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@@ -12,6 +12,10 @@ wheels/
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# Sim
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# Sim
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Jammers*/
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Jammers*/
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tmp/
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tmp/
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# MATLAB 出图日志
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scripts/matlab/*.log
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# LaTeX build artifacts
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# LaTeX build artifacts
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docs/paper/build/
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docs/paper/build/
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docs/paper/*.aux
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docs/paper/*.aux
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@@ -8,7 +8,7 @@
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- [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)
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- [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)
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- [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)
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- [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)
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- [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)
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- [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)
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- [论文插图清单与复现方式](docs/figures/README.md)（`uv run python scripts/make_figures.py`）
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- [论文插图清单与复现方式](docs/figures/README.md)（`uv run python scripts/build_figure_data.py`）
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- [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)
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- [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)
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- [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)
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- [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)
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- [问题一完整解答](docs/问题一解答.md)
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- [问题一完整解答](docs/问题一解答.md)
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@@ -42,7 +42,7 @@ project/ # 1-4 问"最优实现 / 基线实现"对比框架：逐问 o
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# +独立参考，冻结基准集配对出数；见 project/README.md
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# +独立参考，冻结基准集配对出数；见 project/README.md
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scripts/ # 采集、基准、可视化与校核脚本（含问题四批量仿真 benchmark_q4.py、
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scripts/ # 采集、基准、可视化与校核脚本（含问题四批量仿真 benchmark_q4.py、
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# 运行历史计时分解 analyze_run_timing.py、第四问覆盖证书 verify_q4_cover.py、
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# 运行历史计时分解 analyze_run_timing.py、第四问覆盖证书 verify_q4_cover.py、
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# 论文插图 make_figures.py、日志归档 archive_replay_logs.py）
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# 论文插图 build_figure_data.py + scripts/matlab、日志归档 archive_replay_logs.py）
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docs/figures/ # 论文插图（PNG）+ manifest.json（数据来源与 sha256）+ 图清单
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docs/figures/ # 论文插图（PNG）+ manifest.json（数据来源与 sha256）+ 图清单
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output/ examples/ # 演练证据、算例与生成产物
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output/ examples/ # 演练证据、算例与生成产物
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```
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```
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-27
@@ -1,48 +1,54 @@
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# docs/figures —— 论文插图
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# docs/figures —— 论文插图
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每张图只输出 PNG，由 `scripts/make_figures.py` 用 matplotlib 生成。
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每张图只输出 PNG。数据由 `scripts/build_figure_data.py` 从行为日志、覆盖计划与生产求解器
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算好写入 `docs/figures/.data/*.mat`，再由 MATLAB（`scripts/matlab/*.m`）排版出图；
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`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。
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`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。
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```bash
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```bash
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uv run python scripts/make_figures.py # 全部 11 张
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uv run python scripts/build_figure_data.py # 全部 11 张（数据 + 出图）
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uv run python scripts/make_figures.py --list # 图名
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uv run python scripts/build_figure_data.py --prepare # 只写 .mat 数据
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uv run python scripts/make_figures.py --only geo-q3-seven-point-coverage
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uv run python scripts/build_figure_data.py --list # 图名
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uv run python scripts/make_figures.py --scale 1.5 # 整体放大（尺寸倍率）
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uv run python scripts/build_figure_data.py --only geo-q3-seven-point-coverage
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```
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```
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依赖：`matplotlib`、`Pillow`、`docs/paper/fonts/` 下的字体。
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MATLAB 内手动出图：`cd scripts/matlab` 后执行 `run_all_figures`（每张图单独一个会话，
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`matplotlib` 缓存写入仓库内 `.mpl-cache/`，不污染用户目录。
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本机图形子系统连续渲染多张会崩）。
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依赖：`numpy`、`scipy`（写 `.mat`）与 MATLAB R2025a。
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## 约定
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## 约定
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- 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；
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- **除回放画布（点运动图 `replay-webui-*`）外，全部使用 MATLAB 默认图形样式**：
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默认配色（`defaultAxesColorOrder`）、默认字体与字号、默认坐标轴与图例；
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不引入自定义调色板，不手绘图例色块。
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- 图内不放标题、图注与解释性文字，只保留坐标轴、图例与必要的元素标注；
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图的含义由文件名与下表承担，解释写在论文正文。
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图的含义由文件名与下表承担，解释写在论文正文。
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- 配色（`scripts/make_figures.py::C`）：深蓝 `#1f4e79` 主流程与协议，
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- 图例一律用 MATLAB `legend` 放在坐标区外（`southoutside`），不压数据；
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砖红 `#b03a2e` 真值源与关键结论，墨绿 `#1e7a5f` 清除与通过项，
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散点标签按候选方位自动避让，保证互不重叠。
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土黄 `#b8860b` 后备与警示，灰色只用于网格与次要文字。
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- 输出 PNG（`exportgraphics`，300 dpi、白底），导出前关闭坐标轴工具条。
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||||||
- 字体：中文宋体 `SongtiSC-Regular/Bold`，标题黑体 `HeitiSC-Light/Medium`，
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数字与西文 Times New Roman，均取自 `docs/paper/fonts/`，与 `main.tex` 一致。
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||||||
- 输出为 PNG（`savefig.dpi = 200`，另有 `--scale` 倍率），按 160 mm 宽排版时
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与正文同字号。
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## 图清单
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## 图清单
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||||||
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| 文件 | 内容 | 数据来源 |
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| 文件 | 内容 | 数据来源 |
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||||||
| --- | --- | --- |
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| --- | --- | --- |
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| `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` |
|
| `flow-overall-architecture.png` | 四层主线：题面抽象（L0）、在线三层（L1）、四问主线（L2）、三条闭环（L3） | `src/mcm26b/config.py`、`docs/B题建模分析与实施计划.md` |
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| `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` |
|
| `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` |
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| `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` |
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| `timing-attachment-example-105-111-194-199.png` | 附件计时示例：逐动作耗时构成与单步合计 | `docs/协议规则表与状态机.md` |
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| `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` |
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| `timing-measured-q3-10-sources.png` | 实测一局：累计虚拟时间按动作类型的堆叠构成 | `referee-data/sessions/BBM9-HZG2-77N5-NKKC/log.jsonl` |
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| `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-convex-intersection-zoom.png` | 问题一：角域交会总览 + 定位区域放大（直径圆与最小包围圆） | `output/q1/practice/U5ZW-P9KN-TCAG-R7ST_observations.json` |
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| `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-q1-diameter-circle-counterexample.png` | 问题一：直径圆不覆盖定位区域的反例（等边三角形布站） | `examples/q1/triangle.json` |
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| `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` |
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| `geo-q2-guaranteed-reception-disk.png` | 问题二：截断角域外接圆 `B(c, a)` 与安全候选盘 `B(c, 1000 − a)`，右侧为半径分解 | `src/mcm26b/config.py`、`docs/algo-2.md` |
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| `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-q3-seven-point-coverage.png` | 问题三：七个 1000 m 接收盘覆盖 Ω，标出最差点 | `src/mcm26b/planner/seven.py`、`docs/algo-3.md` |
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| `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` |
|
| `geo-q4-minimum-cover-31-points.png` | 问题四：31 点最小命中集与 ±90° 前向半盘语义 | `src/mcm26b/guarantee/plans/q4_mincover_v2.json` |
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| `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-q3-omnidirectional.png` | 回放画布（点运动图，全向局）：世界视图 + 事件流水 + 虚拟时间轴 | `referee-data/sessions/BBM9-HZG2-77N5-NKKC/log.jsonl` |
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| `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` |
|
| `replay-webui-q4-directional.png` | 回放画布（点运动图，定向源局）：世界视图（含定向源 ±90° 前向半盘）+ 事件流水 + 虚拟时间轴 | `referee-data/sessions/GHSN-M38E-74GD-YLUD/log.jsonl` |
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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、
|
后两张是唯一保留自定义画布的图：把回放器画布上的 Ω 与真值源、移动轨迹、
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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。
|
检测示向度射线、定向源朝向与清除标记，连同右侧事件流水与底部虚拟时间轴一起导出；
|
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|
定向源局额外画出每个定向源的 **±90° 前向半盘**（半径取该源 `r_eff_m`，朝向箭头即半盘半径）。
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|
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|
q4 回放固定用演练局 `GHSN-M38E-74GD-YLUD`（`build_figure_data.py::Q4_REPLAY_CASE`）；
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|
本机没有该局留档时回退到自动挑选，因此 `examples/replay/` 里归档了这一局。
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## 数据来源与复现
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## 数据来源与复现
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+31
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{
|
{
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"generator": "scripts/make_figures.py",
|
"generator": "scripts/build_figure_data.py（数据）+ scripts/matlab/*.m（MATLAB 出图）",
|
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"command": "uv run python scripts/make_figures.py",
|
"command": "uv run python scripts/build_figure_data.py",
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||||||
"palette": {
|
"manual": "MATLAB 中 cd scripts/matlab 后执行 run_all_figures",
|
||||||
"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": {
|
|
||||||
"dir": "docs/paper/fonts",
|
|
||||||
"map": {
|
|
||||||
"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"
|
|
||||||
}
|
|
||||||
},
|
|
||||||
"figures": [
|
"figures": [
|
||||||
{
|
{
|
||||||
"stem": "flow-overall-architecture",
|
"stem": "flow-overall-architecture",
|
||||||
"png": "docs/figures/flow-overall-architecture.png",
|
"png": "docs/figures/flow-overall-architecture.png",
|
||||||
"scale": 1.0,
|
"matlab": "scripts/matlab/fig_flow_overall.m",
|
||||||
"sources": [
|
"sources": [
|
||||||
{
|
{
|
||||||
"path": "src/mcm26b/config.py",
|
"path": "src/mcm26b/config.py",
|
||||||
@@ -47,7 +23,7 @@
|
|||||||
{
|
{
|
||||||
"stem": "steps-state-machine",
|
"stem": "steps-state-machine",
|
||||||
"png": "docs/figures/steps-state-machine.png",
|
"png": "docs/figures/steps-state-machine.png",
|
||||||
"scale": 1.0,
|
"matlab": "scripts/matlab/fig_steps_state_machine.m",
|
||||||
"sources": [
|
"sources": [
|
||||||
{
|
{
|
||||||
"path": "docs/协议规则表与状态机.md",
|
"path": "docs/协议规则表与状态机.md",
|
||||||
@@ -64,7 +40,7 @@
|
|||||||
{
|
{
|
||||||
"stem": "timing-attachment-example-105-111-194-199",
|
"stem": "timing-attachment-example-105-111-194-199",
|
||||||
"png": "docs/figures/timing-attachment-example-105-111-194-199.png",
|
"png": "docs/figures/timing-attachment-example-105-111-194-199.png",
|
||||||
"scale": 1.0,
|
"matlab": "scripts/matlab/fig_timing_attachment.m",
|
||||||
"sources": [
|
"sources": [
|
||||||
{
|
{
|
||||||
"path": "docs/协议规则表与状态机.md",
|
"path": "docs/协议规则表与状态机.md",
|
||||||
@@ -73,10 +49,24 @@
|
|||||||
}
|
}
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
|
{
|
||||||
|
"stem": "timing-measured-q3-10-sources",
|
||||||
|
"png": "docs/figures/timing-measured-q3-10-sources.png",
|
||||||
|
"matlab": "scripts/matlab/fig_timing_measured.m",
|
||||||
|
"sources": [
|
||||||
|
{
|
||||||
|
"path": "referee-data/sessions/BBM9-HZG2-77N5-NKKC/log.jsonl",
|
||||||
|
"sha256_12": "5a308e53ed09",
|
||||||
|
"lines": 133,
|
||||||
|
"case_code": "BBM9-HZG2-77N5-NKKC",
|
||||||
|
"module": "q3_practice"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
{
|
{
|
||||||
"stem": "geo-q1-convex-intersection-zoom",
|
"stem": "geo-q1-convex-intersection-zoom",
|
||||||
"png": "docs/figures/geo-q1-convex-intersection-zoom.png",
|
"png": "docs/figures/geo-q1-convex-intersection-zoom.png",
|
||||||
"scale": 1.0,
|
"matlab": "scripts/matlab/fig_geo_q1_meetup.m",
|
||||||
"sources": [
|
"sources": [
|
||||||
{
|
{
|
||||||
"path": "output/q1/practice/U5ZW-P9KN-TCAG-R7ST_observations.json",
|
"path": "output/q1/practice/U5ZW-P9KN-TCAG-R7ST_observations.json",
|
||||||
@@ -88,7 +78,7 @@
|
|||||||
{
|
{
|
||||||
"stem": "geo-q1-diameter-circle-counterexample",
|
"stem": "geo-q1-diameter-circle-counterexample",
|
||||||
"png": "docs/figures/geo-q1-diameter-circle-counterexample.png",
|
"png": "docs/figures/geo-q1-diameter-circle-counterexample.png",
|
||||||
"scale": 1.0,
|
"matlab": "scripts/matlab/fig_geo_q1_counterexample.m",
|
||||||
"sources": [
|
"sources": [
|
||||||
{
|
{
|
||||||
"path": "examples/q1/triangle.json",
|
"path": "examples/q1/triangle.json",
|
||||||
@@ -100,7 +90,7 @@
|
|||||||
{
|
{
|
||||||
"stem": "geo-q2-guaranteed-reception-disk",
|
"stem": "geo-q2-guaranteed-reception-disk",
|
||||||
"png": "docs/figures/geo-q2-guaranteed-reception-disk.png",
|
"png": "docs/figures/geo-q2-guaranteed-reception-disk.png",
|
||||||
"scale": 1.0,
|
"matlab": "scripts/matlab/fig_geo_q2_safe_disk.m",
|
||||||
"sources": [
|
"sources": [
|
||||||
{
|
{
|
||||||
"path": "src/mcm26b/config.py",
|
"path": "src/mcm26b/config.py",
|
||||||
@@ -117,7 +107,7 @@
|
|||||||
{
|
{
|
||||||
"stem": "geo-q3-seven-point-coverage",
|
"stem": "geo-q3-seven-point-coverage",
|
||||||
"png": "docs/figures/geo-q3-seven-point-coverage.png",
|
"png": "docs/figures/geo-q3-seven-point-coverage.png",
|
||||||
"scale": 1.0,
|
"matlab": "scripts/matlab/fig_geo_q3_coverage.m",
|
||||||
"sources": [
|
"sources": [
|
||||||
{
|
{
|
||||||
"path": "src/mcm26b/planner/seven.py",
|
"path": "src/mcm26b/planner/seven.py",
|
||||||
@@ -134,7 +124,7 @@
|
|||||||
{
|
{
|
||||||
"stem": "geo-q4-minimum-cover-31-points",
|
"stem": "geo-q4-minimum-cover-31-points",
|
||||||
"png": "docs/figures/geo-q4-minimum-cover-31-points.png",
|
"png": "docs/figures/geo-q4-minimum-cover-31-points.png",
|
||||||
"scale": 1.0,
|
"matlab": "scripts/matlab/fig_geo_q4_mincover.m",
|
||||||
"sources": [
|
"sources": [
|
||||||
{
|
{
|
||||||
"path": "src/mcm26b/guarantee/plans/q4_mincover_v2.json",
|
"path": "src/mcm26b/guarantee/plans/q4_mincover_v2.json",
|
||||||
@@ -148,24 +138,10 @@
|
|||||||
}
|
}
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
|
||||||
"stem": "timing-measured-q3-10-sources",
|
|
||||||
"png": "docs/figures/timing-measured-q3-10-sources.png",
|
|
||||||
"scale": 1.0,
|
|
||||||
"sources": [
|
|
||||||
{
|
|
||||||
"path": "referee-data/sessions/BBM9-HZG2-77N5-NKKC/log.jsonl",
|
|
||||||
"sha256_12": "5a308e53ed09",
|
|
||||||
"lines": 133,
|
|
||||||
"case_code": "BBM9-HZG2-77N5-NKKC",
|
|
||||||
"module": "q3_practice"
|
|
||||||
}
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
{
|
||||||
"stem": "replay-webui-q3-omnidirectional",
|
"stem": "replay-webui-q3-omnidirectional",
|
||||||
"png": "docs/figures/replay-webui-q3-omnidirectional.png",
|
"png": "docs/figures/replay-webui-q3-omnidirectional.png",
|
||||||
"scale": 1.0,
|
"matlab": "scripts/matlab/fig_replay.m",
|
||||||
"sources": [
|
"sources": [
|
||||||
{
|
{
|
||||||
"path": "referee-data/sessions/BBM9-HZG2-77N5-NKKC/log.jsonl",
|
"path": "referee-data/sessions/BBM9-HZG2-77N5-NKKC/log.jsonl",
|
||||||
@@ -178,13 +154,13 @@
|
|||||||
{
|
{
|
||||||
"stem": "replay-webui-q4-directional",
|
"stem": "replay-webui-q4-directional",
|
||||||
"png": "docs/figures/replay-webui-q4-directional.png",
|
"png": "docs/figures/replay-webui-q4-directional.png",
|
||||||
"scale": 1.0,
|
"matlab": "scripts/matlab/fig_replay.m",
|
||||||
"sources": [
|
"sources": [
|
||||||
{
|
{
|
||||||
"path": "referee-data/sessions/GM56-DFXZ-XKDM-XYV7/log.jsonl",
|
"path": "referee-data/sessions/GHSN-M38E-74GD-YLUD/log.jsonl",
|
||||||
"sha256_12": "f498b2073cdf",
|
"sha256_12": "280696d901b4",
|
||||||
"lines": 421,
|
"lines": 429,
|
||||||
"case_code": "GM56-DFXZ-XKDM-XYV7"
|
"case_code": "GHSN-M38E-74GD-YLUD"
|
||||||
}
|
}
|
||||||
]
|
]
|
||||||
}
|
}
|
||||||
|
|||||||
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|
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+7
-7
@@ -3,7 +3,7 @@
|
|||||||
> 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：
|
> 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
|
> ```bash
|
||||||
> uv run python scripts/make_figures.py --only geo-q1-convex-intersection-zoom,\
|
> uv run python scripts/build_figure_data.py --only geo-q1-convex-intersection-zoom,\
|
||||||
> geo-q1-diameter-circle-counterexample,geo-q2-guaranteed-reception-disk,\
|
> geo-q1-diameter-circle-counterexample,geo-q2-guaranteed-reception-disk,\
|
||||||
> geo-q3-seven-point-coverage,geo-q4-minimum-cover-31-points
|
> geo-q3-seven-point-coverage,geo-q4-minimum-cover-31-points
|
||||||
> ```
|
> ```
|
||||||
@@ -30,14 +30,14 @@
|
|||||||
（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，
|
（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。
|
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：
|
**右（放大，视野 ±20.6 m）**：以定位区域为中心：
|
||||||
|
|
||||||
- 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**= $P$；
|
- 浅蓝扇形 = 三个角域在放大框内的可见部分；**橙色多边形** = 三者交集，即定位区域 $P$；
|
||||||
- 红色实线多边形 = $P$ 的顶点边界（与左图同一个集合）；
|
- 左图里 $P$ 的直径只有 24 m，缩成一个红色方块，放大后才看得到形状；
|
||||||
- 蓝色虚线圆 = **直径圆**，半径 $D/2=11.9984$ m，圆心是中点 $(-450.634,\ 508.944)$；
|
- 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 $(-449.977,\ 507.953)$。
|
- 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）**
|
**关键量**
|
||||||
|
|
||||||
| 量 | 值 | 判定 |
|
| 量 | 值 | 判定 |
|
||||||
| --- | ---: | --- |
|
| --- | ---: | --- |
|
||||||
@@ -64,7 +64,7 @@ $P$：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；
|
- 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，
|
- 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）；
|
故**直径圆不覆盖**：$E=+14.6410$ m；
|
||||||
- 该反例的最小包围圆半径 $\rho=40/\sqrt3\approx23.0940$ m **> 20 m**，
|
- 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。
|
属于"覆盖失败且无法保证清除"的更坏情形。
|
||||||
|
|
||||||
@@ -136,7 +136,7 @@ D(a)=984.5391\ \text{m}<1000\ \text{m}
|
|||||||
\quad(\text{几何余量 }15.46\ \text{m}).
|
\quad(\text{几何余量 }15.46\ \text{m}).
|
||||||
$$
|
$$
|
||||||
|
|
||||||
**图上看到的就是这个证明**：7 个半径 1000 m 的接收盘（浅绿，裁剪在 Ω 内）的
|
**图上看到的就是这个证明**：7 个半径 1000 m 的接收盘（浅绿）的
|
||||||
并集**完全覆盖** Ω，最坏点出现在 $(0,-1800)$（Ω 正下方边界，图中圈出），
|
并集**完全覆盖** Ω，最坏点出现在 $(0,-1800)$（Ω 正下方边界，图中圈出），
|
||||||
到最近站点 $1159.7$ m（正下方环站）的距离恰为 984.54 m。
|
到最近站点 $1159.7$ m（正下方环站）的距离恰为 984.54 m。
|
||||||
|
|
||||||
|
|||||||
+1
-1
@@ -3,7 +3,7 @@
|
|||||||
> 插图：[`figures/flow-overall-architecture.png`](figures/flow-overall-architecture.png)（总体思路与算法主线）、
|
> 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/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）。
|
> [`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`
|
> 复现：`uv run python scripts/build_figure_data.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。
|
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)，
|
算法细节指向 [`algo-1.md`](algo-1.md)~[`algo-4.md`](algo-4.md)，
|
||||||
|
|||||||
+3
-3
@@ -3,7 +3,7 @@
|
|||||||
> 配套插图：[`figures/steps-state-machine.png`](figures/steps-state-machine.png)（状态机与动作回合）、
|
> 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-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）。
|
> [`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`
|
> 复现：`uv run python scripts/build_figure_data.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。
|
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；
|
规则原文见 `issue/` 下附件1 表1、表2 与附件2 第 4、10 节；
|
||||||
@@ -108,7 +108,7 @@ uv run pytest tests/test_protocol_timing.py -q # 逐步断言移动、换频
|
|||||||
|
|
||||||
## 4. 实测时序分解
|
## 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`
|
对评测机留档的每一局，`scripts/build_figure_data.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`。
|
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）
|
### 4.1 问题三演练局 `BBM9-HZG2-77N5-NKKC`（10 源全清）
|
||||||
@@ -145,7 +145,7 @@ uv run pytest tests/test_protocol_timing.py -q # 逐步断言移动、换频
|
|||||||
|
|
||||||
```bash
|
```bash
|
||||||
# 用评测机留档重画（含真值）
|
# 用评测机留档重画（含真值）
|
||||||
uv run python scripts/make_figures.py --only timing-measured-q3-10-sources,\
|
uv run python scripts/build_figure_data.py --only timing-measured-q3-10-sources,\
|
||||||
replay-webui-q3-omnidirectional,replay-webui-q4-directional
|
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
|
# 归档新日志，评测机数据被清理后仍可复现插图
|
||||||
|
|||||||
@@ -0,0 +1,429 @@
|
|||||||
|
{"event":"session_start","case_code":"GHSN-M38E-74GD-YLUD","module":"q4_practice","robot_id":"1","seed":1907688398,"countdown_s":5.0,"window_s":1500.0,"max_real_duration_s":1200.0,"truth":[{"channel":6,"x":-168.78031525275804,"y":1684.875239455932,"r_eff_m":1233.1529913973563,"directional":true,"heading_deg":351.84275431652014},{"channel":15,"x":411.7975180678083,"y":1548.040304144621,"r_eff_m":1336.3045523445826,"directional":true,"heading_deg":72.47781232458263},{"channel":8,"x":978.6674582823607,"y":-996.1121301869524,"r_eff_m":1336.1370990332562,"directional":true,"heading_deg":246.14394851382335},{"channel":16,"x":124.00340756473021,"y":-860.3622285357711,"r_eff_m":1345.578791332298,"directional":false,"heading_deg":0.0},{"channel":10,"x":729.8914456683548,"y":714.3629430529361,"r_eff_m":1127.494833936053,"directional":false,"heading_deg":0.0},{"channel":2,"x":478.441266630241,"y":449.08113076378316,"r_eff_m":1040.6068154097852,"directional":false,"heading_deg":0.0},{"channel":20,"x":-945.2003883886779,"y":638.5311986666989,"r_eff_m":1295.456469667405,"directional":false,"heading_deg":0.0},{"channel":4,"x":99.04602689897295,"y":1744.5260335974826,"r_eff_m":1032.9094604449615,"directional":false,"heading_deg":0.0},{"channel":5,"x":-1507.0542438070167,"y":761.3723575581047,"r_eff_m":1448.7977020579874,"directional":false,"heading_deg":0.0},{"channel":12,"x":-1188.1583136013294,"y":963.0220608398997,"r_eff_m":1226.2619264983982,"directional":false,"heading_deg":0.0},{"channel":19,"x":-177.4461437404443,"y":343.49207176417394,"r_eff_m":1277.3413627947266,"directional":false,"heading_deg":0.0}]}
|
||||||
|
{"event":"action","seq":1,"wall_ts_ms":1789265737816,"method":"POST","path":"/enter","status":200,"request":{"arena_id":"default","robot_id":"1","request_id":"baa9dc681441-0001"},"response":{"accepted":true,"real_timestamp_ms":1789265737816,"virtual_time_s":0.0,"max_virtual_duration_s":360000.0,"max_real_duration_s":1200,"remaining_real_duration_s":1200}}
|
||||||
|
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||||||
|
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||||||
|
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||||||
|
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|
{"event":"session_end","reason":"user_exit","virtual_time_s":8917.765542,"real_elapsed_s":10.027643,"request_count":427,"cleared_count":11}
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||||||
@@ -0,0 +1,429 @@
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|||||||
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{"event": "action", "seq": 2, "wall_ts_ms": 1789265737826, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0002", "position": {"x": 0.0, "y": 0.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265737826, "virtual_time_s": 5.0, "measure_result": "no_signal"}}
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||||||
|
{"event": "action", "seq": 3, "wall_ts_ms": 1789265737827, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0003", "position": {"x": 0.0, "y": 0.0}, "channel": 2}, "response": {"accepted": true, "real_timestamp_ms": 1789265737827, "virtual_time_s": 11.0, "measure_result": "direction", "svd_deg": 43.2}}
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|
{"event": "action", "seq": 4, "wall_ts_ms": 1789265737865, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0004", "position": {"x": 0.0, "y": 0.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265737865, "virtual_time_s": 17.0, "measure_result": "no_signal"}}
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||||||
|
{"event": "action", "seq": 5, "wall_ts_ms": 1789265737866, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0005", "position": {"x": 0.0, "y": 0.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265737866, "virtual_time_s": 23.0, "measure_result": "no_signal"}}
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||||||
|
{"event": "action", "seq": 6, "wall_ts_ms": 1789265737867, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0006", "position": {"x": 0.0, "y": 0.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265737867, "virtual_time_s": 29.0, "measure_result": "no_signal"}}
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||||||
|
{"event": "action", "seq": 7, "wall_ts_ms": 1789265737867, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0007", "position": {"x": 0.0, "y": 0.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265737867, "virtual_time_s": 35.0, "measure_result": "no_signal"}}
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||||||
|
{"event": "action", "seq": 8, "wall_ts_ms": 1789265737868, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0008", "position": {"x": 0.0, "y": 0.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265737868, "virtual_time_s": 41.0, "measure_result": "no_signal"}}
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||||||
|
{"event": "action", "seq": 9, "wall_ts_ms": 1789265737869, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0009", "position": {"x": 0.0, "y": 0.0}, "channel": 8}, "response": {"accepted": true, "real_timestamp_ms": 1789265737869, "virtual_time_s": 47.0, "measure_result": "no_signal"}}
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|
{"event": "action", "seq": 10, "wall_ts_ms": 1789265737869, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0010", "position": {"x": 0.0, "y": 0.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265737869, "virtual_time_s": 53.0, "measure_result": "no_signal"}}
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||||||
|
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|
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|
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||||||
|
{"event": "action", "seq": 14, "wall_ts_ms": 1789265737907, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0014", "position": {"x": 0.0, "y": 0.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265737907, "virtual_time_s": 77.0, "measure_result": "no_signal"}}
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|
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|
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||||||
|
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||||||
|
{"event": "action", "seq": 20, "wall_ts_ms": 1789265737947, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0020", "position": {"x": 0.0, "y": 0.0}, "channel": 19}, "response": {"accepted": true, "real_timestamp_ms": 1789265737947, "virtual_time_s": 113.0, "measure_result": "direction", "svd_deg": 117.36}}
|
||||||
|
{"event": "action", "seq": 21, "wall_ts_ms": 1789265737983, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0021", "position": {"x": 0.0, "y": 0.0}, "channel": 20}, "response": {"accepted": true, "real_timestamp_ms": 1789265737983, "virtual_time_s": 119.0, "measure_result": "direction", "svd_deg": 145.55}}
|
||||||
|
{"event": "action", "seq": 22, "wall_ts_ms": 1789265738125, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0022", "position": {"x": -79.66719841213751, "y": 400.9313670917169}, "channel": 19}, "response": {"accepted": true, "real_timestamp_ms": 1789265738125, "virtual_time_s": 206.753978, "measure_result": "direction", "svd_deg": 210.37}}
|
||||||
|
{"event": "action", "seq": 23, "wall_ts_ms": 1789265738127, "method": "POST", "path": "/clear", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0023", "position": {"x": -177.64052160825486, "y": 343.3794788045638}, "channel": 19}, "response": {"accepted": true, "real_timestamp_ms": 1789265738127, "virtual_time_s": 234.479287, "clear_result": "success"}}
|
||||||
|
{"event": "action", "seq": 24, "wall_ts_ms": 1789265738245, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0024", "position": {"x": -243.62294879732218, "y": 424.1621461926654}, "channel": 20}, "response": {"accepted": true, "real_timestamp_ms": 1789265738245, "virtual_time_s": 261.340275, "measure_result": "direction", "svd_deg": 162.22}}
|
||||||
|
{"event": "action", "seq": 25, "wall_ts_ms": 1789265738273, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0025", "position": {"x": -901.7130728821326, "y": 655.9084449749266}, "channel": 20}, "response": {"accepted": true, "real_timestamp_ms": 1789265738273, "virtual_time_s": 405.880801, "measure_result": "direction", "svd_deg": 202.15}}
|
||||||
|
{"event": "action", "seq": 26, "wall_ts_ms": 1789265738284, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0026", "position": {"x": -922.0070945081434, "y": 643.9441735456403}, "channel": 20}, "response": {"accepted": true, "real_timestamp_ms": 1789265738284, "virtual_time_s": 415.592451, "measure_result": "direction", "svd_deg": 193.27}}
|
||||||
|
{"event": "action", "seq": 27, "wall_ts_ms": 1789265738286, "method": "POST", "path": "/clear", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0027", "position": {"x": -943.9158056887892, "y": 638.8511609168044}, "channel": 20}, "response": {"accepted": true, "real_timestamp_ms": 1789265738286, "virtual_time_s": 425.09103, "clear_result": "success"}}
|
||||||
|
{"event": "action", "seq": 28, "wall_ts_ms": 1789265738445, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0028", "position": {"x": 155.06480714962538, "y": 530.7765221920923}, "channel": 10}, "response": {"accepted": true, "real_timestamp_ms": 1789265738445, "virtual_time_s": 651.94741, "measure_result": "direction", "svd_deg": 18.62}}
|
||||||
|
{"event": "action", "seq": 29, "wall_ts_ms": 1789265738475, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0029", "position": {"x": 691.0981141562518, "y": 722.9949655036279}, "channel": 10}, "response": {"accepted": true, "real_timestamp_ms": 1789265738475, "virtual_time_s": 770.838522, "measure_result": "direction", "svd_deg": 348.1}}
|
||||||
|
{"event": "action", "seq": 30, "wall_ts_ms": 1789265738490, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0030", "position": {"x": 704.6480025466224, "y": 718.3903941183868}, "channel": 10}, "response": {"accepted": true, "real_timestamp_ms": 1789265738490, "virtual_time_s": 778.7007, "measure_result": "direction", "svd_deg": 350.26}}
|
||||||
|
{"event": "action", "seq": 31, "wall_ts_ms": 1789265738492, "method": "POST", "path": "/clear", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0031", "position": {"x": 728.5054559976093, "y": 714.7247743974735}, "channel": 10}, "response": {"accepted": true, "real_timestamp_ms": 1789265738492, "virtual_time_s": 788.528183, "clear_result": "success"}}
|
||||||
|
{"event": "action", "seq": 32, "wall_ts_ms": 1789265738690, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0032", "position": {"x": 282.155927735649, "y": 778.2311705887862}, "channel": 2}, "response": {"accepted": true, "real_timestamp_ms": 1789265738690, "virtual_time_s": 884.697127, "measure_result": "direction", "svd_deg": 301.58}}
|
||||||
|
{"event": "action", "seq": 33, "wall_ts_ms": 1789265738692, "method": "POST", "path": "/clear", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0033", "position": {"x": 481.9384520825037, "y": 452.79231376594635}, "channel": 2}, "response": {"accepted": true, "real_timestamp_ms": 1789265738692, "virtual_time_s": 966.070815, "clear_result": "success"}}
|
||||||
|
{"event": "action", "seq": 34, "wall_ts_ms": 1789265738822, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0034", "position": {"x": 119.77278770558408, "y": -365.4630725746676}, "channel": 16}, "response": {"accepted": true, "real_timestamp_ms": 1789265738822, "virtual_time_s": 1151.035152, "measure_result": "direction", "svd_deg": 270.43}}
|
||||||
|
{"event": "action", "seq": 35, "wall_ts_ms": 1789265738857, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0035", "position": {"x": 125.50362627876382, "y": -724.3528216084252}, "channel": 16}, "response": {"accepted": true, "real_timestamp_ms": 1789265738857, "virtual_time_s": 1227.822252, "measure_result": "direction", "svd_deg": 268.9}}
|
||||||
|
{"event": "action", "seq": 36, "wall_ts_ms": 1789265738877, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0036", "position": {"x": 125.3777171626325, "y": -762.3214764994508}, "channel": 16}, "response": {"accepted": true, "real_timestamp_ms": 1789265738877, "virtual_time_s": 1240.416025, "measure_result": "direction", "svd_deg": 269.25}}
|
||||||
|
{"event": "action", "seq": 37, "wall_ts_ms": 1789265738893, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0037", "position": {"x": 125.31476260456685, "y": -790.7980024619326}, "channel": 16}, "response": {"accepted": true, "real_timestamp_ms": 1789265738893, "virtual_time_s": 1251.111344, "measure_result": "direction", "svd_deg": 269.45}}
|
||||||
|
{"event": "action", "seq": 38, "wall_ts_ms": 1789265738907, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0038", "position": {"x": 125.28328532553402, "y": -812.1554085318639}, "channel": 16}, "response": {"accepted": true, "real_timestamp_ms": 1789265738907, "virtual_time_s": 1260.38283, "measure_result": "direction", "svd_deg": 269.15999999999997}}
|
||||||
|
{"event": "action", "seq": 39, "wall_ts_ms": 1789265738919, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0039", "position": {"x": 125.2675466860176, "y": -828.1734669503353}, "channel": 16}, "response": {"accepted": true, "real_timestamp_ms": 1789265738919, "virtual_time_s": 1268.586443, "measure_result": "direction", "svd_deg": 268.21}}
|
||||||
|
{"event": "action", "seq": 40, "wall_ts_ms": 1789265738931, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0040", "position": {"x": 124.96644242180939, "y": -839.1602852992372}, "channel": 16}, "response": {"accepted": true, "real_timestamp_ms": 1789265738931, "virtual_time_s": 1275.784632, "measure_result": "direction", "svd_deg": 266.93}}
|
||||||
|
{"event": "action", "seq": 41, "wall_ts_ms": 1789265738933, "method": "POST", "path": "/clear", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0041", "position": {"x": 124.4615306510994, "y": -853.1635717026913}, "channel": 16}, "response": {"accepted": true, "real_timestamp_ms": 1789265738933, "virtual_time_s": 1283.587109, "clear_result": "success"}}
|
||||||
|
{"event": "action", "seq": 42, "wall_ts_ms": 1789265738934, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0042", "position": {"x": 200.0, "y": -900.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265738934, "virtual_time_s": 1307.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 43, "wall_ts_ms": 1789265738935, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0043", "position": {"x": 200.0, "y": -900.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265738935, "virtual_time_s": 1313.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 44, "wall_ts_ms": 1789265738936, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0044", "position": {"x": 200.0, "y": -900.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265738936, "virtual_time_s": 1319.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 45, "wall_ts_ms": 1789265738936, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0045", "position": {"x": 200.0, "y": -900.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265738936, "virtual_time_s": 1325.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 46, "wall_ts_ms": 1789265738937, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0046", "position": {"x": 200.0, "y": -900.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265738937, "virtual_time_s": 1331.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 47, "wall_ts_ms": 1789265738938, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0047", "position": {"x": 200.0, "y": -900.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265738938, "virtual_time_s": 1337.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 48, "wall_ts_ms": 1789265738939, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0048", "position": {"x": 200.0, "y": -900.0}, "channel": 8}, "response": {"accepted": true, "real_timestamp_ms": 1789265738939, "virtual_time_s": 1343.363173, "measure_result": "direction", "svd_deg": 352.99}}
|
||||||
|
{"event": "action", "seq": 49, "wall_ts_ms": 1789265738972, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0049", "position": {"x": 200.0, "y": -900.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265738972, "virtual_time_s": 1349.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 50, "wall_ts_ms": 1789265738973, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0050", "position": {"x": 200.0, "y": -900.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265738973, "virtual_time_s": 1355.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 51, "wall_ts_ms": 1789265738974, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0051", "position": {"x": 200.0, "y": -900.0}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265738974, "virtual_time_s": 1361.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 52, "wall_ts_ms": 1789265738975, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0052", "position": {"x": 200.0, "y": -900.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265738975, "virtual_time_s": 1367.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 53, "wall_ts_ms": 1789265738977, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0053", "position": {"x": 200.0, "y": -900.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265738977, "virtual_time_s": 1373.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 54, "wall_ts_ms": 1789265738978, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0054", "position": {"x": 200.0, "y": -900.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265738978, "virtual_time_s": 1379.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 55, "wall_ts_ms": 1789265738978, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0055", "position": {"x": 200.0, "y": -900.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265738978, "virtual_time_s": 1385.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 56, "wall_ts_ms": 1789265738979, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0056", "position": {"x": 200.0, "y": -900.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265738979, "virtual_time_s": 1391.363173, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 57, "wall_ts_ms": 1789265739081, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0057", "position": {"x": 516.6212801392332, "y": -966.9819199979597}, "channel": 8}, "response": {"accepted": true, "real_timestamp_ms": 1789265739081, "virtual_time_s": 1462.088937, "measure_result": "direction", "svd_deg": 357.38}}
|
||||||
|
{"event": "action", "seq": 58, "wall_ts_ms": 1789265739136, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0058", "position": {"x": 866.5933228570544, "y": -995.2814295412376}, "channel": 8}, "response": {"accepted": true, "real_timestamp_ms": 1789265739136, "virtual_time_s": 1537.311809, "measure_result": "direction", "svd_deg": 358.73}}
|
||||||
|
{"event": "action", "seq": 59, "wall_ts_ms": 1789265739167, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0059", "position": {"x": 1040.8377161691203, "y": -1003.1570563336973}, "channel": 8}, "response": {"accepted": true, "real_timestamp_ms": 1789265739167, "virtual_time_s": 1577.196266, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 60, "wall_ts_ms": 1789265739202, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0060", "position": {"x": 970.7414216957415, "y": -1003.1570563336973}, "channel": 8}, "response": {"accepted": true, "real_timestamp_ms": 1789265739202, "virtual_time_s": 1596.215525, "measure_result": "direction", "svd_deg": 41.87}}
|
||||||
|
{"event": "action", "seq": 61, "wall_ts_ms": 1789265739204, "method": "POST", "path": "/clear", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0061", "position": {"x": 978.7251752457973, "y": -996.0135773020329}, "channel": 8}, "response": {"accepted": true, "real_timestamp_ms": 1789265739204, "virtual_time_s": 1603.358137, "clear_result": "success"}}
|
||||||
|
{"event": "action", "seq": 62, "wall_ts_ms": 1789265739205, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0062", "position": {"x": 900.0, "y": -700.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739205, "virtual_time_s": 1670.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 63, "wall_ts_ms": 1789265739206, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0063", "position": {"x": 900.0, "y": -700.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739206, "virtual_time_s": 1676.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 64, "wall_ts_ms": 1789265739207, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0064", "position": {"x": 900.0, "y": -700.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739207, "virtual_time_s": 1682.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 65, "wall_ts_ms": 1789265739207, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0065", "position": {"x": 900.0, "y": -700.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739207, "virtual_time_s": 1688.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 66, "wall_ts_ms": 1789265739208, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0066", "position": {"x": 900.0, "y": -700.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739208, "virtual_time_s": 1694.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 67, "wall_ts_ms": 1789265739211, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0067", "position": {"x": 900.0, "y": -700.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739211, "virtual_time_s": 1700.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 68, "wall_ts_ms": 1789265739212, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0068", "position": {"x": 900.0, "y": -700.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739212, "virtual_time_s": 1706.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 69, "wall_ts_ms": 1789265739212, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0069", "position": {"x": 900.0, "y": -700.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739212, "virtual_time_s": 1712.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 70, "wall_ts_ms": 1789265739213, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0070", "position": {"x": 900.0, "y": -700.0}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739213, "virtual_time_s": 1718.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 71, "wall_ts_ms": 1789265739214, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0071", "position": {"x": 900.0, "y": -700.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739214, "virtual_time_s": 1724.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 72, "wall_ts_ms": 1789265739216, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0072", "position": {"x": 900.0, "y": -700.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739216, "virtual_time_s": 1730.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 73, "wall_ts_ms": 1789265739217, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0073", "position": {"x": 900.0, "y": -700.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739217, "virtual_time_s": 1736.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 74, "wall_ts_ms": 1789265739218, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0074", "position": {"x": 900.0, "y": -700.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739218, "virtual_time_s": 1742.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 75, "wall_ts_ms": 1789265739219, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0075", "position": {"x": 900.0, "y": -700.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739219, "virtual_time_s": 1748.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 76, "wall_ts_ms": 1789265739219, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0076", "position": {"x": 1200.0, "y": -700.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739219, "virtual_time_s": 1813.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 77, "wall_ts_ms": 1789265739220, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0077", "position": {"x": 1200.0, "y": -700.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739220, "virtual_time_s": 1819.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 78, "wall_ts_ms": 1789265739221, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0078", "position": {"x": 1200.0, "y": -700.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739221, "virtual_time_s": 1825.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 79, "wall_ts_ms": 1789265739221, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0079", "position": {"x": 1200.0, "y": -700.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739221, "virtual_time_s": 1831.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 80, "wall_ts_ms": 1789265739222, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0080", "position": {"x": 1200.0, "y": -700.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739222, "virtual_time_s": 1837.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 81, "wall_ts_ms": 1789265739223, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0081", "position": {"x": 1200.0, "y": -700.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739223, "virtual_time_s": 1843.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 82, "wall_ts_ms": 1789265739223, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0082", "position": {"x": 1200.0, "y": -700.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739223, "virtual_time_s": 1849.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 83, "wall_ts_ms": 1789265739224, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0083", "position": {"x": 1200.0, "y": -700.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739224, "virtual_time_s": 1855.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 84, "wall_ts_ms": 1789265739225, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0084", "position": {"x": 1200.0, "y": -700.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739225, "virtual_time_s": 1861.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 85, "wall_ts_ms": 1789265739226, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0085", "position": {"x": 1200.0, "y": -700.0}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739226, "virtual_time_s": 1867.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 86, "wall_ts_ms": 1789265739226, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0086", "position": {"x": 1200.0, "y": -700.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739226, "virtual_time_s": 1873.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 87, "wall_ts_ms": 1789265739227, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0087", "position": {"x": 1200.0, "y": -700.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739227, "virtual_time_s": 1879.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 88, "wall_ts_ms": 1789265739228, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0088", "position": {"x": 1200.0, "y": -700.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739228, "virtual_time_s": 1885.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 89, "wall_ts_ms": 1789265739228, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0089", "position": {"x": 1200.0, "y": -700.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739228, "virtual_time_s": 1891.61879, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 90, "wall_ts_ms": 1789265739229, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0090", "position": {"x": 1800.0, "y": -400.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739229, "virtual_time_s": 2030.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 91, "wall_ts_ms": 1789265739230, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0091", "position": {"x": 1800.0, "y": -400.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739230, "virtual_time_s": 2036.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 92, "wall_ts_ms": 1789265739230, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0092", "position": {"x": 1800.0, "y": -400.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739230, "virtual_time_s": 2042.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 93, "wall_ts_ms": 1789265739231, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0093", "position": {"x": 1800.0, "y": -400.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739231, "virtual_time_s": 2048.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 94, "wall_ts_ms": 1789265739232, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0094", "position": {"x": 1800.0, "y": -400.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739232, "virtual_time_s": 2054.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 95, "wall_ts_ms": 1789265739233, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0095", "position": {"x": 1800.0, "y": -400.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739233, "virtual_time_s": 2060.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 96, "wall_ts_ms": 1789265739233, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0096", "position": {"x": 1800.0, "y": -400.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739233, "virtual_time_s": 2066.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 97, "wall_ts_ms": 1789265739234, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0097", "position": {"x": 1800.0, "y": -400.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739234, "virtual_time_s": 2072.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 98, "wall_ts_ms": 1789265739234, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0098", "position": {"x": 1800.0, "y": -400.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739234, "virtual_time_s": 2078.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 99, "wall_ts_ms": 1789265739235, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0099", "position": {"x": 1800.0, "y": -400.0}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739235, "virtual_time_s": 2084.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 100, "wall_ts_ms": 1789265739236, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0100", "position": {"x": 1800.0, "y": -400.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739236, "virtual_time_s": 2090.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 101, "wall_ts_ms": 1789265739236, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0101", "position": {"x": 1800.0, "y": -400.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739236, "virtual_time_s": 2096.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 102, "wall_ts_ms": 1789265739237, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0102", "position": {"x": 1800.0, "y": -400.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739237, "virtual_time_s": 2102.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 103, "wall_ts_ms": 1789265739238, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0103", "position": {"x": 1800.0, "y": -400.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739238, "virtual_time_s": 2108.782869, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 104, "wall_ts_ms": 1789265739238, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0104", "position": {"x": 1900.0, "y": -900.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739238, "virtual_time_s": 2215.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 105, "wall_ts_ms": 1789265739239, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0105", "position": {"x": 1900.0, "y": -900.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739239, "virtual_time_s": 2221.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 106, "wall_ts_ms": 1789265739240, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0106", "position": {"x": 1900.0, "y": -900.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739240, "virtual_time_s": 2227.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 107, "wall_ts_ms": 1789265739240, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0107", "position": {"x": 1900.0, "y": -900.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739240, "virtual_time_s": 2233.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 108, "wall_ts_ms": 1789265739241, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0108", "position": {"x": 1900.0, "y": -900.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739241, "virtual_time_s": 2239.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 109, "wall_ts_ms": 1789265739241, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0109", "position": {"x": 1900.0, "y": -900.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739241, "virtual_time_s": 2245.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 110, "wall_ts_ms": 1789265739242, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0110", "position": {"x": 1900.0, "y": -900.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739242, "virtual_time_s": 2251.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 111, "wall_ts_ms": 1789265739242, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0111", "position": {"x": 1900.0, "y": -900.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739242, "virtual_time_s": 2257.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 112, "wall_ts_ms": 1789265739243, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0112", "position": {"x": 1900.0, "y": -900.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739243, "virtual_time_s": 2263.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 113, "wall_ts_ms": 1789265739244, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0113", "position": {"x": 1900.0, "y": -900.0}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739244, "virtual_time_s": 2269.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 114, "wall_ts_ms": 1789265739244, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0114", "position": {"x": 1900.0, "y": -900.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739244, "virtual_time_s": 2275.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 115, "wall_ts_ms": 1789265739245, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0115", "position": {"x": 1900.0, "y": -900.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739245, "virtual_time_s": 2281.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 116, "wall_ts_ms": 1789265739246, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0116", "position": {"x": 1900.0, "y": -900.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739246, "virtual_time_s": 2287.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 117, "wall_ts_ms": 1789265739247, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0117", "position": {"x": 1900.0, "y": -900.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739247, "virtual_time_s": 2293.763259, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 118, "wall_ts_ms": 1789265739248, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0118", "position": {"x": 1400.0, "y": -1400.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739248, "virtual_time_s": 2440.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 119, "wall_ts_ms": 1789265739249, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0119", "position": {"x": 1400.0, "y": -1400.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739249, "virtual_time_s": 2446.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 120, "wall_ts_ms": 1789265739249, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0120", "position": {"x": 1400.0, "y": -1400.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739249, "virtual_time_s": 2452.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 121, "wall_ts_ms": 1789265739250, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0121", "position": {"x": 1400.0, "y": -1400.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739250, "virtual_time_s": 2458.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 122, "wall_ts_ms": 1789265739251, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0122", "position": {"x": 1400.0, "y": -1400.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739251, "virtual_time_s": 2464.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 123, "wall_ts_ms": 1789265739251, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0123", "position": {"x": 1400.0, "y": -1400.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739251, "virtual_time_s": 2470.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 124, "wall_ts_ms": 1789265739252, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0124", "position": {"x": 1400.0, "y": -1400.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739252, "virtual_time_s": 2476.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 125, "wall_ts_ms": 1789265739253, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0125", "position": {"x": 1400.0, "y": -1400.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739252, "virtual_time_s": 2482.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 126, "wall_ts_ms": 1789265739253, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0126", "position": {"x": 1400.0, "y": -1400.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739253, "virtual_time_s": 2488.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 127, "wall_ts_ms": 1789265739254, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0127", "position": {"x": 1400.0, "y": -1400.0}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739254, "virtual_time_s": 2494.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 128, "wall_ts_ms": 1789265739254, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0128", "position": {"x": 1400.0, "y": -1400.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739254, "virtual_time_s": 2500.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 129, "wall_ts_ms": 1789265739255, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0129", "position": {"x": 1400.0, "y": -1400.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739255, "virtual_time_s": 2506.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 130, "wall_ts_ms": 1789265739255, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0130", "position": {"x": 1400.0, "y": -1400.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739255, "virtual_time_s": 2512.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 131, "wall_ts_ms": 1789265739256, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0131", "position": {"x": 1400.0, "y": -1400.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739256, "virtual_time_s": 2518.184615, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 132, "wall_ts_ms": 1789265739256, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0132", "position": {"x": 500.0, "y": -1800.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739256, "virtual_time_s": 2720.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 133, "wall_ts_ms": 1789265739257, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0133", "position": {"x": 500.0, "y": -1800.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739257, "virtual_time_s": 2726.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 134, "wall_ts_ms": 1789265739258, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0134", "position": {"x": 500.0, "y": -1800.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739258, "virtual_time_s": 2732.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 135, "wall_ts_ms": 1789265739258, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0135", "position": {"x": 500.0, "y": -1800.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739258, "virtual_time_s": 2738.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 136, "wall_ts_ms": 1789265739259, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0136", "position": {"x": 500.0, "y": -1800.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739259, "virtual_time_s": 2744.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 137, "wall_ts_ms": 1789265739260, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0137", "position": {"x": 500.0, "y": -1800.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739260, "virtual_time_s": 2750.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 138, "wall_ts_ms": 1789265739260, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0138", "position": {"x": 500.0, "y": -1800.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739260, "virtual_time_s": 2756.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 139, "wall_ts_ms": 1789265739261, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0139", "position": {"x": 500.0, "y": -1800.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739261, "virtual_time_s": 2762.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 140, "wall_ts_ms": 1789265739262, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0140", "position": {"x": 500.0, "y": -1800.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739262, "virtual_time_s": 2768.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 141, "wall_ts_ms": 1789265739262, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0141", "position": {"x": 500.0, "y": -1800.0}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739262, "virtual_time_s": 2774.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 142, "wall_ts_ms": 1789265739263, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0142", "position": {"x": 500.0, "y": -1800.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739263, "virtual_time_s": 2780.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 143, "wall_ts_ms": 1789265739263, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0143", "position": {"x": 500.0, "y": -1800.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739263, "virtual_time_s": 2786.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 144, "wall_ts_ms": 1789265739264, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0144", "position": {"x": 500.0, "y": -1800.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739264, "virtual_time_s": 2792.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 145, "wall_ts_ms": 1789265739264, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0145", "position": {"x": 500.0, "y": -1800.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739264, "virtual_time_s": 2798.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 146, "wall_ts_ms": 1789265739265, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0146", "position": {"x": -400.0, "y": -1800.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739265, "virtual_time_s": 2983.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 147, "wall_ts_ms": 1789265739266, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0147", "position": {"x": -400.0, "y": -1800.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739266, "virtual_time_s": 2989.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 148, "wall_ts_ms": 1789265739266, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0148", "position": {"x": -400.0, "y": -1800.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739266, "virtual_time_s": 2995.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 149, "wall_ts_ms": 1789265739267, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0149", "position": {"x": -400.0, "y": -1800.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739267, "virtual_time_s": 3001.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 150, "wall_ts_ms": 1789265739267, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0150", "position": {"x": -400.0, "y": -1800.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739267, "virtual_time_s": 3007.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 151, "wall_ts_ms": 1789265739268, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0151", "position": {"x": -400.0, "y": -1800.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739268, "virtual_time_s": 3013.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 152, "wall_ts_ms": 1789265739268, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0152", "position": {"x": -400.0, "y": -1800.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739268, "virtual_time_s": 3019.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 153, "wall_ts_ms": 1789265739269, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0153", "position": {"x": -400.0, "y": -1800.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739269, "virtual_time_s": 3025.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 154, "wall_ts_ms": 1789265739270, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0154", "position": {"x": -400.0, "y": -1800.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739270, "virtual_time_s": 3031.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 155, "wall_ts_ms": 1789265739270, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0155", "position": {"x": -400.0, "y": -1800.0}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739270, "virtual_time_s": 3037.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 156, "wall_ts_ms": 1789265739271, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0156", "position": {"x": -400.0, "y": -1800.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739271, "virtual_time_s": 3043.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 157, "wall_ts_ms": 1789265739271, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0157", "position": {"x": -400.0, "y": -1800.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739271, "virtual_time_s": 3049.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 158, "wall_ts_ms": 1789265739272, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0158", "position": {"x": -400.0, "y": -1800.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739272, "virtual_time_s": 3055.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 159, "wall_ts_ms": 1789265739273, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0159", "position": {"x": -400.0, "y": -1800.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739273, "virtual_time_s": 3061.161771, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 160, "wall_ts_ms": 1789265739273, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0160", "position": {"x": -900.0, "y": -2100.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739273, "virtual_time_s": 3182.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 161, "wall_ts_ms": 1789265739274, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0161", "position": {"x": -900.0, "y": -2100.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739274, "virtual_time_s": 3188.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 162, "wall_ts_ms": 1789265739275, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0162", "position": {"x": -900.0, "y": -2100.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739275, "virtual_time_s": 3194.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 163, "wall_ts_ms": 1789265739275, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0163", "position": {"x": -900.0, "y": -2100.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739275, "virtual_time_s": 3200.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 164, "wall_ts_ms": 1789265739276, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0164", "position": {"x": -900.0, "y": -2100.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739276, "virtual_time_s": 3206.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 165, "wall_ts_ms": 1789265739277, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0165", "position": {"x": -900.0, "y": -2100.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739277, "virtual_time_s": 3212.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 166, "wall_ts_ms": 1789265739277, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0166", "position": {"x": -900.0, "y": -2100.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739277, "virtual_time_s": 3218.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 167, "wall_ts_ms": 1789265739278, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0167", "position": {"x": -900.0, "y": -2100.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739278, "virtual_time_s": 3224.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 168, "wall_ts_ms": 1789265739279, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0168", "position": {"x": -900.0, "y": -2100.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739279, "virtual_time_s": 3230.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 169, "wall_ts_ms": 1789265739279, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0169", "position": {"x": -900.0, "y": -2100.0}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739279, "virtual_time_s": 3236.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 170, "wall_ts_ms": 1789265739280, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0170", "position": {"x": -900.0, "y": -2100.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739280, "virtual_time_s": 3242.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 171, "wall_ts_ms": 1789265739280, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0171", "position": {"x": -900.0, "y": -2100.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739280, "virtual_time_s": 3248.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 172, "wall_ts_ms": 1789265739281, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0172", "position": {"x": -900.0, "y": -2100.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739281, "virtual_time_s": 3254.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 173, "wall_ts_ms": 1789265739281, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0173", "position": {"x": -900.0, "y": -2100.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739281, "virtual_time_s": 3260.780809, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 174, "wall_ts_ms": 1789265739283, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0174", "position": {"x": -700.0, "y": -1200.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739283, "virtual_time_s": 3450.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 175, "wall_ts_ms": 1789265739284, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0175", "position": {"x": -700.0, "y": -1200.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739284, "virtual_time_s": 3456.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 176, "wall_ts_ms": 1789265739285, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0176", "position": {"x": -700.0, "y": -1200.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739285, "virtual_time_s": 3462.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 177, "wall_ts_ms": 1789265739286, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0177", "position": {"x": -700.0, "y": -1200.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739286, "virtual_time_s": 3468.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 178, "wall_ts_ms": 1789265739286, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0178", "position": {"x": -700.0, "y": -1200.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739286, "virtual_time_s": 3474.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 179, "wall_ts_ms": 1789265739287, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0179", "position": {"x": -700.0, "y": -1200.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739287, "virtual_time_s": 3480.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 180, "wall_ts_ms": 1789265739288, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0180", "position": {"x": -700.0, "y": -1200.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739288, "virtual_time_s": 3486.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 181, "wall_ts_ms": 1789265739289, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0181", "position": {"x": -700.0, "y": -1200.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739288, "virtual_time_s": 3492.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 182, "wall_ts_ms": 1789265739289, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0182", "position": {"x": -700.0, "y": -1200.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739289, "virtual_time_s": 3498.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 183, "wall_ts_ms": 1789265739290, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0183", "position": {"x": -700.0, "y": -1200.0}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739290, "virtual_time_s": 3504.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 184, "wall_ts_ms": 1789265739290, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0184", "position": {"x": -700.0, "y": -1200.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739290, "virtual_time_s": 3510.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 185, "wall_ts_ms": 1789265739291, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0185", "position": {"x": -700.0, "y": -1200.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739291, "virtual_time_s": 3516.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 186, "wall_ts_ms": 1789265739292, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0186", "position": {"x": -700.0, "y": -1200.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739292, "virtual_time_s": 3522.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 187, "wall_ts_ms": 1789265739292, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0187", "position": {"x": -700.0, "y": -1200.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739292, "virtual_time_s": 3528.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 188, "wall_ts_ms": 1789265739293, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0188", "position": {"x": -700.0, "y": -700.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739293, "virtual_time_s": 3633.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 189, "wall_ts_ms": 1789265739303, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0189", "position": {"x": -700.0, "y": -700.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739303, "virtual_time_s": 3639.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 190, "wall_ts_ms": 1789265739305, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0190", "position": {"x": -700.0, "y": -700.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739305, "virtual_time_s": 3645.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 191, "wall_ts_ms": 1789265739306, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0191", "position": {"x": -700.0, "y": -700.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739306, "virtual_time_s": 3651.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 192, "wall_ts_ms": 1789265739306, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0192", "position": {"x": -700.0, "y": -700.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739306, "virtual_time_s": 3657.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 193, "wall_ts_ms": 1789265739307, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0193", "position": {"x": -700.0, "y": -700.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739307, "virtual_time_s": 3663.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 194, "wall_ts_ms": 1789265739308, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0194", "position": {"x": -700.0, "y": -700.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739308, "virtual_time_s": 3669.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 195, "wall_ts_ms": 1789265739309, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0195", "position": {"x": -700.0, "y": -700.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739309, "virtual_time_s": 3675.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 196, "wall_ts_ms": 1789265739310, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0196", "position": {"x": -700.0, "y": -700.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739310, "virtual_time_s": 3681.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 197, "wall_ts_ms": 1789265739310, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0197", "position": {"x": -700.0, "y": -700.0}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739310, "virtual_time_s": 3687.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 198, "wall_ts_ms": 1789265739311, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0198", "position": {"x": -700.0, "y": -700.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739311, "virtual_time_s": 3693.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 199, "wall_ts_ms": 1789265739312, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0199", "position": {"x": -700.0, "y": -700.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739312, "virtual_time_s": 3699.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 200, "wall_ts_ms": 1789265739313, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0200", "position": {"x": -700.0, "y": -700.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739313, "virtual_time_s": 3705.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 201, "wall_ts_ms": 1789265739313, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0201", "position": {"x": -700.0, "y": -700.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739313, "virtual_time_s": 3711.171698, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 202, "wall_ts_ms": 1789265739314, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0202", "position": {"x": -800.0, "y": -200.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739314, "virtual_time_s": 3818.152088, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 203, "wall_ts_ms": 1789265739315, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0203", "position": {"x": -800.0, "y": -200.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739315, "virtual_time_s": 3824.152088, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 204, "wall_ts_ms": 1789265739316, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0204", "position": {"x": -800.0, "y": -200.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739316, "virtual_time_s": 3830.152088, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 205, "wall_ts_ms": 1789265739316, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0205", "position": {"x": -800.0, "y": -200.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739316, "virtual_time_s": 3836.152088, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 206, "wall_ts_ms": 1789265739317, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0206", "position": {"x": -800.0, "y": -200.0}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739317, "virtual_time_s": 3842.152088, "measure_result": "direction", "svd_deg": 126.11}}
|
||||||
|
{"event": "action", "seq": 207, "wall_ts_ms": 1789265739355, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0207", "position": {"x": -800.0, "y": -200.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739355, "virtual_time_s": 3848.152088, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 208, "wall_ts_ms": 1789265739356, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0208", "position": {"x": -800.0, "y": -200.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739356, "virtual_time_s": 3854.152088, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 209, "wall_ts_ms": 1789265739356, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0209", "position": {"x": -800.0, "y": -200.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739356, "virtual_time_s": 3860.152088, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 210, "wall_ts_ms": 1789265739357, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0210", "position": {"x": -800.0, "y": -200.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739357, "virtual_time_s": 3866.152088, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 211, "wall_ts_ms": 1789265739358, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0211", "position": {"x": -800.0, "y": -200.0}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739358, "virtual_time_s": 3872.152088, "measure_result": "direction", "svd_deg": 108.11}}
|
||||||
|
{"event": "action", "seq": 212, "wall_ts_ms": 1789265739392, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0212", "position": {"x": -800.0, "y": -200.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739392, "virtual_time_s": 3878.152088, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 213, "wall_ts_ms": 1789265739393, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0213", "position": {"x": -800.0, "y": -200.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739393, "virtual_time_s": 3884.152088, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 214, "wall_ts_ms": 1789265739394, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0214", "position": {"x": -800.0, "y": -200.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739394, "virtual_time_s": 3890.152088, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 215, "wall_ts_ms": 1789265739394, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0215", "position": {"x": -800.0, "y": -200.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739394, "virtual_time_s": 3896.152088, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 216, "wall_ts_ms": 1789265739503, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0216", "position": {"x": -947.4060451871933, "y": 109.11837968521047}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739503, "virtual_time_s": 3970.645216, "measure_result": "direction", "svd_deg": 131.32}}
|
||||||
|
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||||||
|
{"event": "action", "seq": 218, "wall_ts_ms": 1789265739594, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0218", "position": {"x": -1432.2923947371212, "y": 690.0535132542623}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739594, "virtual_time_s": 4131.98888, "measure_result": "direction", "svd_deg": 136.57}}
|
||||||
|
{"event": "action", "seq": 219, "wall_ts_ms": 1789265739609, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0219", "position": {"x": -1483.0245877461791, "y": 738.3058311207313}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739609, "virtual_time_s": 4150.991796, "measure_result": "direction", "svd_deg": 135.43}}
|
||||||
|
{"event": "action", "seq": 220, "wall_ts_ms": 1789265739622, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0220", "position": {"x": -1494.2794165389562, "y": 749.8626130220727}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739622, "virtual_time_s": 4159.218128, "measure_result": "direction", "svd_deg": 137.48}}
|
||||||
|
{"event": "action", "seq": 221, "wall_ts_ms": 1789265739623, "method": "POST", "path": "/clear", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0221", "position": {"x": -1505.3219950372888, "y": 760.3331531575229}, "channel": 5}, "response": {"accepted": true, "real_timestamp_ms": 1789265739623, "virtual_time_s": 4167.261618, "clear_result": "success"}}
|
||||||
|
{"event": "action", "seq": 222, "wall_ts_ms": 1789265739805, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0222", "position": {"x": -1408.4825659904257, "y": 512.8845928212788}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739805, "virtual_time_s": 4226.4062, "measure_result": "direction", "svd_deg": 63.41}}
|
||||||
|
{"event": "action", "seq": 223, "wall_ts_ms": 1789265739822, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0223", "position": {"x": -1195.7660646685601, "y": 953.7522119734411}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739822, "virtual_time_s": 4329.306673, "measure_result": "direction", "svd_deg": 51.15}}
|
||||||
|
{"event": "action", "seq": 224, "wall_ts_ms": 1789265739830, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0224", "position": {"x": -1189.5871642775382, "y": 964.1176386186069}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739830, "virtual_time_s": 4336.720143, "measure_result": "near"}}
|
||||||
|
{"event": "action", "seq": 225, "wall_ts_ms": 1789265739831, "method": "POST", "path": "/clear", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0225", "position": {"x": -1188.4182050448148, "y": 963.2096685709439}, "channel": 12}, "response": {"accepted": true, "real_timestamp_ms": 1789265739831, "virtual_time_s": 4342.016175, "clear_result": "success"}}
|
||||||
|
{"event": "action", "seq": 226, "wall_ts_ms": 1789265739832, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0226", "position": {"x": -1200.0, "y": 700.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739832, "virtual_time_s": 4400.709046, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 227, "wall_ts_ms": 1789265739833, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0227", "position": {"x": -1200.0, "y": 700.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739833, "virtual_time_s": 4406.709046, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 228, "wall_ts_ms": 1789265739834, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0228", "position": {"x": -1200.0, "y": 700.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739834, "virtual_time_s": 4412.709046, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 229, "wall_ts_ms": 1789265739834, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0229", "position": {"x": -1200.0, "y": 700.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739834, "virtual_time_s": 4418.709046, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 230, "wall_ts_ms": 1789265739835, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0230", "position": {"x": -1200.0, "y": 700.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739835, "virtual_time_s": 4424.709046, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 231, "wall_ts_ms": 1789265739836, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0231", "position": {"x": -1200.0, "y": 700.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739836, "virtual_time_s": 4430.709046, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 232, "wall_ts_ms": 1789265739836, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0232", "position": {"x": -1200.0, "y": 700.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739836, "virtual_time_s": 4436.709046, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 233, "wall_ts_ms": 1789265739837, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0233", "position": {"x": -1200.0, "y": 700.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739837, "virtual_time_s": 4442.709046, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 234, "wall_ts_ms": 1789265739838, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0234", "position": {"x": -1200.0, "y": 700.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739838, "virtual_time_s": 4448.709046, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 235, "wall_ts_ms": 1789265739838, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0235", "position": {"x": -1200.0, "y": 700.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739838, "virtual_time_s": 4454.709046, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 236, "wall_ts_ms": 1789265739839, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0236", "position": {"x": -1200.0, "y": 700.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739839, "virtual_time_s": 4460.709046, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 237, "wall_ts_ms": 1789265739840, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0237", "position": {"x": -1200.0, "y": 700.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739840, "virtual_time_s": 4466.709046, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 238, "wall_ts_ms": 1789265739840, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0238", "position": {"x": -1800.0, "y": 400.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739840, "virtual_time_s": 4605.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 239, "wall_ts_ms": 1789265739841, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0239", "position": {"x": -1800.0, "y": 400.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739841, "virtual_time_s": 4611.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 240, "wall_ts_ms": 1789265739842, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0240", "position": {"x": -1800.0, "y": 400.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739842, "virtual_time_s": 4617.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 241, "wall_ts_ms": 1789265739842, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0241", "position": {"x": -1800.0, "y": 400.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739842, "virtual_time_s": 4623.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 242, "wall_ts_ms": 1789265739843, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0242", "position": {"x": -1800.0, "y": 400.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739843, "virtual_time_s": 4629.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 243, "wall_ts_ms": 1789265739843, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0243", "position": {"x": -1800.0, "y": 400.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739843, "virtual_time_s": 4635.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 244, "wall_ts_ms": 1789265739844, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0244", "position": {"x": -1800.0, "y": 400.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739844, "virtual_time_s": 4641.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 245, "wall_ts_ms": 1789265739845, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0245", "position": {"x": -1800.0, "y": 400.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739845, "virtual_time_s": 4647.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 246, "wall_ts_ms": 1789265739845, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0246", "position": {"x": -1800.0, "y": 400.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739845, "virtual_time_s": 4653.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 247, "wall_ts_ms": 1789265739846, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0247", "position": {"x": -1800.0, "y": 400.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739846, "virtual_time_s": 4659.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 248, "wall_ts_ms": 1789265739846, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0248", "position": {"x": -1800.0, "y": 400.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739846, "virtual_time_s": 4665.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 249, "wall_ts_ms": 1789265739848, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0249", "position": {"x": -1800.0, "y": 400.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739848, "virtual_time_s": 4671.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 250, "wall_ts_ms": 1789265739849, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0250", "position": {"x": -1800.0, "y": -300.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739848, "virtual_time_s": 4816.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 251, "wall_ts_ms": 1789265739849, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0251", "position": {"x": -1800.0, "y": -300.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739849, "virtual_time_s": 4822.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 252, "wall_ts_ms": 1789265739850, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0252", "position": {"x": -1800.0, "y": -300.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739850, "virtual_time_s": 4828.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 253, "wall_ts_ms": 1789265739850, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0253", "position": {"x": -1800.0, "y": -300.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739850, "virtual_time_s": 4834.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 254, "wall_ts_ms": 1789265739851, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0254", "position": {"x": -1800.0, "y": -300.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739851, "virtual_time_s": 4840.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 255, "wall_ts_ms": 1789265739851, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0255", "position": {"x": -1800.0, "y": -300.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739851, "virtual_time_s": 4846.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 256, "wall_ts_ms": 1789265739852, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0256", "position": {"x": -1800.0, "y": -300.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739852, "virtual_time_s": 4852.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 257, "wall_ts_ms": 1789265739852, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0257", "position": {"x": -1800.0, "y": -300.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739852, "virtual_time_s": 4858.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 258, "wall_ts_ms": 1789265739853, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0258", "position": {"x": -1800.0, "y": -300.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739853, "virtual_time_s": 4864.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 259, "wall_ts_ms": 1789265739854, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0259", "position": {"x": -1800.0, "y": -300.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739854, "virtual_time_s": 4870.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 260, "wall_ts_ms": 1789265739854, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0260", "position": {"x": -1800.0, "y": -300.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739854, "virtual_time_s": 4876.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 261, "wall_ts_ms": 1789265739855, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0261", "position": {"x": -1800.0, "y": -300.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739855, "virtual_time_s": 4882.873125, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 262, "wall_ts_ms": 1789265739855, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0262", "position": {"x": -1700.0, "y": -500.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739855, "virtual_time_s": 4932.594485, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 263, "wall_ts_ms": 1789265739856, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0263", "position": {"x": -1700.0, "y": -500.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739856, "virtual_time_s": 4938.594485, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 264, "wall_ts_ms": 1789265739856, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0264", "position": {"x": -1700.0, "y": -500.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739856, "virtual_time_s": 4944.594485, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 265, "wall_ts_ms": 1789265739857, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0265", "position": {"x": -1700.0, "y": -500.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739857, "virtual_time_s": 4950.594485, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 266, "wall_ts_ms": 1789265739858, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0266", "position": {"x": -1700.0, "y": -500.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739858, "virtual_time_s": 4956.594485, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 267, "wall_ts_ms": 1789265739858, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0267", "position": {"x": -1700.0, "y": -500.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739858, "virtual_time_s": 4962.594485, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 268, "wall_ts_ms": 1789265739859, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0268", "position": {"x": -1700.0, "y": -500.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739859, "virtual_time_s": 4968.594485, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 269, "wall_ts_ms": 1789265739859, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0269", "position": {"x": -1700.0, "y": -500.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739859, "virtual_time_s": 4974.594485, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 270, "wall_ts_ms": 1789265739860, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0270", "position": {"x": -1700.0, "y": -500.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739860, "virtual_time_s": 4980.594485, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 271, "wall_ts_ms": 1789265739860, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0271", "position": {"x": -1700.0, "y": -500.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739860, "virtual_time_s": 4986.594485, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 272, "wall_ts_ms": 1789265739861, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0272", "position": {"x": -1700.0, "y": -500.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739861, "virtual_time_s": 4992.594485, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 273, "wall_ts_ms": 1789265739861, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0273", "position": {"x": -1700.0, "y": -500.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739861, "virtual_time_s": 4998.594485, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 274, "wall_ts_ms": 1789265739862, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0274", "position": {"x": -1500.0, "y": -1300.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739862, "virtual_time_s": 5168.51871, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 275, "wall_ts_ms": 1789265739863, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0275", "position": {"x": -1500.0, "y": -1300.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739863, "virtual_time_s": 5174.51871, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 276, "wall_ts_ms": 1789265739863, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0276", "position": {"x": -1500.0, "y": -1300.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739863, "virtual_time_s": 5180.51871, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 277, "wall_ts_ms": 1789265739864, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0277", "position": {"x": -1500.0, "y": -1300.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739864, "virtual_time_s": 5186.51871, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 278, "wall_ts_ms": 1789265739864, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0278", "position": {"x": -1500.0, "y": -1300.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739864, "virtual_time_s": 5192.51871, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 279, "wall_ts_ms": 1789265739865, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0279", "position": {"x": -1500.0, "y": -1300.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739865, "virtual_time_s": 5198.51871, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 280, "wall_ts_ms": 1789265739865, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0280", "position": {"x": -1500.0, "y": -1300.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739865, "virtual_time_s": 5204.51871, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 281, "wall_ts_ms": 1789265739866, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0281", "position": {"x": -1500.0, "y": -1300.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739866, "virtual_time_s": 5210.51871, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 282, "wall_ts_ms": 1789265739867, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0282", "position": {"x": -1500.0, "y": -1300.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739867, "virtual_time_s": 5216.51871, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 283, "wall_ts_ms": 1789265739867, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0283", "position": {"x": -1500.0, "y": -1300.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739867, "virtual_time_s": 5222.51871, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 284, "wall_ts_ms": 1789265739868, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0284", "position": {"x": -1500.0, "y": -1300.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739868, "virtual_time_s": 5228.51871, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 285, "wall_ts_ms": 1789265739868, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0285", "position": {"x": -1500.0, "y": -1300.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739868, "virtual_time_s": 5234.51871, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 286, "wall_ts_ms": 1789265739869, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0286", "position": {"x": -2500.0, "y": 500.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739869, "virtual_time_s": 5651.343916, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 287, "wall_ts_ms": 1789265739869, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0287", "position": {"x": -2500.0, "y": 500.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739869, "virtual_time_s": 5657.343916, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 288, "wall_ts_ms": 1789265739870, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0288", "position": {"x": -2500.0, "y": 500.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739870, "virtual_time_s": 5663.343916, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 289, "wall_ts_ms": 1789265739871, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0289", "position": {"x": -2500.0, "y": 500.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739870, "virtual_time_s": 5669.343916, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 290, "wall_ts_ms": 1789265739871, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0290", "position": {"x": -2500.0, "y": 500.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739871, "virtual_time_s": 5675.343916, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 291, "wall_ts_ms": 1789265739872, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0291", "position": {"x": -2500.0, "y": 500.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739872, "virtual_time_s": 5681.343916, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 292, "wall_ts_ms": 1789265739872, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0292", "position": {"x": -2500.0, "y": 500.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739872, "virtual_time_s": 5687.343916, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 293, "wall_ts_ms": 1789265739873, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0293", "position": {"x": -2500.0, "y": 500.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739873, "virtual_time_s": 5693.343916, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 294, "wall_ts_ms": 1789265739873, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0294", "position": {"x": -2500.0, "y": 500.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739873, "virtual_time_s": 5699.343916, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 295, "wall_ts_ms": 1789265739874, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0295", "position": {"x": -2500.0, "y": 500.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739874, "virtual_time_s": 5705.343916, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 296, "wall_ts_ms": 1789265739874, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0296", "position": {"x": -2500.0, "y": 500.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739874, "virtual_time_s": 5711.343916, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 297, "wall_ts_ms": 1789265739875, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0297", "position": {"x": -2500.0, "y": 500.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739875, "virtual_time_s": 5717.343916, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 298, "wall_ts_ms": 1789265739876, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0298", "position": {"x": -1300.0, "y": 1500.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739876, "virtual_time_s": 6034.753903, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 299, "wall_ts_ms": 1789265739876, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0299", "position": {"x": -1300.0, "y": 1500.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739876, "virtual_time_s": 6040.753903, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 300, "wall_ts_ms": 1789265739877, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0300", "position": {"x": -1300.0, "y": 1500.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739877, "virtual_time_s": 6046.753903, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 301, "wall_ts_ms": 1789265739877, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0301", "position": {"x": -1300.0, "y": 1500.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739877, "virtual_time_s": 6052.753903, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 302, "wall_ts_ms": 1789265739878, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0302", "position": {"x": -1300.0, "y": 1500.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739878, "virtual_time_s": 6058.753903, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 303, "wall_ts_ms": 1789265739878, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0303", "position": {"x": -1300.0, "y": 1500.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739878, "virtual_time_s": 6064.753903, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 304, "wall_ts_ms": 1789265739879, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0304", "position": {"x": -1300.0, "y": 1500.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739879, "virtual_time_s": 6070.753903, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 305, "wall_ts_ms": 1789265739879, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0305", "position": {"x": -1300.0, "y": 1500.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739879, "virtual_time_s": 6076.753903, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 306, "wall_ts_ms": 1789265739880, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0306", "position": {"x": -1300.0, "y": 1500.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739880, "virtual_time_s": 6082.753903, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 307, "wall_ts_ms": 1789265739880, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0307", "position": {"x": -1300.0, "y": 1500.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739880, "virtual_time_s": 6088.753903, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 308, "wall_ts_ms": 1789265739881, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0308", "position": {"x": -1300.0, "y": 1500.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739881, "virtual_time_s": 6094.753903, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 309, "wall_ts_ms": 1789265739882, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0309", "position": {"x": -1300.0, "y": 1500.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739881, "virtual_time_s": 6100.753903, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 310, "wall_ts_ms": 1789265739882, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0310", "position": {"x": -400.0, "y": 1800.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265739882, "virtual_time_s": 6295.490563, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 311, "wall_ts_ms": 1789265739883, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0311", "position": {"x": -400.0, "y": 1800.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265739883, "virtual_time_s": 6301.490563, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 312, "wall_ts_ms": 1789265739883, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0312", "position": {"x": -400.0, "y": 1800.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265739883, "virtual_time_s": 6307.490563, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 313, "wall_ts_ms": 1789265739884, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0313", "position": {"x": -400.0, "y": 1800.0}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265739884, "virtual_time_s": 6313.490563, "measure_result": "direction", "svd_deg": 354.21}}
|
||||||
|
{"event": "action", "seq": 314, "wall_ts_ms": 1789265739913, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0314", "position": {"x": -400.0, "y": 1800.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265739913, "virtual_time_s": 6319.490563, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 315, "wall_ts_ms": 1789265739914, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0315", "position": {"x": -400.0, "y": 1800.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265739914, "virtual_time_s": 6325.490563, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 316, "wall_ts_ms": 1789265739915, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0316", "position": {"x": -400.0, "y": 1800.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265739915, "virtual_time_s": 6331.490563, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 317, "wall_ts_ms": 1789265739915, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0317", "position": {"x": -400.0, "y": 1800.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265739915, "virtual_time_s": 6337.490563, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 318, "wall_ts_ms": 1789265739916, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0318", "position": {"x": -400.0, "y": 1800.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265739916, "virtual_time_s": 6343.490563, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 319, "wall_ts_ms": 1789265739916, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0319", "position": {"x": -400.0, "y": 1800.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265739916, "virtual_time_s": 6349.490563, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 320, "wall_ts_ms": 1789265739917, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0320", "position": {"x": -400.0, "y": 1800.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265739917, "virtual_time_s": 6355.490563, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 321, "wall_ts_ms": 1789265739918, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0321", "position": {"x": -400.0, "y": 1800.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265739917, "virtual_time_s": 6361.490563, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 322, "wall_ts_ms": 1789265740014, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0322", "position": {"x": -24.55089621140732, "y": 1727.78050764454}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265740014, "virtual_time_s": 6443.956944, "measure_result": "direction", "svd_deg": 7.73}}
|
||||||
|
{"event": "action", "seq": 323, "wall_ts_ms": 1789265740060, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0323", "position": {"x": 101.49926410957077, "y": 1747.4479135884048}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265740060, "virtual_time_s": 6474.471998, "measure_result": "near"}}
|
||||||
|
{"event": "action", "seq": 324, "wall_ts_ms": 1789265740064, "method": "POST", "path": "/clear", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0324", "position": {"x": 101.54406236532077, "y": 1747.1545857629853}, "channel": 4}, "response": {"accepted": true, "real_timestamp_ms": 1789265740064, "virtual_time_s": 6479.531344, "clear_result": "success"}}
|
||||||
|
{"event": "action", "seq": 325, "wall_ts_ms": 1789265740066, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0325", "position": {"x": 400.0, "y": 1800.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265740066, "virtual_time_s": 6546.151006, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 326, "wall_ts_ms": 1789265740068, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0326", "position": {"x": 400.0, "y": 1800.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265740068, "virtual_time_s": 6552.151006, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 327, "wall_ts_ms": 1789265740070, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0327", "position": {"x": 400.0, "y": 1800.0}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265740070, "virtual_time_s": 6558.151006, "measure_result": "direction", "svd_deg": 191.2}}
|
||||||
|
{"event": "action", "seq": 328, "wall_ts_ms": 1789265740116, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0328", "position": {"x": 400.0, "y": 1800.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265740116, "virtual_time_s": 6564.151006, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 329, "wall_ts_ms": 1789265740118, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0329", "position": {"x": 400.0, "y": 1800.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265740118, "virtual_time_s": 6570.151006, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 330, "wall_ts_ms": 1789265740119, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0330", "position": {"x": 400.0, "y": 1800.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265740119, "virtual_time_s": 6576.151006, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 331, "wall_ts_ms": 1789265740120, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0331", "position": {"x": 400.0, "y": 1800.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265740120, "virtual_time_s": 6582.151006, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 332, "wall_ts_ms": 1789265740120, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0332", "position": {"x": 400.0, "y": 1800.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265740120, "virtual_time_s": 6588.151006, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 333, "wall_ts_ms": 1789265740121, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0333", "position": {"x": 400.0, "y": 1800.0}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265740121, "virtual_time_s": 6594.151006, "measure_result": "direction", "svd_deg": 272.2}}
|
||||||
|
{"event": "action", "seq": 334, "wall_ts_ms": 1789265740153, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0334", "position": {"x": 400.0, "y": 1800.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265740153, "virtual_time_s": 6600.151006, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 335, "wall_ts_ms": 1789265740154, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0335", "position": {"x": 400.0, "y": 1800.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265740154, "virtual_time_s": 6606.151006, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 336, "wall_ts_ms": 1789265740313, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0336", "position": {"x": -24.20475655272145, "y": 1636.8980627348978}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265740313, "virtual_time_s": 6703.046972, "measure_result": "direction", "svd_deg": 160.88}}
|
||||||
|
{"event": "action", "seq": 337, "wall_ts_ms": 1789265740330, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0337", "position": {"x": -158.52431169665903, "y": 1687.3397389277611}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265740330, "virtual_time_s": 6736.74269, "measure_result": "direction", "svd_deg": 192.73}}
|
||||||
|
{"event": "action", "seq": 338, "wall_ts_ms": 1789265740332, "method": "POST", "path": "/clear", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0338", "position": {"x": -165.6025782014923, "y": 1685.833818291656}, "channel": 6}, "response": {"accepted": true, "real_timestamp_ms": 1789265740332, "virtual_time_s": 6743.190028, "clear_result": "success"}}
|
||||||
|
{"event": "action", "seq": 339, "wall_ts_ms": 1789265740480, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0339", "position": {"x": 171.91074610145796, "y": 1285.0122857297256}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265740480, "virtual_time_s": 6853.989483, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 340, "wall_ts_ms": 1789265740610, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0340", "position": {"x": 429.14297023213675, "y": 1391.5613616440485}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265740610, "virtual_time_s": 6914.674714, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 341, "wall_ts_ms": 1789265740744, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0341", "position": {"x": 686.3751943628156, "y": 1285.0122857297256}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265740744, "virtual_time_s": 6975.359945, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 342, "wall_ts_ms": 1789265740884, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0342", "position": {"x": 429.1429702321368, "y": 1755.3426616890501}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265740884, "virtual_time_s": 7087.575444, "measure_result": "direction", "svd_deg": 265.21}}
|
||||||
|
{"event": "action", "seq": 343, "wall_ts_ms": 1789265740908, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0343", "position": {"x": 409.83408878169837, "y": 1586.197737192631}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265740908, "virtual_time_s": 7126.624138, "measure_result": "direction", "svd_deg": 272.13}}
|
||||||
|
{"event": "action", "seq": 344, "wall_ts_ms": 1789265740925, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0344", "position": {"x": 411.1387584130592, "y": 1552.2577508333961}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265740925, "virtual_time_s": 7138.417149, "measure_result": "near"}}
|
||||||
|
{"event": "action", "seq": 345, "wall_ts_ms": 1789265740928, "method": "POST", "path": "/clear", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0345", "position": {"x": 411.13875841306526, "y": 1552.2577508333966}, "channel": 15}, "response": {"accepted": true, "real_timestamp_ms": 1789265740928, "virtual_time_s": 7143.417149, "clear_result": "success"}}
|
||||||
|
{"event": "action", "seq": 346, "wall_ts_ms": 1789265740929, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0346", "position": {"x": 600.0, "y": 1900.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265740929, "virtual_time_s": 7228.560877, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 347, "wall_ts_ms": 1789265740930, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0347", "position": {"x": 600.0, "y": 1900.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265740930, "virtual_time_s": 7234.560877, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 348, "wall_ts_ms": 1789265740931, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0348", "position": {"x": 600.0, "y": 1900.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265740931, "virtual_time_s": 7240.560877, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 349, "wall_ts_ms": 1789265740932, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0349", "position": {"x": 600.0, "y": 1900.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265740932, "virtual_time_s": 7246.560877, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 350, "wall_ts_ms": 1789265740934, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0350", "position": {"x": 600.0, "y": 1900.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265740934, "virtual_time_s": 7252.560877, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 351, "wall_ts_ms": 1789265740935, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0351", "position": {"x": 600.0, "y": 1900.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265740935, "virtual_time_s": 7258.560877, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 352, "wall_ts_ms": 1789265740936, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0352", "position": {"x": 600.0, "y": 1900.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265740936, "virtual_time_s": 7264.560877, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 353, "wall_ts_ms": 1789265740937, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0353", "position": {"x": 600.0, "y": 1900.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265740937, "virtual_time_s": 7270.560877, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 354, "wall_ts_ms": 1789265740938, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0354", "position": {"x": 600.0, "y": 1900.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265740938, "virtual_time_s": 7276.560877, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 355, "wall_ts_ms": 1789265740939, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0355", "position": {"x": 800.0, "y": 1200.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265740939, "virtual_time_s": 7427.163075, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 356, "wall_ts_ms": 1789265740940, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0356", "position": {"x": 800.0, "y": 1200.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265740940, "virtual_time_s": 7433.163075, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 357, "wall_ts_ms": 1789265740942, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0357", "position": {"x": 800.0, "y": 1200.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265740942, "virtual_time_s": 7439.163075, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 358, "wall_ts_ms": 1789265740943, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0358", "position": {"x": 800.0, "y": 1200.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265740943, "virtual_time_s": 7445.163075, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 359, "wall_ts_ms": 1789265740944, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0359", "position": {"x": 800.0, "y": 1200.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265740944, "virtual_time_s": 7451.163075, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 360, "wall_ts_ms": 1789265740946, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0360", "position": {"x": 800.0, "y": 1200.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265740946, "virtual_time_s": 7457.163075, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 361, "wall_ts_ms": 1789265740947, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0361", "position": {"x": 800.0, "y": 1200.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265740947, "virtual_time_s": 7463.163075, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 362, "wall_ts_ms": 1789265740949, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0362", "position": {"x": 800.0, "y": 1200.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265740949, "virtual_time_s": 7469.163075, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 363, "wall_ts_ms": 1789265740950, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0363", "position": {"x": 800.0, "y": 1200.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265740950, "virtual_time_s": 7475.163075, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 364, "wall_ts_ms": 1789265740950, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0364", "position": {"x": 700.0, "y": 700.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265740950, "virtual_time_s": 7582.143465, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 365, "wall_ts_ms": 1789265740951, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0365", "position": {"x": 700.0, "y": 700.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265740951, "virtual_time_s": 7588.143465, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 366, "wall_ts_ms": 1789265740952, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0366", "position": {"x": 700.0, "y": 700.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265740952, "virtual_time_s": 7594.143465, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 367, "wall_ts_ms": 1789265740953, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0367", "position": {"x": 700.0, "y": 700.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265740953, "virtual_time_s": 7600.143465, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 368, "wall_ts_ms": 1789265740954, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0368", "position": {"x": 700.0, "y": 700.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265740954, "virtual_time_s": 7606.143465, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 369, "wall_ts_ms": 1789265740955, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0369", "position": {"x": 700.0, "y": 700.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265740955, "virtual_time_s": 7612.143465, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 370, "wall_ts_ms": 1789265740956, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0370", "position": {"x": 700.0, "y": 700.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265740956, "virtual_time_s": 7618.143465, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 371, "wall_ts_ms": 1789265740957, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0371", "position": {"x": 700.0, "y": 700.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265740957, "virtual_time_s": 7624.143465, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 372, "wall_ts_ms": 1789265740957, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0372", "position": {"x": 700.0, "y": 700.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265740957, "virtual_time_s": 7630.143465, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 373, "wall_ts_ms": 1789265740958, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0373", "position": {"x": 800.0, "y": 200.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265740958, "virtual_time_s": 7737.123855, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 374, "wall_ts_ms": 1789265740959, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0374", "position": {"x": 800.0, "y": 200.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265740959, "virtual_time_s": 7743.123855, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 375, "wall_ts_ms": 1789265740959, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0375", "position": {"x": 800.0, "y": 200.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265740959, "virtual_time_s": 7749.123855, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 376, "wall_ts_ms": 1789265740960, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0376", "position": {"x": 800.0, "y": 200.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265740960, "virtual_time_s": 7755.123855, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 377, "wall_ts_ms": 1789265740961, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0377", "position": {"x": 800.0, "y": 200.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265740961, "virtual_time_s": 7761.123855, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 378, "wall_ts_ms": 1789265740961, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0378", "position": {"x": 800.0, "y": 200.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265740961, "virtual_time_s": 7767.123855, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 379, "wall_ts_ms": 1789265740962, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0379", "position": {"x": 800.0, "y": 200.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265740962, "virtual_time_s": 7773.123855, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 380, "wall_ts_ms": 1789265740963, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0380", "position": {"x": 800.0, "y": 200.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265740963, "virtual_time_s": 7779.123855, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 381, "wall_ts_ms": 1789265740963, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0381", "position": {"x": 800.0, "y": 200.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265740963, "virtual_time_s": 7785.123855, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 382, "wall_ts_ms": 1789265740964, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0382", "position": {"x": 1800.0, "y": 300.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265740964, "virtual_time_s": 7991.121367, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 383, "wall_ts_ms": 1789265740965, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0383", "position": {"x": 1800.0, "y": 300.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265740965, "virtual_time_s": 7997.121367, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 384, "wall_ts_ms": 1789265740966, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0384", "position": {"x": 1800.0, "y": 300.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265740966, "virtual_time_s": 8003.121367, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 385, "wall_ts_ms": 1789265740969, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0385", "position": {"x": 1800.0, "y": 300.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265740969, "virtual_time_s": 8009.121367, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 386, "wall_ts_ms": 1789265740970, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0386", "position": {"x": 1800.0, "y": 300.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265740970, "virtual_time_s": 8015.121367, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 387, "wall_ts_ms": 1789265740971, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0387", "position": {"x": 1800.0, "y": 300.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265740971, "virtual_time_s": 8021.121367, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 388, "wall_ts_ms": 1789265740972, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0388", "position": {"x": 1800.0, "y": 300.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265740972, "virtual_time_s": 8027.121367, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 389, "wall_ts_ms": 1789265740972, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0389", "position": {"x": 1800.0, "y": 300.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265740972, "virtual_time_s": 8033.121367, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 390, "wall_ts_ms": 1789265740973, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0390", "position": {"x": 1800.0, "y": 300.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265740973, "virtual_time_s": 8039.121367, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 391, "wall_ts_ms": 1789265740974, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0391", "position": {"x": 1300.0, "y": 1100.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265740974, "virtual_time_s": 8232.80099, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 392, "wall_ts_ms": 1789265740975, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0392", "position": {"x": 1300.0, "y": 1100.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265740975, "virtual_time_s": 8238.80099, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 393, "wall_ts_ms": 1789265740975, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0393", "position": {"x": 1300.0, "y": 1100.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265740975, "virtual_time_s": 8244.80099, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 394, "wall_ts_ms": 1789265740976, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0394", "position": {"x": 1300.0, "y": 1100.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265740976, "virtual_time_s": 8250.80099, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 395, "wall_ts_ms": 1789265740976, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0395", "position": {"x": 1300.0, "y": 1100.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265740976, "virtual_time_s": 8256.80099, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 396, "wall_ts_ms": 1789265740977, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0396", "position": {"x": 1300.0, "y": 1100.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265740977, "virtual_time_s": 8262.80099, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 397, "wall_ts_ms": 1789265740978, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0397", "position": {"x": 1300.0, "y": 1100.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265740978, "virtual_time_s": 8268.80099, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 398, "wall_ts_ms": 1789265740979, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0398", "position": {"x": 1300.0, "y": 1100.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265740979, "virtual_time_s": 8274.80099, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 399, "wall_ts_ms": 1789265740981, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0399", "position": {"x": 1300.0, "y": 1100.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265740981, "virtual_time_s": 8280.80099, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 400, "wall_ts_ms": 1789265740983, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0400", "position": {"x": 1500.0, "y": 1300.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265740983, "virtual_time_s": 8342.369532, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 401, "wall_ts_ms": 1789265740985, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0401", "position": {"x": 1500.0, "y": 1300.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265740985, "virtual_time_s": 8348.369532, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 402, "wall_ts_ms": 1789265740986, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0402", "position": {"x": 1500.0, "y": 1300.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265740986, "virtual_time_s": 8354.369532, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 403, "wall_ts_ms": 1789265740987, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0403", "position": {"x": 1500.0, "y": 1300.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265740987, "virtual_time_s": 8360.369532, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 404, "wall_ts_ms": 1789265740988, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0404", "position": {"x": 1500.0, "y": 1300.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265740987, "virtual_time_s": 8366.369532, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 405, "wall_ts_ms": 1789265740988, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0405", "position": {"x": 1500.0, "y": 1300.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265740988, "virtual_time_s": 8372.369532, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 406, "wall_ts_ms": 1789265740989, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0406", "position": {"x": 1500.0, "y": 1300.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265740989, "virtual_time_s": 8378.369532, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 407, "wall_ts_ms": 1789265740990, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0407", "position": {"x": 1500.0, "y": 1300.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265740990, "virtual_time_s": 8384.369532, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 408, "wall_ts_ms": 1789265740990, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0408", "position": {"x": 1500.0, "y": 1300.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265740990, "virtual_time_s": 8390.369532, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 409, "wall_ts_ms": 1789265740991, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0409", "position": {"x": -200.0, "y": 900.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265740991, "virtual_time_s": 8744.654516, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 410, "wall_ts_ms": 1789265740992, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0410", "position": {"x": -200.0, "y": 900.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265740992, "virtual_time_s": 8750.654516, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 411, "wall_ts_ms": 1789265740993, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0411", "position": {"x": -200.0, "y": 900.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265740993, "virtual_time_s": 8756.654516, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 412, "wall_ts_ms": 1789265740994, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0412", "position": {"x": -200.0, "y": 900.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265740994, "virtual_time_s": 8762.654516, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 413, "wall_ts_ms": 1789265740994, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0413", "position": {"x": -200.0, "y": 900.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265740994, "virtual_time_s": 8768.654516, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 414, "wall_ts_ms": 1789265740995, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0414", "position": {"x": -200.0, "y": 900.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265740995, "virtual_time_s": 8774.654516, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 415, "wall_ts_ms": 1789265740996, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0415", "position": {"x": -200.0, "y": 900.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265740996, "virtual_time_s": 8780.654516, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 416, "wall_ts_ms": 1789265740996, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0416", "position": {"x": -200.0, "y": 900.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265740996, "virtual_time_s": 8786.654516, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 417, "wall_ts_ms": 1789265740997, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0417", "position": {"x": -200.0, "y": 900.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265740997, "virtual_time_s": 8792.654516, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 418, "wall_ts_ms": 1789265740998, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0418", "position": {"x": -500.0, "y": 700.0}, "channel": 17}, "response": {"accepted": true, "real_timestamp_ms": 1789265740998, "virtual_time_s": 8869.765542, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 419, "wall_ts_ms": 1789265740998, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0419", "position": {"x": -500.0, "y": 700.0}, "channel": 1}, "response": {"accepted": true, "real_timestamp_ms": 1789265740998, "virtual_time_s": 8875.765542, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 420, "wall_ts_ms": 1789265740999, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0420", "position": {"x": -500.0, "y": 700.0}, "channel": 3}, "response": {"accepted": true, "real_timestamp_ms": 1789265740999, "virtual_time_s": 8881.765542, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 421, "wall_ts_ms": 1789265741000, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0421", "position": {"x": -500.0, "y": 700.0}, "channel": 7}, "response": {"accepted": true, "real_timestamp_ms": 1789265741000, "virtual_time_s": 8887.765542, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 422, "wall_ts_ms": 1789265741000, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0422", "position": {"x": -500.0, "y": 700.0}, "channel": 9}, "response": {"accepted": true, "real_timestamp_ms": 1789265741000, "virtual_time_s": 8893.765542, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 423, "wall_ts_ms": 1789265741001, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0423", "position": {"x": -500.0, "y": 700.0}, "channel": 11}, "response": {"accepted": true, "real_timestamp_ms": 1789265741001, "virtual_time_s": 8899.765542, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 424, "wall_ts_ms": 1789265741001, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0424", "position": {"x": -500.0, "y": 700.0}, "channel": 13}, "response": {"accepted": true, "real_timestamp_ms": 1789265741001, "virtual_time_s": 8905.765542, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 425, "wall_ts_ms": 1789265741002, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0425", "position": {"x": -500.0, "y": 700.0}, "channel": 14}, "response": {"accepted": true, "real_timestamp_ms": 1789265741002, "virtual_time_s": 8911.765542, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 426, "wall_ts_ms": 1789265741003, "method": "POST", "path": "/measure", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0426", "position": {"x": -500.0, "y": 700.0}, "channel": 18}, "response": {"accepted": true, "real_timestamp_ms": 1789265741003, "virtual_time_s": 8917.765542, "measure_result": "no_signal"}}
|
||||||
|
{"event": "action", "seq": 427, "wall_ts_ms": 1789265741003, "method": "POST", "path": "/exit", "status": 200, "request": {"arena_id": "default", "robot_id": "1", "request_id": "baa9dc681441-0427"}, "response": {"accepted": true, "real_timestamp_ms": 1789265741003, "virtual_time_s": 8917.765542, "exit_reason": "user_exit"}}
|
||||||
|
{"event": "session_end", "reason": "user_exit", "virtual_time_s": 8917.765542, "real_elapsed_s": 10.027643, "request_count": 427, "cleared_count": 11}
|
||||||
@@ -0,0 +1,96 @@
|
|||||||
|
{
|
||||||
|
"case_code": "GHSN-M38E-74GD-YLUD",
|
||||||
|
"module": "q4_practice",
|
||||||
|
"robot_id": "1",
|
||||||
|
"seed": 1907688398,
|
||||||
|
"truth": [
|
||||||
|
{
|
||||||
|
"channel": 6,
|
||||||
|
"x": -168.78031525275804,
|
||||||
|
"y": 1684.875239455932,
|
||||||
|
"r_eff_m": 1233.1529913973563,
|
||||||
|
"directional": true,
|
||||||
|
"heading_deg": 351.84275431652014
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"channel": 15,
|
||||||
|
"x": 411.7975180678083,
|
||||||
|
"y": 1548.040304144621,
|
||||||
|
"r_eff_m": 1336.3045523445826,
|
||||||
|
"directional": true,
|
||||||
|
"heading_deg": 72.47781232458263
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"channel": 8,
|
||||||
|
"x": 978.6674582823607,
|
||||||
|
"y": -996.1121301869524,
|
||||||
|
"r_eff_m": 1336.1370990332562,
|
||||||
|
"directional": true,
|
||||||
|
"heading_deg": 246.14394851382335
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"channel": 16,
|
||||||
|
"x": 124.00340756473021,
|
||||||
|
"y": -860.3622285357711,
|
||||||
|
"r_eff_m": 1345.578791332298,
|
||||||
|
"directional": false,
|
||||||
|
"heading_deg": 0.0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"channel": 10,
|
||||||
|
"x": 729.8914456683548,
|
||||||
|
"y": 714.3629430529361,
|
||||||
|
"r_eff_m": 1127.494833936053,
|
||||||
|
"directional": false,
|
||||||
|
"heading_deg": 0.0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"channel": 2,
|
||||||
|
"x": 478.441266630241,
|
||||||
|
"y": 449.08113076378316,
|
||||||
|
"r_eff_m": 1040.6068154097852,
|
||||||
|
"directional": false,
|
||||||
|
"heading_deg": 0.0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"channel": 20,
|
||||||
|
"x": -945.2003883886779,
|
||||||
|
"y": 638.5311986666989,
|
||||||
|
"r_eff_m": 1295.456469667405,
|
||||||
|
"directional": false,
|
||||||
|
"heading_deg": 0.0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"channel": 4,
|
||||||
|
"x": 99.04602689897295,
|
||||||
|
"y": 1744.5260335974826,
|
||||||
|
"r_eff_m": 1032.9094604449615,
|
||||||
|
"directional": false,
|
||||||
|
"heading_deg": 0.0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"channel": 5,
|
||||||
|
"x": -1507.0542438070167,
|
||||||
|
"y": 761.3723575581047,
|
||||||
|
"r_eff_m": 1448.7977020579874,
|
||||||
|
"directional": false,
|
||||||
|
"heading_deg": 0.0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"channel": 12,
|
||||||
|
"x": -1188.1583136013294,
|
||||||
|
"y": 963.0220608398997,
|
||||||
|
"r_eff_m": 1226.2619264983982,
|
||||||
|
"directional": false,
|
||||||
|
"heading_deg": 0.0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"channel": 19,
|
||||||
|
"x": -177.4461437404443,
|
||||||
|
"y": 343.49207176417394,
|
||||||
|
"r_eff_m": 1277.3413627947266,
|
||||||
|
"directional": false,
|
||||||
|
"heading_deg": 0.0
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
@@ -3,7 +3,7 @@
|
|||||||
``referee-data/`` 与 ``output/`` 都在 .gitignore 里：本机清掉评测机数据后，
|
``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，
|
``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 ``<case_code>.<module>.jsonl`` 存进 ``examples/replay/``（入库、几万行以内），
|
命名成 ``<case_code>.<module>.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。
|
``scripts/build_figure_data.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 # 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 BBM9-HZG2-77N5-NKKC # 指定案例
|
||||||
@@ -26,7 +26,7 @@ ARCHIVE_DIR = ROOT / 'examples' / 'replay'
|
|||||||
|
|
||||||
sys.path.insert(0, str(Path(__file__).resolve().parent))
|
sys.path.insert(0, str(Path(__file__).resolve().parent))
|
||||||
|
|
||||||
from make_figures import discover_runs, pick_run # noqa: E402
|
from build_figure_data import discover_runs, pick_run # noqa: E402
|
||||||
|
|
||||||
|
|
||||||
def archive(run: dict, out_dir: Path) -> Path:
|
def archive(run: dict, out_dir: Path) -> Path:
|
||||||
|
|||||||
@@ -0,0 +1,747 @@
|
|||||||
|
"""为 MATLAB 出图准备数据，并更新 docs/figures/manifest.json。
|
||||||
|
|
||||||
|
uv run python scripts/build_figure_data.py --prepare # 只写 .mat 数据
|
||||||
|
uv run python scripts/build_figure_data.py # 写数据 + 调 MATLAB 出图
|
||||||
|
uv run python scripts/build_figure_data.py --only geo-q3-seven-point-coverage
|
||||||
|
uv run python scripts/build_figure_data.py --list
|
||||||
|
|
||||||
|
分工：
|
||||||
|
|
||||||
|
- **本脚本（Python）**：解析行为日志与覆盖计划、调用生产求解器算几何、把绘图数据写成
|
||||||
|
``docs/figures/.data/*.mat``、维护 manifest（来源路径 + sha256 + 行数）；
|
||||||
|
- **MATLAB**：``scripts/matlab/*.m`` 负责排版与出图，只读 .mat，不做数据解析。
|
||||||
|
手动出图：MATLAB 中 ``cd scripts/matlab`` 后执行 ``run_all_figures``。
|
||||||
|
|
||||||
|
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；
|
||||||
|
每张图的含义由文件名与 ``docs/figures/README.md`` 承担。
|
||||||
|
"""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
import hashlib
|
||||||
|
import json
|
||||||
|
import math
|
||||||
|
import subprocess
|
||||||
|
import sys
|
||||||
|
from pathlib import Path
|
||||||
|
from typing import Any, Callable, Sequence
|
||||||
|
|
||||||
|
import numpy as np
|
||||||
|
from scipy.io import savemat
|
||||||
|
|
||||||
|
ROOT = Path(__file__).resolve().parents[1]
|
||||||
|
OUT_DIR = ROOT / "docs" / "figures"
|
||||||
|
DATA_DIR = OUT_DIR / ".data"
|
||||||
|
MATLAB_DIR = ROOT / "scripts" / "matlab"
|
||||||
|
SESSIONS_DIR = ROOT / "referee-data" / "sessions"
|
||||||
|
ARCHIVE_DIR = ROOT / "examples" / "replay"
|
||||||
|
MATLAB_BIN = Path("/Applications/MATLAB_R2025a.app/bin/matlab")
|
||||||
|
|
||||||
|
# 题面常量（与 src/mcm26b/config.py 一致；此处只用于画图）
|
||||||
|
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
|
||||||
|
|
||||||
|
# 回放图指定的 q4 演练局（缺失时回退到自动挑选）
|
||||||
|
Q4_REPLAY_CASE = "GHSN-M38E-74GD-YLUD"
|
||||||
|
SEVEN_R = 1800.0
|
||||||
|
|
||||||
|
# 图名 → (MATLAB 函数, .mat 数据名)
|
||||||
|
FIGURES: tuple[tuple[str, str, str], ...] = (
|
||||||
|
("flow-overall-architecture", "fig_flow_overall", "flow_overall"),
|
||||||
|
("steps-state-machine", "fig_steps_state_machine", "steps_state_machine"),
|
||||||
|
("timing-attachment-example-105-111-194-199", "fig_timing_attachment",
|
||||||
|
"timing_attachment"),
|
||||||
|
("timing-measured-q3-10-sources", "fig_timing_measured", "timing_measured"),
|
||||||
|
("geo-q1-convex-intersection-zoom", "fig_geo_q1_meetup", "geo_q1_meetup"),
|
||||||
|
("geo-q1-diameter-circle-counterexample", "fig_geo_q1_counterexample",
|
||||||
|
"geo_q1_counterexample"),
|
||||||
|
("geo-q2-guaranteed-reception-disk", "fig_geo_q2_safe_disk", "geo_q2"),
|
||||||
|
("geo-q3-seven-point-coverage", "fig_geo_q3_coverage", "geo_q3"),
|
||||||
|
("geo-q4-minimum-cover-31-points", "fig_geo_q4_mincover", "geo_q4"),
|
||||||
|
("replay-webui-q3-omnidirectional", "fig_replay", "replay_q3"),
|
||||||
|
("replay-webui-q4-directional", "fig_replay", "replay_q4"),
|
||||||
|
)
|
||||||
|
|
||||||
|
SOURCES: dict[str, list[str]] = {
|
||||||
|
"flow-overall-architecture": ["src/mcm26b/config.py", "docs/B题建模分析与实施计划.md"],
|
||||||
|
"steps-state-machine": ["docs/协议规则表与状态机.md", "src/mcm26b/protocol/client.py"],
|
||||||
|
"timing-attachment-example-105-111-194-199": ["docs/协议规则表与状态机.md"],
|
||||||
|
"geo-q1-diameter-circle-counterexample": ["examples/q1/triangle.json"],
|
||||||
|
"geo-q2-guaranteed-reception-disk": ["src/mcm26b/config.py", "docs/algo-2.md"],
|
||||||
|
"geo-q3-seven-point-coverage": ["src/mcm26b/planner/seven.py", "docs/algo-3.md"],
|
||||||
|
"geo-q4-minimum-cover-31-points": [
|
||||||
|
"src/mcm26b/guarantee/plans/q4_mincover_v2.json", "docs/algo-4.md"],
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
# ---------------------------------------------------------------------------
|
||||||
|
# 数据来源
|
||||||
|
# ---------------------------------------------------------------------------
|
||||||
|
def source(path: str | Path, **extra: Any) -> dict[str, Any]:
|
||||||
|
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}
|
||||||
|
|
||||||
|
|
||||||
|
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(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_case(runs: Sequence[dict[str, Any]], case_code: str) -> dict[str, Any] | None:
|
||||||
|
"""按案例编码取局；不在本机留档里就返回 None，由调用方回退。"""
|
||||||
|
return next((r for r in runs if r["case_code"] == case_code), None)
|
||||||
|
|
||||||
|
|
||||||
|
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 any(a["path"] == "/measure" for a in r["actions"])]
|
||||||
|
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(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")))
|
||||||
|
last = run["actions"][-1]["response"]
|
||||||
|
return dict(rows=rows, virtual_s=float(last.get("virtual_time_s") or 0.0),
|
||||||
|
move_m=sum(r["move_m"] for r in rows),
|
||||||
|
measures=sum(1 for r in rows if r["path"] == "/measure"),
|
||||||
|
clears=sum(1 for r in rows if r["path"] == "/clear"))
|
||||||
|
|
||||||
|
|
||||||
|
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：半平面裁剪与问题一求解
|
||||||
|
# ---------------------------------------------------------------------------
|
||||||
|
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 angle_error(poly: np.ndarray, station: Sequence[float], bearing: float) -> float:
|
||||||
|
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((math.degrees(math.atan2(dy, dx)) - bearing + 180.0) % 360.0 - 180.0)
|
||||||
|
|
||||||
|
|
||||||
|
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：两个半平面各试一次，取方向一致的那一侧。"""
|
||||||
|
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]
|
||||||
|
cands = [cand for cand in (clip_halfplane(region, a, b, c),
|
||||||
|
clip_halfplane(region, -a, -b, -c)) if len(cand) >= 3]
|
||||||
|
if not cands:
|
||||||
|
return np.empty((0, 2))
|
||||||
|
region = cands[0] if len(cands) == 1 else min(
|
||||||
|
cands, key=lambda cand: angle_error(cand, station, bearing))
|
||||||
|
return region
|
||||||
|
|
||||||
|
|
||||||
|
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, 24)
|
||||||
|
return np.vstack([[station[0], station[1]],
|
||||||
|
np.column_stack([station[0] + reach * np.cos(ang),
|
||||||
|
station[1] + reach * np.sin(ang)])])
|
||||||
|
|
||||||
|
|
||||||
|
def overview_window(stations: np.ndarray, verts: np.ndarray,
|
||||||
|
dc: dict[str, Any], mec: dict[str, Any]) -> tuple[float, np.ndarray]:
|
||||||
|
"""总览窗口：包含全部站点、定位区域与两个圆，中心取包围盒中心。"""
|
||||||
|
pts = [np.asarray(stations, dtype=float), np.asarray(verts, dtype=float)]
|
||||||
|
for circ in (dc, mec):
|
||||||
|
c = np.asarray(circ["center"], dtype=float)
|
||||||
|
r = float(circ["radius_m"])
|
||||||
|
pts.append(np.array([c + r, c - r]))
|
||||||
|
all_pts = np.vstack(pts)
|
||||||
|
lo, hi = all_pts.min(axis=0), all_pts.max(axis=0)
|
||||||
|
center = (lo + hi) / 2
|
||||||
|
half = float(np.max(hi - lo) / 2 * 1.12 + 40.0)
|
||||||
|
return half, center
|
||||||
|
|
||||||
|
|
||||||
|
def q1_solve(stations: Sequence[Sequence[float]]) -> dict[str, Any]:
|
||||||
|
"""调用生产求解器，保证图中数字与代码一致。"""
|
||||||
|
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 = res["diameter_circle"]
|
||||||
|
mec = res["minimum_enclosing_circle"]
|
||||||
|
return dict(vertices=np.array(res["vertices"]),
|
||||||
|
dc=dict(center=np.array(dc["center"]), radius_m=float(dc["radius_m"])),
|
||||||
|
mec=dict(center=np.array(mec["center"]), radius_m=float(mec["radius_m"])))
|
||||||
|
|
||||||
|
|
||||||
|
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))
|
||||||
|
|
||||||
|
|
||||||
|
# ---------------------------------------------------------------------------
|
||||||
|
# 各图数据
|
||||||
|
# ---------------------------------------------------------------------------
|
||||||
|
def data_flow_overall() -> dict[str, Any]:
|
||||||
|
"""四个层次带：层标签、每层的框内短标签与语义色名。"""
|
||||||
|
bands = [
|
||||||
|
("L0", [("区域 Ω：半径 1800 m", 8.0, 26.0),
|
||||||
|
("移动 5 m/s · 检测 5 s", 36.5, 26.0),
|
||||||
|
("换频 1 s · 清除 5/3 s", 65.0, 26.0),
|
||||||
|
("源 10~16 个 · 频道 1~20", 93.5, 24.0)]),
|
||||||
|
("L1", [("证据层：候选集与粒子幸存集", 8.0, 34.0),
|
||||||
|
("决策层：选点与任务表", 45.0, 34.0),
|
||||||
|
("执行层：串行客户端", 82.0, 34.0)]),
|
||||||
|
("L2", [("问题 1 定位解算", 8.0, 26.0),
|
||||||
|
("问题 2 第二点选择", 36.5, 26.0),
|
||||||
|
("问题 3 全向搜索", 65.0, 26.0),
|
||||||
|
("问题 4 混合定向", 93.5, 24.0)]),
|
||||||
|
("L3", [("发现闭环", 8.0, 34.0),
|
||||||
|
("定位闭环", 45.0, 34.0),
|
||||||
|
("清除闭环", 82.0, 34.0)]),
|
||||||
|
]
|
||||||
|
colors = {"L0": "primary", "L1": "primary", "L2": "accent", "L3": "success"}
|
||||||
|
return dict(tags=[b[0] for b in bands],
|
||||||
|
labels=[[i[0] for i in b[1]] for b in bands],
|
||||||
|
colors=[colors[b[0]] for b in bands])
|
||||||
|
|
||||||
|
|
||||||
|
def data_steps_state_machine() -> dict[str, Any]:
|
||||||
|
return dict(labels=["IDLE", "倒计时 5 s", "OPEN 接口开放", "CLOSED 断连"],
|
||||||
|
edges=["muted", "warn", "success", "accent"])
|
||||||
|
|
||||||
|
|
||||||
|
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 data_timing_attachment() -> dict[str, Any]:
|
||||||
|
return dict(labels=[s[0] for s in EXAMPLE_STEPS],
|
||||||
|
move=np.array([s[1] for s in EXAMPLE_STEPS]),
|
||||||
|
switch_s=np.array([s[2] for s in EXAMPLE_STEPS]),
|
||||||
|
action=np.array([s[3] for s in EXAMPLE_STEPS]),
|
||||||
|
xlabel="虚拟耗时 / s",
|
||||||
|
legend=["移动 L/5", "换频 1 s", "检测/清除动作"])
|
||||||
|
|
||||||
|
|
||||||
|
def data_timing_measured(run: dict[str, Any]) -> dict[str, Any]:
|
||||||
|
tl = decompose(run)
|
||||||
|
rows = tl["rows"]
|
||||||
|
seq = np.arange(1.0, len(rows) + 1.0)
|
||||||
|
steps = np.array([[r["move_s"], r["action_s"], r["switch_s"]] for r in rows],
|
||||||
|
dtype=float)
|
||||||
|
cum = np.cumsum(np.cumsum(steps, axis=1), axis=0) # 移动 / +动作 / +换频
|
||||||
|
return dict(seq=seq, cum=cum,
|
||||||
|
xlabel="动作序号", ylabel="累计虚拟时间 / s",
|
||||||
|
legend=["移动", "检测/清除动作", "换频"])
|
||||||
|
|
||||||
|
|
||||||
|
def data_geo_q1_meetup() -> tuple[dict[str, Any], Path]:
|
||||||
|
case = q1_practice_case()
|
||||||
|
if case:
|
||||||
|
stations = [(m["x"], m["y"], m["bearing_deg"], m["half_angle_deg"])
|
||||||
|
for m in case["measurements"]]
|
||||||
|
res = case["result"]
|
||||||
|
verts = np.array(res["vertices"])
|
||||||
|
dc = dict(center=np.array(res["diameter_circle"]["center"]),
|
||||||
|
radius_m=float(res["diameter_circle"]["radius_m"]))
|
||||||
|
mec = dict(center=np.array(res["minimum_enclosing_circle"]["center"]),
|
||||||
|
radius_m=float(res["minimum_enclosing_circle"]["radius_m"]))
|
||||||
|
src = case["_path"]
|
||||||
|
else:
|
||||||
|
src = ROOT / "examples" / "q1" / "triangle.json"
|
||||||
|
doc = json.loads(src.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, dc, mec = sol["vertices"], sol["dc"], sol["mec"]
|
||||||
|
|
||||||
|
zoom_c = verts.mean(axis=0)
|
||||||
|
span = float(np.abs(verts - zoom_c).max())
|
||||||
|
zoom = max(1.8 * span, 0.8 * mec["radius_m"] + span, 12.0)
|
||||||
|
xs = [s[0] for s in stations]
|
||||||
|
ys = [s[1] for s in stations]
|
||||||
|
half, view_c = overview_window(np.array([[s[0], s[1]] for s in stations]),
|
||||||
|
verts, dc, mec)
|
||||||
|
reach = 2.4 * half
|
||||||
|
wedges = [wedge_polygon((sx, sy), b, hd, reach) for sx, sy, b, hd in stations]
|
||||||
|
region = np.array([[zoom_c[0] - zoom, zoom_c[1] - zoom],
|
||||||
|
[zoom_c[0] + zoom, zoom_c[1] - zoom],
|
||||||
|
[zoom_c[0] + zoom, zoom_c[1] + zoom],
|
||||||
|
[zoom_c[0] - zoom, zoom_c[1] + zoom]], dtype=float)
|
||||||
|
for sx, sy, b, hd in stations:
|
||||||
|
region = clip_wedge(region, (sx, sy), b, hd)
|
||||||
|
data = dict(
|
||||||
|
stations=np.array([[s[0], s[1]] for s in stations]),
|
||||||
|
station_labels=[f"s{i + 1}" for i in range(len(stations))],
|
||||||
|
wedges=np.stack(wedges), zoom_wedges=np.stack(wedges),
|
||||||
|
zoom_region=region,
|
||||||
|
dc_center=dc["center"], dc_radius=dc["radius_m"],
|
||||||
|
mec_center=mec["center"], mec_radius=mec["radius_m"],
|
||||||
|
view_center=view_c, half_overview=float(half),
|
||||||
|
zoom_center=zoom_c, zoom_half=float(zoom),
|
||||||
|
legend1=["前向角域 W(s, θ ± 1°)", "定位区域 P"],
|
||||||
|
legend2=["直径圆", "最小包围圆 MEC"])
|
||||||
|
return data, Path(src)
|
||||||
|
|
||||||
|
|
||||||
|
def data_geo_q1_counterexample() -> dict[str, Any]:
|
||||||
|
src = ROOT / "examples" / "q1" / "triangle.json"
|
||||||
|
doc = json.loads(src.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, dc, mec = sol["vertices"], sol["dc"], sol["mec"]
|
||||||
|
zoom_c = verts.mean(axis=0)
|
||||||
|
zoom = max(1.9 * float(np.abs(verts - zoom_c).max()) + mec["radius_m"], 45.0)
|
||||||
|
half, view_c = overview_window(np.array([[s[0], s[1]] for s in stations]),
|
||||||
|
verts, dc, mec)
|
||||||
|
wedges = [wedge_polygon((sx, sy), b, hd, 3600.0) for sx, sy, b, hd in stations]
|
||||||
|
region = np.array([[zoom_c[0] - zoom, zoom_c[1] - zoom],
|
||||||
|
[zoom_c[0] + zoom, zoom_c[1] - zoom],
|
||||||
|
[zoom_c[0] + zoom, zoom_c[1] + zoom],
|
||||||
|
[zoom_c[0] - zoom, zoom_c[1] + zoom]], dtype=float)
|
||||||
|
for sx, sy, b, hd in stations:
|
||||||
|
region = clip_wedge(region, (sx, sy), b, hd)
|
||||||
|
return dict(
|
||||||
|
stations=np.array([[s[0], s[1]] for s in stations]),
|
||||||
|
station_labels=[f"s{i + 1}" for i in range(len(stations))],
|
||||||
|
wedges=np.stack(wedges), zoom_wedges=np.stack(wedges),
|
||||||
|
zoom_region=region,
|
||||||
|
dc_center=dc["center"], dc_radius=dc["radius_m"],
|
||||||
|
mec_center=mec["center"], mec_radius=mec["radius_m"],
|
||||||
|
view_center=view_c, half_overview=float(half),
|
||||||
|
zoom_center=zoom_c, zoom_half=float(zoom),
|
||||||
|
legend1=["前向角域 W(s, θ ± 1°)", "定位区域 P"],
|
||||||
|
legend2=["直径圆", "最小包围圆 MEC"])
|
||||||
|
|
||||||
|
|
||||||
|
def data_geo_q2() -> dict[str, Any]:
|
||||||
|
a = 1500.0 / (2 * math.cos(math.radians(1.0)))
|
||||||
|
safe = R_EFF - a
|
||||||
|
c = np.array([a * math.cos(math.radians(30.0)), a * math.sin(math.radians(30.0))])
|
||||||
|
return dict(omega_r=OMEGA_R, wedge=wedge_polygon((0.0, 0.0), 30.0, 1.0, 1500.0),
|
||||||
|
a=float(a), safe=float(safe), c=c, half=1900.0,
|
||||||
|
legend=["前向角域 W(s1)", "截断角域外接圆 B(c, a)",
|
||||||
|
"安全候选盘 B(c, 1000 − a)"])
|
||||||
|
|
||||||
|
|
||||||
|
def data_geo_q3() -> dict[str, Any]:
|
||||||
|
a = RING_RADIUS_M
|
||||||
|
stations = np.array([[0.0, 0.0]] + [[a * math.cos(k * math.pi / 3),
|
||||||
|
a * math.sin(k * math.pi / 3)] for k in range(6)])
|
||||||
|
return dict(omega_r=OMEGA_R, r_eff=R_EFF,
|
||||||
|
stations=stations,
|
||||||
|
worst=np.array([0.0, -SEVEN_R]),
|
||||||
|
half=float(RING_RADIUS_M + R_EFF + 90.0),
|
||||||
|
legend=["区域 Ω", "1000 m 接收盘", "覆盖站点", "最差点"])
|
||||||
|
|
||||||
|
|
||||||
|
def data_geo_q4() -> dict[str, Any]:
|
||||||
|
plan = load_plan("q4_mincover_v2")
|
||||||
|
pts = np.array(plan["points"], dtype=float)
|
||||||
|
theta = np.linspace(-math.pi / 2, math.pi / 2, 60)
|
||||||
|
half_disk = np.vstack([[0.0, 0.5],
|
||||||
|
np.column_stack([0.85 * np.cos(theta),
|
||||||
|
0.5 + 0.85 * np.sin(theta)])])
|
||||||
|
half = float(max(OMEGA_R, np.abs(pts).max()) * 1.06)
|
||||||
|
return dict(omega_r=OMEGA_R, points=pts, half=half, half_disk=half_disk,
|
||||||
|
radius_label="覆盖半径 1000 m",
|
||||||
|
heading_label="前向半盘 ±90°（朝向未知）",
|
||||||
|
legend=["区域 Ω", "31 点最小命中集"])
|
||||||
|
|
||||||
|
|
||||||
|
def data_replay(run: dict[str, Any], *, directional: bool) -> dict[str, Any]:
|
||||||
|
tl = decompose(run)
|
||||||
|
rows = tl["rows"]
|
||||||
|
truth = run["truth"]
|
||||||
|
solved = set(solved_channels(run))
|
||||||
|
truth_pts, truth_solved, truth_labels = [], [], []
|
||||||
|
for src in truth:
|
||||||
|
ch = int(src["channel"])
|
||||||
|
truth_pts.append([src["x"], src["y"]])
|
||||||
|
truth_solved.append(1.0 if ch in solved else 0.0)
|
||||||
|
truth_labels.append(f"ch{ch}")
|
||||||
|
# 定向源：朝向箭头（长度取该源有效接收半径）+ ±90° 前向半盘
|
||||||
|
headings, half_disks = [], []
|
||||||
|
for src in truth:
|
||||||
|
if not (directional and src.get("directional")):
|
||||||
|
continue
|
||||||
|
r = float(src.get("r_eff_m") or R_EFF)
|
||||||
|
ang = math.radians(float(src.get("heading_deg") or 0.0))
|
||||||
|
headings.append([src["x"], src["y"], r * math.cos(ang), r * math.sin(ang)])
|
||||||
|
arc = ang + np.linspace(-math.pi / 2, math.pi / 2, 49)
|
||||||
|
half_disks.append(np.vstack([[src["x"], src["y"]],
|
||||||
|
np.column_stack([src["x"] + r * np.cos(arc),
|
||||||
|
src["y"] + r * np.sin(arc)])]))
|
||||||
|
half_disk_arr = (np.stack(half_disks) if half_disks
|
||||||
|
else np.zeros((0, 50, 2), dtype=float))
|
||||||
|
path = [(0.0, 0.0)]
|
||||||
|
rays, clears, marks, events = [], [], [], []
|
||||||
|
for act, row in zip(run["actions"], rows):
|
||||||
|
if act["path"] == "/measure" and row["hit"]:
|
||||||
|
bearing = math.radians(float(act["response"].get("svd_deg") or 0.0))
|
||||||
|
rays.append([row["x"], row["y"], 220 * math.cos(bearing),
|
||||||
|
220 * math.sin(bearing)])
|
||||||
|
if act["path"] in ("/measure", "/clear") and row["x"] is not None:
|
||||||
|
if (row["x"], row["y"]) != path[-1]:
|
||||||
|
path.append((row["x"], row["y"]))
|
||||||
|
if act["path"] == "/clear":
|
||||||
|
clears.append([row["x"], row["y"], 1.0 if row["cleared"] else 0.0])
|
||||||
|
marks.append([row["virtual_s"], 1.0 if row["hit"] else 0.0,
|
||||||
|
1.0 if act["path"] == "/clear" and row["cleared"] else 0.0])
|
||||||
|
if len(events) < 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'}"
|
||||||
|
else:
|
||||||
|
detail = "启动会话" if act["path"] == "/enter" else "退出"
|
||||||
|
events.append([act["path"], detail, f"{row['virtual_s']:.0f}"])
|
||||||
|
legend = ["移动轨迹", "检测示向度", "已清除频道", "未清除频道"]
|
||||||
|
if directional:
|
||||||
|
legend = ["移动轨迹", "检测示向度", "定向源前向半盘 (±90°)",
|
||||||
|
"已清除频道", "未清除频道"]
|
||||||
|
# 世界视图窗口：容纳 Ω、轨迹、射线与定向半盘，避免半盘被画到框外
|
||||||
|
geom = [np.asarray(truth_pts, dtype=float), np.asarray(path, dtype=float)]
|
||||||
|
if rays:
|
||||||
|
rays_arr = np.asarray(rays, dtype=float)
|
||||||
|
geom.append(rays_arr[:, :2] + rays_arr[:, 2:])
|
||||||
|
if half_disk_arr.size:
|
||||||
|
geom.append(half_disk_arr.reshape(-1, 2))
|
||||||
|
half = float(max(OMEGA_R, np.abs(np.vstack(geom)).max()) * 1.06)
|
||||||
|
return dict(
|
||||||
|
omega_r=OMEGA_R, half=half,
|
||||||
|
out_png=("replay-webui-q4-directional.png" if directional
|
||||||
|
else "replay-webui-q3-omnidirectional.png"),
|
||||||
|
truth=np.array(truth_pts, dtype=float),
|
||||||
|
truth_solved=np.array(truth_solved, dtype=float).reshape(-1, 1),
|
||||||
|
truth_labels=truth_labels,
|
||||||
|
headings=np.array(headings, dtype=float).reshape(-1, 4),
|
||||||
|
half_disks=half_disk_arr,
|
||||||
|
path=np.array(path, dtype=float),
|
||||||
|
rays=np.array(rays, dtype=float).reshape(-1, 4),
|
||||||
|
clears=np.array(clears, dtype=float).reshape(-1, 3),
|
||||||
|
marks=np.array(marks, dtype=float).reshape(-1, 3),
|
||||||
|
events=events, total_s=float(tl["virtual_s"]), legend=legend)
|
||||||
|
|
||||||
|
|
||||||
|
# ---------------------------------------------------------------------------
|
||||||
|
# 产出
|
||||||
|
# ---------------------------------------------------------------------------
|
||||||
|
def _as_cell(values: Any) -> np.ndarray:
|
||||||
|
"""字符串列表 → object 数组（MATLAB cell）；纯数值嵌套列表 → 数值矩阵。"""
|
||||||
|
if isinstance(values, str):
|
||||||
|
return np.array([values], dtype=object)
|
||||||
|
if isinstance(values, (list, tuple)):
|
||||||
|
if values and all(isinstance(v, (list, tuple)) and
|
||||||
|
all(isinstance(x, (int, float)) for x in v)
|
||||||
|
for v in values):
|
||||||
|
return np.asarray(values, dtype=float)
|
||||||
|
return np.array([_as_cell(v) if isinstance(v, (list, tuple)) else v
|
||||||
|
for v in values], dtype=object)
|
||||||
|
return np.asarray(values)
|
||||||
|
|
||||||
|
|
||||||
|
def write_mat(name: str, data: dict[str, Any]) -> None:
|
||||||
|
"""写 .mat；字符串字段转 object 数组，MATLAB 侧按 cell 读取。"""
|
||||||
|
DATA_DIR.mkdir(parents=True, exist_ok=True)
|
||||||
|
|
||||||
|
def wrap(value: Any, key: str) -> Any: # noqa: ARG001
|
||||||
|
if isinstance(value, (str, list, tuple)):
|
||||||
|
return _as_cell(value)
|
||||||
|
return value
|
||||||
|
|
||||||
|
payload = {key: wrap(value, key) for key, value in data.items()}
|
||||||
|
savemat(DATA_DIR / f"{name}.mat", payload, do_compression=True,
|
||||||
|
long_field_names=True)
|
||||||
|
|
||||||
|
|
||||||
|
def prepare(only: Sequence[str] | None) -> dict[str, list[dict[str, Any]]]:
|
||||||
|
"""写全部 .mat 数据，返回每张图的数据来源。"""
|
||||||
|
want = set(only) if only else None
|
||||||
|
runs = discover_runs()
|
||||||
|
q3 = pick_run(runs, "q3", 10) if runs else None
|
||||||
|
q4 = (pick_case(runs, Q4_REPLAY_CASE) if runs else None) or \
|
||||||
|
(pick_run(runs, "q4", 12) if runs else None)
|
||||||
|
sources: dict[str, list[dict[str, Any]]] = {}
|
||||||
|
|
||||||
|
def need(stem: str) -> bool:
|
||||||
|
return want is None or stem in want
|
||||||
|
|
||||||
|
build: list[tuple[str, str, Callable[[], dict[str, Any]]]] = [
|
||||||
|
("flow-overall-architecture", "flow_overall", data_flow_overall),
|
||||||
|
("steps-state-machine", "steps_state_machine", data_steps_state_machine),
|
||||||
|
("timing-attachment-example-105-111-194-199", "timing_attachment",
|
||||||
|
data_timing_attachment),
|
||||||
|
("geo-q1-diameter-circle-counterexample", "geo_q1_counterexample",
|
||||||
|
data_geo_q1_counterexample),
|
||||||
|
("geo-q2-guaranteed-reception-disk", "geo_q2", data_geo_q2),
|
||||||
|
("geo-q3-seven-point-coverage", "geo_q3", data_geo_q3),
|
||||||
|
("geo-q4-minimum-cover-31-points", "geo_q4", data_geo_q4),
|
||||||
|
]
|
||||||
|
for stem, name, maker in build:
|
||||||
|
if not need(stem):
|
||||||
|
continue
|
||||||
|
write_mat(name, maker())
|
||||||
|
sources[stem] = [source(p) for p in SOURCES.get(stem, [])]
|
||||||
|
|
||||||
|
if need("geo-q1-convex-intersection-zoom"):
|
||||||
|
data, src = data_geo_q1_meetup()
|
||||||
|
write_mat("geo_q1_meetup", data)
|
||||||
|
sources["geo-q1-convex-intersection-zoom"] = [source(src)]
|
||||||
|
if q3:
|
||||||
|
if need("timing-measured-q3-10-sources"):
|
||||||
|
write_mat("timing_measured", data_timing_measured(q3))
|
||||||
|
sources["timing-measured-q3-10-sources"] = [
|
||||||
|
source(q3["source"], case_code=q3["case_code"], module=q3["module"])]
|
||||||
|
if need("replay-webui-q3-omnidirectional"):
|
||||||
|
write_mat("replay_q3", data_replay(q3, directional=False))
|
||||||
|
sources["replay-webui-q3-omnidirectional"] = [
|
||||||
|
source(q3["source"], case_code=q3["case_code"])]
|
||||||
|
if q4 and need("replay-webui-q4-directional"):
|
||||||
|
write_mat("replay_q4", data_replay(q4, directional=True))
|
||||||
|
sources["replay-webui-q4-directional"] = [
|
||||||
|
source(q4["source"], case_code=q4["case_code"])]
|
||||||
|
return sources
|
||||||
|
|
||||||
|
|
||||||
|
def run_matlab(only: Sequence[str] | None, matlab_bin: Path) -> None:
|
||||||
|
"""逐张调用 MATLAB 出图。
|
||||||
|
|
||||||
|
本机实测：同一 MATLAB 批处理会话里渲染第二张图时图形子系统会崩溃，
|
||||||
|
因此每张图单独起一个会话（每次约数秒），并显式 exit。
|
||||||
|
"""
|
||||||
|
if not matlab_bin.is_file():
|
||||||
|
raise SystemExit(f"未找到 MATLAB：{matlab_bin}")
|
||||||
|
want = set(only) if only else None
|
||||||
|
log = MATLAB_DIR / "matlab_run.log"
|
||||||
|
lines: list[str] = []
|
||||||
|
for stem, fn, name in FIGURES:
|
||||||
|
if want and stem not in want:
|
||||||
|
continue
|
||||||
|
call = f"{fn}('{name}')" if fn == "fig_replay" else f"{fn}()"
|
||||||
|
script = (f"cd('{MATLAB_DIR}'); addpath('{MATLAB_DIR}'); "
|
||||||
|
f"{call}; exit")
|
||||||
|
proc = subprocess.run([str(matlab_bin), "-batch", script],
|
||||||
|
capture_output=True, text=True, check=False)
|
||||||
|
ok = (OUT_DIR / f"{stem}.png").is_file()
|
||||||
|
lines.append(f"{'OK ' if ok else 'FAIL'} {stem}")
|
||||||
|
if not ok:
|
||||||
|
tail = [ln for ln in (proc.stdout + proc.stderr).splitlines()
|
||||||
|
if ln.strip() and "Keyboard" not in ln and "TISFile" not in ln]
|
||||||
|
lines.extend(f" {ln}" for ln in tail[-6:])
|
||||||
|
log.write_text("\n".join(lines) + "\n", encoding="utf-8")
|
||||||
|
|
||||||
|
|
||||||
|
def finish(only: Sequence[str] | None, sources: dict[str, list[dict[str, Any]]]) -> None:
|
||||||
|
"""删掉历史遗留的 SVG，写 manifest。"""
|
||||||
|
for stale in OUT_DIR.glob("*.svg"):
|
||||||
|
stale.unlink()
|
||||||
|
want = set(only) if only else None
|
||||||
|
entries = []
|
||||||
|
for stem, fn, _name in FIGURES:
|
||||||
|
if want and stem not in want:
|
||||||
|
continue
|
||||||
|
png = OUT_DIR / f"{stem}.png"
|
||||||
|
entry = {"stem": stem, "png": str(png.relative_to(ROOT)),
|
||||||
|
"matlab": f"scripts/matlab/{fn}.m",
|
||||||
|
"sources": sources.get(stem, [])}
|
||||||
|
if not png.is_file():
|
||||||
|
entry["missing"] = True
|
||||||
|
entries.append(entry)
|
||||||
|
manifest = {
|
||||||
|
"generator": "scripts/build_figure_data.py（数据）+ scripts/matlab/*.m（MATLAB 出图）",
|
||||||
|
"command": "uv run python scripts/build_figure_data.py"
|
||||||
|
+ (f" --only {','.join(only)}" if only else ""),
|
||||||
|
"manual": "MATLAB 中 cd scripts/matlab 后执行 run_all_figures",
|
||||||
|
"figures": entries,
|
||||||
|
}
|
||||||
|
(OUT_DIR / "manifest.json").write_text(
|
||||||
|
json.dumps(manifest, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> int:
|
||||||
|
parser = argparse.ArgumentParser(description=__doc__.splitlines()[0])
|
||||||
|
parser.add_argument("--only", default="", help="逗号分隔的图名子集（见 --list）")
|
||||||
|
parser.add_argument("--prepare", action="store_true", help="只写 .mat 数据，不调 MATLAB")
|
||||||
|
parser.add_argument("--list", action="store_true", help="列出全部图名")
|
||||||
|
parser.add_argument("--matlab", default=str(MATLAB_BIN), help="matlab 可执行文件路径")
|
||||||
|
args = parser.parse_args()
|
||||||
|
names = [stem for stem, _fn, _name in FIGURES]
|
||||||
|
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 set(names)]
|
||||||
|
if unknown:
|
||||||
|
parser.error(f"未知图名 {unknown}")
|
||||||
|
|
||||||
|
sources = prepare(only or None)
|
||||||
|
if args.prepare:
|
||||||
|
print(f"[fig] 已写入 {len(list(DATA_DIR.glob('*.mat')))} 个 .mat → "
|
||||||
|
f"{DATA_DIR.relative_to(ROOT)}")
|
||||||
|
return 0
|
||||||
|
targets = only or names
|
||||||
|
for stem in targets: # 先清掉旧文件：只认本次生成的
|
||||||
|
(OUT_DIR / f"{stem}.png").unlink(missing_ok=True)
|
||||||
|
run_matlab(only or None, Path(args.matlab))
|
||||||
|
finish(only or None, sources)
|
||||||
|
missing = []
|
||||||
|
for stem in targets:
|
||||||
|
if (OUT_DIR / f"{stem}.png").is_file():
|
||||||
|
print(f"[fig] OK {stem}")
|
||||||
|
else:
|
||||||
|
missing.append(stem)
|
||||||
|
print(f"[fig] 缺失 {stem}")
|
||||||
|
print(f"[fig] manifest → {(OUT_DIR / 'manifest.json').relative_to(ROOT)}")
|
||||||
|
if missing:
|
||||||
|
print(f"[fig] {len(missing)} 张未生成：{', '.join(missing)}")
|
||||||
|
return 0
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
raise SystemExit(main())
|
||||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,65 @@
|
|||||||
|
function fig_flow_overall()
|
||||||
|
%FIG_FLOW_OVERALL 四层主线：题面抽象（L0）、在线三层（L1）、四问主线（L2）、三条闭环（L3）。
|
||||||
|
% 仅保留分层框图与层标签，图内不放任何说明性文字。
|
||||||
|
|
||||||
|
S = fig_style();
|
||||||
|
D = load_data(S, 'flow_overall');
|
||||||
|
H = geom_helpers();
|
||||||
|
fig = figure('Color', 'w', 'Visible', 'off');
|
||||||
|
ax = axes(fig, 'Position', [0.02 0.06 0.96 0.90], ...
|
||||||
|
'XLim', [0 100], 'YLim', [0 100], 'Visible', 'off');
|
||||||
|
hold(ax, 'on');
|
||||||
|
|
||||||
|
n = numel(D.tags);
|
||||||
|
x_tag = 7; % 层标签中心
|
||||||
|
x_lo = 15; x_hi = 99; % 框体水平范围
|
||||||
|
box_gap = 2.2; % 框间距（放箭头）
|
||||||
|
pad = 1.4; % 框内左右留白
|
||||||
|
band_h = 14; % 层高
|
||||||
|
band_gap = 6.5;
|
||||||
|
y_top = 96;
|
||||||
|
|
||||||
|
% 统一字号：逐行按量得的文本宽度试算，保证一排框加间距放得下
|
||||||
|
fs = ax.FontSize;
|
||||||
|
while fs > 8
|
||||||
|
need_max = 0;
|
||||||
|
for b = 1:n
|
||||||
|
labels = D.labels{b};
|
||||||
|
m = numel(labels);
|
||||||
|
need = sum(cellfun(@(s) H.text_width(ax, s, fs), labels)) ...
|
||||||
|
+ 2 * pad * m + box_gap * (m - 1);
|
||||||
|
need_max = max(need_max, need);
|
||||||
|
end
|
||||||
|
if need_max <= x_hi - x_lo
|
||||||
|
break;
|
||||||
|
end
|
||||||
|
fs = fs - 0.5;
|
||||||
|
end
|
||||||
|
|
||||||
|
for b = 1:n
|
||||||
|
labels = D.labels{b};
|
||||||
|
m = numel(labels);
|
||||||
|
tw = cellfun(@(s) H.text_width(ax, s, fs), labels);
|
||||||
|
avail = (x_hi - x_lo) - box_gap * (m - 1);
|
||||||
|
w = (tw + 2 * pad) * avail / sum(tw + 2 * pad);
|
||||||
|
y = y_top - band_h - (b - 1) * (band_h + band_gap);
|
||||||
|
color = pick_color(S, D.colors{b});
|
||||||
|
text(ax, x_tag, y + band_h / 2, D.tags{b}, 'FontSize', fs + 1, ...
|
||||||
|
'HorizontalAlignment', 'center', 'VerticalAlignment', 'middle');
|
||||||
|
x = x_lo;
|
||||||
|
for i = 1:m
|
||||||
|
rectangle(ax, 'Position', [x, y, w(i), band_h], 'FaceColor', 'w', ...
|
||||||
|
'EdgeColor', color, 'LineWidth', 1.1);
|
||||||
|
text(ax, x + w(i) / 2, y + band_h / 2, labels{i}, 'FontSize', fs, ...
|
||||||
|
'HorizontalAlignment', 'center', 'VerticalAlignment', 'middle', ...
|
||||||
|
'Interpreter', 'none');
|
||||||
|
if i < m
|
||||||
|
H.arrow(ax, [x + w(i) + 0.25, y + band_h / 2], ...
|
||||||
|
[x + w(i) + box_gap - 0.25, y + band_h / 2], color);
|
||||||
|
end
|
||||||
|
x = x + w(i) + box_gap;
|
||||||
|
end
|
||||||
|
end
|
||||||
|
hold(ax, 'off');
|
||||||
|
fig_save(fig, S, 'flow-overall-architecture.png');
|
||||||
|
end
|
||||||
@@ -0,0 +1,52 @@
|
|||||||
|
function fig_geo_q1_counterexample()
|
||||||
|
%FIG_GEO_Q1_COUNTEREXAMPLE 问题一：等边三角形布站时直径圆不覆盖定位区域的反例。
|
||||||
|
|
||||||
|
S = fig_style();
|
||||||
|
D = load_data(S, 'geo_q1_counterexample');
|
||||||
|
H = geom_helpers();
|
||||||
|
fig = figure('Color', 'w', 'Visible', 'off');
|
||||||
|
t = tiledlayout(fig, 1, 2, 'TileSpacing', 'compact', 'Padding', 'compact');
|
||||||
|
|
||||||
|
% 左：角域交会总览
|
||||||
|
ax1 = nexttile(t);
|
||||||
|
hold(ax1, 'on');
|
||||||
|
hw = gobjects(0);
|
||||||
|
for i = 1:size(D.wedges, 1)
|
||||||
|
hw = H.wedge(ax1, squeeze(D.wedges(i, :, :)), pick_color(S, 'primary'), 0.25);
|
||||||
|
end
|
||||||
|
hr = plot(ax1, D.zoom_center(1), D.zoom_center(2), 's', 'MarkerSize', 6, ...
|
||||||
|
'MarkerFaceColor', pick_color(S, 'accent'), 'MarkerEdgeColor', 'none');
|
||||||
|
plot(ax1, D.stations(:, 1), D.stations(:, 2), 'o', 'MarkerSize', 6, ...
|
||||||
|
'MarkerFaceColor', pick_color(S, 'accent'), 'MarkerEdgeColor', 'none');
|
||||||
|
H.label_points(ax1, D.stations, D.station_labels, pick_color(S, 'accent'));
|
||||||
|
hold(ax1, 'off');
|
||||||
|
axis(ax1, 'equal');
|
||||||
|
xlim(ax1, D.view_center(1) + [-D.half_overview, D.half_overview]);
|
||||||
|
ylim(ax1, D.view_center(2) + [-D.half_overview, D.half_overview]);
|
||||||
|
xlabel(ax1, 'x / m');
|
||||||
|
ylabel(ax1, 'y / m');
|
||||||
|
legend(ax1, [hw(1), hr], D.legend1, 'Location', 'southoutside', ...
|
||||||
|
'Orientation', 'horizontal');
|
||||||
|
|
||||||
|
% 右：定位区域放大
|
||||||
|
ax2 = nexttile(t);
|
||||||
|
hold(ax2, 'on');
|
||||||
|
for i = 1:size(D.zoom_wedges, 1)
|
||||||
|
H.wedge(ax2, squeeze(D.zoom_wedges(i, :, :)), pick_color(S, 'primary'), 0.25);
|
||||||
|
end
|
||||||
|
H.poly(ax2, D.zoom_region, pick_color(S, 'accent'), 1, 'none', 0.5);
|
||||||
|
hd = H.circle(ax2, D.dc_center, D.dc_radius, pick_color(S, 'violet'), 1.2, '--');
|
||||||
|
hm = H.circle(ax2, D.mec_center, D.mec_radius, pick_color(S, 'success'), 1.4, '-');
|
||||||
|
H.marker(ax2, D.dc_center, pick_color(S, 'violet'), 5, true);
|
||||||
|
H.marker(ax2, D.mec_center, pick_color(S, 'success'), 5, true);
|
||||||
|
hold(ax2, 'off');
|
||||||
|
axis(ax2, 'equal');
|
||||||
|
xlim(ax2, D.zoom_center(1) + [-D.zoom_half, D.zoom_half]);
|
||||||
|
ylim(ax2, D.zoom_center(2) + [-D.zoom_half, D.zoom_half]);
|
||||||
|
xlabel(ax2, 'x / m');
|
||||||
|
ylabel(ax2, 'y / m');
|
||||||
|
legend(ax2, [hd, hm], D.legend2, 'Location', 'southoutside', ...
|
||||||
|
'Orientation', 'horizontal');
|
||||||
|
|
||||||
|
fig_save(fig, S, 'geo-q1-diameter-circle-counterexample.png');
|
||||||
|
end
|
||||||
@@ -0,0 +1,52 @@
|
|||||||
|
function fig_geo_q1_meetup()
|
||||||
|
%FIG_GEO_Q1_MEETUP 问题一：角域交会总览与定位区域放大（直径圆、最小包围圆）。
|
||||||
|
|
||||||
|
S = fig_style();
|
||||||
|
D = load_data(S, 'geo_q1_meetup');
|
||||||
|
H = geom_helpers();
|
||||||
|
fig = figure('Color', 'w', 'Visible', 'off');
|
||||||
|
t = tiledlayout(fig, 1, 2, 'TileSpacing', 'compact', 'Padding', 'compact');
|
||||||
|
|
||||||
|
% 左：角域交会总览（交会区域在总览里只是一个点，放大后见右图）
|
||||||
|
ax1 = nexttile(t);
|
||||||
|
hold(ax1, 'on');
|
||||||
|
hw = gobjects(0);
|
||||||
|
for i = 1:size(D.wedges, 1)
|
||||||
|
hw = H.wedge(ax1, squeeze(D.wedges(i, :, :)), pick_color(S, 'primary'), 0.25);
|
||||||
|
end
|
||||||
|
hr = plot(ax1, D.zoom_center(1), D.zoom_center(2), 's', 'MarkerSize', 6, ...
|
||||||
|
'MarkerFaceColor', pick_color(S, 'accent'), 'MarkerEdgeColor', 'none');
|
||||||
|
plot(ax1, D.stations(:, 1), D.stations(:, 2), 'o', 'MarkerSize', 6, ...
|
||||||
|
'MarkerFaceColor', pick_color(S, 'accent'), 'MarkerEdgeColor', 'none');
|
||||||
|
H.label_points(ax1, D.stations, D.station_labels, pick_color(S, 'accent'));
|
||||||
|
hold(ax1, 'off');
|
||||||
|
axis(ax1, 'equal');
|
||||||
|
xlim(ax1, D.view_center(1) + [-D.half_overview, D.half_overview]);
|
||||||
|
ylim(ax1, D.view_center(2) + [-D.half_overview, D.half_overview]);
|
||||||
|
xlabel(ax1, 'x / m');
|
||||||
|
ylabel(ax1, 'y / m');
|
||||||
|
legend(ax1, [hw(1), hr], D.legend1, 'Location', 'southoutside', ...
|
||||||
|
'Orientation', 'horizontal');
|
||||||
|
|
||||||
|
% 右：定位区域放大
|
||||||
|
ax2 = nexttile(t);
|
||||||
|
hold(ax2, 'on');
|
||||||
|
for i = 1:size(D.zoom_wedges, 1)
|
||||||
|
H.wedge(ax2, squeeze(D.zoom_wedges(i, :, :)), pick_color(S, 'primary'), 0.25);
|
||||||
|
end
|
||||||
|
H.poly(ax2, D.zoom_region, pick_color(S, 'accent'), 1, 'none', 0.5);
|
||||||
|
hd = H.circle(ax2, D.dc_center, D.dc_radius, pick_color(S, 'violet'), 1.2, '--');
|
||||||
|
hm = H.circle(ax2, D.mec_center, D.mec_radius, pick_color(S, 'success'), 1.4, '-');
|
||||||
|
H.marker(ax2, D.dc_center, pick_color(S, 'violet'), 5, true);
|
||||||
|
H.marker(ax2, D.mec_center, pick_color(S, 'success'), 5, true);
|
||||||
|
hold(ax2, 'off');
|
||||||
|
axis(ax2, 'equal');
|
||||||
|
xlim(ax2, D.zoom_center(1) + [-D.zoom_half, D.zoom_half]);
|
||||||
|
ylim(ax2, D.zoom_center(2) + [-D.zoom_half, D.zoom_half]);
|
||||||
|
xlabel(ax2, 'x / m');
|
||||||
|
ylabel(ax2, 'y / m');
|
||||||
|
legend(ax2, [hd, hm], D.legend2, 'Location', 'southoutside', ...
|
||||||
|
'Orientation', 'horizontal');
|
||||||
|
|
||||||
|
fig_save(fig, S, 'geo-q1-convex-intersection-zoom.png');
|
||||||
|
end
|
||||||
@@ -0,0 +1,55 @@
|
|||||||
|
function fig_geo_q2_safe_disk()
|
||||||
|
%FIG_GEO_Q2_SAFE_DISK 问题二：截断角域外接圆与保证接收的安全候选盘。
|
||||||
|
|
||||||
|
S = fig_style();
|
||||||
|
D = load_data(S, 'geo_q2');
|
||||||
|
H = geom_helpers();
|
||||||
|
fig = figure('Color', 'w', 'Visible', 'off');
|
||||||
|
t = tiledlayout(fig, 1, 2, 'TileSpacing', 'compact', 'Padding', 'compact');
|
||||||
|
|
||||||
|
% 左：真实几何（Ω 内的角域与两个候选圆）
|
||||||
|
ax1 = nexttile(t);
|
||||||
|
hold(ax1, 'on');
|
||||||
|
H.circle(ax1, [0 0], D.omega_r, pick_color(S, 'primary'), 1.2, '-');
|
||||||
|
hw = H.wedge(ax1, D.wedge, pick_color(S, 'accent'), 0.25);
|
||||||
|
hd = H.circle(ax1, D.c, D.a, pick_color(S, 'violet'), 1.2, '--');
|
||||||
|
hs = H.disk(ax1, D.c, D.safe, pick_color(S, 'success'), 0.30, '-');
|
||||||
|
H.marker(ax1, [0 0], pick_color(S, 'accent'), 6, true);
|
||||||
|
H.marker(ax1, D.c, pick_color(S, 'violet'), 5, true);
|
||||||
|
H.label_points(ax1, [0 0], {'s1'}, pick_color(S, 'accent'));
|
||||||
|
H.label_points(ax1, D.c, {'c'}, pick_color(S, 'violet'));
|
||||||
|
hold(ax1, 'off');
|
||||||
|
axis(ax1, 'equal');
|
||||||
|
xlim(ax1, [-D.half, D.half]);
|
||||||
|
ylim(ax1, [-D.half, D.half]);
|
||||||
|
xlabel(ax1, 'x / m');
|
||||||
|
ylabel(ax1, 'y / m');
|
||||||
|
legend(ax1, [hw, hd, hs], D.legend, 'Location', 'southoutside', ...
|
||||||
|
'Orientation', 'horizontal');
|
||||||
|
|
||||||
|
% 右：半径分解 a + (1000 − a) = 1000 m
|
||||||
|
ax2 = nexttile(t);
|
||||||
|
hold(ax2, 'on');
|
||||||
|
H.circle(ax2, [0 0], D.a, pick_color(S, 'violet'), 1.2, '--');
|
||||||
|
H.disk(ax2, [0 0], D.safe, pick_color(S, 'success'), 0.30, '-');
|
||||||
|
H.marker(ax2, [0 0], 'k', 5, true);
|
||||||
|
ang = deg2rad(35);
|
||||||
|
p_out = D.a * [cos(ang), sin(ang)];
|
||||||
|
p_in = D.safe * [cos(-ang), sin(-ang)];
|
||||||
|
H.arrow(ax2, [0 0], p_out, pick_color(S, 'violet'));
|
||||||
|
H.arrow(ax2, [0 0], p_in, pick_color(S, 'success'));
|
||||||
|
text(ax2, p_out(1) * 1.06, p_out(2) * 1.12, sprintf('a = %.1f m', D.a), ...
|
||||||
|
'Color', pick_color(S, 'violet'), 'Interpreter', 'none');
|
||||||
|
text(ax2, p_in(1) * 1.04, p_in(2) * 1.30, sprintf('1000 − a = %.1f m', D.safe), ...
|
||||||
|
'Color', pick_color(S, 'success'), 'HorizontalAlignment', 'right', ...
|
||||||
|
'Interpreter', 'none');
|
||||||
|
text(ax2, -D.safe * 0.45, 0, 'c', 'Color', 'k', ...
|
||||||
|
'HorizontalAlignment', 'right', 'VerticalAlignment', 'middle');
|
||||||
|
hold(ax2, 'off');
|
||||||
|
axis(ax2, 'equal');
|
||||||
|
xlim(ax2, [-D.a * 1.15, D.a * 1.75]);
|
||||||
|
ylim(ax2, [-D.a * 1.05, D.a * 1.05]);
|
||||||
|
axis(ax2, 'off');
|
||||||
|
|
||||||
|
fig_save(fig, S, 'geo-q2-guaranteed-reception-disk.png');
|
||||||
|
end
|
||||||
@@ -0,0 +1,29 @@
|
|||||||
|
function fig_geo_q3_coverage()
|
||||||
|
%FIG_GEO_Q3_COVERAGE 问题三：七个 1000 m 接收盘覆盖区域 Ω。
|
||||||
|
|
||||||
|
S = fig_style();
|
||||||
|
D = load_data(S, 'geo_q3');
|
||||||
|
H = geom_helpers();
|
||||||
|
fig = figure('Color', 'w', 'Visible', 'off');
|
||||||
|
ax = axes(fig);
|
||||||
|
hold(ax, 'on');
|
||||||
|
|
||||||
|
hd = gobjects(0);
|
||||||
|
for i = 1:size(D.stations, 1)
|
||||||
|
hd = H.disk(ax, D.stations(i, :), D.r_eff, pick_color(S, 'success'), 0.18, '-');
|
||||||
|
end
|
||||||
|
hw = H.circle(ax, [0 0], D.omega_r, pick_color(S, 'primary'), 1.2, '-');
|
||||||
|
hs = plot(ax, D.stations(:, 1), D.stations(:, 2), 'o', 'MarkerSize', 6, ...
|
||||||
|
'MarkerFaceColor', pick_color(S, 'accent'), 'MarkerEdgeColor', 'none');
|
||||||
|
hx = H.marker(ax, D.worst, 'k', 8, false);
|
||||||
|
hold(ax, 'off');
|
||||||
|
axis(ax, 'equal');
|
||||||
|
xlim(ax, [-D.half, D.half]);
|
||||||
|
ylim(ax, [-D.half, D.half]);
|
||||||
|
xlabel(ax, 'x / m');
|
||||||
|
ylabel(ax, 'y / m');
|
||||||
|
legend(ax, [hw, hd(1), hs, hx], D.legend, 'Location', 'southoutside', ...
|
||||||
|
'Orientation', 'horizontal');
|
||||||
|
|
||||||
|
fig_save(fig, S, 'geo-q3-seven-point-coverage.png');
|
||||||
|
end
|
||||||
@@ -0,0 +1,44 @@
|
|||||||
|
function fig_geo_q4_mincover()
|
||||||
|
%FIG_GEO_Q4_MINCOVER 问题四：31 点最小命中集与前向半盘覆盖语义。
|
||||||
|
|
||||||
|
S = fig_style();
|
||||||
|
D = load_data(S, 'geo_q4');
|
||||||
|
H = geom_helpers();
|
||||||
|
fig = figure('Color', 'w', 'Visible', 'off');
|
||||||
|
t = tiledlayout(fig, 1, 2, 'TileSpacing', 'compact', 'Padding', 'compact');
|
||||||
|
|
||||||
|
% 左：Ω 内的 31 个覆盖点
|
||||||
|
ax1 = nexttile(t);
|
||||||
|
hold(ax1, 'on');
|
||||||
|
hw = H.circle(ax1, [0 0], D.omega_r, pick_color(S, 'primary'), 1.2, '-');
|
||||||
|
hp = plot(ax1, D.points(:, 1), D.points(:, 2), 'o', 'MarkerSize', 5, ...
|
||||||
|
'MarkerFaceColor', pick_color(S, 'accent'), 'MarkerEdgeColor', 'none');
|
||||||
|
hold(ax1, 'off');
|
||||||
|
axis(ax1, 'equal');
|
||||||
|
xlim(ax1, [-D.half, D.half]);
|
||||||
|
ylim(ax1, [-D.half, D.half]);
|
||||||
|
xlabel(ax1, 'x / m');
|
||||||
|
ylabel(ax1, 'y / m');
|
||||||
|
legend(ax1, [hw, hp], D.legend, 'Location', 'southoutside', ...
|
||||||
|
'Orientation', 'horizontal');
|
||||||
|
|
||||||
|
% 右：前向半盘（朝向未知，±90°）
|
||||||
|
ax2 = nexttile(t);
|
||||||
|
hold(ax2, 'on');
|
||||||
|
H.poly(ax2, D.half_disk, pick_color(S, 'accent'), 0.30, 'none', 0.5);
|
||||||
|
H.circle(ax2, [0 0.5], 0.85, pick_color(S, 'muted'), 0.9, '-');
|
||||||
|
plot(ax2, [0 0], [0.5 - 0.85, 0.5 + 0.85], '--', ...
|
||||||
|
'Color', pick_color(S, 'accent'), 'LineWidth', 1.0);
|
||||||
|
H.arrow(ax2, [0 0.5], [0.85 0.5], pick_color(S, 'accent'));
|
||||||
|
text(ax2, 0.425, 0.30, D.radius_label, 'HorizontalAlignment', 'center', ...
|
||||||
|
'Interpreter', 'none');
|
||||||
|
text(ax2, 0.0, 1.55, D.heading_label, 'HorizontalAlignment', 'center', ...
|
||||||
|
'Interpreter', 'none');
|
||||||
|
hold(ax2, 'off');
|
||||||
|
axis(ax2, 'equal');
|
||||||
|
xlim(ax2, [-1.15 1.35]);
|
||||||
|
ylim(ax2, [-0.55 1.75]);
|
||||||
|
axis(ax2, 'off');
|
||||||
|
|
||||||
|
fig_save(fig, S, 'geo-q4-minimum-cover-31-points.png');
|
||||||
|
end
|
||||||
@@ -0,0 +1,109 @@
|
|||||||
|
function fig_replay(name)
|
||||||
|
%FIG_REPLAY 回放画布（点运动图）：世界视图 + 事件流水 + 虚拟时间轴。
|
||||||
|
% name: 'replay_q3' 或 'replay_q4'，对应 docs/figures/.data/<name>.mat。
|
||||||
|
% 本图是唯一保留自定义画布版式的图：三个区互不重叠，图例置于世界视图下方。
|
||||||
|
|
||||||
|
if nargin < 1
|
||||||
|
name = 'replay_q3';
|
||||||
|
end
|
||||||
|
S = fig_style();
|
||||||
|
D = load_data(S, name);
|
||||||
|
H = geom_helpers();
|
||||||
|
fig = figure('Color', 'w', 'Visible', 'off', 'Position', [100 100 1040 660]);
|
||||||
|
|
||||||
|
c_path = [0.35 0.35 0.35];
|
||||||
|
c_ray = pick_color(S, 'primary');
|
||||||
|
c_solved = pick_color(S, 'success');
|
||||||
|
c_unsolv = pick_color(S, 'accent');
|
||||||
|
c_head = pick_color(S, 'violet');
|
||||||
|
|
||||||
|
% ---------------- 世界视图 ----------------
|
||||||
|
ax = axes(fig, 'Position', [0.075 0.40 0.49 0.56]);
|
||||||
|
hold(ax, 'on');
|
||||||
|
H.circle(ax, [0 0], D.omega_r, pick_color(S, 'primary'), 1.2, '-');
|
||||||
|
h_path = plot(ax, D.path(:, 1), D.path(:, 2), 'Color', c_path, 'LineWidth', 0.9);
|
||||||
|
h_ray = plot(ax, nan, nan, 'Color', c_ray, 'LineWidth', 0.8);
|
||||||
|
for i = 1:size(D.rays, 1)
|
||||||
|
p0 = D.rays(i, 1:2);
|
||||||
|
p1 = p0 + D.rays(i, 3:4);
|
||||||
|
plot(ax, [p0(1) p1(1)], [p0(2) p1(2)], 'Color', c_ray, 'LineWidth', 0.8);
|
||||||
|
end
|
||||||
|
h_disk = gobjects(0);
|
||||||
|
for i = 1:size(D.half_disks, 1)
|
||||||
|
disk = squeeze(D.half_disks(i, :, :));
|
||||||
|
h_disk(end + 1) = patch(ax, 'XData', disk(:, 1), 'YData', disk(:, 2), ...
|
||||||
|
'FaceColor', c_head, 'FaceAlpha', 0.10, ...
|
||||||
|
'EdgeColor', c_head, 'LineWidth', 0.8); %#ok<AGROW>
|
||||||
|
end
|
||||||
|
for i = 1:size(D.headings, 1)
|
||||||
|
p0 = D.headings(i, 1:2);
|
||||||
|
p1 = p0 + D.headings(i, 3:4);
|
||||||
|
H.arrow(ax, p0, p1, c_head);
|
||||||
|
end
|
||||||
|
solved = D.truth_solved > 0.5;
|
||||||
|
h_solved = plot(ax, D.truth(solved, 1), D.truth(solved, 2), 'o', ...
|
||||||
|
'MarkerSize', 6, 'MarkerFaceColor', c_solved, 'MarkerEdgeColor', 'none');
|
||||||
|
h_unsolv = plot(ax, D.truth(~solved, 1), D.truth(~solved, 2), 'o', ...
|
||||||
|
'MarkerSize', 6, 'MarkerFaceColor', c_unsolv, 'MarkerEdgeColor', 'none');
|
||||||
|
label_color = repmat(c_unsolv, size(D.truth, 1), 1);
|
||||||
|
label_color(solved, :) = repmat(c_solved, nnz(solved), 1);
|
||||||
|
H.label_points(ax, D.truth, D.truth_labels, label_color);
|
||||||
|
plot(ax, D.clears(D.clears(:, 3) > 0.5, 1), D.clears(D.clears(:, 3) > 0.5, 2), ...
|
||||||
|
'x', 'MarkerSize', 7, 'LineWidth', 1.4, 'Color', c_solved);
|
||||||
|
plot(ax, D.clears(D.clears(:, 3) <= 0.5, 1), D.clears(D.clears(:, 3) <= 0.5, 2), ...
|
||||||
|
'o', 'MarkerSize', 6, 'MarkerEdgeColor', 'k', 'MarkerFaceColor', 'none');
|
||||||
|
hold(ax, 'off');
|
||||||
|
axis(ax, 'equal');
|
||||||
|
xlim(ax, [-D.half, D.half]);
|
||||||
|
ylim(ax, [-D.half, D.half]);
|
||||||
|
xlabel(ax, 'x / m');
|
||||||
|
ylabel(ax, 'y / m');
|
||||||
|
hleg = [h_path, h_ray];
|
||||||
|
if ~isempty(h_disk)
|
||||||
|
hleg(end + 1) = h_disk(1);
|
||||||
|
end
|
||||||
|
hleg = [hleg, h_solved, h_unsolv];
|
||||||
|
legend(ax, hleg, D.legend, 'Location', 'southoutside', 'Orientation', 'horizontal');
|
||||||
|
|
||||||
|
% ---------------- 事件流水 ----------------
|
||||||
|
ex = axes(fig, 'Position', [0.625 0.40 0.345 0.56], ...
|
||||||
|
'XLim', [0 1], 'YLim', [0 1], 'Visible', 'off');
|
||||||
|
hold(ex, 'on');
|
||||||
|
cols = [0.00 0.34 1.00];
|
||||||
|
align = {'left', 'left', 'right'};
|
||||||
|
head = {'动作', '参数', 't / s'};
|
||||||
|
for j = 1:3
|
||||||
|
text(ex, cols(j), 0.97, head{j}, 'FontWeight', 'bold', ...
|
||||||
|
'HorizontalAlignment', align{j});
|
||||||
|
end
|
||||||
|
for i = 1:size(D.events, 1)
|
||||||
|
y = 0.90 - (i - 1) * 0.088;
|
||||||
|
for j = 1:3
|
||||||
|
text(ex, cols(j), y, D.events{i, j}, 'HorizontalAlignment', align{j}, ...
|
||||||
|
'Interpreter', 'none');
|
||||||
|
end
|
||||||
|
end
|
||||||
|
hold(ex, 'off');
|
||||||
|
|
||||||
|
% ---------------- 虚拟时间轴 ----------------
|
||||||
|
tx = axes(fig, 'Position', [0.075 0.155 0.90 0.125]);
|
||||||
|
hold(tx, 'on');
|
||||||
|
rectangle(tx, 'Position', [0 0.34 D.total_s 0.32], ...
|
||||||
|
'FaceColor', pick_color(S, 'primary'), 'FaceAlpha', 0.12, ...
|
||||||
|
'EdgeColor', 'none');
|
||||||
|
for i = 1:size(D.marks, 1)
|
||||||
|
t = D.marks(i, 1);
|
||||||
|
if D.marks(i, 3) > 0.5
|
||||||
|
plot(tx, [t t], [0.05 0.95], 'Color', c_solved, 'LineWidth', 1.0);
|
||||||
|
elseif D.marks(i, 2) > 0.5
|
||||||
|
plot(tx, [t t], [0.22 0.78], 'Color', c_unsolv, 'LineWidth', 0.8);
|
||||||
|
end
|
||||||
|
end
|
||||||
|
hold(tx, 'off');
|
||||||
|
xlim(tx, [0 D.total_s]);
|
||||||
|
ylim(tx, [0 1]);
|
||||||
|
set(tx, 'YTick', []);
|
||||||
|
xlabel(tx, '虚拟时间 t / s');
|
||||||
|
|
||||||
|
fig_save(fig, S, D.out_png{1});
|
||||||
|
end
|
||||||
@@ -0,0 +1,11 @@
|
|||||||
|
function fig_save(fig, S, name)
|
||||||
|
%FIG_SAVE 导出白底 PNG（300 dpi）并关闭图形窗口。
|
||||||
|
% 导出前关掉坐标轴工具条，避免交互按钮被画进图片。
|
||||||
|
axs = findall(fig, 'Type', 'axes');
|
||||||
|
for k = 1:numel(axs)
|
||||||
|
axs(k).Toolbar.Visible = 'off';
|
||||||
|
end
|
||||||
|
exportgraphics(fig, fullfile(S.out_dir, name), 'Resolution', S.dpi, ...
|
||||||
|
'BackgroundColor', 'white');
|
||||||
|
close(fig);
|
||||||
|
end
|
||||||
@@ -0,0 +1,34 @@
|
|||||||
|
function fig_steps_state_machine()
|
||||||
|
%FIG_STEPS_STATE_MACHINE 会话状态机：IDLE → 倒计时 → OPEN → CLOSED。
|
||||||
|
% 只画状态框与迁移箭头，图内不放任何说明性文字。
|
||||||
|
|
||||||
|
S = fig_style();
|
||||||
|
D = load_data(S, 'steps_state_machine');
|
||||||
|
H = geom_helpers();
|
||||||
|
fig = figure('Color', 'w', 'Visible', 'off', 'Position', [100 100 900 240]);
|
||||||
|
ax = axes(fig, 'Position', [0.02 0.10 0.96 0.80], ...
|
||||||
|
'XLim', [0 100], 'YLim', [0 100], 'Visible', 'off');
|
||||||
|
hold(ax, 'on');
|
||||||
|
|
||||||
|
n = numel(D.labels);
|
||||||
|
w = 21;
|
||||||
|
gap = 4.0;
|
||||||
|
x0 = (100 - (n * w + (n - 1) * gap)) / 2;
|
||||||
|
y0 = 25;
|
||||||
|
h = 50;
|
||||||
|
for i = 1:n
|
||||||
|
x = x0 + (i - 1) * (w + gap);
|
||||||
|
color = pick_color(S, D.edges{i});
|
||||||
|
rectangle(ax, 'Position', [x, y0, w, h], 'FaceColor', 'w', ...
|
||||||
|
'EdgeColor', color, 'LineWidth', 1.2);
|
||||||
|
text(ax, x + w / 2, y0 + h / 2, D.labels{i}, ...
|
||||||
|
'HorizontalAlignment', 'center', 'VerticalAlignment', 'middle', ...
|
||||||
|
'Interpreter', 'none');
|
||||||
|
if i < n
|
||||||
|
H.arrow(ax, [x + w + 0.5, y0 + h / 2], ...
|
||||||
|
[x + w + gap - 0.5, y0 + h / 2], color);
|
||||||
|
end
|
||||||
|
end
|
||||||
|
hold(ax, 'off');
|
||||||
|
fig_save(fig, S, 'steps-state-machine.png');
|
||||||
|
end
|
||||||
@@ -0,0 +1,11 @@
|
|||||||
|
function S = fig_style()
|
||||||
|
%FIG_STYLE 出图环境：目录、导出参数与 MATLAB 默认配色。
|
||||||
|
% 除 fig_replay（回放画布，点运动图）外，各图一律使用 MATLAB 默认图形样式：
|
||||||
|
% 默认配色、默认字体、默认坐标轴与图例；本函数不设置任何自定义样式。
|
||||||
|
|
||||||
|
root = fileparts(fileparts(fileparts(mfilename('fullpath'))));
|
||||||
|
S.data_dir = fullfile(root, 'docs', 'figures', '.data');
|
||||||
|
S.out_dir = fullfile(root, 'docs', 'figures');
|
||||||
|
S.dpi = 300; % 论文插图导出分辨率
|
||||||
|
S.c = get(groot, 'defaultAxesColorOrder'); % 默认配色（7×3）
|
||||||
|
end
|
||||||
@@ -0,0 +1,29 @@
|
|||||||
|
function fig_timing_attachment()
|
||||||
|
%FIG_TIMING_ATTACHMENT 附件计时示例：逐动作的耗时构成（堆叠条形）与单步合计。
|
||||||
|
|
||||||
|
S = fig_style();
|
||||||
|
D = load_data(S, 'timing_attachment');
|
||||||
|
fig = figure('Color', 'w', 'Visible', 'off');
|
||||||
|
ax = axes(fig);
|
||||||
|
|
||||||
|
n = numel(D.labels);
|
||||||
|
Y = [D.move(:), D.switch_s(:), D.action(:)];
|
||||||
|
y = (n:-1:1)'; % 动作按先后从上到下排列
|
||||||
|
barh(ax, y, Y, 'stacked');
|
||||||
|
total = sum(Y, 2);
|
||||||
|
xlim(ax, [0, max(total) * 1.18]);
|
||||||
|
hold(ax, 'on');
|
||||||
|
for i = 1:n
|
||||||
|
if total(i) > 0
|
||||||
|
text(ax, total(i) + max(total) * 0.02, y(i), ...
|
||||||
|
sprintf('%.0f s', total(i)), 'VerticalAlignment', 'middle', ...
|
||||||
|
'Interpreter', 'none');
|
||||||
|
end
|
||||||
|
end
|
||||||
|
hold(ax, 'off');
|
||||||
|
set(ax, 'YTick', 1:n, 'YTickLabel', flipud(D.labels(:)), ...
|
||||||
|
'TickLabelInterpreter', 'none');
|
||||||
|
xlabel(ax, D.xlabel);
|
||||||
|
legend(ax, D.legend);
|
||||||
|
fig_save(fig, S, 'timing-attachment-example-105-111-194-199.png');
|
||||||
|
end
|
||||||
@@ -0,0 +1,17 @@
|
|||||||
|
function fig_timing_measured()
|
||||||
|
%FIG_TIMING_MEASURED 实测一局：累计虚拟时间按动作类型的堆叠构成。
|
||||||
|
|
||||||
|
S = fig_style();
|
||||||
|
D = load_data(S, 'timing_measured');
|
||||||
|
fig = figure('Color', 'w', 'Visible', 'off');
|
||||||
|
ax = axes(fig);
|
||||||
|
|
||||||
|
seq = D.seq(:);
|
||||||
|
bands = [D.cum(:, 1), diff(D.cum, 1, 2)]; % area 对矩阵按列堆叠，这里给每层厚度
|
||||||
|
h = area(ax, seq, bands, 'FaceAlpha', 1);
|
||||||
|
xlim(ax, [seq(1), seq(end)]);
|
||||||
|
xlabel(ax, D.xlabel);
|
||||||
|
ylabel(ax, D.ylabel);
|
||||||
|
legend(ax, h, D.legend, 'Location', 'northwest');
|
||||||
|
fig_save(fig, S, 'timing-measured-q3-10-sources.png');
|
||||||
|
end
|
||||||
@@ -0,0 +1,194 @@
|
|||||||
|
function H = geom_helpers()
|
||||||
|
%GEOM_HELPERS 几何示意图共用的绘制函数。
|
||||||
|
% 只使用 MATLAB 默认图形对象与默认配色，不做自定义样式。
|
||||||
|
|
||||||
|
H.circle = @draw_circle;
|
||||||
|
H.wedge = @draw_wedge;
|
||||||
|
H.disk = @draw_disk;
|
||||||
|
H.poly = @draw_poly;
|
||||||
|
H.marker = @draw_marker;
|
||||||
|
H.arrow = @draw_arrow;
|
||||||
|
H.label_points = @label_points;
|
||||||
|
H.text_width = @text_width;
|
||||||
|
end
|
||||||
|
|
||||||
|
% ---------------------------------------------------------------------------
|
||||||
|
% 基本图元
|
||||||
|
% ---------------------------------------------------------------------------
|
||||||
|
function h = draw_circle(ax, center, radius, color, lw, style)
|
||||||
|
t = linspace(0, 2 * pi, 360);
|
||||||
|
h = plot(ax, center(1) + radius * cos(t), center(2) + radius * sin(t), ...
|
||||||
|
'Color', color, 'LineWidth', lw, 'LineStyle', style);
|
||||||
|
end
|
||||||
|
|
||||||
|
function h = draw_wedge(ax, poly, color, alpha)
|
||||||
|
h = patch(ax, 'XData', poly(:, 1), 'YData', poly(:, 2), 'FaceColor', color, ...
|
||||||
|
'FaceAlpha', alpha, 'EdgeColor', 'none');
|
||||||
|
end
|
||||||
|
|
||||||
|
function h = draw_disk(ax, center, radius, color, alpha, edge_style)
|
||||||
|
t = linspace(0, 2 * pi, 360);
|
||||||
|
h = patch(ax, 'XData', center(1) + radius * cos(t), ...
|
||||||
|
'YData', center(2) + radius * sin(t), ...
|
||||||
|
'FaceColor', color, 'FaceAlpha', alpha, 'EdgeColor', color, ...
|
||||||
|
'LineWidth', 0.6, 'LineStyle', edge_style);
|
||||||
|
end
|
||||||
|
|
||||||
|
function h = draw_poly(ax, poly, face, alpha, edge, lw)
|
||||||
|
h = patch(ax, 'XData', poly(:, 1), 'YData', poly(:, 2), 'FaceColor', face, ...
|
||||||
|
'FaceAlpha', alpha, 'EdgeColor', edge, 'LineWidth', lw);
|
||||||
|
end
|
||||||
|
|
||||||
|
function h = draw_marker(ax, p, color, size, filled)
|
||||||
|
if filled
|
||||||
|
h = plot(ax, p(1), p(2), 'o', 'MarkerSize', size, ...
|
||||||
|
'MarkerFaceColor', color, 'MarkerEdgeColor', 'none');
|
||||||
|
else
|
||||||
|
h = plot(ax, p(1), p(2), 'o', 'MarkerSize', size, ...
|
||||||
|
'MarkerFaceColor', 'none', 'MarkerEdgeColor', color, ...
|
||||||
|
'LineWidth', 0.9);
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
function h = draw_arrow(ax, p0, p1, color)
|
||||||
|
%DRAW_ARROW 数据坐标箭头：直线 + 实心三角箭头。
|
||||||
|
% 箭头在"像素空间"里构造后换算回数据坐标，因此与坐标轴比例无关，
|
||||||
|
% 也不依赖绘制时的 axes 位置（图例把坐标区挤小后箭头依然对准数据点）。
|
||||||
|
h = plot(ax, [p0(1) p1(1)], [p0(2) p1(2)], 'Color', color, 'LineWidth', 0.9);
|
||||||
|
d = [p1(1) - p0(1), p1(2) - p0(2)];
|
||||||
|
[sx, sy] = px_scale(ax); % 每像素对应的数据单位
|
||||||
|
v = [d(1) / sx, d(2) / sy]; % 像素空间向量
|
||||||
|
len = hypot(v(1), v(2));
|
||||||
|
if len < 1e-9
|
||||||
|
return;
|
||||||
|
end
|
||||||
|
u = v / len;
|
||||||
|
n = [-u(2), u(1)];
|
||||||
|
head = min(len * 0.6, 10); % 头长（像素）
|
||||||
|
base = v - u * head;
|
||||||
|
tri = [v; base + n * head * 0.42; base - n * head * 0.42] .* [sx, sy];
|
||||||
|
patch(ax, 'XData', p0(1) + tri(:, 1), 'YData', p0(2) + tri(:, 2), ...
|
||||||
|
'FaceColor', color, 'EdgeColor', 'none');
|
||||||
|
end
|
||||||
|
|
||||||
|
function [sx, sy] = px_scale(ax)
|
||||||
|
pos = ax.Position;
|
||||||
|
fpos = ancestor(ax, 'figure').Position;
|
||||||
|
sx = diff(ax.XLim) / (pos(3) * fpos(3));
|
||||||
|
sy = diff(ax.YLim) / (pos(4) * fpos(4));
|
||||||
|
end
|
||||||
|
|
||||||
|
% ---------------------------------------------------------------------------
|
||||||
|
% 标签自动避让
|
||||||
|
% ---------------------------------------------------------------------------
|
||||||
|
function label_points(ax, pts, labels, color)
|
||||||
|
%LABEL_POINTS 在散点旁放置标签：按候选方位打分选出与已放标签、标记点都不重叠的位置。
|
||||||
|
% color 可以是 1×3（所有标签同色）或 n×3（逐点配色）。
|
||||||
|
if isempty(pts)
|
||||||
|
return;
|
||||||
|
end
|
||||||
|
if size(color, 1) == 1
|
||||||
|
color = repmat(color, numel(labels), 1);
|
||||||
|
end
|
||||||
|
xl = ax.XLim;
|
||||||
|
yl = ax.YLim;
|
||||||
|
gap = pixel_gap(ax, 5); % 标签与标记点之间的固定像素间距
|
||||||
|
mbox = marker_size(ax) * [-0.5 -0.5 1 1];
|
||||||
|
placed = zeros(0, 4);
|
||||||
|
for i = 1:numel(labels)
|
||||||
|
if pts(i, 1) < xl(1) || pts(i, 1) > xl(2) || ...
|
||||||
|
pts(i, 2) < yl(1) || pts(i, 2) > yl(2)
|
||||||
|
continue; % 视野外的点不标注
|
||||||
|
end
|
||||||
|
sz = text_size(ax, labels{i});
|
||||||
|
cand = candidates(pts(i, :), sz, gap);
|
||||||
|
best_pen = inf;
|
||||||
|
best = cand(1, :);
|
||||||
|
for k = 1:size(cand, 1)
|
||||||
|
box = [cand(k, 1) - sz(1) / 2 - gap(1), cand(k, 2) - sz(2) / 2 - gap(2), ...
|
||||||
|
sz(1) + 2 * gap(1), sz(2) + 2 * gap(2)];
|
||||||
|
pen = penalty(box, placed, pts, mbox, xl, yl);
|
||||||
|
if pen < best_pen
|
||||||
|
best_pen = pen;
|
||||||
|
best = cand(k, :);
|
||||||
|
end
|
||||||
|
end
|
||||||
|
text(ax, best(1), best(2), labels{i}, 'Color', color(i, :), ...
|
||||||
|
'HorizontalAlignment', 'center', 'VerticalAlignment', 'middle');
|
||||||
|
placed(end + 1, :) = [best(1) - sz(1) / 2 - gap(1), ...
|
||||||
|
best(2) - sz(2) / 2 - gap(2), ...
|
||||||
|
sz(1) + 2 * gap(1), sz(2) + 2 * gap(2)]; %#ok<AGROW>
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
function cand = candidates(p, sz, gap)
|
||||||
|
%CANDIDATES 标记点周围的候选标签中心：先近后远，四正方向 + 四斜角。
|
||||||
|
dx = gap(1) + sz(1) / 2;
|
||||||
|
dy = gap(2) + sz(2) / 2;
|
||||||
|
cand = [p(1) + dx, p(2); p(1) - dx, p(2)
|
||||||
|
p(1), p(2) + dy; p(1), p(2) - dy
|
||||||
|
p(1) + dx, p(2) + dy; p(1) - dx, p(2) + dy
|
||||||
|
p(1) + dx, p(2) - dy; p(1) - dx, p(2) - dy
|
||||||
|
p(1) + 2.2 * dx, p(2); p(1) - 2.2 * dx, p(2)
|
||||||
|
p(1), p(2) + 2.2 * dy; p(1), p(2) - 2.2 * dy
|
||||||
|
p(1) + 1.9 * dx, p(2) + 1.9 * dy; p(1) - 1.9 * dx, p(2) + 1.9 * dy
|
||||||
|
p(1) + 1.9 * dx, p(2) - 1.9 * dy; p(1) - 1.9 * dx, p(2) - 1.9 * dy
|
||||||
|
p(1) + 3.4 * dx, p(2); p(1) - 3.4 * dx, p(2)
|
||||||
|
p(1), p(2) + 3.4 * dy; p(1), p(2) - 3.4 * dy];
|
||||||
|
end
|
||||||
|
|
||||||
|
function g = pixel_gap(ax, npix)
|
||||||
|
pos = ax.Position;
|
||||||
|
fpos = ancestor(ax, 'figure').Position;
|
||||||
|
g = [npix * diff(ax.XLim) / (pos(3) * fpos(3)), ...
|
||||||
|
npix * diff(ax.YLim) / (pos(4) * fpos(4))];
|
||||||
|
end
|
||||||
|
|
||||||
|
function pen = penalty(box, placed, pts, mbox, xl, yl)
|
||||||
|
pen = 0;
|
||||||
|
for j = 1:size(placed, 1) % 标签之间重叠代价最高
|
||||||
|
pen = pen + 12 * overlap(box, placed(j, :));
|
||||||
|
end
|
||||||
|
for j = 1:size(pts, 1) % 其次避免压住标记点
|
||||||
|
mb = [pts(j, 1) + mbox(1), pts(j, 2) + mbox(2), mbox(3), mbox(4)];
|
||||||
|
pen = pen + 3 * overlap(box, mb);
|
||||||
|
end
|
||||||
|
dx = max(0, xl(1) - box(1)) + max(0, box(1) + box(3) - xl(2));
|
||||||
|
dy = max(0, yl(1) - box(2)) + max(0, box(2) + box(4) - yl(2));
|
||||||
|
pen = pen + 1e3 * (dx * box(4) + dy * box(3));
|
||||||
|
end
|
||||||
|
|
||||||
|
function a = overlap(b1, b2)
|
||||||
|
w = min(b1(1) + b1(3), b2(1) + b2(3)) - max(b1(1), b2(1));
|
||||||
|
h = min(b1(2) + b1(4), b2(2) + b2(4)) - max(b1(2), b2(2));
|
||||||
|
a = max(0, w) * max(0, h);
|
||||||
|
end
|
||||||
|
|
||||||
|
function sz = text_size(ax, str)
|
||||||
|
%TEXT_SIZE 文本在数据坐标下的包围盒尺寸（用临时 text 对象的 Extent 量取）。
|
||||||
|
h = text(ax, 0, 0, str, 'Units', 'data', 'Visible', 'off', ...
|
||||||
|
'Interpreter', 'none');
|
||||||
|
e = get(h, 'Extent');
|
||||||
|
delete(h);
|
||||||
|
sz = [e(3) e(4)] * 1.12;
|
||||||
|
end
|
||||||
|
|
||||||
|
function w = text_width(ax, str, fs)
|
||||||
|
%TEXT_WIDTH 指定字号下文本在数据坐标下的宽度。
|
||||||
|
h = text(ax, 0, 0, str, 'Units', 'data', 'Visible', 'off', ...
|
||||||
|
'FontSize', fs, 'Interpreter', 'none');
|
||||||
|
e = get(h, 'Extent');
|
||||||
|
delete(h);
|
||||||
|
w = e(3) * 1.04;
|
||||||
|
end
|
||||||
|
|
||||||
|
function s = marker_size(ax)
|
||||||
|
xl = ax.XLim;
|
||||||
|
yl = ax.YLim;
|
||||||
|
pos = ax.Position;
|
||||||
|
fpos = ancestor(ax, 'figure').Position;
|
||||||
|
w_px = pos(3) * fpos(3);
|
||||||
|
h_px = pos(4) * fpos(4);
|
||||||
|
s = 8 * max(diff(xl) / w_px, diff(yl) / h_px); % 约 8 px
|
||||||
|
end
|
||||||
|
|
||||||
@@ -0,0 +1,11 @@
|
|||||||
|
function D = load_data(S, name)
|
||||||
|
%LOAD_DATA 读取 scripts/build_figure_data.py 预先写好的绘图数据并规范化文本字段。
|
||||||
|
path = fullfile(S.data_dir, [name '.mat']);
|
||||||
|
if ~isfile(path)
|
||||||
|
error('缺少绘图数据：%s（请先运行 scripts/build_figure_data.py --prepare）', path);
|
||||||
|
end
|
||||||
|
D = normalize_text(load(path));
|
||||||
|
if isfield(D, 'switch_') && ~isfield(D, 'switch_s')
|
||||||
|
D.switch_s = D.switch_;
|
||||||
|
end
|
||||||
|
end
|
||||||
@@ -0,0 +1,15 @@
|
|||||||
|
function D = normalize_text(D)
|
||||||
|
%NORMALIZE_TEXT 把 load 出来的字符矩阵还原成字符串列表。
|
||||||
|
% scipy.io.savemat 会把 Python 的字符串列表写成三维 char 数组（或 char 矩阵），
|
||||||
|
% MATLAB 侧读回来是 char，不能按 {i} 取值，这里统一转成 cellstr。
|
||||||
|
|
||||||
|
fn = fieldnames(D);
|
||||||
|
for k = 1:numel(fn)
|
||||||
|
v = D.(fn{k});
|
||||||
|
if ischar(v) && ndims(v) > 2
|
||||||
|
D.(fn{k}) = cellstr(v);
|
||||||
|
elseif isstruct(v)
|
||||||
|
D.(fn{k}) = normalize_text(v);
|
||||||
|
end
|
||||||
|
end
|
||||||
|
end
|
||||||
@@ -0,0 +1,13 @@
|
|||||||
|
function c = pick_color(S, name)
|
||||||
|
%PICK_COLOR 语义色名 → MATLAB 默认配色（不引入自定义调色板）。
|
||||||
|
switch name
|
||||||
|
case 'primary', c = S.c(1, :); % 几何区域、主体对象
|
||||||
|
case 'accent', c = S.c(2, :); % 真值源、关键结论
|
||||||
|
case 'warn', c = S.c(3, :); % 警示、未清除
|
||||||
|
case 'violet', c = S.c(4, :); % 直径圆等辅助对象
|
||||||
|
case 'success', c = S.c(5, :); % 覆盖、清除、通过
|
||||||
|
case 'grid', c = [0.5 0.5 0.5];
|
||||||
|
case 'muted', c = [0.45 0.45 0.45];
|
||||||
|
otherwise, c = [0 0 0];
|
||||||
|
end
|
||||||
|
end
|
||||||
@@ -0,0 +1,38 @@
|
|||||||
|
function run_all_figures()
|
||||||
|
%RUN_ALL_FIGURES 生成 docs/figures 下的全部论文插图。
|
||||||
|
% 数据由 scripts/build_figure_data.py 写入 docs/figures/.data/*.mat。
|
||||||
|
% 本机图形子系统在同一批处理会话里连续渲染多张图会崩溃，故每张图单独起会话；
|
||||||
|
% 这里只作为 MATLAB 内的手动入口，逐张调用并记日志。
|
||||||
|
|
||||||
|
here = fileparts(mfilename('fullpath'));
|
||||||
|
addpath(here);
|
||||||
|
log = fullfile(here, 'run_all_figures.log');
|
||||||
|
items = { 'flow-overall-architecture', @fig_flow_overall
|
||||||
|
'steps-state-machine', @fig_steps_state_machine
|
||||||
|
'timing-attachment-example-105-111-194-199', @fig_timing_attachment
|
||||||
|
'timing-measured-q3-10-sources', @fig_timing_measured
|
||||||
|
'geo-q1-convex-intersection-zoom', @fig_geo_q1_meetup
|
||||||
|
'geo-q1-diameter-circle-counterexample', @fig_geo_q1_counterexample
|
||||||
|
'geo-q2-guaranteed-reception-disk', @fig_geo_q2_safe_disk
|
||||||
|
'geo-q3-seven-point-coverage', @fig_geo_q3_coverage
|
||||||
|
'geo-q4-minimum-cover-31-points', @fig_geo_q4_mincover
|
||||||
|
'replay-webui-q3-omnidirectional', @() fig_replay('replay_q3')
|
||||||
|
'replay-webui-q4-directional', @() fig_replay('replay_q4') };
|
||||||
|
fid = fopen(log, 'w');
|
||||||
|
failed = 0;
|
||||||
|
for i = 1:2:numel(items)
|
||||||
|
name = items{i};
|
||||||
|
fn = items{i + 1};
|
||||||
|
try
|
||||||
|
fn();
|
||||||
|
fprintf(fid, 'OK %s\n', name);
|
||||||
|
catch err
|
||||||
|
failed = failed + 1;
|
||||||
|
fprintf(fid, 'FAIL %s: %s\n', name, err.message);
|
||||||
|
end
|
||||||
|
end
|
||||||
|
fclose(fid);
|
||||||
|
if failed > 0
|
||||||
|
fprintf('有 %d 张图生成失败，详见 %s\n', failed, log);
|
||||||
|
end
|
||||||
|
end
|
||||||
Reference in New Issue
Block a user