26, 2) with (x, y) coordinates
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radii: np.array of shape (26) with radius of each circle
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sum_of_radii: Sum of all radii
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"""
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# Initialize arrays for 26 circles
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n = 26
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centers = np.zeros((n, 2))
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# Place circles in a structured pattern
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# This is a simple pattern - evolution will improve this
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# First, place a large circle in the center
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centers[0] = [0.5, 0.5]
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# Place 8 circles around it in a ring
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for i in range(8):
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angle = 2 * np.pi * i / 8
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centers[i + 1] = [0.5 + 0.3 * np.cos(angle), 0.5 + 0.3 * np.sin(angle)]
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# Place 16 more circles in an outer ring
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for i in range(16):
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angle = 2 * np.pi * i / 16
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centers[i + 9] = [0.5 + 0.7 * np.cos(angle), 0.5 + 0.7 * np.sin(angle)]
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# Additional positioning adjustment to make sure all circles
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# are inside the square and don't overlap
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# Clip to ensure everything is inside the unit square
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centers = np.clip(centers, 0.01, 0.99)
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# Compute maximum valid radii for this configuration
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radii = compute_max_radii(centers)
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return centers, radii
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def compute_max_radii(centers):
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"""
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Compute the maximum possible radii for each circle position
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such that they don't overlap and stay within the unit square.
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Args:
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centers: np.array of shape (n, 2) with (x, y) coordinates
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Returns:
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np.array of shape (n) with radius of each circle
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"""
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n = centers.shape[0]
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radii = np.ones(n)
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# First, limit by distance to square borders
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for i in range(n):
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x, y = centers[i]
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# Distance to borders
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radii[i] = min(x, y, 1 - x, 1 - y)
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for i in range(n):
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for j in range(i + 1, n):
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dist = np.sqrt(np.sum((centers[i] - centers[j]) ** 2))
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# Then, limit by distance to other circles
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# Each pair of circles with centers at distance d can have
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# sum of radii at most d to avoid overlap
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for i in range(n):
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for j in range(i + 1, n):
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dist = np.sqrt(np.sum((centers[i] - centers[j]) ** 2))
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# If current radii would cause overlap
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if radii[i] + radii[j] > dist:
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# Scale both radii proportionally
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scale = dist / (radii[i] + radii[j])
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radii[i] *= scale
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radii[j] *= scale
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# Ensure no negative radii due to numerical issues
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radii = np.maximum(radii, 0.0)
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return radii
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# EVOLVE-BLOCK-END
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# This part remains fixed (not evolved)
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def run_packing():
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"""Run the circle packing constructor for n=26"""
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centers, radii = construct_packing()
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# Calculate the sum of radii
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sum_radii = np.sum(radii)
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return centers, radii, sum_radii
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