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"size": "scalable", + "__class__": "FontEntry" + }, + { + "fname": "/Users/peng/Library/Fonts/MonaspaceKrypton-SemiWideSemiBoldItalic.otf", + "index": 0, + "name": "Monaspace Krypton SemiWide SemiBold", + "style": "italic", + "variant": "normal", + "weight": 400, + "stretch": "expanded", + "size": "scalable", + "__class__": "FontEntry" + } + ], + "__class__": "FontManager" +} \ No newline at end of file diff --git a/README.md b/README.md index 64b6981..11155c6 100644 --- a/README.md +++ b/README.md @@ -3,6 +3,12 @@ 统一框架：有界误差几何定位、主动选点、带覆盖证明的搜索、按真实动作耗时调度。 分析依据 `issue/B题.pdf`、附件1《模拟器使用说明》、附件2《通信接口说明及编程指南》。 +**文档总入口：[docs/README.md](docs/README.md)**（分类索引、阅读顺序与口径登记）。 + +- [总体思路与流程图（四问主线、端到端流程图、执行时间速查）](docs/总体思路与流程图.md) +- [执行时间与执行步骤（计时模型、状态机、附件示例推演、实测分解）](docs/执行时间与执行步骤.md) +- [几何计算示意图册（逐图说明：角域交会、覆盖、最小命中集）](docs/几何计算示意图册.md) +- [论文插图清单与复现方式](docs/figures/README.md)（`uv run python scripts/make_figures.py`） - [四问建模分析与 P0–P7 实施计划](docs/B题建模分析与实施计划.md) - [协议规则表、字段表与状态机（P0 交付）](docs/协议规则表与状态机.md) - [问题一完整解答](docs/问题一解答.md) @@ -35,7 +41,9 @@ tests/ # pytest（含解耦守卫：运行时零导入 referee + 规 project/ # 1-4 问"最优实现 / 基线实现"对比框架：逐问 optimal+baseline # +独立参考，冻结基准集配对出数；见 project/README.md scripts/ # 采集、基准、可视化与校核脚本（含问题四批量仿真 benchmark_q4.py、 - # 运行历史计时分解 analyze_run_timing.py、第四问覆盖证书 verify_q4_cover.py） + # 运行历史计时分解 analyze_run_timing.py、第四问覆盖证书 verify_q4_cover.py、 + # 论文插图 make_figures.py、日志归档 archive_replay_logs.py） +docs/figures/ # 论文插图（PNG）+ manifest.json（数据来源与 sha256）+ 图清单 output/ examples/ # 演练证据、算例与生成产物 ``` diff --git a/docs/README.md b/docs/README.md new file mode 100644 index 0000000..0e8497e --- /dev/null +++ b/docs/README.md @@ -0,0 +1,71 @@ +# docs 索引 + +仓库文档分四类：**总览与流程**、**逐问算法**、**验证与对比**、**论文与插图**。 +阅读顺序建议按下面的表格从上到下。 + +## 总览与流程 + +| 文档 | 内容 | +| --- | --- | +| [`总体思路与流程图.md`](总体思路与流程图.md) | 四问主线、端到端流程图（mermaid）、执行步骤与执行时间速查、交付物与验收锚点 | +| [`执行时间与执行步骤.md`](执行时间与执行步骤.md) | 计时模型、会话状态机与动作回合、附件示例逐步推演、实测日志分解、时间预算与安全阀 | +| [`B题建模分析与实施计划.md`](B题建模分析与实施计划.md) | 四问建模取舍与 P0–P7 实施计划（最早的设计文档） | +| [`协议规则表与状态机.md`](协议规则表与状态机.md) | 指令字段表、结果码、计时模型、状态机（P0 交付） | + +## 逐问算法 + +| 文档 | 内容 | +| --- | --- | +| [`algo-1.md`](algo-1.md) | 问题一实现口径：半平面交、顶点对直径、直径圆充要判定、MEC 清除证书 | +| [`问题一解答.md`](问题一解答.md) | 问题一论文式解答：模型边界、算法可复现步骤、反例构造、演练验证 | +| [`algo-2.md`](algo-2.md) | 问题二：候选集 K1、保证接收盘、安全盘 B(c, 1000−a)、最坏后验选点 | +| [`algo-3.md`](algo-3.md) | 问题三：三层在线架构、七点解析覆盖、覆盖账本、任务调度与停止条件 | +| [`algo-3-bayes.md`](algo-3-bayes.md) | 问题三 `bayes` 策略：网格幸存集滤波、信息增益选点、动态 TSP、Optuna 调参 | +| [`algo-4.md`](algo-4.md) | 问题四：`forward_half_disk` 最小命中集、位置×朝向联合信念、后备盲清 | + +## 优化与验证 + +| 文档 | 内容 | +| --- | --- | +| [`第三四问架构优化与运行提速方案.md`](第三四问架构优化与运行提速方案.md) | 运行历史复核、分层目标架构、P0–P2 优化项与实施路线 | +| [`第三四问图论与动态规划优化方案.md`](第三四问图论与动态规划优化方案.md) | 图论/DP 引入方案与实测回填（含未采用的改动与原因） | +| [`算法审核与优化-20260911.md`](算法审核与优化-20260911.md) | 一次外部口径的算法审核记录与结论 | +| [`最优与基线实现对比.md`](最优与基线实现对比.md) | 1–4 问「最优实现 / 基线实现」对比框架与结果（论文口径说明） | +| [`B题问题3-4相关论文列表.md`](B题问题3-4相关论文列表.md) | 题 3、4 相关文献清单 | + +## 论文与插图 + +| 路径 | 内容 | +| --- | --- | +| [`paper/main.tex`](paper/main.tex) | 论文正文（`latexmk -xelatex main.tex`） | +| [`paper/README.md`](paper/README.md) | 论文编译方式、目录结构与待办标记 | +| [`figures/README.md`](figures/README.md) | 插图清单、配色与字体约定、数据来源与复现命令 | +| [`figures/manifest.json`](figures/manifest.json) | 每张图的数据来源与 sha256、生成命令 | +| [`../project/README.md`](../project/README.md) | 对比框架目录结构与运行方式 | + +## 口径登记 + +同一事实在多份文档中出现时，以下列来源为准；发现不一致请先改文档，再复核图。 + +| 事实 | 权威来源 | +| --- | --- | +| 题面常量（Ω、速度、各动作耗时、源与频道范围） | `src/mcm26b/config.py`（带 `[题面]` / `[工程]` 标注） | +| 指令字段与结果码 | `src/mcm26b/protocol/rules.py` + [`协议规则表与状态机.md`](协议规则表与状态机.md) | +| 问题一数值（D、ρ、E） | `mcm26b.geometry.solve` 的返回，或 [`问题一解答.md`](问题一解答.md) | +| 覆盖计划与证书 | `src/mcm26b/guarantee/plans/*.json`（`q4_mincover_v2.json` 为默认） | +| 实测虚拟时间 | 行为日志 `virtual_time_s` 字段与 `evaluation.recompute_virtual_time` | +| 冻结基准集对比结果 | `project/results/*.md`（由 `uv run python -m project.run` 生成） | + +已知的两处需要随环境更新的引用： + +1. [`问题一解答.md`](问题一解答.md) 引用的 `output/q1/figures/*.png` 属于早期 + 离线插图（`output/` 未入库）；现行插图在 [`figures/`](figures/README.md)。 +2. 多份文档提到的官方演练报告位于 `output/q3/practice/`、`output/q4/`， + 同样未入库；需要时用 `scripts/verify_q3_practice.py` 对留档目录复算。 + +## 写作约定 + +- 只写结论与依据，不使用比喻、排比与自评式措辞（例如「唯一权威」「关键洞察」）。 +- 数字必须能在代码或数据中找到出处；图内不放标题与解释段落， + 说明写在正文，图名与清单见 [`figures/README.md`](figures/README.md)。 +- 中文引号统一使用「」，避免与代码中的 ASCII 引号混淆。 diff --git a/docs/figures/README.md b/docs/figures/README.md new file mode 100644 index 0000000..7bc435a --- /dev/null +++ b/docs/figures/README.md @@ -0,0 +1,62 @@ +# docs/figures —— 论文插图 + +每张图只输出 PNG，由 `scripts/make_figures.py` 用 matplotlib 生成。 +`manifest.json` 记录每张图的数据来源（路径 + sha256 前 12 位 + 行数）与生成命令。 + +```bash +uv run python scripts/make_figures.py # 全部 11 张 +uv run python scripts/make_figures.py --list # 图名 +uv run python scripts/make_figures.py --only geo-q3-seven-point-coverage +uv run python scripts/make_figures.py --scale 1.5 # 整体放大（尺寸倍率） +``` + +依赖：`matplotlib`、`Pillow`、`docs/paper/fonts/` 下的字体。 +`matplotlib` 缓存写入仓库内 `.mpl-cache/`，不污染用户目录。 + +## 约定 + +- 图内不放标题、图注与解释性文字，只保留坐标轴、图例与数据标注； + 图的含义由文件名与下表承担，解释写在论文正文。 +- 配色（`scripts/make_figures.py::C`）：深蓝 `#1f4e79` 主流程与协议， + 砖红 `#b03a2e` 真值源与关键结论，墨绿 `#1e7a5f` 清除与通过项， + 土黄 `#b8860b` 后备与警示，灰色只用于网格与次要文字。 +- 字体：中文宋体 `SongtiSC-Regular/Bold`，标题黑体 `HeitiSC-Light/Medium`， + 数字与西文 Times New Roman，均取自 `docs/paper/fonts/`，与 `main.tex` 一致。 +- 输出为 PNG（`savefig.dpi = 200`，另有 `--scale` 倍率），按 160 mm 宽排版时 + 与正文同字号。 + +## 图清单 + +| 文件 | 内容 | 数据来源 | +| --- | --- | --- | +| `flow-overall-architecture.png` | 总体思路：题面抽象、在线三层、四问主线、三条闭环 | `src/mcm26b/config.py`、`docs/B题建模分析与实施计划.md` | +| `steps-state-machine.png` | 会话状态机（IDLE / 倒计时 / OPEN / CLOSED） | `docs/协议规则表与状态机.md`、`src/mcm26b/protocol/client.py` | +| `timing-attachment-example-105-111-194-199.png` | 附件计时示例逐步推演 | `docs/协议规则表与状态机.md` | +| `timing-measured-q3-10-sources.png` | 实测一局的虚拟时间分解（累计曲线 + 构成） | `referee-data/sessions/BBM9-HZG2-77N5-NKKC/log.jsonl` | +| `geo-q1-convex-intersection-zoom.png` | 问题一：角域交会总览 + 定位区域放大（直径圆与 MEC） | `output/q1/practice/U5ZW-P9KN-TCAG-R7ST_observations.json` | +| `geo-q1-diameter-circle-counterexample.png` | 问题一：直径圆不覆盖的反例（等边三角形布站） | `examples/q1/triangle.json` | +| `geo-q2-guaranteed-reception-disk.png` | 问题二：候选盘、截断角域外接圆、安全盘 `B(c, 1000−a)` | `src/mcm26b/config.py`、`docs/algo-2.md` | +| `geo-q3-seven-point-coverage.png` | 问题三：七点覆盖（7 个 1000 m 接收盘的并集覆盖 Ω）与三套计划对比 | `src/mcm26b/planner/seven.py`、`docs/algo-3.md` | +| `geo-q4-minimum-cover-31-points.png` | 问题四：31 点最小命中集与 `forward_half_disk` 语义 | `src/mcm26b/guarantee/plans/q4_mincover_v2.json` | +| `replay-webui-q3-omnidirectional.png` | WebUI 回放画布复现（全向局，10 源全清） | `referee-data/sessions/BBM9-HZG2-77N5-NKKC/log.jsonl` | +| `replay-webui-q4-directional.png` | WebUI 回放画布复现（定向源局） | `referee-data/sessions/GM56-DFXZ-XKDM-XYV7/log.jsonl` | + +后两张对应 WebUI 的预览功能：把回放器画布上的 Ω 与真值源、运动轨迹、 +检测示向度射线、清除标记，以及右侧事件流水与底部虚拟时间轴一起导出。 + +## 数据来源与复现 + +- `timing-measured-*`、`replay-webui-*` 读评测机行为日志（JSONL，含真值）。 + `referee-data/` 被 `.gitignore` 忽略，因此另归档两局到 `examples/replay/`； + 没有评测机数据时脚本自动改读归档，图一致。 + + ```bash + uv run python scripts/archive_replay_logs.py --list # 本机有哪些局 + uv run python scripts/archive_replay_logs.py <案例编码> # 追加归档 + ``` + +- `geo-q1-convex-intersection-zoom.png` 读官方演练留档 + `output/q1/practice/*_observations.json`（同样被忽略）。文件缺失时改读 + `examples/q1/triangle.json` 反例算例，图仍可用，只是案例不同。 +- 问题一的几何量由生产求解器 `mcm26b.geometry.solve` 现算； + 问题三、问题四直接读覆盖计划与证书，不手抄数字。 diff --git a/docs/figures/flow-overall-architecture.png b/docs/figures/flow-overall-architecture.png new file mode 100644 index 0000000000000000000000000000000000000000..be9c164e02c1eb1019d519dfc87571d75940250e GIT binary patch literal 75727 zcmeFYWl&ph)b>lE&=yJ!S_%}Yp#@spo#O5ipv5J42(C3sffg+i+=2uP1PEGzqQQa$ zFU1lPTm$6f|2*%U@8|28ch6+9XU{!*XWzMHt?T-&I0HR(dRi7*3JMB(O$}8e3JPjz z3JS{o>onvmuTq;8$Y0U{Y8C;;-p&EwH-1hOx^Dt}JiP-v-QIErI{Ep#d3%WnzIr7n 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zf%$b<433nIp&faK%v#RQD+Fa4thzmGpUCey^4R3o;uyUtz2Ay+nn|;0o5nqx4HERn nEmU$Nadv_As8aq$s(hZQ#Hxz literal 0 HcmV?d00001 diff --git a/docs/几何计算示意图册.md b/docs/几何计算示意图册.md new file mode 100644 index 0000000..d9cd843 --- /dev/null +++ b/docs/几何计算示意图册.md @@ -0,0 +1,208 @@ +# 几何计算示意图册 + +> 本册逐图给出坐标口径、关键量与图中各元素的含义。插图位于 [`figures/`](figures/)，复现命令： +> +> ```bash +> uv run python scripts/make_figures.py --only geo-q1-convex-intersection-zoom,\ +> geo-q1-diameter-circle-counterexample,geo-q2-guaranteed-reception-disk,\ +> geo-q3-seven-point-coverage,geo-q4-minimum-cover-31-points +> ``` +> +> 图中的数字由脚本现算：问题一调用生产求解器，问题三、四直接读覆盖计划与证书； +> 来源与 sha256 记在 [`figures/manifest.json`](figures/manifest.json)。 + +统一的坐标与符号约定： + +- 世界坐标以 Ω 圆心为原点，$x$ 轴向右、$y$ 轴向上，单位**米**； +- Ω 是半径 $R=1800$ m 的圆盘；源的有效接收半径 $r_{\rm eff}\in[1000,1500]$ m； +- 示向度 $\theta$ 以 $+x$ 轴为 $0°$ 逆时针为正，误差半角 $\delta=1°$； +- 清除半径 $r_{\rm clear}=20$ m； +- "可保证清除" ⟺ 存在一点使整个候选区域落在该点 20 m 内 ⟺ $\rho\le 20$ m（充分）。 + +--- + +## 图 1　问题一：角域交会与定位区域 + +![问题一角域交会](figures/geo-q1-convex-intersection-zoom.png) + +**左（总览）**：三个检测点（官方演练案例 `U5ZW-P9KN-TCAG-R7ST`，频道 9） +各自的**前向角域** $W_i=\{p:\angle(p-s_i)-\theta_i\in[-1°,+1°]\}$ 画成窄扇形 +（2° 宽，图中放大成可见宽度）；三者交集就是定位区域 $P$。检测点相距 600~900 m， +而 $P$ 的直径只有 24 m，所以左图里 $P$ 缩成一个点——这是**必须做局部放大**的原因。 + +**右（放大，视野 ±31.4 m）**：以最小包围圆圆心为中心： + +- 浅蓝扇形 = 三个角域在放大框内的可见部分；三者**重叠成白色区域**= $P$； +- 红色实线多边形 = $P$ 的顶点边界（与左图同一个集合）； +- 蓝色虚线圆 = **直径圆**，半径 $D/2=11.9984$ m，圆心是中点 $(-450.634,\ 508.944)$； +- 绿色实线圆 = **最小包围圆（MEC）**，$\rho=12.0686$ m，圆心 $(-449.977,\ 507.953)$。 + +**关键量（图 (c) 栏）** + +| 量 | 值 | 判定 | +| --- | ---: | --- | +| 直径 $D(P)$ | 23.9967 m | 顶点对枚举（凸集上最远点必为顶点） | +| MEC 半径 $\rho$ | 12.0686 m | Welzl 算法 + 支撑点枚举对照 | +| 直径圆最大超出 $E$ | +0.6040 m | $E>0$ ⇒ **直径圆不覆盖** $P$ | +| $\rho\le20$ m | 成立 | ⇒ **存在可保证清除的点**（取 MEC 圆心） | + +> 这两个结论不矛盾：题目问"直径圆能否覆盖"（答案：不能，$E>0$） +> 与"能否保证清除"（答案：能，$\rho\le20$ m）是**两个不同的问题**。 +> $E$ 的定义：$E=\max_i\lVert v_i-o\rVert-D/2$，$o$ 为直径中点； +> 精确算术下最远顶点对就在圆周上，故 $E\ge0$，$E>0$ 即覆盖失败， +> 达到最大值的顶点就是可独立复核的失败证据。 + +--- + +## 图 2　问题一：直径圆不覆盖的反例 + +![直径圆反例](figures/geo-q1-diameter-circle-counterexample.png) + +等边三角形布站（$S_1(-1000,0)$、$S_2(540,-866)$、$S_3(520,901)$，示向度 +$1°,121°,241°$，误差半角 $1°$）。三条 2° 宽的角域交出一个**等边三角形** +$P$：顶点 $(0,0)$、$(40,0)$、$(20,34.641)$。 + +- 直径 $D=40.0000$ m，最远点对是底边两端 ⇒ 直径圆圆心 $(20,0)$、半径 20 m； +- 到第三个顶点 $(20,34.641)$ 的距离是 $20\sqrt3\approx34.6410$ m > 20 m， + 故**直径圆不覆盖**：$E=+14.6410$ m（图中箭头所指）； +- 该反例的最小包围圆半径 $\rho=40/\sqrt3\approx23.0940$ m **> 20 m**， + 属于"覆盖失败且无法保证清除"的更坏情形。 + +> 反例是**符合题设测向条件**的：把真实源放在三角形中心 $(20,20\sqrt3/3)$， +> 三个检测点的真实方位与读数偏差均小于 $1°$，且三个检测距离都小于 1500 m， +> 所以它不是"脱离测向模型的任意图形"。构造与证明见 +> [`问题一解答.md`](问题一解答.md) 第六节。 + +--- + +## 图 3　问题二：保证接收的候选盘与安全盘 + +![问题二保证接收盘](figures/geo-q2-guaranteed-reception-disk.png) + +**候选集**（首次观测之后可能的位置集合）： + +$$ +K_1=\Omega\ \cap\ W(s_1,\theta_1\pm\delta)\ \cap\ B(s_1,\ 1500), +$$ + +即"Omega 内、首次角域内、且距离不超过最大接收半径"的三者之交。 + +**解析安全盘**：截断角域（扇形，半径 $R_{\max}=1500$ m、半角 $\delta=1°$） +的最小包围圆恰为 $B(c,a)$，其中 $c=s_1+a\boldsymbol u$（$\boldsymbol u$ 为示向度单位向量）， + +$$ +a=\frac{R_{\max}}{2\cos\delta}=\frac{1500}{2\cos1°}=750.1142\ \text{m}. +$$ + +于是对安全盘内任一点 $q$、扇形内任一点 $p$： + +$$ +\lVert q-p\rVert\le a+(1000-a)=1000\ \text{m} +\ \Longrightarrow\ q\ \text{必然收到源的信号}, +$$ + +$$ +\boxed{\ \text{安全盘半径}=1000-a=249.8858\ \text{m}\ } +$$ + +（严格非空；图中绿色实心圆，圆心 $c=(649.62,\ 375.06)$）。 +第二检测点就在该盘内选，目标是**最小化最坏保守后验包围半径**， +移动与检测成本作次目标；交会角只用于同分筛选与可解释性说明。 + +> 图中 $a$ 与 1000 m 两个圆几乎重合是可预期的：$\delta$ 只有 $1°$， +> $a=R_{\max}/(2\cos\delta)$ 与 $R_{\max}/2$ 相差 0.0114%， +> 因此**安全盘的"安全"主要来自角域约束，而不是圆心位置**。 + +--- + +## 图 4　问题三：七点解析覆盖 + +![问题三七点覆盖](figures/geo-q3-seven-point-coverage.png) + +**站点集**：原点 + 半径 $a$ 的六等分环， +$S(a)=\{(0,0)\}\cup\{a(\cos k\pi/3,\ \sin k\pi/3):k=0,\dots,5\}$。 + +**定理（`algo-3.md` §4.2）** 当 $0 **本轮修复的正确性缺陷**：旧版 `no_signal` 的朝向裁剪规则反向、且漏计格内角裕量， +> 会删掉真源所在的朝向档。已修复，并由 +> `tests/test_joint_belief.py` 的随机观测序列保留性测试固化。 + +--- + +## 附：把图接进论文 + +`docs/paper/main.tex` 目前用表格承载结论，插图按下例插入即可： + +```latex +\begin{figure}[htbp] + \centering + \includegraphics[width=0.95\textwidth]{figures/geo-q1-convex-intersection-zoom.png} + \caption{问题一：角域交会得到的定位区域，以及直径圆与最小包围圆的关系。} + \label{fig:geo-q1} +\end{figure} +``` + +图片按 160 mm 宽排版。图内不含标题与图注，说明写在 `\caption` 与正文。 diff --git a/docs/总体思路与流程图.md b/docs/总体思路与流程图.md new file mode 100644 index 0000000..bd203e1 --- /dev/null +++ b/docs/总体思路与流程图.md @@ -0,0 +1,178 @@ +# 总体思路与流程图 + +> 插图：[`figures/flow-overall-architecture.png`](figures/flow-overall-architecture.png)（总体思路与算法主线）、 +> [`figures/steps-state-machine.png`](figures/steps-state-machine.png)（执行步骤）、 +> [`figures/timing-attachment-example-105-111-194-199.png`](figures/timing-attachment-example-105-111-194-199.png)（附件计时示例）。 +> 复现：`uv run python scripts/make_figures.py --only flow-overall-architecture,steps-state-machine,timing-attachment-example-105-111-194-199` + +本文给出四问的思路、端到端流程图、执行步骤与执行时间。 +算法细节指向 [`algo-1.md`](algo-1.md)~[`algo-4.md`](algo-4.md)， +协议细节指向 [`协议规则表与状态机.md`](协议规则表与状态机.md)。 + +--- + +## 1. 主线 + +把题面约束写成可计算的几何集合和计时账本，四问共用一套「证据 — 决策 — 执行」结构， +每问都给出可验证的保证： + +| 问 | 保证 | +| --- | --- | +| 1 | 直径由顶点对枚举给出；最小包围圆半径 $\rho\le20$ m 时存在可保证清除的点 | +| 2 | 第二检测点取在解析安全盘 $B(c,1000-a)$（半径 249.8858 m）内，必然收到信号 | +| 3 | 七点计划覆盖整个 Ω（解析上界 984.5391 m < 1000 m），据此可判定频道无源 | +| 4 | 31 点最小命中集在 15 m / 72 朝向档证书下缺口为 0 | + +![总体思路与算法主线](figures/flow-overall-architecture.png) + +--- + +## 2. 四层结构 + +| 层 | 内容 | 作用 | +| --- | --- | --- | +| L0 题面抽象 | Ω 半径 1800 m；移动 5 m/s、检测 5 s、换频 1 s、清除 5 s / 3 s；观测 `direction/no_signal/near`；源 10~16 个，频道 1~20，定向源覆盖 ±90° | 后续推导只用这些量，不引入题面之外的信息 | +| L1 在线三层 | 证据层（候选集与粒子）、决策层（选点与任务表）、执行层（串行客户端） | 依赖单向向下，几何结论与调度启发式可分别测试 | +| L2 四问 | Q1 定位解算 → Q2 第二点选择 → Q3 全向搜索 → Q4 混合定向 | 后一问复用前一问的内核 | +| L3 三条闭环 | 发现、定位、清除 | 每环有明确的进入与退出条件 | + +L0 的常量集中在 `src/mcm26b/config.py`，带 `[题面]` / `[工程]` 标注。 +证据层只给出「可能在哪里」，决策层只读证据并产出动作， +执行层负责发送动作并维护虚拟时钟。 + +--- + +## 3. 四问思路 + +### 问题一 + +1. 检测点 $s_i$ 与示向度 $\theta_i$ 给出前向角域 + $W_i=\{p:\angle(p-s_i)-\theta_i\in[-1°,+1°]\}$，定位区域是半平面交 $P=\bigcap_i W_i$； +2. 直径 $D(P)=\max_{i,j}\lVert v_i-v_j\rVert$ 只需枚举顶点对（凸集上最远点必为顶点）； +3. 直径圆能否覆盖 $P$：唯一候选圆心是最远顶点对的中点。若 $a,b$ 同在该圆内， + 三角不等式两处同时取等，圆心只能是 $ab$ 中点，因此只需在该点检查全部顶点； +4. 能否保证清除：最小包围圆半径 $\rho\le20$ m 时，停在 MEC 圆心即可清除。 + 这是充分条件，不是必要条件。 + +结论：直径圆不一定覆盖定位区域，见 [`geo-q1-counterexample.png`](figures/geo-q1-diameter-circle-counterexample.png)； +官方演练案例是「覆盖失败但 $\rho=12.07$ m $\le20$ m，可保证清除」。 + +### 问题二 + +候选集 $K_1=\Omega\cap W(s_1,\theta_1\pm\delta)\cap B(s_1,1500)$。 +截断角域（扇形）的最小包围圆为 $B(c,a)$，$a=R_{\max}/(2\cos\delta)=750.1142$ m， +故安全盘 $B(c,1000-a)$ 的半径为 249.8858 m，盘内任一点到扇形内任一点的距离 +不超过 1000 m，即必然收到信号。在该盘内以最坏保守后验包围半径为主目标选点， +移动与检测成本作次目标，交会角只用于同分筛选。详见 [`algo-2.md`](algo-2.md)。 + +### 问题三 + +发现保证用七点计划（原点 + 半径 $a=1159.7$ m 的六等分环）：解析上界 +$D(a)=\max\{a/\sqrt3,\ \sqrt{R^2+a^2-\sqrt3Ra}\}=984.5391$ m < 1000 m， +Ω 内任意位置的源都在某站点 1000 m 内。证据层按频道维护候选集与粒子幸存集， +负观测按 `full_disk` 语义排除 1000 m 圆盘；决策层用信息增益选点， +任务表包含检测、定位、清除三类任务，排序为开放路径问题； +所有频道销账即完成证明成立，立即 `/exit`。 + +### 问题四 + +定向源只向朝向 ±90° 的前向半球辐射，覆盖语义改为 `forward_half_disk`。 +七点在该语义下有缺口，改用离线贪心得到的 31 点最小命中集（设计半径 965 m， +前向角裕量 5°），并以 15 m / 72 朝向档的运行期证书校核（325.62 万个采样格，缺口 0， +最坏命中 990.05 m）。负观测只约束朝向，因此维护位置 × 朝向联合信念， +信念坍缩到有限格时使用后备盲清。详见 [`algo-4.md`](algo-4.md)。 + +--- + +## 4. 端到端流程 + +```mermaid +flowchart TD + S([开始：/enter 成功
现实预算 1200 s 起算]) --> P0[读配置 ProblemConfig] + P0 --> PLAN{按问题选择覆盖计划} + PLAN -->|问题 3| S7[七点全向计划
解析上界 984.54 m] + PLAN -->|问题 4| S31[31 点最小命中集
forward_half_disk 证书] + S7 --> LOOP + S31 --> LOOP + + subgraph LOOP[主循环：动作回合] + direction TB + NEXT[选下一个任务
信息增益 / 最坏后验半径
滚动 2-opt 排序] --> SEND[/发送动作/] + SEND --> RESP{accepted?} + RESP -->|false| FIX[不更新状态
记录并重排任务] + RESP -->|true| CLK[更新虚拟时钟、位置、频道] + FIX --> NEXT + CLK --> OBS{观测类型} + OBS -->|direction| HIT[登记新源
同频道安排第二点交会] + OBS -->|no_signal| NEG[负观测裁剪
位置候选或朝向档] + OBS -->|near| SKIP[距离过近，换点重测] + HIT --> DONE{该频道 ρ ≤ 20 m?} + NEG --> DONE + SKIP --> DONE + DONE -->|是| CLR[/清除动作/] + DONE -->|否| NEXT + CLR --> LEDGER[覆盖账本销账] + LEDGER --> FIN{全部频道销账?} + FIN -->|否| NEXT + end + + FIN -->|是| EXITQ[完成证明成立，立即 /exit] + EXITQ --> REP[日志复算与统计] + REP --> END([结束：虚拟时间即成绩]) + + classDef main fill:#dce6f1,stroke:#1f4e79,color:#1c2430 + classDef acc fill:#f6dcd8,stroke:#b03a2e,color:#1c2430 + classDef ok fill:#d8ece5,stroke:#1e7a5f,color:#1c2430 + class NEXT,SEND,RESP,CLK,OBS main + class CLR,FIN,EXITQ acc + class LEDGER,REP ok +``` + +会话状态机与单次动作回合见 [`figures/steps-state-machine.png`](figures/steps-state-machine.png)， +逐步计时示例见 [`figures/timing-attachment-example-105-111-194-199.png`](figures/timing-attachment-example-105-111-194-199.png)。 + +--- + +## 5. 执行步骤与执行时间 + +一次动作回合：本地预校验 → 发送 → 等响应计时 → 按响应更新状态。 +异常时同 `request_id` 同内容重发，400 与 409 立即失败。 + +| 动作 | 虚拟耗时 | 说明 | +| --- | --- | --- | +| `/enter`、`/exit` | 0 s | 不改变虚拟时刻，`/exit` 不切频道 | +| 移动 | 直线距离 / 5 m·s⁻¹ | 同点不动为 0 s | +| 换测向频道 | 1 s | 仅 `/measure` 触发，`/clear` 不切换 | +| 检测 `/measure` | 5 s | 与返回结果无关 | +| 清除 `/clear` | 5 s / 3 s | 成功 5 s，未发现 3 s | + +实测样例（评测机日志 `BBM9-HZG2-77N5-NKKC`，问题三演练，10 源全清）： + +| 项 | 数值 | +| --- | --- | +| 总虚拟时间 | 3134.643 s | +| 移动（里程 11.9 km） | 2379.6 s | +| 检测与清除动作（119 + 10 次） | 645.0 s | +| 换频（110 次） | 110.0 s | +| 现实耗时 | 1.889 s | + +三项之和等于响应中的 `virtual_time_s`，与 `evaluation.recompute_virtual_time` 口径一致。 +分解图见 [`figures/timing-measured-q3-10-sources.png`](figures/timing-measured-q3-10-sources.png)， +定向局（`GM56-…`，虚拟 8703.766 s，现实 3.397 s）与复现命令见 +[`执行时间与执行步骤.md`](执行时间与执行步骤.md)。 + +--- + +## 6. 交付物与验收锚点 + +| 问 | 算法文档 | 主要实现 | 锚点 | +| --- | --- | --- | --- | +| 1 | [`algo-1.md`](algo-1.md)、[`问题一解答.md`](问题一解答.md) | `src/mcm26b/geometry/` | 演练复算 $D=23.9967$ m、$\rho=12.0686$ m、$E=+0.6040$ m | +| 2 | [`algo-2.md`](algo-2.md) | `geometry/`、`belief/`、`planner/` | 安全盘半径 249.8858 m | +| 3 | [`algo-3.md`](algo-3.md)、[`algo-3-bayes.md`](algo-3-bayes.md) | `planner/bayes_loop.py`、`planner/seven.py` | 七点上界 984.5391 m < 1000 m | +| 4 | [`algo-4.md`](algo-4.md) | `planner/directional.py`、`belief/joint.py` | 证书缺口 0，最坏命中 990.05 m | +| 1–4 | [`最优与基线实现对比.md`](最优与基线实现对比.md) | `project/` | `uv run python -m project.run` | + +优化过程与未采用的改动见 +[`第三四问架构优化与运行提速方案.md`](第三四问架构优化与运行提速方案.md)、 +[`第三四问图论与动态规划优化方案.md`](第三四问图论与动态规划优化方案.md)。 diff --git a/docs/执行时间与执行步骤.md b/docs/执行时间与执行步骤.md new file mode 100644 index 0000000..fa23cb3 --- /dev/null +++ b/docs/执行时间与执行步骤.md @@ -0,0 +1,178 @@ +# 执行时间与执行步骤 + +> 配套插图：[`figures/steps-state-machine.png`](figures/steps-state-machine.png)（状态机与动作回合）、 +> [`figures/timing-attachment-example-105-111-194-199.png`](figures/timing-attachment-example-105-111-194-199.png)（附件示例逐步推演）、 +> [`figures/timing-measured-q3-10-sources.png`](figures/timing-measured-q3-10-sources.png)（实测一局的时序分解）。 +> 复现：`uv run python scripts/make_figures.py --only steps-state-machine,timing-attachment-example-105-111-194-199,timing-measured-q3-10-sources` + +本文说明每一步做什么、每步花多少虚拟时间、这些数字如何验证。 +规则原文见 `issue/` 下附件1 表1、表2 与附件2 第 4、10 节； +可执行表格在 `src/mcm26b/protocol/rules.py` 与 `src/mcm26b/config.py` 的 `CostConfig`。 + +--- + +## 1. 计时模型 + +忽略微秒量化时，一次会话的总虚拟时间为 + +$$ +T=\underbrace{\frac{L}{5}}_{\text{移动}}+\underbrace{5N_m}_{\text{检测}} ++\underbrace{N_s}_{\text{换频}}+\underbrace{5N_c^{+}}_{\text{清除成功}} ++\underbrace{3N_c^{-}}_{\text{清除未发现}}, +\qquad L=\text{路径长度（米）},\ 5\ \text{m/s}. +$$ + +规则： + +- 移动按两点间直线距离计，不计加减速； +- 换频只在 `/measure` 触发，任意两频道间固定 1 s，`/clear` 不切换频道； +- 检测固定 5 s，与结果无关，`direction` 与 `no_signal` 同价； +- 清除成功 5 s（光学定位 3 s + 激光清除 2 s），未发现目标 3 s（仅光学定位）； +- `/enter`、`/exit` 不产生虚拟时间； +- 访问顺序是开放路径问题，起点固定、终点自由，不必回到起点。 + +![执行步骤：状态机与动作回合](figures/steps-state-machine.png) + +--- + +## 2. 执行步骤 + +### 2.1 会话级状态机 + +| 状态 | 进入条件 | 允许的动作 | 退出条件 | +| --- | --- | --- | --- | +| `IDLE` | 界面待机（演练不限次 / 正式各 3 次） | — | 点击"开始测试" | +| `COUNTDOWN` | 数据准备完成 | —（接口未开放） | 5 s 倒计时结束 | +| `OPEN` | 倒计时结束，接口在 `:2026` 开放 | `/enter` → `/measure` `/clear` → `/exit` | 25 分钟窗口到期 / 源全清后主动 `/exit` / 中止 | +| `CLOSED` | 窗口到期或进程退出 | —（连接关闭，已登记动作可完成） | — | + +现实预算与现实窗口是两条独立时钟：`/enter` 成功后 `max_real_duration_s = 1200 s` +起算（程序侧），测试窗口 `test_window_s = 1500 s`（服务端侧）。 +客户端维护本地截止时钟，剩余不足 60 s（`reserve_exit_s`，工程参数）时不再发起新动作， +只保证 `/exit` 能发出去。 + +### 2.2 单次动作回合（严格串行） + +![动作回合](figures/steps-state-machine.png) + +1. 本地预校验：`channel ∈ [1,20]`、坐标有限且 $\lvert x\rvert,\lvert y\rvert\le 2\times10^6$、 + `request_id` 长度与字符集，与服务器 400 语义一致，省一次往返； +2. 串行发送：同一时刻只有一个未决请求，不并发（并发会得到 409）； +3. 等服务端计时：`accepted=true` 才更新状态，虚拟时刻取响应中的 `virtual_time_s`， + 不做本地累加；`accepted=false` 抛 `ActionRejected`，状态不更新， + `virtual_time_s=0` 不计入时钟； +4. 更新本地状态：位置、当前频道、剩余现实预算，追加 JSONL 会话日志； +5. 异常处理：网络错误、429、500 时同 `request_id` 同内容重发 + （请求体一次性序列化，最多 `max_attempts` 次，指数退避）； + 400、404、405、409、413、415 立即失败。 + +重发不会重复计时，服务端按 `request_id` 幂等。 + +### 2.3 任务类型 + +| 任务 | 触发 | 动作序列 | 虚拟成本 | +| --- | --- | --- | --- | +| 覆盖扫描 | 某频道尚未被任何站点覆盖 | 移动到覆盖点 → `/measure` | 距离/5 + 5 s（+ 换频 1 s） | +| 定位交会 | 某频道收到 `direction` | 移动到第二检测点 → `/measure` | 距离/5 + 5 s（+ 1 s） | +| 清除 | 同频道候选区域 ρ ≤ 20 m | 移动到 MEC 圆心附近 → `/clear` | 距离/5 + 5 s 或 3 s | +| 后备盲清（问题四） | 联合信念坍缩到有限格 | 依次到可疑格 `/clear` | 距离/5 + 3 s 或 5 s | +| 机会测量 | 已停靠且该频道待测 | 原地 `/measure` | 5 s | + +任务表排序是开放路径问题，默认用滚动 2-opt 与 Or-opt； +精确 Held-Karp 与路线感知探点在本模拟器上为负收益，默认关闭，见 +[`第三四问图论与动态规划优化方案.md`](第三四问图论与动态规划优化方案.md) §8.6。 + +--- + +## 3. 附件计时示例逐步推演（105 / 111 / 194 / 199） + +| 步 | 指令 | 移动 | 换频 | 动作 | 本步 | 累计 | +| --- | --- | --- | --- | --- | --- | --- | +| 1 | `/enter` | 0 | 0 | 0 | 0 | 0 | +| 2 | `/measure (300,400) ch1` | 500 m → 100 s | 0（初始即 1） | 5 | 105 | 105 | +| 3 | `/measure (300,400) ch2` | 0 | 1 | 5 | 6 | 111 | +| 4 | `/clear (300,0) ch3` | 400 m → 80 s | 0 | 3（未发现） | 83 | 194 | +| 5 | `/measure (300,0) ch2` | 0 | 0（第 3 步后已是 2） | 5 | 5 | 199 | +| 6 | `/exit` | 0 | 0 | 0 | 0 | 199 | + +![附件计时示例逐步推演](figures/timing-attachment-example-105-111-194-199.png) + +验证方式： + +```bash +uv run mcm26b sim-check # 客户端 → 本地模拟器链路，输出 [105, 111, 194, 199] +uv run pytest tests/test_protocol_timing.py -q # 逐步断言移动、换频、动作三个分项 +``` + +--- + +## 4. 实测时序分解 + +对评测机留档的每一局，`scripts/make_figures.py` 按与 `referee.simulator` +同源的规则逐动作复算，并检查分项之和是否等于响应中的 `virtual_time_s`。 + +### 4.1 问题三演练局 `BBM9-HZG2-77N5-NKKC`（10 源全清） + +| 项 | 数值 | 占比 | +| --- | ---: | ---: | +| 总虚拟时间 | 3134.643 s | 100% | +| 移动（里程 11.9 km） | 2379.6 s | 75.9% | +| 检测与清除动作（119 + 10 次） | 645.0 s | 20.6% | +| 换频（110 次） | 110.0 s | 3.5% | +| 现实耗时 | 1.889 s | — | + +### 4.2 问题四演练局 `GM56-DFXZ-XKDM-XYV7`（12 源，含 3 个定向源） + +| 项 | 数值 | 占比 | +| --- | ---: | ---: | +| 总虚拟时间 | 8703.766 s | 100% | +| 移动（里程 32.4 km） | 6489.8 s | 74.6% | +| 检测与清除动作（338 + 79 次） | 1951.0 s | 22.4% | +| 换频（263 次） | 263.0 s | 3.0% | +| 现实耗时 | 3.397 s | — | + +![实测执行时序分解](figures/timing-measured-q3-10-sources.png) + +### 4.3 结论 + +1. 移动占约 75%，优化重点是路径长度，这解释了七点计划（7 点、6.96 km 巡回） + 优于 49 点网格的原因； +2. 动作占约 21%，检测 5 s 是下限，因此找全后立即退出比复扫更省时间； +3. 现实耗时与成绩无关，本地回环为毫秒级，官方口径取虚拟时间， + 程序预算（1200 s）只用于限制计算耗时。 + +### 4.4 复现命令 + +```bash +# 用评测机留档重画（含真值） +uv run python scripts/make_figures.py --only timing-measured-q3-10-sources,\ + replay-webui-q3-omnidirectional,replay-webui-q4-directional + +# 归档新日志，评测机数据被清理后仍可复现插图 +uv run python scripts/archive_replay_logs.py --list +uv run python scripts/archive_replay_logs.py BBM9-HZG2-77N5-NKKC + +# 按官方口径逐微秒复算（接受客户端 JSONL 或评测机 log.jsonl） +uv run python scripts/analyze_run_timing.py referee-data/sessions/BBM9-HZG2-77N5-NKKC/log.jsonl +uv run python scripts/analyze_run_timing.py examples/replay/*.jsonl --json /tmp/timing.json +uv run python scripts/verify_q3_practice.py output/q3/practice/<本局目录> +``` + +--- + +## 5. 时间预算与安全阀 + +| 约束 | 值 | 来源 | 客户端行为 | +| --- | --- | --- | --- | +| 移动速度 | 5 m/s | 题面 | 路径长度决定虚拟时间 | +| 检测 / 换频 | 5 s / 1 s | 题面 | 避免高频扫频 | +| 清除成功 / 未发现 | 5 s / 3 s | 题面 | 盲清代价可控 | +| 测试窗口 | 1500 s（现实） | 题面 | 窗口到期接口关闭 | +| 程序预算 | 1200 s（现实） | 题面 | `/enter` 后本地时钟起算 | +| 退出预留 | 60 s | 工程 | 剩余不足时只允许 `/exit` | +| 虚拟世界限时 | 360000 s | 题面 | 实测最坏为 1e4 量级，未触及 | +| 行为日志上限 | 2 MB | 题面 | 控制请求数 | + +安全阀见 [`algo-3.md`](algo-3.md) §7.2 与 [`algo-4.md`](algo-4.md) §5.2： +预算将尽、连续无新发现或联合信念长时间不收敛时，转入最低成本收尾， +先清除并登记已有发现，再 `/exit`，并写入 `stop_reason`。 diff --git a/examples/replay/BBM9-HZG2-77N5-NKKC.q3_practice.jsonl b/examples/replay/BBM9-HZG2-77N5-NKKC.q3_practice.jsonl new file mode 100644 index 0000000..fd349e4 --- /dev/null +++ b/examples/replay/BBM9-HZG2-77N5-NKKC.q3_practice.jsonl @@ -0,0 +1,133 @@ 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"exit_reason": "user_exit"}} +{"event": "session_end", "reason": "user_exit", "virtual_time_s": 8868.39161, "real_elapsed_s": 13.428012, "request_count": 398, "cleared_count": 11} diff --git a/referee-data/sessions/RS35-JWSZ-7PJR-48ME/meta.json b/referee-data/sessions/RS35-JWSZ-7PJR-48ME/meta.json new file mode 100644 index 0000000..d089e00 --- /dev/null +++ b/referee-data/sessions/RS35-JWSZ-7PJR-48ME/meta.json @@ -0,0 +1,96 @@ +{ + "case_code": "RS35-JWSZ-7PJR-48ME", + "module": "q4_formal", + "robot_id": "1", + "seed": 524636976, + "truth": [ + { + "channel": 19, + "x": -206.10766492851073, + "y": 1160.8055169225704, + "r_eff_m": 1028.289877243241, + "directional": true, + "heading_deg": 288.58862711279323 + }, + { + "channel": 14, + "x": 755.2806278559268, + "y": 250.29082865203878, + "r_eff_m": 1020.46483315481, + "directional": true, + "heading_deg": 291.8630536595404 + }, + { + "channel": 18, + "x": 966.1057750947382, + "y": -528.7766243925598, + "r_eff_m": 1431.3029992563347, + "directional": true, + "heading_deg": 152.43896706878402 + }, + { + "channel": 9, + "x": 263.1408255158642, + "y": 857.6002010138432, + "r_eff_m": 1124.292095106724, + "directional": false, + "heading_deg": 0.0 + }, + { + "channel": 13, + "x": -87.51220801888897, + "y": -1032.2242344411166, + "r_eff_m": 1128.989839175949, + "directional": false, + "heading_deg": 0.0 + }, + { + "channel": 15, + "x": 319.83243385729406, + "y": 113.48421543474046, + "r_eff_m": 1024.2663476707392, + "directional": false, + "heading_deg": 0.0 + }, + { + "channel": 7, + "x": -1171.4978647108244, + "y": -1073.4538615834038, + "r_eff_m": 1247.2912686345992, + "directional": false, + "heading_deg": 0.0 + }, + { + "channel": 6, + "x": 659.9240002207289, + "y": 156.96230063594635, + "r_eff_m": 1090.6727395531848, + "directional": false, + "heading_deg": 0.0 + }, + { + "channel": 20, + "x": -726.0390048597063, + "y": 836.3218839802242, + "r_eff_m": 1274.2222659503636, + "directional": false, + "heading_deg": 0.0 + }, + { + "channel": 12, + "x": -1706.9890741103702, + "y": 282.3965606193818, + "r_eff_m": 1071.3644107996988, + "directional": false, + "heading_deg": 0.0 + }, + { + "channel": 2, + "x": 1188.125441370153, + "y": -193.71523353215824, + "r_eff_m": 1092.5104751409474, + "directional": false, + "heading_deg": 0.0 + } + ] +} \ No newline at end of file diff --git a/scripts/archive_replay_logs.py b/scripts/archive_replay_logs.py new file mode 100644 index 0000000..816e8bb --- /dev/null +++ b/scripts/archive_replay_logs.py @@ -0,0 +1,92 @@ +"""把评测机一局的日志归档到 ``examples/replay/``，供无 referee-data 时复现插图。 + +``referee-data/`` 与 ``output/`` 都在 .gitignore 里：本机清掉评测机数据后， +``docs/figures/*.png`` 就无法复现。本脚本把"作图用到的那几局"抽出来， +命名成 ``..jsonl`` 存进 ``examples/replay/``（入库、几万行以内）， +``scripts/make_figures.py`` 在没有评测机数据时自动改读这里。 + + uv run python scripts/archive_replay_logs.py # 归档作图默认选中的两局 + uv run python scripts/archive_replay_logs.py BBM9-HZG2-77N5-NKKC # 指定案例 + uv run python scripts/archive_replay_logs.py --list # 只看有哪些局 + +归档是**内容等价**的：只做 JSON 重新格式化（逐行 compact 输出），不改字段， +并在文件头写入一条 ``session_start``（评测机日志本就自带），保持解析兼容。 +""" + +from __future__ import annotations + +import argparse +import json +import sys +from pathlib import Path + +ROOT = Path(__file__).resolve().parents[1] +SESSIONS_DIR = ROOT / 'referee-data' / 'sessions' +ARCHIVE_DIR = ROOT / 'examples' / 'replay' + +sys.path.insert(0, str(Path(__file__).resolve().parent)) + +from make_figures import discover_runs, pick_run # noqa: E402 + + +def archive(run: dict, out_dir: Path) -> Path: + """把一局日志写成归档 JSONL：逐行原样紧凑输出（字段不变，只重新格式化）。""" + out_dir.mkdir(parents=True, exist_ok=True) + target = out_dir / f"{run['case_code']}.{run['module']}.jsonl" + lines: list[str] = [] + for line in run["source"].read_text(encoding='utf-8').splitlines(): + line = line.strip() + if not line: + continue + try: + doc = json.loads(line) + except json.JSONDecodeError: + continue + lines.append(json.dumps(doc, ensure_ascii=False, separators=(',', ':'))) + target.write_text('\n'.join(lines) + '\n', encoding='utf-8') + return target + + +def main() -> int: + parser = argparse.ArgumentParser(description=__doc__.splitlines()[0]) + parser.add_argument('cases', nargs='*', help='案例编码；缺省=作图默认选中的那几局') + parser.add_argument('--list', action='store_true', help='列出可选案例后退出') + parser.add_argument('--out', default=str(ARCHIVE_DIR)) + args = parser.parse_args() + + runs = discover_runs() + if not runs: + print('没有找到可归档的日志：referee-data/sessions/*/log.jsonl 与 ' + 'examples/replay/*.jsonl 都为空。') + return 1 + if args.list: + for run in runs: + clears = sum(1 for a in run["actions"] if a["path"] == "/clear") + print(f"{run['case_code']} {run['module']:<12} 真值 {len(run['truth']):2d} " + f"动作 {len(run['actions']):4d} 清除 {clears:3d}") + return 0 + + picked = [] + if args.cases: + wanted = set(args.cases) + picked = [r for r in runs if r["case_code"] in wanted] + missing = wanted - {r["case_code"] for r in picked} + if missing: + print(f'未找到案例：{sorted(missing)}') + return 1 + else: + for module, truth in (('q3', 10), ('q4', 12)): + run = pick_run(runs, module=module, truth=truth) + if run and run not in picked: + picked.append(run) + + for run in picked: + path = archive(run, Path(args.out)) + print(f"[archive] {run['case_code']:<20} {run['module']:<12} " + f"真值 {len(run['truth']):2d} 动作 {len(run['actions']):4d} → " + f"{path.relative_to(ROOT)}") + return 0 + + +if __name__ == '__main__': + raise SystemExit(main()) diff --git a/scripts/make_figures.py b/scripts/make_figures.py new file mode 100644 index 0000000..dba1c9b --- /dev/null +++ b/scripts/make_figures.py @@ -0,0 +1,1182 @@ +"""docs/figures 的论文插图生成器（matplotlib 版）。 + + uv run python scripts/make_figures.py # 全部 11 张 + uv run python scripts/make_figures.py --list # 图名 + uv run python scripts/make_figures.py --only flow-overall-architecture + uv run python scripts/make_figures.py --scale 1.5 # 尺寸倍率 + +约定（与 docs/figures/README.md 对应）： + +- **只输出 PNG**（不生成 SVG），分辨率按论文插图设置； +- **图内不放标题、图注与解释性文字**，只保留坐标轴、图例与数据标注； + 图的含义由文件名与 README 清单承担，解释写在论文正文； +- 字体取自 ``docs/paper/fonts/``（宋体 / 黑体 / Times New Roman），与 main.tex 一致； +- 数据来源与 sha256 写入 ``docs/figures/manifest.json``。 +""" + +from __future__ import annotations + +import argparse +import hashlib +import json +import math +import os +import sys +from pathlib import Path +from typing import Any, Callable, Iterable, Sequence + +ROOT = Path(__file__).resolve().parents[1] +FONT_DIR = ROOT / "docs" / "paper" / "fonts" +OUT_DIR = ROOT / "docs" / "figures" +SESSIONS_DIR = ROOT / "referee-data" / "sessions" +ARCHIVE_DIR = ROOT / "examples" / "replay" +CACHE_DIR = ROOT / ".mpl-cache" + +# matplotlib 的缓存目录：仓库内可写，避免污染用户目录 +CACHE_DIR.mkdir(exist_ok=True) +os.environ.setdefault("MPLCONFIGDIR", str(CACHE_DIR)) +os.environ.setdefault("XDG_CACHE_HOME", str(CACHE_DIR)) + +import matplotlib # noqa: E402 +matplotlib.use("Agg") +import numpy as np # noqa: E402 +from matplotlib import font_manager as fm # noqa: E402 +from matplotlib import pyplot as plt # noqa: E402 +from matplotlib.lines import Line2D # noqa: E402 +from matplotlib.patches import Circle, FancyArrowPatch, FancyBboxPatch, Polygon # noqa: E402 + +sys.path.insert(0, str(Path(__file__).resolve().parent)) + +# 题面常量（与 src/mcm26b/config.py 一致） +OMEGA_R = 1800.0 +R_EFF = 1000.0 +SPEED_MPS = 5.0 +MEASURE_S = 5.0 +SWITCH_S = 1.0 +CLEAR_OK_S = 5.0 +CLEAR_NO_S = 3.0 +RING_RADIUS_M = 1159.7 +SEVEN_R = 1800.0 +Q4_DESIGN_R = 965.0 +Q4_HEADING_MARGIN_DEG = 5.0 + +# 论文配色：低饱和，单色打印可辨 +C = { + "ink": "#1c2430", + "muted": "#5c6673", + "grid": "#e4e9ee", + "primary": "#1f4e79", + "primary_fill": "#dce6f1", + "accent": "#b03a2e", + "accent_fill": "#f6dcd8", + "success": "#1e7a5f", + "success_fill": "#d8ece5", + "warn": "#b8860b", + "warn_fill": "#f6ecd2", + "violet": "#5b4b8a", +} + +FONTS = { + "song": "SongtiSC-Regular.ttf", + "song_bold": "SongtiSC-Bold.ttf", + "hei": "HeitiSC-Light.ttf", + "hei_bold": "HeitiSC-Medium.ttf", + "times": "Times New Roman.ttf", + "times_bold": "Times New Roman Bold.ttf", +} + + +# --------------------------------------------------------------------------- +# 样式 +# --------------------------------------------------------------------------- +def setup_style() -> dict[str, Any]: + """注册自带字体并设全局样式，返回 FontProperties 字典。""" + for name in FONTS.values(): + path = FONT_DIR / name + if path.is_file(): + fm.fontManager.addfont(str(path)) + props = {key: fm.FontProperties(fname=str(FONT_DIR / name)) + for key, name in FONTS.items() if (FONT_DIR / name).is_file()} + plt.rcParams.update({ + "figure.dpi": 120, + "savefig.dpi": 200, + "font.family": [props["song"].get_name(), "DejaVu Sans"], + "font.size": 8.5, + "axes.titlesize": 9, + "axes.labelsize": 8.5, + "xtick.labelsize": 8, + "ytick.labelsize": 8, + "legend.fontsize": 8, + "axes.edgecolor": C["muted"], + "axes.labelcolor": C["ink"], + "text.color": C["ink"], + "xtick.color": C["muted"], + "ytick.color": C["muted"], + "axes.grid": False, + "axes.unicode_minus": False, + "lines.linewidth": 1.2, + }) + return props + + +def new_axes(width_mm: float, height_mm: float, *, ncols: int = 1, + nrows: int = 1, scale: float = 1.0, **kw: Any) -> tuple[Any, Any]: + """按毫米尺寸建图（论文按 160 mm 宽排版时用 1.0 倍）。""" + fig, axes = plt.subplots(nrows, ncols, + figsize=(width_mm / 25.4 * scale, height_mm / 25.4 * scale), + layout="constrained", **kw) + return fig, axes + + +def axes_for_panels(panel_mm: float, aspects: Sequence[float], *, scale: float = 1.0, + width_ratios: Sequence[float] | None = None, + extra_mm: float = 30.0, **kw: Any) -> tuple[Any, Any]: + """按"每个面板高 panel_mm、宽 = 高 × 宽高比"手工排版。 + + 等比例坐标轴（``set_aspect('equal')``）在自动布局（constrained/tight）下会被 + 挤成一小块，因此这里直接按数据比例分配位置：每个子图的方框宽高比等于 + 数据宽高比，等比例坐标轴正好铺满方框。 + """ + del kw + ratios = list(width_ratios) if width_ratios else [1.0] * len(aspects) + widths = [panel_mm * aspect * ratio for aspect, ratio in zip(aspects, ratios)] + left_mm, right_mm, top_mm = 16.0, 6.0, 6.0 + gap_mm, bottom_mm = 16.0, 15.0 + total_w = left_mm + sum(widths) + gap_mm * (len(widths) - 1) + right_mm + total_h = top_mm + panel_mm + bottom_mm + fig = plt.figure(figsize=(total_w / 25.4 * scale, total_h / 25.4 * scale)) + + def frac_x(mm: float) -> float: + return mm / total_w + + def frac_y(mm: float) -> float: + return mm / total_h + + axes = [] + cursor = left_mm + for width in widths: + box = [frac_x(cursor), frac_y(bottom_mm), frac_x(width), frac_y(panel_mm)] + axes.append(fig.add_axes(box)) + cursor += width + gap_mm + return fig, (axes if len(axes) > 1 else axes[0]) + + +def polar_axes(ax: Any, half: float, *, grid: float = 500.0, + center: Sequence[float] = (0.0, 0.0)) -> None: + """世界坐标视图：等比例、留白、细网格；``center`` 为视图中心。""" + cx, cy = float(center[0]), float(center[1]) + step = grid + ticks = [] + while step <= half * 1.2: + ticks += [-step, step] + step *= 2 + ticks = sorted({round(cx + t) for t in ticks if abs(t) <= half * 1.05} | + {round(cy + t) for t in ticks if abs(t) <= half * 1.05}) + # 顺序要紧：set_xticks 会在数据范围内重新 autoscale，必须最后再钉住范围 + ax.set_xticks(ticks) + ax.set_yticks(ticks) + ax.set_xlim(cx - half, cx + half) + ax.set_ylim(cy - half, cy + half) + # 面板方框由 axes_for_panels 按数据宽高比分配，刻度范围也是 1:1， + # 不需要再让 matplotlib 调 aspect（它会反过来改写已设定的范围） + ax.set_aspect("auto") + ax.grid(True, color=C["grid"], lw=0.6) + for side in ("top", "right"): + ax.spines[side].set_visible(False) + ax.set_axisbelow(True) + + +def save(fig: Any, stem: str, sources: Sequence[dict[str, Any]], scale: float) -> dict[str, Any]: + """落盘 PNG（仅 PNG：论文插图不再维护矢量版），返回 manifest 条目。""" + OUT_DIR.mkdir(parents=True, exist_ok=True) + png = OUT_DIR / f"{stem}.png" + fig.savefig(png, format="png") + plt.close(fig) + return {"stem": stem, "png": str(png.relative_to(ROOT)), "scale": scale, + "sources": list(sources)} + + +def source(path: str | Path, **extra: Any) -> dict[str, Any]: + """记录数据来源：仓库内相对路径、sha256 前 12 位、行数。""" + p = Path(path) + p = p if p.is_absolute() else ROOT / p + digest, lines = "-", 0 + if p.is_file(): + data = p.read_bytes() + digest = hashlib.sha256(data).hexdigest()[:12] + lines = data.count(b"\n") + (0 if data.endswith(b"\n") else 1) + rel = str(p.relative_to(ROOT)) if p.is_relative_to(ROOT) else str(p) + return {"path": rel, "sha256_12": digest, "lines": lines, **extra} + + +# --------------------------------------------------------------------------- +# 行为日志：解析、计时复算、归档回退 +# --------------------------------------------------------------------------- +def parse_jsonl(path: Path) -> dict[str, Any]: + """兼容评测机 ``event=action`` 与客户端 ``event=accepted`` 两种日志。""" + meta: dict[str, Any] = {} + actions: list[dict[str, Any]] = [] + fallback: dict[str, dict[str, Any]] = {} + seq = 0 + for line in path.read_text(encoding="utf-8").splitlines(): + line = line.strip() + if not line: + continue + try: + ev = json.loads(line) + except json.JSONDecodeError: + continue + kind = ev.get("event") + if kind == "session_start": + meta = ev + elif kind == "action": + seq += 1 + actions.append(dict(seq=ev.get("seq", seq), path=ev.get("path", ""), + request=ev.get("request") or {}, + response=ev.get("response") or {}, + wall_ts_ms=ev.get("wall_ts_ms"))) + elif kind == "accepted": + fallback[str(ev.get("request_id", ""))] = ev + elif kind == "step" and str(ev.get("request_id", "")) not in fallback: + fallback[str(ev.get("request_id", ""))] = ev + if not actions: + for ev in fallback.values(): + if not ev.get("path"): + continue + seq += 1 + stamp = ev.get("logged_at_unix_s") + actions.append(dict(seq=seq, path=ev["path"], request=ev.get("request") or {}, + response=ev.get("response") or {}, + wall_ts_ms=stamp * 1000 if stamp else None)) + if not actions: + raise ValueError(f"{path} 没有可回放的动作事件") + return dict(label=path.stem, case_code=meta.get("case_code") or path.parent.name, + module=meta.get("module") or "?", robot_id=str(meta.get("robot_id") or "?"), + truth=list(meta.get("truth") or []), actions=actions, source=path) + + +def discover_runs() -> list[dict[str, Any]]: + runs: list[dict[str, Any]] = [] + if SESSIONS_DIR.is_dir(): + for log in sorted(SESSIONS_DIR.glob("*/log.jsonl")): + try: + runs.append(parse_jsonl(log)) + except ValueError: + continue + if not runs and ARCHIVE_DIR.is_dir(): + for log in sorted(ARCHIVE_DIR.glob("*.jsonl")): + try: + runs.append(parse_jsonl(log)) + except ValueError: + continue + return runs + + +def pick_run(runs: Sequence[dict[str, Any]], module: str, truth: int) -> dict[str, Any]: + cands = [r for r in runs if r["module"].startswith(module) and len(r["truth"]) >= truth + and sum(1 for a in r["actions"] if a["path"] == "/measure") > 0] + if not cands: + cands = [r for r in runs if r["module"].startswith(module)] + return sorted(cands, key=lambda r: (abs(len(r["truth"]) - truth), len(r["actions"])))[0] + + +def decompose(run: dict[str, Any]) -> dict[str, Any]: + """按附件规则逐动作复算移动 / 换频 / 动作耗时。""" + pos = (0.0, 0.0) + channel: int | None = None + rows: list[dict[str, Any]] = [] + for act in run["actions"]: + req, res = act["request"], act["response"] + move_m = switch = action_s = 0.0 + if act["path"] in ("/measure", "/clear") and "position" in req: + tgt = (float(req["position"]["x"]), float(req["position"]["y"])) + move_m = math.dist(pos, tgt) + if move_m > 0: + pos = tgt + if act["path"] == "/measure": + ch = int(req.get("channel", 0)) + switch = 0.0 if channel in (None, ch) else SWITCH_S + channel = ch + action_s = MEASURE_S + elif act["path"] == "/clear": + action_s = CLEAR_OK_S if str(res.get("clear_result")) == "success" else CLEAR_NO_S + rows.append(dict(seq=act["seq"], path=act["path"], move_s=move_m / SPEED_MPS, + switch_s=switch, action_s=action_s, move_m=move_m, + virtual_s=float(res.get("virtual_time_s") or 0.0), + hit=str(res.get("measure_result")) == "direction", + cleared=str(res.get("clear_result")) == "success", + channel=req.get("channel"), + x=req.get("position", {}).get("x"), + y=req.get("position", {}).get("y"))) + wall = [r for r in run["actions"] if r.get("wall_ts_ms")] + real_s = (wall[-1]["wall_ts_ms"] - wall[0]["wall_ts_ms"]) / 1000.0 if len(wall) > 1 else 0.0 + return dict(rows=rows, virtual_s=float(run["actions"][-1]["response"].get("virtual_time_s") or 0), + real_s=real_s, + move_s=sum(r["move_s"] for r in rows), + switch_s=sum(r["switch_s"] for r in rows), + action_s=sum(r["action_s"] for r in rows), + move_m=sum(r["move_m"] for r in rows)) + + +def solved_channels(run: dict[str, Any]) -> list[int]: + return sorted({int(a["request"]["channel"]) for a in run["actions"] + if a["path"] == "/clear" and "channel" in a["request"] + and str(a["response"].get("clear_result")) == "success"}) + + +# --------------------------------------------------------------------------- +# 几何工具 +# --------------------------------------------------------------------------- +def clip_halfplane(poly: np.ndarray, a: float, b: float, c: float) -> np.ndarray: + """Sutherland–Hodgman：半平面 a·x + b·y <= c 裁剪凸多边形。""" + if len(poly) == 0: + return poly + out: list[list[float]] = [] + n = len(poly) + for i in range(n): + cur, nxt = poly[i], poly[(i + 1) % n] + dc = a * cur[0] + b * cur[1] - c + dn = a * nxt[0] + b * nxt[1] - c + if dc <= 1e-9: + out.append(list(cur)) + if dn > 1e-9: + t = dc / (dc - dn) + out.append([cur[0] + t * (nxt[0] - cur[0]), cur[1] + t * (nxt[1] - cur[1])]) + elif dn <= 1e-9: + t = dc / (dc - dn) + out.append([cur[0] + t * (nxt[0] - cur[0]), cur[1] + t * (nxt[1] - cur[1])]) + return np.array(out) if out else np.empty((0, 2)) + + +def wedge_polygon(station: Sequence[float], bearing: float, half_deg: float, + reach: float) -> np.ndarray: + a0, a1 = math.radians(bearing - half_deg), math.radians(bearing + half_deg) + ang = np.linspace(a0, a1, 16) + pts = [[station[0], station[1]]] + \ + [[station[0] + reach * math.cos(t), station[1] + reach * math.sin(t)] for t in ang] + return np.array(pts) + + +def clip_convex(region: np.ndarray, a: float, b: float, c: float) -> np.ndarray: + """半平面 a·x + b·y <= c 裁剪（对 numpy 数组的薄封装）。""" + return clip_halfplane(np.asarray(region, dtype=float), a, b, c) + + +def clip_wedge(region: np.ndarray, station: Sequence[float], bearing: float, + half_deg: float) -> np.ndarray: + """用角域 W(s, θ ± δ) 裁剪区域。 + + 角域是两条边界射线的半平面交。示向度可能跨越 0/360 度，法向的正负不能靠叉积 + 猜：两个半平面各试一次，用"结果中心与站点的连线是否落在示向度 ±δ 内"来判定 + 哪一侧是角域内部。 + """ + region = np.asarray(region, dtype=float) + if len(region) == 0: + return region + for edge in (bearing - half_deg, bearing + half_deg): + ang = math.radians(edge) + a, b = -math.sin(ang), math.cos(ang) + c = a * station[0] + b * station[1] + candidates = [cand for cand in (clip_convex(region, a, b, c), + clip_convex(region, -a, -b, -c)) + if len(cand) >= 3] + if not candidates: + return np.empty((0, 2)) + if len(candidates) == 1: + region = candidates[0] + continue + region = min(candidates, key=lambda cand: _direction_error(cand, station, + bearing, half_deg)) + return region + + +def _direction_error(poly: np.ndarray, station: Sequence[float], bearing: float, + half_deg: float) -> float: + """多边形中心方向与示向度的偏差；用于挑正确的半平面一侧。""" + centre = poly.mean(axis=0) + dx, dy = centre[0] - station[0], centre[1] - station[1] + if abs(dx) < 1e-12 and abs(dy) < 1e-12: + return 0.0 + return abs(angle_diff(math.degrees(math.atan2(dy, dx)), bearing)) + + +def polygon_area(poly: np.ndarray) -> float: + if len(poly) < 3: + return 0.0 + x, y = poly[:, 0], poly[:, 1] + return 0.5 * abs(float(np.dot(x, np.roll(y, -1)) - np.dot(y, np.roll(x, -1)))) + + +def angle_diff(a: float, b: float) -> float: + return (a - b + 180.0) % 360.0 - 180.0 + + +def wedge_clip(station: Sequence[float], bearing: float, half_deg: float, + box: Sequence[float]) -> np.ndarray: + """角域与视窗矩形的交集，用于局部放大图。""" + x0, y0, x1, y1 = box + poly = np.array([[x0, y0], [x1, y0], [x1, y1], [x0, y1]], dtype=float) + return clip_wedge(poly, station, bearing, half_deg) + + +def q1_solve(stations: Sequence[Sequence[float]]) -> dict[str, Any]: + """调用生产求解器，避免图中数字与代码不一致。""" + sys.path.insert(0, str(ROOT / "src")) + from mcm26b import Measurement, solve # noqa: PLC0415 + res = solve([Measurement(x, y, b, h) for x, y, b, h in stations]) + dc, mec = res["diameter_circle"], res["minimum_enclosing_circle"] + return dict(vertices=np.array(res["vertices"]), pair=res["diameter_pair"], + dc=dc, mec=mec) + + +def q1_practice_case() -> dict[str, Any] | None: + for path in sorted((ROOT / "output" / "q1" / "practice").glob("*_observations.json")): + doc = json.loads(path.read_text(encoding="utf-8")) + if doc.get("result"): + doc["_path"] = path + return doc + return None + + +def load_plan(name: str) -> dict[str, Any]: + path = ROOT / "src" / "mcm26b" / "guarantee" / "plans" / f"{name}.json" + return json.loads(path.read_text(encoding="utf-8")) + + +def seven_bound(a: float = RING_RADIUS_M, radius: float = SEVEN_R) -> float: + return max(a / math.sqrt(3), math.sqrt(radius ** 2 + a ** 2 - math.sqrt(3) * radius * a)) + + +# --------------------------------------------------------------------------- +# 排版小工具 +# --------------------------------------------------------------------------- +def draw_boxes(ax: Any, boxes: Sequence[dict[str, Any]], font: Any) -> None: + """画一组统一风格的圆角框（流程示意图用）。""" + for b in boxes: + ax.add_patch(FancyBboxPatch((b["x"], b["y"]), b["w"], b["h"], + boxstyle="round,pad=0.02,rounding_size=0.6", + linewidth=1.0, edgecolor=b.get("edge", C["primary"]), + facecolor=b.get("face", C["primary_fill"]), + zorder=2)) + ax.text(b["x"] + b["w"] / 2, b["y"] + b["h"] / 2, b["label"], + ha="center", va="center", fontproperties=b.get("font", font["hei_bold"]), + fontsize=b.get("size", 8.2), color=b.get("color", C["ink"]), + linespacing=1.5, zorder=3) + + +def connect(ax: Any, p0: Sequence[float], p1: Sequence[float], *, + color: str | None = None, style: str = "-", lw: float = 1.0, + rad: float = 0.0) -> None: + ax.add_patch(FancyArrowPatch(p0, p1, arrowstyle="-|>", mutation_scale=9, + linewidth=lw, color=color or C["muted"], + linestyle=style, zorder=4, + connectionstyle=f"arc3,rad={rad}")) + + +def chips(ax: Any, items: Sequence[tuple[str, str]], *, x: float = 0.02, y: float = 0.02, + dy: float = 0.06, font: Any = None) -> None: + """左下角竖排色块图例（坐标用 axes 分数）。""" + for i, (label, color) in enumerate(items): + yy = y + i * dy + ax.add_patch(FancyBboxPatch((x, yy - 0.012), 0.018, 0.024, + boxstyle="round,pad=0.002,rounding_size=0.004", + transform=ax.transAxes, facecolor=color, + edgecolor="none", zorder=5, clip_on=False)) + ax.text(x + 0.026, yy, label, transform=ax.transAxes, va="center", ha="left", + fontproperties=font, fontsize=7.6, color=C["ink"], zorder=5) + + +# =========================================================================== +# 1. 总体思路与算法主线 +# =========================================================================== +def fig_flow_overall(font: dict[str, Any]) -> Any: + fig, ax = new_axes(170, 96) + ax.set_xlim(0, 120) + ax.set_ylim(0, 56) + ax.axis("off") + + def band(tag: str, y: float, items: Sequence[tuple[str, float, float]], + face: str, color: str) -> None: + ax.text(3.0, y + 3.0, tag, ha="center", va="center", + fontproperties=font["hei_bold"], fontsize=8.6, color=color) + for label, x, width in items: + draw_boxes(ax, [dict(x=x, y=y, w=width, h=6.0, label=label, face=face, + edge=color, font=font["song"], size=7.8)], font) + ax.plot([8.0, 116.0], [y - 1.6, y - 1.6], color=C["grid"], lw=0.8, zorder=1) + + band("L0", 46.0, [ + ("区域 Ω：半径 1800 m", 9.0, 26.5), + ("移动 5 m/s · 检测 5 s", 36.0, 26.5), + ("换频 1 s · 清除 5/3 s", 63.0, 26.5), + ("源 10~16 个 · 频道 1~20", 90.0, 25.5)], C["primary_fill"], C["primary"]) + + band("L1", 33.0, [ + ("证据层：候选集与粒子幸存集", 9.0, 33.0), + ("决策层：选点与任务表", 44.0, 33.0), + ("执行层：串行客户端", 79.0, 33.0)], C["primary_fill"], C["primary"]) + for x in (42.6, 77.6): + connect(ax, (x, 36.0), (x + 1.4, 36.0), color=C["ink"]) + + band("L2", 20.0, [ + ("问题 1 定位解算", 9.0, 25.5), + ("问题 2 第二点选择", 35.5, 25.5), + ("问题 3 全向搜索", 62.0, 25.5), + ("问题 4 混合定向", 88.5, 27.0)], C["accent_fill"], C["accent"]) + + band("L3", 7.0, [ + ("发现闭环", 9.0, 33.0), + ("定位闭环", 44.0, 33.0), + ("清除闭环", 79.0, 33.0)], C["success_fill"], C["success"]) + return fig + + +# =========================================================================== +# 2. 执行步骤：会话状态机 +# =========================================================================== +def fig_steps_state_machine(font: dict[str, Any]) -> Any: + fig, ax = new_axes(160, 34) + ax.set_xlim(0, 100) + ax.set_ylim(0, 22) + ax.axis("off") + states = [("IDLE", 3, C["grid"], C["muted"]), + ("倒计时 5 s", 26, C["warn_fill"], C["warn"]), + ("OPEN 接口开放", 49, C["success_fill"], C["success"]), + ("CLOSED 断连", 72, C["accent_fill"], C["accent"])] + for label, x, face, edge in states: + draw_boxes(ax, [dict(x=x, y=9, w=22, h=6.5, label=label, face=face, edge=edge, + font=font["hei_bold"], size=8.4)], font) + for i in range(3): + connect(ax, (25 + i * 23 + 0.3, 12.2), (26 + i * 23 - 0.5, 12.2), color=C["ink"]) + ax.text(50, 6.2, "现实预算 1200 s（程序）与测试窗口 1500 s（服务端）独立计时", + ha="center", fontproperties=font["song"], fontsize=7.6, color=C["muted"]) + ax.text(83, 4.0, "剩余不足 60 s 时预留 /exit", ha="center", + fontproperties=font["song"], fontsize=7.6, color=C["accent"]) + return fig + + +# =========================================================================== +# 3. 执行时间：附件示例逐步推演 +# =========================================================================== +EXAMPLE_STEPS = [ + ("/enter", 0.0, 0.0, 0.0), + ("/measure ch1", 100.0, 0.0, 5.0), + ("/measure ch2", 0.0, 1.0, 5.0), + ("/clear ch3", 80.0, 0.0, 3.0), + ("/measure ch2", 0.0, 0.0, 5.0), + ("/exit", 0.0, 0.0, 0.0), +] + + +def fig_timing_attachment(font: dict[str, Any]) -> Any: + fig, ax = new_axes(160, 46) + y = np.arange(len(EXAMPLE_STEPS))[::-1] + move = np.array([s[1] for s in EXAMPLE_STEPS]) + switch = np.array([s[2] for s in EXAMPLE_STEPS]) + action = np.array([s[3] for s in EXAMPLE_STEPS]) + ax.barh(y, move, color=C["primary"], height=0.6, label="移动 L/5") + ax.barh(y, switch, left=move, color=C["warn"], height=0.6, label="换频 1 s") + ax.barh(y, action, left=move + switch, color=C["success"], height=0.6, + label="检测/清除动作") + cumulative = np.cumsum(move + switch + action) + for i, (yy, total, acc) in enumerate(zip(y, move + switch + action, cumulative)): + if total > 0: + ax.text(move[i] + switch[i] + action[i] + 2, yy, f"{total:.0f} s", + va="center", fontproperties=font["times"], fontsize=7.6, color=C["ink"]) + ax.text(-4, yy, f"{acc:.0f}", va="center", ha="right", + fontproperties=font["times_bold"], fontsize=7.8, color=C["accent"]) + ax.set_yticks(y) + ax.set_yticklabels([s[0] for s in EXAMPLE_STEPS], fontproperties=font["times"], + fontsize=7.8) + ax.set_xlabel("虚拟耗时 / s", fontproperties=font["song"]) + ax.set_xlim(-14, 132) + ax.text(-4, len(EXAMPLE_STEPS) - 0.35, "累计", ha="right", va="center", + fontproperties=font["song"], fontsize=7.6, color=C["accent"]) + ax.legend(prop=font["song"], frameon=False, loc="lower right", ncols=3) + for side in ("top", "right"): + ax.spines[side].set_visible(False) + ax.grid(True, axis="x", color=C["grid"], lw=0.6) + ax.set_axisbelow(True) + return fig + + +# =========================================================================== +# 4. 执行时间：实测日志分解 +# =========================================================================== +def fig_timing_measured(run: dict[str, Any], font: dict[str, Any]) -> Any: + tl = decompose(run) + rows = tl["rows"] + seq = np.array([r["seq"] for r in rows]) + move = np.cumsum([r["move_s"] for r in rows]) + switch = np.cumsum([r["switch_s"] for r in rows]) + action = np.cumsum([r["action_s"] for r in rows]) + total = move + switch + action + parts = [tl["move_s"], tl["action_s"], tl["switch_s"]] + labels = ["移动", "检测/清除", "换频"] + colors = [C["primary"], C["success"], C["warn"]] + + fig, (ax, ax2) = new_axes(170, 54, ncols=2, width_ratios=[1.45, 1.0]) + ax.stackplot(seq, move, switch, action, colors=colors, + labels=["移动 L/5", "检测/清除动作", "换频 1 s"], lw=0) + ax.set_xlim(seq[0], seq[-1]) + ax.set_ylim(0, total[-1] * 1.08) + ax.set_xlabel("动作序号", fontproperties=font["song"]) + ax.set_ylabel("累计虚拟时间 / s", fontproperties=font["song"]) + ax.legend(prop=font["song"], frameon=False, loc="upper left") + for side in ("top", "right"): + ax.spines[side].set_visible(False) + ax.grid(True, axis="y", color=C["grid"], lw=0.6) + ax.set_axisbelow(True) + + # 右：构成条形 + 汇总（同一坐标下三段，末段极窄故编号标注） + ax2.set_xlim(0, 1) + ax2.set_ylim(0, 1) + ax2.axis("off") + bar_y, bar_h = 0.62, 0.14 + left = 0.0 + for i, (value, color) in enumerate(zip(parts, colors)): + frac = value / total[-1] + ax2.add_patch(FancyBboxPatch((left, bar_y), frac, bar_h, + boxstyle="round,pad=0,rounding_size=0.005", + facecolor=color, edgecolor="none")) + if frac > 0.06: + ax2.text(left + frac / 2, bar_y + bar_h / 2, f"{value:,.0f} s", ha="center", + va="center", fontproperties=font["song"], fontsize=7.4, + color="white") + left += frac + ax2.text(0.0, 0.84, f"虚拟 {total[-1]:,.1f} s", fontproperties=font["song"], + fontsize=7.8, color=C["ink"]) + ax2.text(0.5, 0.84, f"现实 {tl['real_s']:.2f} s", fontproperties=font["song"], + fontsize=7.8, color=C["ink"]) + ax2.text(1.0, 0.84, f"加速 {total[-1] / max(tl['real_s'], 1e-9):,.0f} 倍", ha="right", + fontproperties=font["song"], fontsize=7.8, color=C["accent"]) + for i, (value, label, color) in enumerate(zip(parts, labels, colors)): + ax2.add_patch(FancyBboxPatch((0.0 + i * 0.36, 0.40), 0.03, 0.05, + boxstyle="round,pad=0.002,rounding_size=0.01", + facecolor=color, edgecolor="none")) + ax2.text(0.05 + i * 0.36, 0.425, + f"{i + 1} {label} {value:,.0f} s", fontproperties=font["song"], + fontsize=7.4, va="center") + ax2.text(0.0, 0.24, f"检测 {sum(1 for r in rows if r['path'] == '/measure')} 次 · " + f"清除 {sum(1 for r in rows if r['path'] == '/clear')} 次 · " + f"里程 {tl['move_m'] / 1000:.1f} km", + fontproperties=font["song"], fontsize=7.4, color=C["muted"]) + return fig + + +# =========================================================================== +# 5. 问题一：交会定位区域 +# =========================================================================== +def _q1_data() -> dict[str, Any]: + case = q1_practice_case() + if case: + return dict(subtitle=f"官方演练 {case['case_code']}", + stations=[(m["x"], m["y"], m["bearing_deg"], m["half_angle_deg"]) + for m in case["measurements"]], + verts=np.array(case["result"]["vertices"]), + dc=case["result"]["diameter_circle"], + mec=case["result"]["minimum_enclosing_circle"], + src=case["_path"]) + doc = json.loads((ROOT / "examples" / "q1" / "triangle.json").read_text(encoding="utf-8")) + sol = q1_solve([(m["x"], m["y"], m["bearing_deg"], m.get("half_angle_deg", 1.0)) + for m in doc["measurements"]]) + return dict(subtitle="反例算例 triangle.json", + stations=[(m["x"], m["y"], m["bearing_deg"], m.get("half_angle_deg", 1.0)) + for m in doc["measurements"]], + verts=sol["vertices"], dc=sol["dc"], mec=sol["mec"], + src=ROOT / "examples" / "q1" / "triangle.json") + + +def fig_q1_meetup(font: dict[str, Any]) -> Any: + data = _q1_data() + stations = data["stations"] + xs = [s[0] for s in stations] + ys = [s[1] for s in stations] + cx, cy = (min(xs) + max(xs)) / 2, (min(ys) + max(ys)) / 2 + half = max(max(xs) - min(xs), max(ys) - min(ys)) / 2 * 1.35 + 60 + reach = 2.4 * half + mec_c = data["mec"]["center"] + mec_r = data["mec"]["radius_m"] + dc_c, dc_r = data["dc"]["center"], data["dc"]["radius_m"] + # 放大窗口取定位区域外接框的 1.8 倍，使多边形、直径圆、MEC 同框且尺寸可比 + verts = data["verts"] + zoom_c = (float(verts[:, 0].mean()), float(verts[:, 1].mean())) + span = float(np.abs(verts - np.array(zoom_c)).max()) + zoom = max(1.8 * span, 0.8 * mec_r + span, 12.0) + + fig, axes = axes_for_panels(62.0, [1.0, 1.0], width_ratios=[1.0, 1.0]) + ax, axz = axes + polar_axes(ax, half, grid=half / 2) + for sx, sy, bearing, hd in stations: + ax.add_patch(Polygon(wedge_polygon((sx, sy), bearing, hd, reach), closed=True, + facecolor=C["primary"], alpha=0.16, edgecolor="none")) + ax.plot([sx], [sy], marker="o", ms=4, color=C["primary"]) + ax.annotate(f"({sx:.0f}, {sy:.0f})", (sx, sy), textcoords="offset points", + xytext=(6, 4), fontproperties=font["times"], fontsize=7.2, + color=C["primary"]) + ax.add_patch(Polygon(data["verts"], closed=True, facecolor=C["accent"], + edgecolor=C["accent"], lw=1.0)) + ax.annotate("定位区域 P →", (float(data["verts"][:, 0].mean()), + float(data["verts"][:, 1].mean())), + textcoords="offset points", xytext=(14, -18), + fontproperties=font["song"], fontsize=7.6, color=C["accent"], + arrowprops=dict(arrowstyle="-", color=C["accent"], lw=0.9)) + ax.set_xlabel("x / m", fontproperties=font["song"]) + ax.set_ylabel("y / m", fontproperties=font["song"]) + + polar_axes(axz, zoom, grid=zoom / 2, center=zoom_c) + axz.set_xticks([]) + axz.set_yticks([]) + axz.set_ylabel("") + # 放大面板：角域按面板的坐标范围裁剪，范围与 xlim/ylim 一致 + xlim, ylim = axz.get_xlim(), axz.get_ylim() + box = (float(xlim[0]), float(ylim[0]), float(xlim[1]), float(ylim[1])) + for sx, sy, bearing, hd in stations: + poly = wedge_clip((sx, sy), bearing, hd, box) + if len(poly): + axz.add_patch(Polygon(poly, closed=True, facecolor=C["primary"], + alpha=0.28, edgecolor="none")) + region = np.array([[box[0], box[1]], [box[2], box[1]], + [box[2], box[3]], [box[0], box[3]]], dtype=float) + for sx, sy, bearing, hd in stations: + region = clip_wedge(region, (sx, sy), bearing, hd) + if len(region) >= 3: + axz.add_patch(Polygon(region, closed=True, facecolor=C["accent_fill"], + edgecolor=C["accent"], lw=1.6)) + axz.add_patch(Polygon(data["verts"], closed=True, facecolor=C["accent_fill"], + edgecolor=C["accent"], lw=1.0)) + axz.add_patch(Circle(dc_c, dc_r, facecolor="none", edgecolor=C["violet"], + lw=1.2, ls=(0, (5, 3)))) + axz.add_patch(Circle(mec_c, mec_r, facecolor="none", edgecolor=C["success"], lw=1.4)) + axz.plot([dc_c[0]], [dc_c[1]], marker="o", ms=3.4, color=C["violet"]) + axz.plot([mec_c[0]], [mec_c[1]], marker="o", ms=3.4, color=C["success"]) + outside = max(data["verts"], key=lambda v: math.dist(v, dc_c)) + axz.annotate("", xy=outside, xytext=dc_c, + arrowprops=dict(arrowstyle="-|>", color=C["accent"], lw=1.0)) + axz.annotate("E > 0", (outside[0], outside[1]), textcoords="offset points", + xytext=(10, 6), fontproperties=font["times"], fontsize=7.4, + color=C["accent"]) + axz.set_xlabel(f"x / m（放大 ±{zoom:.0f} m）", fontproperties=font["song"]) + chips(ax, [("前向角域 W(s, θ ± 1°)", C["primary"]), ("定位区域 P", C["accent"])]) + chips(axz, [("直径圆（不覆盖）", C["violet"]), ("最小包围圆 MEC", C["success"])]) + return fig + + +# =========================================================================== +# 6. 问题一：直径圆反例 +# =========================================================================== +def fig_q1_counterexample(font: dict[str, Any]) -> Any: + doc = json.loads((ROOT / "examples" / "q1" / "triangle.json").read_text(encoding="utf-8")) + stations = [(m["x"], m["y"], m["bearing_deg"], m.get("half_angle_deg", 1.0)) + for m in doc["measurements"]] + sol = q1_solve(stations) + verts = sol["vertices"] + dc, mec = sol["dc"], sol["mec"] + mec_r = mec["radius_m"] + mec_c, dc_c = mec["center"], dc["center"] + # 反例的定位区域是边长 40 m 的等边三角形：取 1.8 倍直径做放大窗口 + zoom = max(1.8 * float(np.abs(verts - np.array(mec_c)).max()) * 2.0, 40.0) + + fig, axes = axes_for_panels(60.0, [1.0, 1.0]) + ax, axz = axes + half = 1200.0 + polar_axes(ax, half, grid=400.0) + for sx, sy, bearing, hd in stations: + ax.add_patch(Polygon(wedge_polygon((sx, sy), bearing, hd, 3 * half), closed=True, + facecolor=C["primary"], alpha=0.14, edgecolor="none")) + ax.plot([sx], [sy], marker="o", ms=4, color=C["primary"]) + ax.annotate(f"({sx:.0f}, {sy:.0f})", (sx, sy), textcoords="offset points", + xytext=(6, 4), fontproperties=font["times"], fontsize=7.2, + color=C["primary"]) + ax.add_patch(Polygon(verts, closed=True, facecolor=C["accent"], edgecolor=C["accent"])) + ax.set_xlabel("x / m", fontproperties=font["song"]) + ax.set_ylabel("y / m", fontproperties=font["song"]) + + polar_axes(axz, zoom, grid=zoom / 2, center=mec_c) + axz.set_xticks([]) + axz.set_yticks([]) + axz.set_ylabel("") + box = (mec_c[0] - zoom, mec_c[1] - zoom, mec_c[0] + zoom, mec_c[1] + zoom) + for sx, sy, bearing, hd in stations: + poly = wedge_clip((sx, sy), bearing, hd, box) + if len(poly): + axz.add_patch(Polygon(poly, closed=True, facecolor=C["primary"], + alpha=0.24, edgecolor="none")) + region = np.array([[box[0], box[1]], [box[2], box[1]], + [box[2], box[3]], [box[0], box[3]]], dtype=float) + for sx, sy, bearing, hd in stations: + region = clip_wedge(region, (sx, sy), bearing, hd) + if len(region) >= 3: + axz.add_patch(Polygon(region, closed=True, facecolor=C["accent_fill"], + edgecolor=C["accent"], lw=1.6)) + axz.add_patch(Circle(dc_c, dc["radius_m"], facecolor="none", edgecolor=C["violet"], + lw=1.4, ls=(0, (5, 3)))) + axz.add_patch(Circle(mec_c, mec_r, facecolor="none", edgecolor=C["success"], lw=1.4)) + outside = max(verts, key=lambda v: math.dist(v, dc_c)) + axz.annotate("最大超出顶点", xy=outside, xytext=(outside[0] + 6, outside[1] - 10), + fontproperties=font["song"], fontsize=7.6, color=C["accent"], + arrowprops=dict(arrowstyle="-|>", color=C["accent"], lw=1.0)) + axz.set_xlabel(f"x / m（放大 ±{zoom:.0f} m）", fontproperties=font["song"]) + chips(axz, [("直径圆（不覆盖）", C["violet"]), ("最小包围圆 MEC", C["success"])]) + return fig + + +# =========================================================================== +# 7. 问题二：保证接收盘 +# =========================================================================== +def fig_q2_safe_disk(font: dict[str, Any]) -> Any: + delta = math.radians(1.0) + a = 1500.0 / (2 * math.cos(delta)) + safe = R_EFF - a + bearing = 30.0 + c = (a * math.cos(math.radians(bearing)), a * math.sin(math.radians(bearing))) + + fig, axes = axes_for_panels(64.0, [1.0, 1.0], width_ratios=[1.0, 1.0]) + ax, axz = axes + half = 1900.0 + polar_axes(ax, half, grid=500.0) + ax.add_patch(Circle((0, 0), OMEGA_R, facecolor="none", edgecolor=C["primary"], lw=1.2)) + ax.add_patch(Polygon(wedge_polygon((0, 0), bearing, 1.0, 1500.0), closed=True, + facecolor=C["accent"], alpha=0.5, edgecolor=C["accent"], lw=1.0)) + ax.plot([0], [0], marker="o", ms=4, color=C["accent"]) + ax.annotate("s1", (0, 0), textcoords="offset points", xytext=(6, -10), + fontproperties=font["times"], fontsize=7.6, color=C["accent"]) + ax.add_patch(Circle(c, a, facecolor="none", edgecolor=C["violet"], lw=1.0, + ls=(0, (5, 3)))) + ax.add_patch(Circle(c, safe, facecolor=C["success"], alpha=0.35, + edgecolor=C["success"], lw=1.2)) + ax.annotate("", xy=c, xytext=(0, 0), + arrowprops=dict(arrowstyle="-|>", color=C["violet"], lw=1.0)) + ax.annotate(f"a = {a:.1f} m", ((c[0] + 0) / 2, (c[1] + 0) / 2), + textcoords="offset points", xytext=(-6, 26), ha="right", + fontproperties=font["song"], fontsize=7.6, color=C["violet"], + arrowprops=dict(arrowstyle="-", color=C["violet"], lw=0.8)) + ax.annotate(f"安全盘半径 {safe:.1f} m", (c[0], c[1] - safe * 0.7), + textcoords="offset points", xytext=(14, -20), ha="left", + fontproperties=font["song"], fontsize=7.6, color=C["success"], + arrowprops=dict(arrowstyle="-", color=C["success"], lw=0.8)) + ax.text(0, OMEGA_R * 0.98, "Ω：R = 1800 m", fontproperties=font["song"], + fontsize=7.6, color=C["primary"], ha="center", va="top") + ax.set_xlabel("x / m", fontproperties=font["song"]) + ax.set_ylabel("y / m", fontproperties=font["song"]) + + # 右：安全性依据（两半径相加 = 1000 m） + axz.set_aspect("auto") + axz.axis("off") + axz.set_xlim(-1.15, 1.25) + axz.set_ylim(-0.35, 1.05) + r_safe, r_a = safe / 1000.0, a / 1000.0 + axz.add_patch(Circle((0, 0.45), r_a, facecolor=C["violet"], alpha=0.16, + edgecolor=C["violet"], lw=1.0, ls=(0, (4, 3)))) + axz.add_patch(Circle((0, 0.45), r_safe, facecolor=C["success"], alpha=0.35, + edgecolor=C["success"], lw=1.2)) + axz.plot([0], [0.45], marker="o", ms=3.4, color=C["ink"]) + ang = math.radians(20) + axz.annotate("", xy=(r_a * math.cos(ang), 0.45 + r_a * math.sin(ang)), + xytext=(0, 0.45), arrowprops=dict(arrowstyle="-", color=C["violet"], lw=1.0)) + axz.annotate("", xy=(-r_safe * math.cos(ang), 0.45 - r_safe * math.sin(ang)), + xytext=(0, 0.45), arrowprops=dict(arrowstyle="-", color=C["success"], lw=1.0)) + axz.text(0.30, 0.72, f"a = {a:.1f} m", fontproperties=font["song"], fontsize=7.6, + color=C["violet"]) + axz.text(-0.62, 0.18, f"1000 − a = {safe:.1f} m", fontproperties=font["song"], + fontsize=7.6, color=C["success"]) + chips(ax, [("前向角域 W(s1)", C["accent"]), ("截断角域外接圆 B(c, a)", C["violet"]), + ("安全候选盘 B(c, 1000 − a)", C["success"])]) + return fig + + +# =========================================================================== +# 8. 问题三：七点覆盖 +# =========================================================================== +def fig_q3_seven_coverage(font: dict[str, Any]) -> Any: + a = RING_RADIUS_M + stations = [(0.0, 0.0)] + [(a * math.cos(k * math.pi / 3), a * math.sin(k * math.pi / 3)) + for k in range(6)] + bound = seven_bound(a) + fig, axes = axes_for_panels(66.0, [1.0, 0.95], width_ratios=[1.0, 0.95]) + ax, axr = axes + half = 2050.0 + polar_axes(ax, half, grid=600.0) + ax.add_patch(Circle((0, 0), OMEGA_R, facecolor="#f7fafc", edgecolor=C["primary"], lw=1.4)) + for px, py in stations: + ax.add_patch(Circle((px, py), R_EFF, facecolor=C["success"], alpha=0.28, + edgecolor=C["success"], lw=0.8)) + ax.add_patch(Circle((0, 0), OMEGA_R, facecolor="none", edgecolor=C["primary"], lw=1.4)) + for px, py in stations: + ax.plot([px], [py], marker="o", ms=4.2, color=C["accent"]) + ax.plot([0, a], [0, 0], color=C["accent"], lw=0.9) + ax.text(a / 2, 60, f"a = {a:.1f} m", ha="center", fontproperties=font["times"], + fontsize=7.6, color=C["accent"]) + ax.plot([0], [-SEVEN_R], marker="o", ms=4.6, mfc="none", mec=C["accent"], mew=1.2) + ax.annotate(f"最坏点 {bound:.2f} m", (0, -SEVEN_R), textcoords="offset points", + xytext=(-4, 14), ha="center", fontproperties=font["song"], fontsize=7.6, + color=C["accent"], + arrowprops=dict(arrowstyle="-", color=C["accent"], lw=0.8)) + ax.text(0, OMEGA_R, "Ω", ha="center", va="bottom", fontproperties=font["song"], + fontsize=8, color=C["primary"]) + ax.set_xlabel("x / m", fontproperties=font["song"]) + ax.set_ylabel("y / m", fontproperties=font["song"]) + chips(ax, [("覆盖站点（原点 + 六等分环）", C["accent"]), ("1000 m 接收盘", C["success"])]) + + axr.axis("off") + axr.set_xlim(0, 1) + axr.set_ylim(0, 1) + rows = [("七点解析（默认）", "7", f"{bound:.2f} m", C["success_fill"], C["success"]), + ("49 点网格基线", "49", "989.95 m", "#f7f9fb", C["muted"]), + ("31 点最小命中集（题 4）", "31", "990.05 m", "#f7f9fb", C["muted"])] + header = ["方案", "点数", "覆盖半径上界"] + xs = [0.02, 0.62, 0.78] + for x, head in zip(xs, header): + axr.text(x, 0.9, head, fontproperties=font["hei_bold"], fontsize=7.8, + color=C["primary"]) + for i, (name, count, dist, face, edge) in enumerate(rows): + y = 0.76 - i * 0.13 + axr.add_patch(FancyBboxPatch((0.0, y - 0.045), 1.0, 0.11, + boxstyle="round,pad=0.004,rounding_size=0.02", + facecolor=face, edgecolor=edge, lw=0.8)) + axr.text(xs[0], y, name, fontproperties=font["song"], fontsize=7.6) + axr.text(xs[1], y, count, fontproperties=font["times"], fontsize=7.6) + axr.text(xs[2], y, dist, fontproperties=font["times"], fontsize=7.6) + return fig + + +# =========================================================================== +# 9. 问题四：31 点最小命中集 +# =========================================================================== +def fig_q4_mincover(font: dict[str, Any]) -> Any: + plan = load_plan("q4_mincover_v2") + pts = np.array(plan["points"], dtype=float) + cert = plan["certificate"] + + fig, axes = axes_for_panels(64.0, [1.0, 1.0], width_ratios=[1.0, 1.0]) + ax, axr = axes + half = 2150.0 + polar_axes(ax, half, grid=600.0) + ax.add_patch(Circle((0, 0), OMEGA_R, facecolor="#f7fafc", edgecolor=C["primary"], lw=1.4)) + ax.plot(pts[:, 0], pts[:, 1], ls="none", marker="o", ms=4.2, color=C["accent"], + label=f"{len(pts)} 个覆盖点") + ax.legend(prop=font["song"], frameon=False, loc="lower left") + ax.text(0, OMEGA_R, "Ω", ha="center", va="bottom", fontproperties=font["song"], + fontsize=8, color=C["primary"]) + ax.set_xlabel("x / m", fontproperties=font["song"]) + ax.set_ylabel("y / m", fontproperties=font["song"]) + ax.set_xlabel("x / m", fontproperties=font["song"]) + + # 右：forward_half_disk 语义与证书 + axr.axis("off") + axr.set_xlim(0, 1) + axr.set_ylim(0, 1) + axr.add_patch(Circle((0.36, 0.66), 0.24, facecolor="#f7f9fb", edgecolor=C["muted"], + lw=0.9)) + half_disk = [[0.36, 0.66]] + [[0.36 + 0.24 * math.cos(math.radians(-90 + 180 * i / 24)), + 0.66 + 0.24 * math.sin(math.radians(-90 + 180 * i / 24))] + for i in range(25)] + axr.add_patch(Polygon(half_disk, closed=True, facecolor=C["accent"], alpha=0.32, + edgecolor="none")) + axr.annotate("", xy=(0.57, 0.66), xytext=(0.36, 0.66), + arrowprops=dict(arrowstyle="-|>", color=C["accent"], lw=1.2)) + axr.plot([0.36, 0.36], [0.42, 0.90], color=C["accent"], lw=0.9, ls=(0, (4, 3))) + axr.annotate("", xy=(0.60, 0.95), xytext=(0.12, 0.95), + arrowprops=dict(arrowstyle="<->", color=C["muted"], lw=0.8)) + axr.text(0.36, 0.90, "覆盖半径 1000 m", ha="center", fontproperties=font["song"], + fontsize=7.4, color=C["muted"]) + axr.text(0.62, 0.60, "朝向未知\n±90° 前向半盘", ha="left", va="top", + fontproperties=font["song"], fontsize=7.4, color=C["accent"], linespacing=1.6) + return fig +# =========================================================================== +# 10/11. WebUI 回放复现 +# =========================================================================== +def fig_replay(run: dict[str, Any], font: dict[str, Any], *, directional: bool) -> Any: + tl = decompose(run) + rows = tl["rows"] + truth = run["truth"] + solved = set(solved_channels(run)) + + fig = plt.figure(figsize=(170 / 25.4, 108 / 25.4)) + ax = fig.add_axes([0.04, 0.30, 0.60, 0.66]) + polar_axes(ax, 2100.0, grid=1000.0) + ax.add_patch(Circle((0, 0), OMEGA_R, facecolor="#f7fafc", edgecolor=C["primary"], lw=1.4)) + for src in truth: + ch = int(src["channel"]) + color = C["accent"] if ch in solved else C["warn"] + ax.plot([src["x"]], [src["y"]], marker="o", ms=5, color=color, zorder=5) + ax.annotate(f"ch{ch}", (src["x"], src["y"]), textcoords="offset points", + xytext=(5, 2), fontproperties=font["times"], fontsize=6.8, color=color) + if directional and src.get("directional"): + hd = math.radians(float(src.get("heading_deg") or 0.0)) + ax.annotate("", xy=(src["x"] + 200 * math.cos(hd), src["y"] + 200 * math.sin(hd)), + xytext=(src["x"], src["y"]), + arrowprops=dict(arrowstyle="-|>", color=C["accent"], lw=1.0)) + path = [(0.0, 0.0)] + for row in rows: + if row["x"] is None: + continue + if (row["x"], row["y"]) != path[-1]: + path.append((row["x"], row["y"])) + if len(path) > 1: + px, py = zip(*path) + ax.plot(px, py, color=C["primary"], lw=1.1, alpha=0.85, zorder=3) + for act, row in zip(run["actions"], rows): + if row["x"] is None: + continue + if act["path"] == "/measure" and row["hit"]: + bearing = math.radians(float(act["response"].get("svd_deg") or 0.0)) + ax.annotate("", xy=(row["x"] + 220 * math.cos(bearing), + row["y"] + 220 * math.sin(bearing)), + xytext=(row["x"], row["y"]), + arrowprops=dict(arrowstyle="-|>", color=C["success"], lw=0.7, + alpha=0.55)) + ax.plot([row["x"]], [row["y"]], marker="o", ms=2.6, color=C["success"]) + elif act["path"] == "/clear": + ax.plot([row["x"]], [row["y"]], marker="o", ms=7, mfc="none", + mec=C["success"] if row["cleared"] else C["muted"], mew=1.2) + if row["cleared"]: + ax.plot([row["x"]], [row["y"]], marker="x", ms=5, color=C["success"], + mew=1.6) + ax.set_xlabel("x / m", fontproperties=font["song"]) + ax.set_ylabel("y / m", fontproperties=font["song"]) + ax.legend(handles=[ + Line2D([], [], marker="o", ls="none", color=C["success"], label="已清除频道"), + Line2D([], [], marker="o", ls="none", color=C["warn"], label="未清除频道"), + Line2D([], [], color=C["accent"], lw=1.2, label="定向源朝向"), + Line2D([], [], color=C["success"], lw=0.8, label="检测示向度"), + ], prop=font["song"], frameon=False, loc="upper center", + bbox_to_anchor=(0.5, -0.13), ncols=4) + + # 右侧：事件流水（前 10 条） + axt = fig.add_axes([0.70, 0.30, 0.285, 0.62]) + axt.axis("off") + axt.set_xlim(0, 1) + axt.set_ylim(0, 1) + axt.text(0.0, 1.0, run["case_code"], fontproperties=font["times_bold"], fontsize=7.8, + color=C["primary"], va="top") + axt.text(0.0, 0.93, f"{run['module']} · 源 {len(truth)} · " + f"全清 {len(solved)}/{len(truth)}", fontproperties=font["song"], + fontsize=7.4, color=C["muted"], va="top") + axt.text(0.0, 0.86, "动作 参数 虚拟 t/s", fontproperties=font["hei_bold"], + fontsize=7.4, color=C["primary"], va="top") + for i, (act, row) in enumerate(list(zip(run["actions"], rows))[:10]): + if act["path"] == "/measure": + detail = f"ch{row['channel']} ({row['x']:.0f},{row['y']:.0f})" + elif act["path"] == "/clear": + detail = f"ch{row['channel']} {'成功' if row['cleared'] else '未发现'}" + elif act["path"] == "/enter": + detail = "启动" + else: + detail = "退出" + axt.text(0.0, 0.78 - i * 0.075, act["path"], fontproperties=font["times"], + fontsize=7.2, va="top") + axt.text(0.45, 0.78 - i * 0.075, detail, fontproperties=font["song"], + fontsize=7.2, va="top") + axt.text(1.0, 0.78 - i * 0.075, f"{row['virtual_s']:.0f}", + fontproperties=font["times"], fontsize=7.2, va="top", ha="right") + + # 底部：虚拟时间轴（检测命中 / 清除刻度） + axb = fig.add_axes([0.04, 0.13, 0.945, 0.09]) + axb.set_xlim(0, max(tl["virtual_s"], 1e-9)) + axb.set_ylim(0, 1) + axb.axis("off") + axb.add_patch(FancyBboxPatch((0, 0.35), tl["virtual_s"], 0.3, + boxstyle="round,pad=0,rounding_size=0", + facecolor=C["primary_fill"], edgecolor="none")) + for act, row in zip(run["actions"], rows): + if act["path"] == "/measure" and row["hit"]: + axb.plot([row["virtual_s"], row["virtual_s"]], [0.2, 0.8], color=C["accent"], + lw=0.9) + elif act["path"] == "/clear" and row["cleared"]: + axb.plot([row["virtual_s"], row["virtual_s"]], [0.05, 0.95], color=C["success"], + lw=1.4) + axb.text(0, 1.15, "0 s", fontproperties=font["times"], fontsize=7.2, color=C["muted"]) + axb.text(tl["virtual_s"], 1.15, f"{tl['virtual_s']:,.0f} s", ha="right", + fontproperties=font["times"], fontsize=7.2, color=C["muted"]) + axb.text(tl["virtual_s"] / 2, 1.15, "竖线：检测到信号（红）/ 成功清除（绿）", + ha="center", fontproperties=font["song"], fontsize=7.2, color=C["muted"]) + return fig + + +# =========================================================================== +# 入口 +# =========================================================================== +def build_figures(only: Sequence[str] | None, scale: float) -> list[dict[str, Any]]: + font = setup_style() + want = set(only) if only else None + runs = discover_runs() + q3 = pick_run(runs, "q3", 10) if runs else None + q4 = pick_run(runs, "q4", 12) if runs else None + if not runs: + print("[fig] 未找到 JSONL，跳过与日志相关的 3 张图") + + jobs: list[tuple[str, Callable[[], Any], list[dict[str, Any]]]] = [ + ("flow-overall-architecture", lambda: fig_flow_overall(font), + [source("src/mcm26b/config.py"), source("docs/B题建模分析与实施计划.md")]), + ("steps-state-machine", lambda: fig_steps_state_machine(font), + [source("docs/协议规则表与状态机.md"), source("src/mcm26b/protocol/client.py")]), + ("timing-attachment-example-105-111-194-199", lambda: fig_timing_attachment(font), + [source("docs/协议规则表与状态机.md")]), + ("geo-q1-convex-intersection-zoom", lambda: fig_q1_meetup(font), []), + ("geo-q1-diameter-circle-counterexample", lambda: fig_q1_counterexample(font), + [source("examples/q1/triangle.json")]), + ("geo-q2-guaranteed-reception-disk", lambda: fig_q2_safe_disk(font), + [source("src/mcm26b/config.py"), source("docs/algo-2.md")]), + ("geo-q3-seven-point-coverage", lambda: fig_q3_seven_coverage(font), + [source("src/mcm26b/planner/seven.py"), source("docs/algo-3.md")]), + ("geo-q4-minimum-cover-31-points", lambda: fig_q4_mincover(font), + [source("src/mcm26b/guarantee/plans/q4_mincover_v2.json"), source("docs/algo-4.md")]), + ] + if q3: + jobs.append(("timing-measured-q3-10-sources", lambda: fig_timing_measured(q3, font), + [source(q3["source"], case_code=q3["case_code"], module=q3["module"])])) + jobs.append(("replay-webui-q3-omnidirectional", + lambda: fig_replay(q3, font, directional=False), + [source(q3["source"], case_code=q3["case_code"])])) + if q4: + jobs.append(("replay-webui-q4-directional", + lambda: fig_replay(q4, font, directional=True), + [source(q4["source"], case_code=q4["case_code"])])) + + entries: list[dict[str, Any]] = [] + for stem, maker, sources in jobs: + if want and stem not in want: + continue + fig = maker() + if stem == "geo-q1-convex-intersection-zoom": + sources = [source(_q1_data()["src"])] + entry = save(fig, stem, sources, scale) + entries.append(entry) + print(f"[fig] {stem:<44} → {entry['png']}") + return entries + + +def main() -> int: + names = ["flow-overall-architecture", "steps-state-machine", + "timing-attachment-example-105-111-194-199", "timing-measured-q3-10-sources", + "geo-q1-convex-intersection-zoom", "geo-q1-diameter-circle-counterexample", + "geo-q2-guaranteed-reception-disk", "geo-q3-seven-point-coverage", + "geo-q4-minimum-cover-31-points", "replay-webui-q3-omnidirectional", + "replay-webui-q4-directional"] + parser = argparse.ArgumentParser(description=__doc__.splitlines()[0]) + parser.add_argument("--only", default="", help="逗号分隔的图名子集") + parser.add_argument("--scale", type=float, default=1.0, help="尺寸倍率") + parser.add_argument("--list", action="store_true") + args = parser.parse_args() + if args.list: + print("\n".join(names)) + return 0 + only = [s.strip() for s in args.only.split(",") if s.strip()] + unknown = [s for s in only if s not in names] + if unknown: + parser.error(f"未知图名 {unknown}") + entries = build_figures(only or None, args.scale) + manifest = {"generator": "scripts/make_figures.py", + "command": "uv run python scripts/make_figures.py" + + (f" --only {args.only}" if args.only else ""), + "palette": C, "fonts": {"dir": "docs/paper/fonts", "map": FONTS}, + "figures": entries} + path = OUT_DIR / "manifest.json" + path.write_text(json.dumps(manifest, ensure_ascii=False, indent=2) + "\n", + encoding="utf-8") + print(f"[fig] manifest → {path.relative_to(ROOT)}（{len(entries)} 张）") + return 0 + + +if __name__ == "__main__": + raise SystemExit(main())

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