feat: normalize CM93 objects for S-52 presentation
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OpenAI Codex
120
docs/报告/CM95_S52_全国对象规范化阶段报告_v1.md
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120
docs/报告/CM95_S52_全国对象规范化阶段报告_v1.md
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# CM95 S-52 全国对象规范化阶段报告 v1
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## 1. 目标
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本阶段沿 OpenCPN CM93 `CreateS57Obj()` 与 S-52 Presentation Lookup 流程，补齐 CM93 私有/扩展对象类到标准 S-57/S-52 Presentation 语义的规范化。
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范围为 Dataset 1 日本数据。本阶段不重建正式 release，只进行全库只读审计、单 Tile 回归和 Presentation 映射实现。
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## 2. 参考资源
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- CM93 对象字典：`/root/sourceserver/cm95-data/CM93JAPAN/CM93OBJ.DIC`
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- CM93 属性字典：`/root/sourceserver/cm95-data/CM93JAPAN/CM93ATTR.DIC`
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- OpenCPN `chartsymbols.xml`
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- OpenCPN `S52RAZDS.RLE`
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- OpenCPN `cm93.cpp` 中的对象替代逻辑
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- S-57 object class catalog 与 `attdecode.csv`
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- 完整 3057 条 Presentation Lookup IR
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## 3. 本阶段新增的主要规范化
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- `ITDARE → DEPARE`
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- `FSHHAV → FSHFAC`
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- `BRTFAC → BERTHS`
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- `TNKCON → SILTNK`
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- `PRDINS → PRDARE`
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- `ROADPT → ROADWY`
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- `VEGARE → VEGATN`
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- `SLTPAN → LNDRGN + CATLND=15`
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- `TELPHC → CONVYR + CATCON=1`
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- `DIFFUS → OBSTRN + CATOBS=3`
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- `SLIPWY → SLCONS + CATSLC=13`
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- `LNDSTS → SLCONS + CATSLC=11`
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- `RMPARE → SLCONS + CATSLC=12`
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- `DYKARE / DYKCRW → DYKCON`
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- `SILBUI → SILTNK + CATSIL=1`
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Landmark 类按 S-52 `LNDMRK + CATLMK` 规范化：
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- `CHIMNY → CATLMK=3`
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- `DSHAER → CATLMK=4`
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- `FLGSTF → CATLMK=5`
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- `FLASTK → CATLMK=6`
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- `MSTCON → CATLMK=7`
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- `WNDMIL → CATLMK=18`
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- `WIMCON → CATLMK=19`
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另外保留 OpenCPN Presentation Library 的扩展类大小写别名：
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- `RIVBNK → rivbnk`
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- `CANBNK → canbnk`
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## 4. 全国审计结果
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Dataset 1 共扫描 `1,282,431` 个 `chart_feature`。
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最终 v7 审计：
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- S-52 Lookup 命中：`1,246,817`
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- 全对象表观命中率：`97.2229%`
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- `unsupported_csp_counts = {}`
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- 条件存在但属性不匹配：`0`
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- no-candidate：`35,614`
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其中几何可绘制对象总数为 `1,251,374`。
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## 5. 不应计入普通 Presentation 缺口的对象
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以下三类合计 `4,502` 个，不能作为“漏画”处理：
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- `NATARE`：`1,516`，OpenCPN Presentation Library 明确为 `No data` 且 instruction 为空。
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- `$COMPS`：`1,494`，属于制图罗盘辅助对象。
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- `M_PROD`：`1,492`，属于生产信息元数据对象。
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剔除上述对象后，需要普通 Presentation 的对象数为 `1,246,872`，其中已命中 `1,246,817`。
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有效覆盖率：`99.9956%`。
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剩余未安全规范化的普通地物仅 `55` 个。
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## 6. 剩余 55 个语义复核项
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- `TREPNT` Point：19
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- `BUIREL` Area：13
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- `TOWERS` Area：8
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- `HILARE` Area：5
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- `CEMTRY` Point/Area：7
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- `RADDOM` Point：3
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这些对象没有足够证据支持无损的一对一标准化。本阶段明确保留，不为追求数字上的 100% 而制造猜测映射。
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后续如处理，应继续以 CM93 原始属性、S-57 类定义、S-52 Lookup 条件和 OpenCPN 实际行为共同确认。
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## 7. 福冈湾回归
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重新生成 `z12/3531/1641` v10 normalized PBF：
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- Feature：`3293`
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- Layer：`23`
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- `hard_gate_unmapped = []`
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- unresolved CSP：`0`
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- `SOUNDG02 = 1881`
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- `LIGHTS05 = 62`
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- `OBSTRN04 = 19`
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浏览器实际加载 `presentation_v10.html` 后进入 READY；灯火、灯弧、测深、危险物、岸线构造和原有主图层均正常。
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浏览器唯一 404 为 `/favicon.ico`，与地图资源无关。
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## 8. 结论
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本阶段确认：CM95 当前主要 Presentation 缺口已经不再是大规模对象类未映射问题。
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经过 CM93→S-57/S-52 对象规范化后，全国普通可绘制对象的有效 S-52 Lookup 覆盖率达到 `99.9956%`，且当前实际出现的 CSP 类型均已被 Resolver 支持。
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下一阶段重点应从“补对象类”转向：
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1. 对剩余 55 个小样本对象做语义复核；
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2. 检查已命中 Lookup 的 `TE/TX/LC/AP` 是否全部被 MapLibre 后端完整执行；
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3. 检查 Sprite/vector-only symbol 资源闭合；
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4. 用 OpenCPN 对照图做视觉差异审计，而不是继续扩大类替换表。
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@@ -6,6 +6,84 @@ from .presentation import static_rule_hints
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from .csp import S52MarinerSettings, resolve_csp_hints
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OPENCPN_CM93_CLASS_SUBSTITUTIONS: dict[str, str] = {
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"ITDARE": "DEPARE",
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"_m_sor": "M_COVR",
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"SPOGRD": "DMPGRD",
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"FSHHAV": "FSHFAC",
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"OFSPRD": "CTNARE",
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"BRTFAC": "BERTHS",
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"TNKCON": "SILTNK",
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"ROADPT": "ROADWY",
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"VEGARE": "VEGATN",
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"PRDINS": "PRDARE",
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"DYKARE": "DYKCON",
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"DYKCRW": "DYKCON",
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"SLTPAN": "LNDRGN",
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"TELPHC": "CONVYR",
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"DIFFUS": "OBSTRN",
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"SLIPWY": "SLCONS",
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"LNDSTS": "SLCONS",
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"RMPARE": "SLCONS",
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}
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# OpenCPN's current Presentation Library contains these extension Lookup names
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# in lowercase, while this CM93 dictionary stores the corresponding classes
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# in uppercase. Keep the aliases explicit: lookup matching must remain
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# case-sensitive because other extension classes (for example TOPMAR/topmar)
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# have distinct semantics.
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CM93_PRESENTATION_CLASS_ALIASES: dict[str, str] = {
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"RIVBNK": "rivbnk",
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"CANBNK": "canbnk",
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}
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CM93_LANDMARK_CLASS_TO_CATLMK: dict[str, int] = {
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"CHIMNY": 3,
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"DSHAER": 4,
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"FLGSTF": 5,
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"FLASTK": 6,
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"MSTCON": 7,
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"WNDMIL": 18,
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"WIMCON": 19,
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}
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CM93_CLASS_SYNTHETIC_ATTRIBUTES: dict[str, dict[str, Any]] = {
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"SILBUI": {"CATSIL": 1},
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"SLTPAN": {"CATLND": 15},
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"TELPHC": {"CATCON": 1},
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"DIFFUS": {"CATOBS": 3},
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"SLIPWY": {"CATSLC": 13},
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"LNDSTS": {"CATSLC": 11},
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"RMPARE": {"CATSLC": 12},
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}
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def normalize_cm93_object_class_for_s52(object_class: str) -> str:
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"""Return the OpenCPN-compatible Presentation Library object class."""
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name = str(object_class or "")
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if name in CM93_LANDMARK_CLASS_TO_CATLMK:
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return "LNDMRK"
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if name == "SILBUI":
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return "SILTNK"
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name = OPENCPN_CM93_CLASS_SUBSTITUTIONS.get(name, name)
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return CM93_PRESENTATION_CLASS_ALIASES.get(name, name)
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def normalize_cm93_object_for_s52(
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object_class: str, geometry_type: str, attrs: dict[str, Any]
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) -> tuple[str, dict[str, Any]]:
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"""Normalize CM93 class/attributes into the S-57/S-52 presentation view."""
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source_class = str(object_class or "")
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out = normalize_cm93_attributes_for_s52(attrs)
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if str(geometry_type).upper() == "POINT":
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catlmk = CM93_LANDMARK_CLASS_TO_CATLMK.get(source_class)
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if catlmk is not None:
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out.setdefault("CATLMK", catlmk)
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for key, value in CM93_CLASS_SYNTHETIC_ATTRIBUTES.get(source_class, {}).items():
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out.setdefault(key, value)
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return normalize_cm93_object_class_for_s52(source_class), out
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CM93_COLMAR_TO_S57_COLOUR: dict[int, str] = {
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1: "4", # green
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2: "2", # black
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@@ -326,9 +404,12 @@ class S52LookupRegistry:
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if table_geometry is None:
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return None
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table_name, lookup_geometry = table_geometry
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lookup_class, lookup_attrs = normalize_cm93_object_for_s52(
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object_class, geometry_type, attrs
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)
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return find_best_lookup(
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self.by_class.get(str(object_class), []),
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attrs,
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self.by_class.get(lookup_class, []),
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lookup_attrs,
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table_name=table_name,
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geometry_type=lookup_geometry,
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)
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@@ -343,6 +424,9 @@ class S52LookupRegistry:
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sounding_depth_m: float | None = None,
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associated_depth_ranges: list[dict[str, Any]] | None = None,
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) -> dict[str, Any]:
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lookup_class, normalized_attrs = normalize_cm93_object_for_s52(
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object_class, geometry_type, attrs
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)
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row = self.resolve(object_class, geometry_type, attrs)
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if row is None:
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return {}
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@@ -354,17 +438,18 @@ class S52LookupRegistry:
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"s52_table_name": str(row.get("table_name") or ""),
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}
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out.update(dict(row.get("_static_hints") or {}))
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if lookup_class != str(object_class):
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out["s52_object_class"] = lookup_class
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procedures = [
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token.strip()
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for token in str(out.get("s52_csp") or "").split(",")
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if token.strip()
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]
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normalized_attrs = normalize_cm93_attributes_for_s52(attrs)
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unresolved: list[str] = []
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for procedure in procedures:
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resolved = resolve_csp_hints(
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procedure,
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str(object_class),
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lookup_class,
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str(geometry_type),
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normalized_attrs,
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self.settings,
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242
tools/cm95_s52_full_database_audit.py
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242
tools/cm95_s52_full_database_audit.py
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from __future__ import annotations
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import argparse
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from collections import Counter, defaultdict
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import json
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import os
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from pathlib import Path
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from typing import Any
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from dotenv import load_dotenv
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import pymysql
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from cm95pbf.s52 import (
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lookup_condition_matches,
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normalize_cm93_attributes_for_s52,
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normalize_cm93_object_for_s52,
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)
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IMPLEMENTED_CSP = frozenset({
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"DEPARE01", "DEPARE02", "DEPCNT02", "LIGHTS05", "SOUNDG02",
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"OBSTRN04", "WRECKS02", "QUAPOS01", "SLCONS03", "RESTRN01",
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"RESARE02", "TOPMAR01",
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})
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def _json_object(value: Any) -> dict[str, Any]:
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if value is None:
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return {}
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if isinstance(value, dict):
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return value
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try:
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parsed = json.loads(value)
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except (TypeError, json.JSONDecodeError):
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return {}
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return parsed if isinstance(parsed, dict) else {}
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def _geometry_key(geometry_type: str, point_table: str, boundary_table: str):
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return {
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"POINT": (point_table, "Point"),
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"SOUNDING": (point_table, "Point"),
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"LINE": ("Lines", "Line"),
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"AREA": (boundary_table, "Area"),
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}.get(str(geometry_type).upper())
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def _prepare_lookups(rows: list[dict[str, Any]]):
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index: dict[tuple[str, str, str], list[dict[str, Any]]] = defaultdict(list)
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for row in rows:
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key = (
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str(row.get("object_class") or ""),
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str(row.get("table_name") or ""),
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str(row.get("geometry_type") or ""),
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)
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index[key].append(row)
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for key, candidates in index.items():
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candidates.sort(key=lambda r: (-len(r.get("attribute_conditions_raw") or []), int(r.get("id") or 0)))
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return index
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def _resolve(candidates: list[dict[str, Any]], attrs: dict[str, Any]):
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normalized = normalize_cm93_attributes_for_s52(attrs)
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fallback = None
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for row in candidates:
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conditions = row.get("attribute_conditions_raw") or []
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if not conditions:
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if fallback is None:
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fallback = row
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continue
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if all(lookup_condition_matches(c, normalized) for c in conditions):
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return row
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return fallback
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def main() -> int:
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parser = argparse.ArgumentParser(description="流式审计整个 CM95 Dataset 的 S-52 Lookup/CSP 覆盖率。")
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parser.add_argument("--lookups", required=True, type=Path)
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parser.add_argument("--output", required=True, type=Path)
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parser.add_argument("--env-file", default=Path(".env"), type=Path)
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parser.add_argument("--dataset-id", default=1, type=int)
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parser.add_argument("--point-table", default="Paper")
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parser.add_argument("--boundary-table", default="Plain")
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args = parser.parse_args()
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lookup_rows = json.loads(args.lookups.read_text(encoding="utf-8"))
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lookup_index = _prepare_lookups(lookup_rows)
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load_dotenv(args.env_file)
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conn = pymysql.connect(
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host=os.environ["CM93_DB_HOST"],
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port=int(os.environ.get("CM93_DB_PORT", "3306")),
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user=os.environ["CM93_DB_USER"],
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password=os.environ["CM93_DB_PASSWORD"],
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database=os.environ["CM93_DB_NAME"],
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charset=os.environ.get("CM93_DB_CHARSET", "utf8mb4"),
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autocommit=True,
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cursorclass=pymysql.cursors.SSCursor,
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)
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total = 0
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matched = 0
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no_lookup = 0
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empty_candidates = 0
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by_geometry = Counter()
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matched_by_geometry = Counter()
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no_lookup_by_key = Counter()
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no_candidate_by_key = Counter()
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condition_miss_by_key = Counter()
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matched_by_key = Counter()
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rcids = Counter()
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csp_counts = Counter()
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implemented_csp_counts = Counter()
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unsupported_csp_counts = Counter()
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opcode_counts = Counter()
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direct_symbol_counts = Counter()
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substitution_counts = Counter()
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sql = (
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"SELECT object_class, geometry_type, attributes_json "
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"FROM chart_feature WHERE dataset_id=%s ORDER BY id"
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)
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with conn.cursor() as cur:
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cur.execute(sql, (args.dataset_id,))
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for object_class, geometry_type, attrs_raw in cur:
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total += 1
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object_class = str(object_class)
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geometry_type = str(geometry_type)
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attrs = _json_object(attrs_raw)
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lookup_class, lookup_attrs = normalize_cm93_object_for_s52(
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object_class, geometry_type, attrs
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)
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if lookup_class != object_class:
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substitution_counts[(object_class, lookup_class, geometry_type)] += 1
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by_geometry[geometry_type] += 1
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tg = _geometry_key(geometry_type, args.point_table, args.boundary_table)
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if tg is None:
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no_lookup += 1
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empty_candidates += 1
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no_lookup_by_key[(object_class, geometry_type)] += 1
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no_candidate_by_key[(object_class, geometry_type)] += 1
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continue
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table_name, lookup_geometry = tg
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candidates = lookup_index.get((lookup_class, table_name, lookup_geometry), [])
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if not candidates:
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no_lookup += 1
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empty_candidates += 1
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no_lookup_by_key[(object_class, geometry_type)] += 1
|
||||
no_candidate_by_key[(object_class, geometry_type)] += 1
|
||||
continue
|
||||
hit = _resolve(candidates, lookup_attrs)
|
||||
if hit is None:
|
||||
no_lookup += 1
|
||||
no_lookup_by_key[(object_class, geometry_type)] += 1
|
||||
condition_miss_by_key[(object_class, geometry_type)] += 1
|
||||
continue
|
||||
matched += 1
|
||||
matched_by_geometry[geometry_type] += 1
|
||||
matched_by_key[(object_class, geometry_type)] += 1
|
||||
rcids[str(hit.get("rcid") or "")] += 1
|
||||
rules = hit.get("rules") or []
|
||||
for rule in rules:
|
||||
opcode = str(rule.get("opcode") or "")
|
||||
if opcode:
|
||||
opcode_counts[opcode] += 1
|
||||
args_list = rule.get("args") or []
|
||||
if opcode == "SY" and args_list:
|
||||
direct_symbol_counts[str(args_list[0])[:8]] += 1
|
||||
if opcode == "CS" and args_list:
|
||||
name = str(args_list[0])[:8]
|
||||
csp_counts[name] += 1
|
||||
if name in IMPLEMENTED_CSP:
|
||||
implemented_csp_counts[name] += 1
|
||||
else:
|
||||
unsupported_csp_counts[name] += 1
|
||||
conn.close()
|
||||
|
||||
top_no_lookup = [
|
||||
{"object_class": k[0], "geometry_type": k[1], "count": v}
|
||||
for k, v in no_lookup_by_key.most_common()
|
||||
]
|
||||
top_matched = [
|
||||
{"object_class": k[0], "geometry_type": k[1], "count": v}
|
||||
for k, v in matched_by_key.most_common()
|
||||
]
|
||||
report = {
|
||||
"schema": "navsea.cm95.s52-full-database-audit/v1",
|
||||
"dataset_id": args.dataset_id,
|
||||
"point_table": args.point_table,
|
||||
"boundary_table": args.boundary_table,
|
||||
"feature_count": total,
|
||||
"matched_lookup_count": matched,
|
||||
"no_lookup_count": no_lookup,
|
||||
"no_candidate_count": empty_candidates,
|
||||
"condition_no_match_count": no_lookup - empty_candidates,
|
||||
"match_rate": matched / total if total else None,
|
||||
"geometry_counts": dict(by_geometry),
|
||||
"matched_geometry_counts": dict(matched_by_geometry),
|
||||
"lookup_rcid_top100": rcids.most_common(100),
|
||||
"opcode_counts": dict(opcode_counts),
|
||||
"csp_counts": dict(csp_counts),
|
||||
"implemented_csp_counts": dict(implemented_csp_counts),
|
||||
"unsupported_csp_counts": dict(unsupported_csp_counts),
|
||||
"direct_symbol_top100": direct_symbol_counts.most_common(100),
|
||||
"class_substitution_counts": [
|
||||
{"source_object_class": k[0], "s52_object_class": k[1], "geometry_type": k[2], "count": v}
|
||||
for k, v in substitution_counts.most_common()
|
||||
],
|
||||
"no_lookup_by_object_geometry": top_no_lookup,
|
||||
"no_candidate_by_object_geometry": [
|
||||
{"object_class": k[0], "geometry_type": k[1], "count": v}
|
||||
for k, v in no_candidate_by_key.most_common()
|
||||
],
|
||||
"condition_no_match_by_object_geometry": [
|
||||
{"object_class": k[0], "geometry_type": k[1], "count": v}
|
||||
for k, v in condition_miss_by_key.most_common()
|
||||
],
|
||||
"matched_by_object_geometry": top_matched,
|
||||
"notes": {
|
||||
"context_dependent_csp": "本报告只统计 Lookup 实际触发量，不执行需要邻接几何、sounding depth、TOPMAR 平台关系等上下文的 CSP。",
|
||||
"implemented_csp": sorted(IMPLEMENTED_CSP),
|
||||
},
|
||||
}
|
||||
args.output.parent.mkdir(parents=True, exist_ok=True)
|
||||
args.output.write_text(json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8")
|
||||
print(json.dumps({
|
||||
"feature_count": total,
|
||||
"matched_lookup_count": matched,
|
||||
"no_lookup_count": no_lookup,
|
||||
"no_candidate_count": empty_candidates,
|
||||
"condition_no_match_count": no_lookup - empty_candidates,
|
||||
"match_rate": report["match_rate"],
|
||||
"csp_counts": report["csp_counts"],
|
||||
"unsupported_csp_counts": report["unsupported_csp_counts"],
|
||||
"class_substitution_counts": report["class_substitution_counts"],
|
||||
"top_no_lookup": top_no_lookup[:30],
|
||||
}, ensure_ascii=False, indent=2))
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
Reference in New Issue
Block a user