From 4da11f61858e4c3b9d72bb1026aeb03ffa99d6fc Mon Sep 17 00:00:00 2001 From: gaozheng Date: Mon, 29 Jun 2026 10:03:48 +0800 Subject: [PATCH] =?UTF-8?q?feat(radar):=20=E4=B8=89=E7=BB=B4=E9=9B=B7?= =?UTF-8?q?=E8=BE=BE=E6=8E=A5=E5=85=A5=E8=AE=BE=E8=AE=A1=20+=20Mala=20?= =?UTF-8?q?=E8=BD=AC=E6=8D=A2=E5=99=A8=E5=8E=9F=E5=9E=8B(=E5=B7=B2?= =?UTF-8?q?=E8=BF=87=E6=9E=B6=E6=9E=84=E8=AF=84=E5=AE=A1)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - tools/radar_convert: RADAR_TYPE_MALAMIRA 转换插件原型(info/convert/probe) .rad→.head / .rd3→.data(原样) / .pos→.cor；probe 用真实数据确诊数据体 主序 = position-major reshape(K,M,N)，X=道/Y=通道/Z=采样，无需轴置换 - docs/spec: 2026-06-29 三维雷达体渲染+切片+异常接入设计 核心论点=只换最内层 reader、下游渲染/切片/异常链复用；含已验证数据事实、 内存实算、插件化转换层、双数据集测试策略；已过 opus 架构评审(PASS-WITH-CONCERNS, HIGH-1 填体逻辑须抽共享helper / HIGH-2 明星路 in-app 渲染属首次非已验证 已并入) - samples/radar/malamira_南同大道: 6 线 .head/.cor 入库(大 .data gitignore,附重生成命令) - 记录客户文档 §3.3 BITS 公式 bug(漏 SAMPLES 维)，须同步后端 --- .gitignore | 3 + ...026-06-29-3d-radar-volume-ingest-design.md | 183 ++++++ samples/radar/malamira_南同大道/README.md | 21 + .../radar/malamira_南同大道/南同大道_000.cor | 527 ++++++++++++++++++ .../radar/malamira_南同大道/南同大道_000.head | 34 ++ .../radar/malamira_南同大道/南同大道_001.cor | 335 +++++++++++ .../radar/malamira_南同大道/南同大道_001.head | 34 ++ .../radar/malamira_南同大道/南同大道_002.cor | 346 ++++++++++++ .../radar/malamira_南同大道/南同大道_002.head | 34 ++ .../radar/malamira_南同大道/南同大道_003.cor | 245 ++++++++ .../radar/malamira_南同大道/南同大道_003.head | 34 ++ .../radar/malamira_南同大道/南同大道_004.cor | 313 +++++++++++ .../radar/malamira_南同大道/南同大道_004.head | 34 ++ .../radar/malamira_南同大道/南同大道_005.cor | 342 ++++++++++++ .../radar/malamira_南同大道/南同大道_005.head | 34 ++ tools/radar_convert/README.md | 71 +++ tools/radar_convert/malamira.py | 350 ++++++++++++ 17 files changed, 2940 insertions(+) create mode 100644 docs/superpowers/specs/2026-06-29-3d-radar-volume-ingest-design.md create mode 100644 samples/radar/malamira_南同大道/README.md create mode 100644 samples/radar/malamira_南同大道/南同大道_000.cor create mode 100644 samples/radar/malamira_南同大道/南同大道_000.head create mode 100644 samples/radar/malamira_南同大道/南同大道_001.cor create mode 100644 samples/radar/malamira_南同大道/南同大道_001.head create mode 100644 samples/radar/malamira_南同大道/南同大道_002.cor create mode 100644 samples/radar/malamira_南同大道/南同大道_002.head create mode 100644 samples/radar/malamira_南同大道/南同大道_003.cor create mode 100644 samples/radar/malamira_南同大道/南同大道_003.head create mode 100644 samples/radar/malamira_南同大道/南同大道_004.cor create mode 100644 samples/radar/malamira_南同大道/南同大道_004.head create mode 100644 samples/radar/malamira_南同大道/南同大道_005.cor create mode 100644 samples/radar/malamira_南同大道/南同大道_005.head create mode 100644 tools/radar_convert/README.md create mode 100644 tools/radar_convert/malamira.py diff --git a/.gitignore b/.gitignore index 209932b..6bf0190 100644 --- a/.gitignore +++ b/.gitignore @@ -56,3 +56,6 @@ docs/剖面网格数据的色阶数据2等文件.tar /installer/staging/ /installer/dist/ /installer/redist/ + +# ---- Radar sample data: keep .head/.cor (small text), ignore big .data binaries ---- +samples/**/*.data diff --git a/docs/superpowers/specs/2026-06-29-3d-radar-volume-ingest-design.md b/docs/superpowers/specs/2026-06-29-3d-radar-volume-ingest-design.md new file mode 100644 index 0000000..d18ebf9 --- /dev/null +++ b/docs/superpowers/specs/2026-06-29-3d-radar-volume-ingest-design.md @@ -0,0 +1,183 @@ +# 三维雷达 DS 接入设计：规范化格式 → 体渲染 + 切片 + 异常 — 2026-06-29 + +> 负责人范围：**仅三维雷达的体渲染 + 切片 + 异常标注**（不含 2D 波列图详情页、不含二维雷达）。 +> 本 spec 基于精读现有架构（HEAD `main`）+ Explore 代理交叉验证 + 用真实 Mala 数据实测确诊。 +> 所有"数据事实"均已用 `D:/Downloads/MALA南同大道_rSlicer` 6 条测线核对，**无未验证假设**。 + +--- + +## 1. 背景与锁定决策 + +客户新增雷达数据类型，模型层级沿用 `项目 → GS → TM(TmObject) → DS列表`。三维雷达 TM 携带 +`头信息(.head)` + DS 列表 `= 雷达RTK轨迹(.cor,备份+快照) + 每频率 雷达3D-频率N(打标.index + 通道1..N data.data)`。 +数据体 = **K 切片(沿运动) × M 通道(sweep) × N 采样(深度)**（与 IDS/OpenGPR 手册一致）。 + +四项锁定决策（用户 2026-06-29 确认）： + +| 维度 | 决策 | +|---|---| +| 职责范围 | 仅三维体 + 切片 + 异常；不做 2D 波列图详情、不做二维雷达 | +| 数据来源 | 后端未就绪 → 先读**本地已转换好的目录**（后端就绪后切按 DS 下载） | +| 输入格式 | 客户端**规范化 `.head/.data/.cor/.index`**（新写 reader） | +| 渲染规模 | 先**单线 / 下采样稠密体**打通 | + +--- + +## 2. 已验证的数据事实（★C++ reader 必须遵守，零假设） + +实测工具：`tools/radar_convert/malamira.py probe`（B-scan/C-scan 主序核对）。 + +1. **数据体主序 = position-major**：磁盘扫描顺序 = `(道0:通道0..M-1)(道1:通道0..M-1)…`，每 sweep 内 N 采样连续。 + 即 `flat.reshape(K, M, N)[道][通道][采样]`。probe 确诊：position-major 的 B-scan 出现连续直达波 + + 地层 + 双曲线绕射；channel-major 为竖条乱码（已排除）。 +2. **直接对应 geopro 体轴** `X=道(nx=K)` / `Y=通道(ny=M)` / `Z=采样(nz=N)`，**无需轴置换**——与现有 + `Gpr3dvVolumeBridge` 轴映射完全一致。⚠️ 但**磁盘主序(采样最快→通道→道)与体内存布局(道最快，`((k·ny+j)·nx+i)`， + `ScalarVolumeI16.hpp:58`)相反**，新 reader 必须**逐体素散射重排填值**（照 bridge 的 `vol.at(to,j,s)=`）， + **严禁 memcpy/整块拷贝**。"无需转置"指轴语义，不是字节布局。 +3. **维度推导**：`M=NUMBER_OF_CH`、`N=SAMPLES`、`K=LAST_TRACE/NUMBER_OF_CH`（`.head` 的 `LAST_TRACE` + 是**总扫描数**=K×M，不是道数）。 +4. **数据类型**：int16 小端(`.rd3`/`bits=16`) / int32 小端(`.rd7`/`bits=32`)。`-32768` 是直达波饱和真实值，**非空值哨兵**。 +5. **`BITS` 公式 bug**：客户文档 §3.3 `BITS = 文件大小/LAST_TRACE/NUMBER_OF_CH×8` **漏了 SAMPLES 维、量纲错**。 + 正确：`bytes = 文件大小/(LAST_TRACE×SAMPLES)`，并与扩展名交叉校验。**须同步后端**（见 `tools/radar_convert/README.md`）。 + +--- + +## 3. 架构论点：只换最内层 reader，下游 100% 复用 + +现有真实雷达体链路是分层的，**只有最内层 reader 绑定厂商格式**： + +``` +Api3dRepository::createGprVolume [api/Api3dRepository.cpp:128] 注册 dd_voxel/灰度色阶/预填 cachedGrid + └ data::createGprVolumeGrid [data/GprVolumeRepository.cpp:38] + ├ io::gpr::buildLineVolumeFromGpr3dv ← 仅此层绑定厂商 .iprb/.ord（读 Impulse 原始） + └ data::builtI16ToVolumeGrid [data/GprVolumeRepository.cpp:11] int16→float 稠密体 + → 勾选 → VtkSceneController.loadVolume → VtkSceneView.addVolume → render::buildVoxel(GPU RayCast) + → SliceTool / InteractionManager / AnomalyDrawTool （切片 B/C-scan + 点线面异常，全现成） +``` + +**新增一个产 `core::BuiltI16`（同轴映射 X=道/Y=通道/Z=采样）的规范化 reader**，则 `builtI16ToVolumeGrid` +往下的渲染/切片/异常链**零改动**。这正是 `GprVolumeRepository.cpp:14` 注释写明的"数据层方案 A"。 + +### 完全复用、不碰的部分 +`render::buildVoxel`（GPU 体绘制）、三级树 voxel 段（`CategoryConfig.hpp:23` `dd_voxel`）、勾选→`loadVolume`→`addVolume`、 +切片（`SliceTool` updown 深度 C-scan / leftright·frontback B-scan + `InteractionManager`）、 +异常（`AnomalyDrawTool` 点/线/面 → `dd_anomaly` 挂体）、跨视图色阶联动、`builtI16ToVolumeGrid` 适配器。 + +--- + +## 4. 插件化转换层（已落地 Mala） + +转换 = "按雷达型号的插件"，本地 Python 工具 = 未来服务端下发插件的原型，契约不变： + +``` +plugin_id : RADAR_TYPE_MALAMIRA # 对齐文档 §2.1 型号列表 +supports(fileset) -> bool +convert(lineDir, prefix, outDir) -> {head, data, cor} # 厂商原始 → 规范化 +``` + +- **`RADAR_TYPE_MALAMIRA`（已完成）**：`tools/radar_convert/malamira.py`。`.rad→.head`(§3.3)、 + `.rd3→.data`(§3.5 原样拷贝)、`.pos→.cor`(§2.2.2)。`info/convert/probe` 三命令。6 条线全部转换 + 校验通过。 + 与文档偏差 5 处见 `tools/radar_convert/README.md`（含 BITS 公式修正）。 +- **`RADAR_TYPE_IMPLUSE`（规划，暂不做）**：见 §7。 + +客户端职责（未来）：设备对接/原始导入 → 按型号拉插件 → `convert` → 喂规范化 reader。 + +**契约两点待补（登记）**：(a) `convert` 返回 `{head,data,cor}` **未含 `.index`(打标)**，有打标的型号需扩约定； +(b) 规范化 `.data` 无扩展名，C++ reader 解析字节宽(2/4) **单点依赖 `.head` 的 `BITS` 字段** → 保证转换器 BITS 永远正确是隐性前提（`malamira.py` 的 `filesize==LAST_TRACE×SAMPLES×bytes` 断言已守住，见 §2.5）。 + +--- + +## 5. 新增 / 改动清单（C++ 侧，待实现） + +| # | 文件 | 动作 | +|---|---|---| +| ① | `src/io/gpr/NormalizedRadarReader.{hpp,cpp}` **新** | 纯函数：`parseHead(.head)→RadarHeader`；`readDataCube(.data,header)→cube`（按 `BITS`+`ENDIAN_TYPE` 解二进制，`reshape(K,M,N)` 主序已定）；`parseCor(.cor)→vector`（先解析，世界配准后置） | +| ② | `src/io/gpr/NormalizedRadarVolumeBridge.{hpp,cpp}` **新** | `buildLineVolumeFromNormalized(lineDir,prefix,metrics,coarse,targetDy)→core::BuiltI16`。⚠️ **DRY**：`Gpr3dvVolumeBridge.cpp:133-197` 的值域扫描/`Quant`构造/逐体素填值/spacing 当前内联且耦合 Impulse 模型——动工时**先把这段抽成共享 helper**（签名接受抽象立方体访问器 `(c,t,s)→short` + 通道偏移/几何），两个 bridge 同调；`planChannelInterpolation`/`depthOfSample` 已是共享纯函数。**不要复制填体循环**（否则两份独立漂移） | +| ③ | `src/data/GprVolumeRepository.{hpp,cpp}` 改 | 加 `createRadarVolumeGrid(lineDir,prefix,coarse,targetDy)`（调②，复用 `builtI16ToVolumeGrid`）。**不动**现有 `createGprVolumeGrid` | +| ④ | `src/data/api/Api3dRepository.{cpp,hpp}` 改 | 加 `createRadarVolume(...)`（≈`createGprVolume` 复制换调③），仍注册 `dd_voxel` | +| ⑤ | `src/app/main.cpp` 改 | 本地导入入口「导入三维雷达测线目录」：选目录+前缀 → `createRadarVolume` → `refreshAnalysis` → 自动勾选渲染（后端就绪后换按 DS 下载） | +| ⑥ | 测试 | `tests/io/gpr/test_normalized_radar_reader.cpp`（喂 `tests/data/radar/` 截断样例，断言维度/字节序/通道插值/主序） | + +### 几何映射（关键算法，纯函数易测） +- **X(沿线 spacing)** = `DISTANCE_INTERVAL`（距离模式，本期唯一支持）。 +- **Y(通道横向)** = 复用 `GprGeometry::planChannelInterpolation(chXOffsets, targetDy)`（`GprGeometry.hpp:27`）—— + 通道偏移取自 `.head` 的 `CH_X_OFFSETS`（不读 `.ord`），线内插值、**绝不跨线**（默认 2.5cm）。 +- **Z(深度 spacing)** = `TIMEWINDOW/(SAMPLES-1) × 波速/2`；波速由 `DIELECTRIC` 求，`.rad` 无该字段时用默认波速。 +- **量化** → `core::BuiltI16`（复用 `core/algo/GprVolumeBuilder.hpp`）。 +- **`.cor`/`.index`** 本期只解析不深用：单线放原点沿 +X，切片/异常即可工作。逐道 GPS 世界配准 + 打标 → 多线阶段。 + +--- + +## 6. 分期 + +- **P0（本期）**：①–⑥，单线规范化体打通。**验收**：导入 `samples/radar/malamira_南同大道`（如 000 线）→ + 树出现 `dd_voxel` → 勾选渲染 → 切 updown/leftright/frontback → 画点/线/面异常并挂体下。 +- **P1**：`.cor` 逐道 GPS 世界配准 + 高程、`.index` 打标、多线合一场景。 +- **P2**：大体量 → 把 `gpr_poc` 的 `ChunkedVolumeStore`+`*VolumeSource` 核外/LOD 接进 app（碰 controller/view，单独立项）。 + +--- + +## 7. 双数据集测试策略 + Impulse 转换器决策 + +已有完整 POC 基于**另一套雷达数据 明星路（Impulse）**，交接见 `.superpowers/sdd/HANDOFF-2026-06-27-gpr-lod-slice.md`。 +明星路 数据在本地（`D:/Downloads/明星路`，14G，20 测线）。 + +**关键差异**：明星路 是 `RADAR_TYPE_IMPLUSE`——每线 **14 通道为 14 个独立 `.iprb` 二进制**（`_A01.._A14`，各 ~74MB）+ +逐通道 `.iprh` + `.ord` + `.gps/.time/.cor/.mrk`。Mala 则把 16 通道打进**一个** position-major `.rd3`。 +现有 C++ P1 链（`buildLineVolumeFromGpr3dv`）**能直读 `.iprb`**。 + +> ⚠️ **校正（评审 HIGH-2）**：明星路真正"经验证"的渲染是 **`gpr_poc` CLI 的核外 LOD 多线**路径，**不是** app 内 +> `createGprVolume→builtI16ToVolumeGrid→loadVolume→addVolume` 的**稠密单体**路径——后者的 **app 导入 UI 触发从未接** +> （HANDOFF-2026-06-27 §6 第 3 条："数据层 `createGprVolume` 已就绪，但 UI 触发未接"）。故 app 内稠密渲染对**两套数据都是首次**。 + +**决策：本期不建 Impulse→规范化 转换器。** 理由： +1. Impulse `.iprb` 原始二进制远比 Mala "改名+字段映射"复杂（14 个独立通道文件、需逆向二进制布局）；且 P1 链含**处理** + （gain/filter），而规范化 `.data` 是**原始**——raw vs processed 语义需先厘清。高成本、低边际价值。 +2. 明星路 的 `.iprb` 已有现成 in-app 数据层入口（`createGprVolume`，只差接 UI 触发），复用成本低。 + +**双数据集测试（校正后表述）**： +- **Mala（16ch，规范化 reader 新路径）** + **明星路（14ch，现有 `.iprb` P1 路径）** 在 app 内**首次**稠密渲染， + 二者喂**同一条下游 render/slice/anomaly 链** → 互证下游对两种通道数/几何无关。**前置任务**：明星路 in-app 导入入口 + 同样需接（复用现成 `createGprVolume`，与清单⑤同形）。 +- 以 **`gpr_poc` CLI 的明星路成像作为离线对照基线**（那才是已验证的），不声称 in-app 已验证。 +- ⚠️ 注意：明星路是**处理后**数据、Mala 是**原始**数据 → 双测只验"管路通 + 几何/通道数无关"，**不验"成像一致"**（二者有无增益滤波，视觉不可比）。 +- 把 **`RADAR_TYPE_IMPLUSE` 转换器列为规划的第二插件**，待规范化管线需吞并 Impulse（多半与服务端插件同步）时再做， + 届时一并解决 raw/processed 取舍。当前"插件产规范化→reader 吃规范化"契约**仅对 Mala 一家成立，属过渡态**。 + +--- + +## 8. 风险 / 待确认 + +1. **`.cor` 坐标语义**：`.pos` 是本地投影坐标（米），按文档直映入经纬度列、N/E/M 占位、解状态=4。 + 真实 CRS 未知；单线渲染不依赖 `.cor` 配准，多线阶段需后端给 `CRS_CODE`。 +2. **波速默认值**：Mala `.rad` 无 `DIELECTRIC` → Z 深度 spacing 用默认波速（建议介电常数≈9 / v≈0.1 m·ns⁻¹）， + 仅影响深度标尺，不影响体结构。需确认默认值。 +3. **采集模式**：本期只支持**距离模式**（X 用 `DISTANCE_INTERVAL`）；时间模式（`SCAN_SECOND`）推迟。 +4. **大体量 / 内存实算**：app 侧 `ScalarVolume` 是 `std::vector`（8 字节/体素，**比 int16 体放大 4×**，是真正天花板）。 + 单线最大线（K=3778, ny≈49@2.5cm, N=516）：coarse=4 → nx=945 → 体素 23.9M → **≈182 MiB**（+中间 BuiltI16 48MB +VTK 副本，单线峰值 <0.5GB，**P0 安全**）； + coarse=1 全分辨率 → **≈764 MB** 仅体（单线勉强，非 P0 默认）。**多线/全分辨率必走 P2 核外**（`ChunkedVolumeStore`，已有 gpr_poc 实现）。 + +--- + +## 9. 测试计划 + +- **转换器（已验证）**：`info` 维度校验 6/6 通过；`convert` 产物 `.data` 与源 `.rd3` 字节一致；`probe` 主序确诊。 +- **C++ reader 单测**：`tests/data/radar/` 放截断样例（position-major 可按字节前截 K' 道得合法小体）； + 断言 K/M/N、字节序、`planChannelInterpolation` 行数、主序填值正确。 +- **bridge/repo 单测**：`createRadarVolumeGrid` 产 `VolumeGrid` 维度/spacing/vmin-vmax 合理；NaN 空值语义。 +- **联调（人工）**：`build.bat app` → 导入样例 → 渲染 + 三向切片 + 三类异常；对照 明星路 现有路径同场景。 +- 失败排查看桌面日志 `%LOCALAPPDATA%/Geomative/Geopro3/logs/geopro_*.log`。 + +--- + +## 10. 文件地图（现有锚点） + +- 数据体模型 `src/data/repo/I3dSceneRepository.hpp:19`（`VolumeGrid` 稠密 float） +- 渲染入口 `src/controller/I3dSceneView.hpp:45`（`addVolume`）/ `src/app/VtkSceneView.cpp:173` +- 体素工厂 `src/render/actors/VoxelActor.hpp:29/47`（`buildVoxel`/`buildVoxelI16`） +- GPR IO `src/io/gpr/Gpr3dvVolumeBridge.hpp:47`（轴映射范本）/ `GprGeometry.hpp:27,32`（通道插值/深度） +- 体进 app `src/data/api/Api3dRepository.cpp:128`（`createGprVolume`）/ `src/data/GprVolumeRepository.cpp:11,38` +- 切片/异常 `src/render/interact/SliceTool.hpp` / `InteractionManager.hpp:52,57` / `AnomalyDrawTool.hpp:33` +- 三级树 `src/app/panels/columns/CategoryAnalysisTab.hpp:28` / `CategoryConfig.hpp:23` +- 转换器 `tools/radar_convert/malamira.py` + `README.md`；样例 `samples/radar/malamira_南同大道/` +- 详情视图扩展（如未来做 2D 波列图，非本期）`docs/superpowers/specs/2026-06-28-dataset-detail-view-architecture-and-extension-guide.md` diff --git a/samples/radar/malamira_南同大道/README.md b/samples/radar/malamira_南同大道/README.md new file mode 100644 index 0000000..625291d --- /dev/null +++ b/samples/radar/malamira_南同大道/README.md @@ -0,0 +1,21 @@ +# 样例：MALA南同大道（RADAR_TYPE_MALAMIRA → 规范化格式） + +三维雷达联调/单测固定样例。由 `tools/radar_convert/malamira.py` 从原始 Mala Mira +数据转换而来（16 通道、516 采样、距离模式，6 条测线）。 + +- `*.head` / `*.cor`：**纳入 git**（小文本）。 +- `*.data`：**.gitignore 忽略**（每条 ~40–62MB，共 ~277MB，过大不入库）。需要时按下方命令重生成。 + +## 重新生成 .data（及全部规范化档） + +```bash +python tools/radar_convert/malamira.py convert \ + "D:/Downloads/MALA南同大道_rSlicer" \ + --out "samples/radar/malamira_南同大道" +``` + +原始数据来源：`D:/Downloads/MALA南同大道_rSlicer`（厂商 Mala rSlicer 导出，`.rad/.rd3/_G01.pos`）。 + +## 已验证数据事实（见 tools/radar_convert/README.md） +- `.data` 主序 = **position-major** `(K道, M通道, N采样)`，int16 小端，无需转置。 +- 维度：K∈[2333,3778]，M=16，N=516；`K = LAST_TRACE / NUMBER_OF_CH`。 diff --git a/samples/radar/malamira_南同大道/南同大道_000.cor b/samples/radar/malamira_南同大道/南同大道_000.cor new file mode 100644 index 0000000..a6279fa --- /dev/null +++ b/samples/radar/malamira_南同大道/南同大道_000.cor @@ -0,0 +1,527 @@ +VERSION:1 +1 317.179340 N 472.759046 E 49.980000 M 4 +12 317.201303 N 472.700649 E 51.040000 M 4 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66.110000 M 4 diff --git a/samples/radar/malamira_南同大道/南同大道_000.head b/samples/radar/malamira_南同大道/南同大道_000.head new file mode 100644 index 0000000..5789cfe --- /dev/null +++ b/samples/radar/malamira_南同大道/南同大道_000.head @@ -0,0 +1,34 @@ +DATE:2022-03-10 +START_TIME:10:46 +STOP_TIME: +UNITS:m +MODE:距离模式 +ANTENNAS:200 MHz shielded +FREQUENCY:5351.611816 +STACKS:2 +LAST_TRACE:60448 +POSITIVE_DIRECTION:1 +SAMPLES:516 +TIME_INTERVAL:0.000000 +TIMEWINDOW:96.419553 +DEPTH: +ZERO_POSITION: +DIELECTRIC: +SOIL_TYPE: +BITS:16 +MARK: +DISTANCE_INTERVAL:0.099194 +START_POSITION:0.000000 +STOP_POSITION:374.656262 +WHEEL_GPS: +WHEEL_CALIBRATION:84.4270000000 +SCAN_SECOND: +NUMBER_OF_CH:16 +CH_X_OFFSETS:0.080 0.160 0.240 0.320 0.400 0.480 0.560 0.640 0.720 0.800 0.880 0.960 1.040 1.120 1.200 1.280 +RTK_X_OFFSET: +RTK_Y_OFFSET:0.350 +RTK_Z_OFFSET: +GAIN: +FILTER: +SMOOTH: +ENDIAN_TYPE:1 diff --git a/samples/radar/malamira_南同大道/南同大道_001.cor b/samples/radar/malamira_南同大道/南同大道_001.cor new file mode 100644 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4 +2326 347.871418 N 723.292309 E 146.140000 M 4 +2332 347.919036 N 723.817200 E 146.220000 M 4 +2333 347.924942 N 723.934680 E 146.300000 M 4 diff --git a/samples/radar/malamira_南同大道/南同大道_005.head b/samples/radar/malamira_南同大道/南同大道_005.head new file mode 100644 index 0000000..9630475 --- /dev/null +++ b/samples/radar/malamira_南同大道/南同大道_005.head @@ -0,0 +1,34 @@ +DATE:2022-03-10 +START_TIME:11:02 +STOP_TIME: +UNITS:m +MODE:距离模式 +ANTENNAS:200 MHz shielded +FREQUENCY:5351.611816 +STACKS:2 +LAST_TRACE:37328 +POSITIVE_DIRECTION:1 +SAMPLES:516 +TIME_INTERVAL:0.000000 +TIMEWINDOW:96.419553 +DEPTH: +ZERO_POSITION: +DIELECTRIC: +SOIL_TYPE: +BITS:16 +MARK: +DISTANCE_INTERVAL:0.095987 +START_POSITION:0.000000 +STOP_POSITION:223.841500 +WHEEL_GPS: +WHEEL_CALIBRATION:84.4270000000 +SCAN_SECOND: +NUMBER_OF_CH:16 +CH_X_OFFSETS:0.080 0.160 0.240 0.320 0.400 0.480 0.560 0.640 0.720 0.800 0.880 0.960 1.040 1.120 1.200 1.280 +RTK_X_OFFSET: +RTK_Y_OFFSET:0.350 +RTK_Z_OFFSET: +GAIN: +FILTER: +SMOOTH: +ENDIAN_TYPE:1 diff --git a/tools/radar_convert/README.md b/tools/radar_convert/README.md new file mode 100644 index 0000000..4855a35 --- /dev/null +++ b/tools/radar_convert/README.md @@ -0,0 +1,71 @@ +# radar_convert — 雷达原始数据 → 规范化格式 转换插件（本地原型） + +把厂商原始雷达数据转换成客户端**规范化格式** `.head / .data / .cor (/.index)`，供三维雷达 +渲染器消费。本目录是**未来"服务端下发转换插件"的本地原型**：今天的 Python 工具实现的 +`convert` 契约，将来由客户端按设备型号拉取对应插件执行，接口不变。 + +当前实现型号：**`RADAR_TYPE_MALAMIRA`**（Mala Mira rSlicer，`.rad + .rd3|.rd7 + _G01.pos`）。 + +--- + +## 插件契约（本地工具 = 未来插件，接口一致） + +``` +plugin_id : RADAR_TYPE_MALAMIRA +supports(fileset) -> bool # 据文件组成判断是否本插件可处理 +convert(lineDir, prefix, outDir) -> {head,data,cor} +``` + +- **输入**：一条测线三件套 `{prefix}.rad` + `{prefix}.rd3|.rd7` + `{prefix}_G01.pos`（轨迹可选）。 +- **输出**：规范化目录 `{prefix}.head` + `{prefix}.data` + `{prefix}.cor`。 +- 映射规则源自客户《雷达业务开发说明》§3.3（.rad→.head）/ §3.5（.rd3→.data）/ §2.2.2（.pos→.cor）。 + +## 用法 + +```bash +# 1) 列出目录内测线 + 维度一致性校验（不写文件） +python tools/radar_convert/malamira.py info + +# 2) 转换（--prefix 省略=全部测线） +python tools/radar_convert/malamira.py convert --out [--prefix 南同大道_000] + +# 3) probe：出图核对 .rd3 数据体主序（写一张 PNG 到 --out） +python tools/radar_convert/malamira.py probe --prefix 南同大道_000 --out +``` + +--- + +## 数据体维度与排列（★渲染器必读，已用真实数据核对） + +- 体维度：`K`(道/切片，沿运动) × `M`(通道) × `N`(采样/深度)。 + - `M = NUMBER_OF_CH`，`N = SAMPLES`，`K = LAST_TRACE / NUMBER_OF_CH`。 + - `.rad` 的 `LAST TRACE` 是**总扫描数**（=K×M），不是道数 K。`.head` 原样透传该值， + 渲染器按 `K = LAST_TRACE / NUMBER_OF_CH` 求道数。 +- **`.data` 主序 = position-major（已 probe 核对，MALA南同大道_000）**： + 磁盘扫描顺序 = `(道0: 通道0..M-1)(道1: 通道0..M-1)…`，每个 sweep 内 `N` 个采样连续。 + 即 `flat.reshape(K, M, N)[道][通道][采样]`。 + - 直接对应 geopro 体轴 `X=道(nx=K)`、`Y=通道(ny=M)`、`Z=采样(nz=N)`，**无需转置**。 + - 反例（错误主序）：channel-major `reshape(M,K,N)` 的 B-scan 呈竖条乱码——probe 已排除。 +- 数据类型：`int16` 小端（`.rd3`）/ `int32` 小端（`.rd7`）。`.rd3` 中出现 `-32768` + 为直达波饱和的真实值，非空值哨兵。 + +--- + +## 与客户文档的偏差（实现时的取舍，便于后端对齐） + +| # | 项 | 文档 | 本工具 | 理由 | +|---|---|---|---|---| +| 1 | `BITS` 计算 | `文件大小/LAST_TRACE/NUMBER_OF_CH×8` | `bytes = 文件大小/(LAST_TRACE×SAMPLES)`，×8；并与扩展名(.rd3→16/.rd7→32)交叉校验 | 文档公式漏了 SAMPLES 维、量纲不符；本式对 6 条线均得 16，且 `文件大小==LAST_TRACE×SAMPLES×bytes` 严格成立 | +| 2 | `ENDIAN_TYPE` | §3.3 表："留空" | 填 `1`（小端） | 同节要点 1 明确"通常小端即 1"；渲染需确定字节序 | +| 3 | `WHEEL_CALIBRATION` | §3.3 表："留空" | 透传 `.rad` 实际值 | `.rad` 有该字段，透传更忠实（不影响渲染） | +| 4 | `.cor` 坐标 | 北→纬度 / 东→经度 | 同文档直映，N/E/M 为占位标识，解状态=4 | `.pos` 是本地投影坐标(米)、非经纬度；CRS 未知。单线渲染不依赖 .cor 配准，多线阶段再处理 | +| 5 | `.index` | 可选打标文件 | 本数据集无打标 → 不产出 | 该目录仅有 FCODES.TXT(编码字典)，无 .index 源 | + +--- + +## 已验证（MALA南同大道_rSlicer，6 条测线，2026-06-29） + +- `info`：6 条线全部通过 `文件大小 == LAST_TRACE×SAMPLES×bytes` 校验。 + K∈[2333,3778]，M=16，N=516，bits=16，距离模式，dx≈0.095–0.099m，时窗 96.42ns，均含轨迹。 +- `convert`：6 条线 `.head/.data/.cor` 全部产出；`.data` 与源 `.rd3` 字节数严格一致。 +- `probe`：position-major B-scan 出现连续直达波 + 地层 + 双曲线绕射 → 主序确认。 diff --git a/tools/radar_convert/malamira.py b/tools/radar_convert/malamira.py new file mode 100644 index 0000000..13f368c --- /dev/null +++ b/tools/radar_convert/malamira.py @@ -0,0 +1,350 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +RADAR_TYPE_MALAMIRA 转换插件（本地原型）。 + +把 Mala Mira rSlicer 原始三件套（.rad + .rd3|.rd7 + _G01.pos）转换成客户端规范化 +格式（.head + .data + .cor），并提供 probe 子命令出图核对 .rd3 数据体主序。 + +本工具实现的 convert 契约 = 未来"服务端下发插件"的接口： + plugin_id : RADAR_TYPE_MALAMIRA + supports(fileset) -> bool + convert(lineDir, prefix, outDir) -> {head, data, cor} + +字段映射规则见客户《雷达业务开发说明》§3.3 / §2.2.2 / §3.5。与文档的少量偏差见 README.md。 +""" + +import argparse +import os +import shutil +import sys + +import numpy as np + +PLUGIN_ID = "RADAR_TYPE_MALAMIRA" + +# 规范化 .head 字段顺序（三维雷达，文档 §1.2.2）。 +HEAD_FIELD_ORDER = [ + "DATE", "START_TIME", "STOP_TIME", "UNITS", "MODE", "ANTENNAS", "FREQUENCY", + "STACKS", "LAST_TRACE", "POSITIVE_DIRECTION", "SAMPLES", "TIME_INTERVAL", + "TIMEWINDOW", "DEPTH", "ZERO_POSITION", "DIELECTRIC", "SOIL_TYPE", "BITS", + "MARK", "DISTANCE_INTERVAL", "START_POSITION", "STOP_POSITION", "WHEEL_GPS", + "WHEEL_CALIBRATION", "SCAN_SECOND", "NUMBER_OF_CH", "CH_X_OFFSETS", + "RTK_X_OFFSET", "RTK_Y_OFFSET", "RTK_Z_OFFSET", "GAIN", "FILTER", "SMOOTH", + "ENDIAN_TYPE", +] + + +# --------------------------------------------------------------------------- +# 解析 .rad +# --------------------------------------------------------------------------- +def parse_rad(rad_path): + """读 Mala .rad（ASCII，KEY:VALUE 行）→ dict（保留原始键，值去首尾空白）。""" + raw = {} + with open(rad_path, "r", encoding="utf-8", errors="replace") as f: + for line in f: + if ":" not in line: + continue + key, _, val = line.partition(":") + raw[key.strip()] = val.strip() + return raw + + +def _f(raw, key, default=None): + v = raw.get(key, "") + if v == "" or v is None: + return default + try: + return float(v) + except ValueError: + return default + + +def _i(raw, key, default=None): + v = _f(raw, key, None) + return int(round(v)) if v is not None else default + + +def compute_dims(raw, data_path): + """从 .rad + 数据文件大小推导体维度并做一致性校验。 + + 返回 dict：positions(K)=道/切片数, channels(M), samples(N), + last_trace(总扫描数=K*M), bits, bytes_per_sample。 + """ + samples = _i(raw, "SAMPLES") + channels = _i(raw, "NUMBER_OF_CH") + last_trace = _i(raw, "LAST TRACE") # Mala 中 = 总扫描数(道 * 通道) + if not samples or not channels or not last_trace: + raise ValueError( + "缺少 SAMPLES / NUMBER_OF_CH / LAST TRACE，无法推导维度: %s" % data_path) + + ext = os.path.splitext(data_path)[1].lower() + bytes_per_sample = 2 if ext == ".rd3" else 4 if ext == ".rd7" else None + if bytes_per_sample is None: + raise ValueError("未知数据扩展名(仅 .rd3/.rd7): %s" % data_path) + + filesize = os.path.getsize(data_path) + expect = last_trace * samples * bytes_per_sample + if filesize != expect: + raise ValueError( + "数据体大小不符: %s 实际 %d 字节, 期望 LAST_TRACE(%d)*SAMPLES(%d)*%d = %d" + % (data_path, filesize, last_trace, samples, bytes_per_sample, expect)) + + if last_trace % channels != 0: + raise ValueError( + "LAST_TRACE(%d) 不能被 NUMBER_OF_CH(%d) 整除，无法切分道/通道" + % (last_trace, channels)) + + positions = last_trace // channels + return { + "positions": positions, + "channels": channels, + "samples": samples, + "last_trace": last_trace, + "bits": bytes_per_sample * 8, + "bytes_per_sample": bytes_per_sample, + "filesize": filesize, + } + + +# --------------------------------------------------------------------------- +# .rad -> .head +# --------------------------------------------------------------------------- +def build_head(raw, dims): + """按 §3.3 把 .rad 映射成规范化 .head 字段 dict。无对应字段留空。""" + ch_y = raw.get("CH_Y_OFFSETS", "").split() + head = {k: "" for k in HEAD_FIELD_ORDER} + head.update({ + "DATE": raw.get("DATE", ""), + "START_TIME": raw.get("TIME", ""), + "UNITS": raw.get("UNITS", ""), + "MODE": "距离模式", # Mala 默认距离模式(§3.3 要点 4) + "ANTENNAS": raw.get("ANTENNAS", ""), + "FREQUENCY": raw.get("FREQUENCY", ""), + "STACKS": raw.get("STACKS", ""), + "LAST_TRACE": str(dims["last_trace"]), + "POSITIVE_DIRECTION": raw.get("POSITIVE DIRECTION", ""), + "SAMPLES": str(dims["samples"]), + "TIME_INTERVAL": raw.get("TIME INTERVAL", ""), + "TIMEWINDOW": raw.get("TIMEWINDOW", ""), + "BITS": str(dims["bits"]), + "DISTANCE_INTERVAL": raw.get("DISTANCE INTERVAL", ""), + "START_POSITION": raw.get("START POSITION", ""), + "STOP_POSITION": raw.get("STOP POSITION", ""), + "WHEEL_CALIBRATION": raw.get("WHEEL CALIBRATION", ""), + "NUMBER_OF_CH": str(dims["channels"]), + "CH_X_OFFSETS": raw.get("CH_X_OFFSETS", "").strip(), + "RTK_Y_OFFSET": ch_y[0] if ch_y else "", # §3.3：取 CH_Y_OFFSETS 首元素 + "ENDIAN_TYPE": "1", # Mala rd3 小端(§3.3 要点 1) + }) + return head + + +def write_head(head, out_path): + with open(out_path, "w", encoding="utf-8", newline="\n") as f: + for k in HEAD_FIELD_ORDER: + f.write("%s:%s\n" % (k, head.get(k, ""))) + + +# --------------------------------------------------------------------------- +# .pos -> .cor (§2.2.2 场景二) +# --------------------------------------------------------------------------- +def convert_pos_to_cor(pos_path, cor_path): + """.pos(本地坐标: 序号 北 东 高程) → .cor(序号 纬度 N 经度 E 高程 M 解状态=4)。 + + 注：.pos 为本地投影坐标(米)，按文档直接映射 北→纬度 / 东→经度；N/E/M 为占位标识， + 解状态固定填 4(RTK Fixed)。单线渲染不依赖 .cor 做世界配准，多线阶段再用。 + """ + rows = [] + with open(pos_path, "r", encoding="utf-8", errors="replace") as f: + for line in f: + s = line.strip() + if not s or s.upper().startswith("UNITS"): + continue + parts = s.split() + if len(parts) < 4: + continue + idx = int(float(parts[0])) + north, east, elev = float(parts[1]), float(parts[2]), float(parts[3]) + rows.append((idx, north, east, elev)) + with open(cor_path, "w", encoding="utf-8", newline="\n") as f: + f.write("VERSION:1\n") + for idx, north, east, elev in rows: + f.write("%d\t%.6f\tN\t%.6f\tE\t%.6f\tM\t4\n" % (idx, north, east, elev)) + return len(rows) + + +# --------------------------------------------------------------------------- +# 测线发现 +# --------------------------------------------------------------------------- +def find_lines(line_dir): + """遍历目录，返回有效测线 [(prefix, rad, data, pos|None)]（§3.2 抽取规则）。""" + out = [] + for name in sorted(os.listdir(line_dir)): + if not name.lower().endswith(".rad"): + continue + prefix = name[:-4] + rad = os.path.join(line_dir, name) + data = None + for ext in (".rd3", ".rd7"): + cand = os.path.join(line_dir, prefix + ext) + if os.path.exists(cand): + data = cand + break + if data is None: + print(" [跳过] %s 缺 .rd3/.rd7 数据文件" % prefix, file=sys.stderr) + continue + pos = os.path.join(line_dir, prefix + "_G01.pos") + out.append((prefix, rad, data, pos if os.path.exists(pos) else None)) + return out + + +# --------------------------------------------------------------------------- +# convert +# --------------------------------------------------------------------------- +def convert_line(prefix, rad, data, pos, out_dir): + raw = parse_rad(rad) + dims = compute_dims(raw, data) + os.makedirs(out_dir, exist_ok=True) + + head = build_head(raw, dims) + write_head(head, os.path.join(out_dir, prefix + ".head")) + shutil.copyfile(data, os.path.join(out_dir, prefix + ".data")) # §3.5 原样拷贝 + cor_n = convert_pos_to_cor(pos, os.path.join(out_dir, prefix + ".cor")) if pos else 0 + + print("[%s] 道(K)=%d 通道(M)=%d 采样(N)=%d bits=%d .data=%.1fMB .cor=%d点%s" + % (prefix, dims["positions"], dims["channels"], dims["samples"], + dims["bits"], dims["filesize"] / 1e6, cor_n, + "" if pos else " (无轨迹)")) + return dims + + +def cmd_convert(args): + if args.prefix: + rad = os.path.join(args.line_dir, args.prefix + ".rad") + data = None + for ext in (".rd3", ".rd7"): + if os.path.exists(os.path.join(args.line_dir, args.prefix + ext)): + data = os.path.join(args.line_dir, args.prefix + ext) + pos = os.path.join(args.line_dir, args.prefix + "_G01.pos") + convert_line(args.prefix, rad, data, pos if os.path.exists(pos) else None, + args.out) + else: + lines = find_lines(args.line_dir) + print("发现 %d 条测线，输出 → %s" % (len(lines), args.out)) + for prefix, rad, data, pos in lines: + convert_line(prefix, rad, data, pos, args.out) + + +# --------------------------------------------------------------------------- +# probe：核对 .rd3 数据体主序 +# --------------------------------------------------------------------------- +def load_flat(data_path, dims, endian="<"): + dt = np.dtype("%si%d" % (endian, dims["bytes_per_sample"])) + flat = np.fromfile(data_path, dtype=dt) + n = dims["last_trace"] * dims["samples"] + if flat.size != n: + raise ValueError("读到 %d 个样本，期望 %d" % (flat.size, n)) + return flat.astype(np.float32) + + +def _clip(img): + """按 99 分位绝对值裁剪对比度，返回 (img, vmax)。""" + v = np.percentile(np.abs(img), 99) or 1.0 + return img, v + + +def cmd_probe(args): + import matplotlib + matplotlib.use("Agg") + import matplotlib.pyplot as plt + + raw = parse_rad(os.path.join(args.line_dir, args.prefix + ".rad")) + data = None + for ext in (".rd3", ".rd7"): + cand = os.path.join(args.line_dir, args.prefix + ext) + if os.path.exists(cand): + data = cand + dims = compute_dims(raw, data) + K, M, N = dims["positions"], dims["channels"], dims["samples"] + flat = load_flat(data, dims, "<" if args.endian == "little" else ">") + os.makedirs(args.out, exist_ok=True) + + print("[probe] %s K(道)=%d M(通道)=%d N(采样)=%d amp[min=%.0f max=%.0f mean|.|=%.1f]" + % (args.prefix, K, M, N, flat.min(), flat.max(), np.abs(flat).mean())) + + ch = args.channel + # H1: position-major sweeps 顺序 = (pos0:ch0..chM-1)(pos1:..) → reshape(K,M,N) + h1 = flat.reshape(K, M, N) + bscan_h1 = h1[:, ch, :].T # (N 采样 × K 道) + # H2: channel-major sweeps 顺序 = (ch0:pos0..posK-1)(ch1:..) → reshape(M,K,N) + h2 = flat.reshape(M, K, N) + bscan_h2 = h2[ch, :, :].T # (N 采样 × K 道) + # C-scan（H1 主序下某采样深度的 道×通道 平面） + cscan_h1 = h1[:, :, args.depth] # (K × M) + + panels = [ + ("H1 position-major B-scan ch%d" % ch, bscan_h1, "trace (K)", "sample (N)"), + ("H2 channel-major B-scan ch%d" % ch, bscan_h2, "trace (K)", "sample (N)"), + ("H1 C-scan @sample %d" % args.depth, cscan_h1, "channel (M)", "trace (K)"), + ] + fig, axes = plt.subplots(1, 3, figsize=(18, 6)) + for axp, (title, img, xl, yl) in zip(axes, panels): + _, vmax = _clip(img) + axp.imshow(img, aspect="auto", cmap="gray", vmin=-vmax, vmax=vmax, + interpolation="nearest") + axp.set_title(title) + axp.set_xlabel(xl) + axp.set_ylabel(yl) + fig.suptitle("%s %s -- main-order check: the coherent B-scan (layers/hyperbolas) is correct" + % (PLUGIN_ID, args.prefix), fontsize=12) + fig.tight_layout() + out_png = os.path.join(args.out, "probe_%s.png" % args.prefix) + fig.savefig(out_png, dpi=110) + print("[probe] 出图 → %s" % out_png) + + +# --------------------------------------------------------------------------- +def cmd_info(args): + lines = find_lines(args.line_dir) + print("目录 %s 发现 %d 条测线 (plugin=%s)" % (args.line_dir, len(lines), PLUGIN_ID)) + for prefix, rad, data, pos in lines: + raw = parse_rad(rad) + dims = compute_dims(raw, data) + print(" %-18s K=%-5d M=%-3d N=%-4d bits=%d dx=%s tw=%sns ch_x=%d个 轨迹=%s" + % (prefix, dims["positions"], dims["channels"], dims["samples"], + dims["bits"], raw.get("DISTANCE INTERVAL", "?"), + raw.get("TIMEWINDOW", "?"), + len(raw.get("CH_X_OFFSETS", "").split()), + "有" if pos else "无")) + + +def main(): + ap = argparse.ArgumentParser(description="RADAR_TYPE_MALAMIRA 转换插件(本地原型)") + sub = ap.add_subparsers(dest="cmd", required=True) + + p = sub.add_parser("info", help="列出目录内测线 + 维度校验") + p.add_argument("line_dir") + p.set_defaults(func=cmd_info) + + p = sub.add_parser("convert", help="转换为规范化 .head/.data/.cor") + p.add_argument("line_dir") + p.add_argument("--prefix", default=None, help="只转某条线(默认全部)") + p.add_argument("--out", required=True, help="输出目录") + p.set_defaults(func=cmd_convert) + + p = sub.add_parser("probe", help="出图核对 .rd3 数据体主序") + p.add_argument("line_dir") + p.add_argument("--prefix", required=True) + p.add_argument("--out", required=True) + p.add_argument("--channel", type=int, default=0) + p.add_argument("--depth", type=int, default=200, help="C-scan 取的采样深度") + p.add_argument("--endian", choices=["little", "big"], default="little") + p.set_defaults(func=cmd_probe) + + args = ap.parse_args() + args.func(args) + + +if __name__ == "__main__": + main()