feat(understand): drawing_scale_check - is this drawing to scale against that one
Equipment tags found exactly once in each drawing are matched (a tag found twice - a plan copy, a legend - is reported ambiguous and takes no part; two plan copies resolve to the cluster that matches the most tags). For every pair of matched tags at least min_pair_mm apart on the reference, the ratio of their distances is taken in millimetres by each drawing's inferred unit; the median, the quartiles, the share within +/-10 % of the median, the same per room of the reference, and the verdict: to_scale (>= 80 %, with its factor), schematic (<= 50 %), partly, or insufficient under three matched tags. server.py grows SECTION 26 to two tools with drawing_scale_check (core, read-only, tagged analysis/query); alias record, inventory, README release snapshot 243, frozen group sizes (analysis 14). Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01FKFStjEFzpGyLq5bMpWxTd
This commit is contained in:
Umut CAN
co-authored by
Claude Opus 5.5
Claude Opus 5.5
parent
2459694880
commit
7aaead43d9
@@ -27,8 +27,8 @@ Live through COM on Windows, or headless through ezdxf anywhere — one typed co
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</div>
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> **v1.5 release snapshot:** 242 tools · 8 resources · 5 prompt templates · 4516 collected tests.
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> 242 is the **registered** count; a default install advertises 237 over `tools/list`,
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> **v1.5 release snapshot:** 243 tools · 8 resources · 5 prompt templates · 4516 collected tests.
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> 243 is the **registered** count; a default install advertises 238 over `tools/list`,
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> because `ENABLE_3D` is unset. `system_about` is the runtime authority.
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## Why this exists
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@@ -122,7 +122,7 @@ Claude Desktop, Cursor, or any stdio MCP host. For HTTP: `autocad-mcp --transpor
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| Quality loop | `drawing_preflight` → `drawing_plan` → `drawing_critique` → `drawing_refine` → `drawing_finalize` (0–100 score) |
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| Delivery | `drawing_deliver`: DXF/PDF/PNG + SHA-256 manifest + reopen-parity checks |
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<sub>242 tools in 26 groups; <code>TOOL_PACKS=core</code> hides the nine <code>pid_*</code> tools, the 22 environment tools, the 14 mechanical tools and the 12 architectural tools (<code>TOOL_PACKS=core,mech</code> keeps the mechanical ones, <code>TOOL_PACKS=core,arch</code> the architectural ones) from a client that needs none of them. Plus 8 resources that cost nothing in the tool budget (<code>autocad://drawing/info</code>, <code>layers</code>, <code>blocks</code>, <code>entities/stats</code>, <code>entities/{layer_name}</code>, <code>system/status</code>, <code>pid/symbols</code>, <code>standards/isa51</code>) and 5 prompt templates.</sub>
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<sub>243 tools in 26 groups; <code>TOOL_PACKS=core</code> hides the nine <code>pid_*</code> tools, the 22 environment tools, the 14 mechanical tools and the 12 architectural tools (<code>TOOL_PACKS=core,mech</code> keeps the mechanical ones, <code>TOOL_PACKS=core,arch</code> the architectural ones) from a client that needs none of them. Plus 8 resources that cost nothing in the tool budget (<code>autocad://drawing/info</code>, <code>layers</code>, <code>blocks</code>, <code>entities/stats</code>, <code>entities/{layer_name}</code>, <code>system/status</code>, <code>pid/symbols</code>, <code>standards/isa51</code>) and 5 prompt templates.</sub>
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**Two rules worth knowing.** Every coordinate in and out of a tool is WCS on both engines — the one exception is TEXT `rotation`, which stays in the entity frame because a mirrored TEXT is mirror-imaged and no scalar angle expresses that. And never read vertices back and shoelace them: that loses **28.2%** of the area on a semicircular edge, silently. `analysis_measure_entity(handle)` reads the real geometry and states its own accuracy.
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@@ -2494,6 +2494,25 @@ TOOL_ALIASES: dict[str, ToolAliases] = {
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"yabanci cizim",
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),
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),
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"drawing_scale_check": ToolAliases(
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acad=(),
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synonyms=(
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"scale check",
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"is the p&id to scale",
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"is this drawing to scale",
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"schematic or to scale",
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"unscaled p&id",
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"tag distances against the layout",
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"can i measure pipe on the p&id",
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"ölçek",
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"olcek",
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"ölçek kontrolü",
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"olcek kontrolu",
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"ölçekli mi",
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"olcekli mi",
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"масштаб",
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),
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),
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}
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@@ -3,13 +3,13 @@
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"schema_version": 1,
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"package_version": "1.5.1",
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"totals": {
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"tools": 242,
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"tools": 243,
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"resources": 8,
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"prompts": 5,
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"groups": 26
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},
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"groups": {
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"analysis": 13,
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"analysis": 14,
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"architecture": 12,
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"batch": 3,
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"blocks": 9,
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@@ -1116,6 +1116,20 @@
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"title": "Save As"
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}
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},
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{
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"name": "drawing_scale_check",
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"group": "analysis",
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"cost": "read",
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"summary": "Is this drawing to scale against a reference? Tag distances, ratios, a verdict.",
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"tags": [
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"analysis",
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"query"
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],
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"annotations": {
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"title": "Understand: Scale Check",
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"readOnlyHint": true
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}
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},
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{
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"name": "drawing_settings",
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"group": "system",
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@@ -0,0 +1,272 @@
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"""drawing_scale_check: is this drawing to scale against that one?
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A P&ID and a layout of one plant carry the same equipment tags. If the P&ID
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were drawn to scale, the distance between two tanks on it would be the distance
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on the layout times one factor, for every pair. On a schematic it is not - and
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a pipe length measured on a schematic is a length of drawn line, not of pipe.
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The check, in the order it runs:
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1. **Scope.** Model-space tags are read (`describe.tag_occurrences`) and the
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drawings split into clusters (`clusters.find_clusters`, outliers left out).
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Every pair of scopes - the whole drawing or one of its eight largest
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clusters, on each side - is tried, and the pair that matches the most tags
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wins (ties: the whole drawing first, then the larger cluster). Two copies
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of one plan side by side therefore resolve to one copy instead of making
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every tag ambiguous.
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2. **Match.** Only a tag found exactly once in each scope is matched. A tag
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found more than once in either (a plan copy, a legend, a second sheet) is
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``ambiguous`` and takes no part: picking one of its positions would be a
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guess.
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3. **Pairs.** For every two matched tags whose distance on the reference
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drawing ``b`` is at least ``min_pair_mm``, the ratio of their distance on
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``a`` to that on ``b`` is taken, both converted to millimetres by each
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drawing's inferred unit (`units.infer_units`).
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4. **Statistics.** The median ratio, the quartiles and their range, and the
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share of pairs within +/-10 % of the median - overall, and per room of the
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reference drawing (the labelled faces `describe.find_rooms` finds) or, for
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tags in no room, per cluster.
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5. **Verdict.** ``to_scale`` when at least 80 % of the pairs are within the
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band (``factor`` is then the median: a drawing at a different but uniform
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scale is recognised); ``schematic`` at 50 % or less; ``partly`` in between;
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``insufficient`` with fewer than three matched tags or no pair above the
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floor.
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A tag label is not an equipment centre: the band and the floor are there to
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absorb the offset between the two, and the result says so. Pure; neither
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drawing is touched.
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"""
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from __future__ import annotations
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import math
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import statistics
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from itertools import combinations
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from engineering.arch.faces import face_containing
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from engineering.understand.describe import FACE_TOL_FRACTION, find_rooms, prepare, tag_occurrences
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from engineering.understand.snapshot import Snapshot
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from engineering.understand.units import infer_units
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__all__ = ["MIN_TAGS", "SCHEMATIC_SHARE", "TO_SCALE_SHARE", "WITHIN", "match_tags", "scale_check"]
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#: The band around the median a pair must fall in to count as consistent.
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WITHIN = 0.10
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TO_SCALE_SHARE = 0.80
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SCHEMATIC_SHARE = 0.50
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MIN_TAGS = 3
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#: Clusters per drawing tried as a scope, largest first.
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MAX_SCOPE_CLUSTERS = 8
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#: Pair rows listed in the result, farthest from the median first.
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PAIR_ROW_CAP = 200
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NOTE = (
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"Tag labels are not equipment centres; the +/-10 % band and the min_pair_mm floor absorb "
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"the offset between a label and what it labels."
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)
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def _side(snap: Snapshot) -> dict:
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prep = prepare(snap)
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prep["tags"] = [o for o in tag_occurrences(snap, prep=prep) if o["space"] == "Model"]
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return prep
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def _scoped(side: dict, cluster: str | None, name: str) -> list[dict]:
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if cluster is None:
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return side["tags"]
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ids = [c["id"] for c in side["clusters"]]
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if cluster not in ids:
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raise ValueError(f"{name}: no cluster {cluster!r}; the drawing has {ids}")
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return [o for o in side["tags"] if o["cluster"] == cluster]
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def _match(side_a: dict, side_b: dict, cluster_a: str | None, cluster_b: str | None) -> dict:
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occ_a = _scoped(side_a, cluster_a, "cluster_a")
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occ_b = _scoped(side_b, cluster_b, "cluster_b")
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count_a: dict[str, list[dict]] = {}
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count_b: dict[str, list[dict]] = {}
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for o in occ_a:
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count_a.setdefault(o["tag"], []).append(o)
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for o in occ_b:
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count_b.setdefault(o["tag"], []).append(o)
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matched = {
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tag: (tuple(count_a[tag][0]["at"]), tuple(count_b[tag][0]["at"]))
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for tag in sorted(set(count_a) & set(count_b))
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if len(count_a[tag]) == 1 and len(count_b[tag]) == 1
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}
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ambiguous = sorted(
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tag
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for tag in set(count_a) | set(count_b)
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if len(count_a.get(tag, ())) > 1 or len(count_b.get(tag, ())) > 1
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)
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return {
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"matched": matched,
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"ambiguous": ambiguous,
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"occurrences": {
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tag: {"a": len(count_a.get(tag, ())), "b": len(count_b.get(tag, ()))}
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for tag in ambiguous
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},
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"only_a": sorted(t for t in count_a if t not in count_b and len(count_a[t]) == 1),
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"only_b": sorted(t for t in count_b if t not in count_a and len(count_b[t]) == 1),
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"cluster_a": cluster_a,
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"cluster_b": cluster_b,
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}
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def match_tags(a: Snapshot, b: Snapshot, *, cluster_a=None, cluster_b=None) -> dict:
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"""``{"matched": {tag: (pa, pb)}, "ambiguous": [tag, ...], ...}`` within the
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given scopes (a cluster id such as ``"C1"``, or None for the whole model
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space). ``pa`` / ``pb`` are the tag's positions in drawing units. Also
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``occurrences`` (per ambiguous tag, how often each side has it),
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``only_a`` / ``only_b`` and the scopes used. An unknown cluster id is
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refused with the ids the drawing has."""
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return _match(_side(a), _side(b), cluster_a, cluster_b)
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def _stats(ratios: list[float]) -> dict:
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if not ratios:
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return {"median": None, "q1": None, "q3": None, "iqr": None, "within_10pct": None}
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median = statistics.median(ratios)
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if len(ratios) >= 2:
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q1, _q2, q3 = statistics.quantiles(ratios, n=4, method="inclusive")
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else:
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q1 = q3 = ratios[0]
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within = sum(1 for r in ratios if abs(r - median) <= WITHIN * median) / len(ratios)
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return {"median": median, "q1": q1, "q3": q3, "iqr": q3 - q1, "within_10pct": within}
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def _verdict(tag_count: int, pair_count: int, stats: dict) -> str:
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if tag_count < MIN_TAGS or pair_count == 0 or not stats["median"] or stats["median"] <= 0:
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return "insufficient"
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if stats["within_10pct"] >= TO_SCALE_SHARE:
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return "to_scale"
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if stats["within_10pct"] <= SCHEMATIC_SHARE:
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return "schematic"
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return "partly"
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def _summary(tags: list[str], rows: list[dict]) -> dict:
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stats = _stats([r["ratio"] for r in rows])
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verdict = _verdict(len(tags), len(rows), stats)
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return {
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"verdict": verdict,
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"factor": stats["median"] if verdict == "to_scale" else None,
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**stats,
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"pair_count": len(rows),
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}
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def scale_check(a: Snapshot, b: Snapshot, *, min_pair_mm=2000.0) -> dict:
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"""Is drawing ``a`` to scale against the reference drawing ``b``?
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Returns ``{"verdict", "factor", "median", "q1", "q3", "iqr", "within_10pct",
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"pair_count", "pairs", "pairs_truncated", "pairs_below_floor", "matched",
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"ambiguous", "occurrences", "only_a", "only_b", "groups", "scope", "units",
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"min_pair_mm", "thresholds", "notes"}``. ``pairs`` lists at most 200 rows,
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farthest from the median first; ``matched`` is ``[{"tag", "a": [x, y],
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"b": [x, y]}]`` in drawing units. Refused before anything is computed: a
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``min_pair_mm`` that is not a positive finite number.
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"""
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try:
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floor = float(min_pair_mm)
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except (TypeError, ValueError):
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raise ValueError(f"min_pair_mm: expected a number, got {min_pair_mm!r}") from None
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if not math.isfinite(floor) or floor <= 0.0:
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raise ValueError(f"min_pair_mm: must be a positive number of millimetres, got {floor:g}")
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side_a, side_b = _side(a), _side(b)
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best = None
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for ca in [None] + [c["id"] for c in side_a["clusters"][:MAX_SCOPE_CLUSTERS]]:
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for cb in [None] + [c["id"] for c in side_b["clusters"][:MAX_SCOPE_CLUSTERS]]:
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m = _match(side_a, side_b, ca, cb)
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if best is None or len(m["matched"]) > len(best["matched"]):
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best = m
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tol_b = side_b["diag"] * FACE_TOL_FRACTION if side_b["diag"] > 0 else 1.0
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rooms_b = find_rooms(side_b["kept"], tol=tol_b, membership=side_b["membership"])
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units = {}
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notes = [NOTE]
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for key, snap, side, rooms in (
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("a", a, side_a, None),
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("b", b, side_b, rooms_b),
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):
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areas = [row["face"]["area"] for row, _f in rooms["labelled"]] if rooms else []
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u = infer_units(snap, records=side["kept"], room_areas=areas)
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units[key] = {
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"unit": u["inferred"],
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"mm_per_unit": u["mm_per_unit"],
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"declared": u["declared"],
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}
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if u["mm_per_unit"] is None:
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notes.append(
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f"drawing {key}: no unit could be settled; its drawing units are taken as mm"
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)
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fa = units["a"]["mm_per_unit"] or 1.0
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fb = units["b"]["mm_per_unit"] or 1.0
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matched = best["matched"]
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tags = sorted(matched)
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rows: list[dict] = []
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below = 0
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for ti, tj in combinations(tags, 2):
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d_b = math.dist(matched[ti][1], matched[tj][1]) * fb
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if d_b < floor:
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below += 1
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continue
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d_a = math.dist(matched[ti][0], matched[tj][0]) * fa
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rows.append({"tags": [ti, tj], "a_mm": d_a, "b_mm": d_b, "ratio": d_a / d_b})
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overall = _summary(tags, rows)
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faces = [face for _row, face in rooms_b["labelled"]]
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room_of = {id(face): row for row, face in rooms_b["labelled"]}
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groups: dict[str, dict] = {}
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for tag in tags:
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pb = matched[tag][1]
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face = face_containing(faces, pb) if faces else None
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if face is not None:
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row = room_of[id(face)]
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key = " ".join(p for p in ("room", row["number"], row["name"]) if p)
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kind = "room"
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else:
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cluster = next(
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(o["cluster"] for o in side_b["tags"] if o["tag"] == tag and tuple(o["at"]) == pb),
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None,
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)
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key, kind = (cluster or "unclustered"), "cluster"
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groups.setdefault(key, {"group": key, "kind": kind, "tags": []})["tags"].append(tag)
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group_rows = []
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for key in sorted(groups):
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g = groups[key]
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if len(g["tags"]) < 2:
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continue
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members = set(g["tags"])
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inside = [r for r in rows if r["tags"][0] in members and r["tags"][1] in members]
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group_rows.append({**g, **_summary(g["tags"], inside)})
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median = overall["median"]
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listed = sorted(
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rows,
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key=lambda r: (-(abs(r["ratio"] - median) if median else 0.0), r["tags"]),
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)[:PAIR_ROW_CAP]
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return {
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**overall,
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"pairs": listed,
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"pairs_truncated": len(rows) > PAIR_ROW_CAP,
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"pairs_below_floor": below,
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"matched": [{"tag": t, "a": list(matched[t][0]), "b": list(matched[t][1])} for t in tags],
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"ambiguous": best["ambiguous"],
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"occurrences": best["occurrences"],
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"only_a": best["only_a"],
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"only_b": best["only_b"],
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"groups": group_rows,
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"scope": {"cluster_a": best["cluster_a"], "cluster_b": best["cluster_b"]},
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"units": units,
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"min_pair_mm": floor,
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"thresholds": {
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"within": WITHIN,
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"to_scale_share": TO_SCALE_SHARE,
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"schematic_share": SCHEMATIC_SHARE,
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"min_tags": MIN_TAGS,
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},
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"notes": notes,
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}
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@@ -10555,7 +10555,7 @@ async def arch_plan_from_spec(
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# ---------------------------------------------------------------------------
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# ── SECTION 26: Understanding & QA (1 tool) ─────────────────────────────────
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# ── SECTION 26: Understanding & QA (2 tools) ────────────────────────────────
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# ---------------------------------------------------------------------------
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@@ -10628,6 +10628,91 @@ async def drawing_understand(
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return await asyncio.to_thread(describe, snap)
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|
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@cad_tool(
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summary="Is this drawing to scale against a reference? Tag distances, ratios, a verdict.",
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cost="read",
|
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)
|
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@mcp.tool(
|
||||
annotations={"title": "Understand: Scale Check", "readOnlyHint": True},
|
||||
tags={"analysis", "query"},
|
||||
)
|
||||
async def drawing_scale_check(
|
||||
reference: Annotated[
|
||||
str,
|
||||
Field(
|
||||
description="The reference drawing of the same plant (a DXF, usually the layout): "
|
||||
"distances on it are the ones the other drawing is measured against."
|
||||
),
|
||||
],
|
||||
path: Annotated[
|
||||
str | None,
|
||||
Field(
|
||||
default=None,
|
||||
description="The drawing to check (usually the P&ID); omitted: the current document.",
|
||||
),
|
||||
] = None,
|
||||
min_pair_mm: Annotated[
|
||||
float,
|
||||
Field(
|
||||
default=2000.0,
|
||||
gt=0,
|
||||
description="Tag pairs closer than this on the reference (mm) are left out: a tag "
|
||||
"label is not an equipment centre.",
|
||||
),
|
||||
] = 2000.0,
|
||||
ctx: Context = None,
|
||||
) -> dict:
|
||||
"""Is the drawing to scale against the reference - or a schematic whose lengths
|
||||
are lengths of drawn line, not of pipe? Read-only on both drawings.
|
||||
|
||||
Equipment tags are matched between the two (a Cyrillic look-alike such as
|
||||
`Т4100` is the Latin `T4100`). Only a tag found exactly once in each is used;
|
||||
a tag found more than once (plan copies, a legend, a second sheet) is listed
|
||||
in `ambiguous` and takes no part. When a drawing holds several bodies of
|
||||
content (two copies of one plan), the pair of scopes - whole drawing or one
|
||||
cluster on each side - that matches the most tags is used and named in
|
||||
`scope`. For every two matched tags at least `min_pair_mm` apart on the
|
||||
reference, the ratio of their distances is taken (both in millimetres by
|
||||
each drawing's inferred unit, see `drawing_understand`). The result gives
|
||||
the matched tags, the median ratio, the quartiles and their range, the
|
||||
share of pairs within +/-10 % of the median, the same per room of the
|
||||
reference (or per cluster for tags in no room) in `groups`, and a verdict:
|
||||
`to_scale` (at least 80 % within the band; `factor` is the median, so a
|
||||
uniform other scale is recognised), `schematic` (50 % or less), `partly`
|
||||
in between, `insufficient` with fewer than three matched tags or no pair
|
||||
above the floor. Tag labels are not equipment centres; the band and the
|
||||
floor absorb that offset, and the result's `notes` say so.
|
||||
|
||||
Refused before anything is read: a `reference` or `path` that does not
|
||||
exist, a DXF over `MAX_DXF_BYTES` (the refusal names the size and the
|
||||
variable), a file the engine cannot parse (a DWG headlessly), and a
|
||||
`min_pair_mm` that is not a positive finite number.
|
||||
"""
|
||||
import asyncio
|
||||
|
||||
from ezdxf.lldxf.const import DXFError
|
||||
|
||||
from engineering.understand.scale import scale_check
|
||||
from engineering.understand.snapshot import take_snapshot
|
||||
|
||||
ref = validate_path(reference)
|
||||
if not ref.is_file():
|
||||
raise ToolError(f"reference: no such file {str(ref)!r}")
|
||||
target = None
|
||||
if path:
|
||||
target = validate_path(path)
|
||||
if not target.is_file():
|
||||
raise ToolError(f"path: no such file {str(target)!r}")
|
||||
await ctx.info(f"drawing_scale_check: {target or 'current document'} against {ref}")
|
||||
backend = _backend(ctx)
|
||||
try:
|
||||
checked = await take_snapshot(backend, str(target) if target else None)
|
||||
against = await take_snapshot(backend, str(ref))
|
||||
return await asyncio.to_thread(scale_check, checked, against, min_pair_mm=min_pair_mm)
|
||||
except (ValueError, OSError, RuntimeError, DXFError) as exc:
|
||||
raise ToolError(str(exc)) from exc
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# ── RESOURCES ───────────────────────────────────────────────────────────────
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@@ -495,7 +495,7 @@ async def test_tool_groups_is_byte_identical_to_the_source_declared_grouping():
|
||||
|
||||
|
||||
async def test_tool_group_sizes_are_unchanged():
|
||||
"""Frozen snapshot of the surface (242 tools, 26 groups).
|
||||
"""Frozen snapshot of the surface (243 tools, 26 groups).
|
||||
|
||||
Taken before @cad_tool landed at 131 tools; `batch` moved 2 -> 3 when
|
||||
v1.5.0's `cad_batch` joined `entity_batch_create`/`entity_batch_modify`, and
|
||||
@@ -595,13 +595,14 @@ async def test_tool_group_sizes_are_unchanged():
|
||||
Track H group U opened SECTION 26 (Understanding & QA) with
|
||||
`drawing_understand`, tagged `analysis` and `query`: `analysis` outranks
|
||||
`query` in `_GROUP_TAG_PRIORITY`, so the reader files under `analysis`
|
||||
(12 -> 13) beside the other whole-drawing queries. This snapshot is
|
||||
branch-local: the track H merge task recomputes it once the understand,
|
||||
network and diff branches have landed.
|
||||
(12 -> 13) beside the other whole-drawing queries, and
|
||||
`drawing_scale_check`, tagged the same, followed it (13 -> 14). This
|
||||
snapshot is branch-local: the track H merge task recomputes it once the
|
||||
understand, network and diff branches have landed.
|
||||
"""
|
||||
sizes = {label: len(names) for label, names in (await server._tool_groups()).items()}
|
||||
assert sizes == {
|
||||
"analysis": 13,
|
||||
"analysis": 14,
|
||||
"architecture": 12,
|
||||
"batch": 3,
|
||||
"blocks": 9,
|
||||
@@ -628,4 +629,4 @@ async def test_tool_group_sizes_are_unchanged():
|
||||
"validation": 1,
|
||||
"view": 4,
|
||||
}
|
||||
assert sum(sizes.values()) == 242
|
||||
assert sum(sizes.values()) == 243
|
||||
|
||||
@@ -0,0 +1,192 @@
|
||||
"""drawing_scale_check: tag matching and ratio statistics.
|
||||
|
||||
The hand-built plans put six tags at coordinates written below; every pair
|
||||
distance and ratio in the comments is worked out from them.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
from itertools import combinations
|
||||
|
||||
import pytest
|
||||
|
||||
from engineering.understand.scale import match_tags, scale_check
|
||||
from engineering.understand.snapshot import EntityRecord, Snapshot, read_snapshot
|
||||
from tests.fixtures.plant_pair import build_plant_pair
|
||||
|
||||
EPS = 1e-12
|
||||
|
||||
#: Six tags of one plant, in millimetres. The closest pair is T4100-T4500,
|
||||
#: hypot(6000, 4000) = 7211.1, so every pair clears the 2 m floor.
|
||||
PLAN = {
|
||||
"T4100": (0.0, 0.0),
|
||||
"T4200": (12000.0, 0.0),
|
||||
"T4300": (12000.0, 9000.0),
|
||||
"T4400": (0.0, 9000.0),
|
||||
"T4500": (6000.0, 4000.0),
|
||||
"T4600": (20000.0, 15000.0),
|
||||
}
|
||||
|
||||
|
||||
def text(handle, value, x, y):
|
||||
return EntityRecord(
|
||||
handle=handle, type="TEXT", layer="TAGS", space="Model", points=((x, y),), text=value
|
||||
)
|
||||
|
||||
|
||||
def outline(handle, x0, y0, x1, y1):
|
||||
return EntityRecord(
|
||||
handle=handle,
|
||||
type="LWPOLYLINE",
|
||||
layer="0",
|
||||
space="Model",
|
||||
points=((x0, y0), (x1, y0), (x1, y1), (x0, y1)),
|
||||
bulges=(0.0, 0.0, 0.0, 0.0),
|
||||
closed=True,
|
||||
)
|
||||
|
||||
|
||||
def snapshot(records):
|
||||
return Snapshot(
|
||||
source="test",
|
||||
insunits=4,
|
||||
extmin=None,
|
||||
extmax=None,
|
||||
layers={},
|
||||
layouts=("Model",),
|
||||
records=tuple(records),
|
||||
)
|
||||
|
||||
|
||||
def tags(positions, prefix="H", factor=1.0, dx=0.0):
|
||||
return [
|
||||
text(f"{prefix}{i}", tag, x * factor + dx, y * factor)
|
||||
for i, (tag, (x, y)) in enumerate(sorted(positions.items()))
|
||||
]
|
||||
|
||||
|
||||
def test_a_drawing_at_exactly_half_scale_is_to_scale_with_factor_one_half():
|
||||
result = scale_check(snapshot(tags(PLAN, "A", 0.5)), snapshot(tags(PLAN, "B")))
|
||||
assert result["verdict"] == "to_scale"
|
||||
assert result["factor"] == pytest.approx(0.5, abs=EPS)
|
||||
assert result["median"] == pytest.approx(0.5, abs=EPS)
|
||||
assert result["iqr"] == pytest.approx(0.0, abs=EPS)
|
||||
assert result["within_10pct"] == 1.0
|
||||
assert result["pair_count"] == 15 # C(6, 2)
|
||||
assert result["pairs_below_floor"] == 0
|
||||
assert [m["tag"] for m in result["matched"]] == sorted(PLAN)
|
||||
assert result["ambiguous"] == []
|
||||
assert result["units"]["a"]["unit"] == result["units"]["b"]["unit"] == "mm"
|
||||
|
||||
|
||||
def test_a_rearranged_drawing_is_schematic():
|
||||
# The same six tags, shuffled onto each other's places and one moved off.
|
||||
rearranged = {
|
||||
"T4100": (12000.0, 9000.0),
|
||||
"T4200": (0.0, 0.0),
|
||||
"T4300": (20000.0, 15000.0),
|
||||
"T4400": (6000.0, 4000.0),
|
||||
"T4500": (12000.0, 0.0),
|
||||
"T4600": (0.0, 20000.0),
|
||||
}
|
||||
result = scale_check(snapshot(tags(rearranged, "A")), snapshot(tags(PLAN, "B")))
|
||||
ratios = sorted(
|
||||
math.dist(rearranged[i], rearranged[j]) / math.dist(PLAN[i], PLAN[j])
|
||||
for i, j in combinations(sorted(PLAN), 2)
|
||||
)
|
||||
median = ratios[7] # 15 ratios: the 8th
|
||||
within = sum(1 for r in ratios if abs(r - median) <= 0.1 * median) / 15
|
||||
assert result["median"] == pytest.approx(median, abs=EPS)
|
||||
assert result["within_10pct"] == pytest.approx(within, abs=EPS)
|
||||
assert within <= 0.5
|
||||
assert result["verdict"] == "schematic"
|
||||
assert result["factor"] is None
|
||||
|
||||
|
||||
def test_a_tag_found_twice_is_ambiguous_and_takes_no_part():
|
||||
# T4400 appears twice on the reference: neither copy is matched.
|
||||
reference = [*tags(PLAN, "B"), text("DUP", "T4400", 3000.0, 12000.0)]
|
||||
matched = match_tags(snapshot(tags(PLAN, "A", 0.5)), snapshot(reference))
|
||||
assert "T4400" not in matched["matched"]
|
||||
assert matched["ambiguous"] == ["T4400"]
|
||||
assert matched["occurrences"] == {"T4400": {"a": 1, "b": 2}}
|
||||
assert matched["matched"]["T4200"] == ((6000.0, 0.0), (12000.0, 0.0))
|
||||
|
||||
result = scale_check(snapshot(tags(PLAN, "A", 0.5)), snapshot(reference))
|
||||
assert result["ambiguous"] == ["T4400"]
|
||||
assert "T4400" not in [m["tag"] for m in result["matched"]]
|
||||
assert result["pair_count"] == 10 # C(5, 2): the ambiguous tag is in no pair
|
||||
assert all("T4400" not in row["tags"] for row in result["pairs"])
|
||||
assert result["verdict"] == "to_scale"
|
||||
assert result["factor"] == pytest.approx(0.5, abs=EPS)
|
||||
|
||||
|
||||
def test_two_plan_copies_on_the_reference_resolve_to_one_copy():
|
||||
# The reference holds the plan twice, 60 000 apart, each inside its own
|
||||
# outline: over the whole drawing every tag is ambiguous, inside one copy
|
||||
# every tag is unique.
|
||||
reference = [
|
||||
outline("O1", -1000.0, -1000.0, 21000.0, 16000.0),
|
||||
*tags(PLAN, "L"),
|
||||
outline("O2", 59000.0, -1000.0, 81000.0, 16000.0),
|
||||
*tags(PLAN, "R", dx=60000.0),
|
||||
]
|
||||
whole = match_tags(snapshot(tags(PLAN, "A", 0.5)), snapshot(reference))
|
||||
assert whole["matched"] == {}
|
||||
assert whole["ambiguous"] == sorted(PLAN)
|
||||
result = scale_check(snapshot(tags(PLAN, "A", 0.5)), snapshot(reference))
|
||||
assert result["scope"] == {"cluster_a": None, "cluster_b": "C1"}
|
||||
assert len(result["matched"]) == 6
|
||||
assert result["ambiguous"] == []
|
||||
assert result["verdict"] == "to_scale"
|
||||
assert result["factor"] == pytest.approx(0.5, abs=EPS)
|
||||
|
||||
|
||||
def test_cyrillic_look_alike_tags_match_their_latin_twins():
|
||||
# "Т4100" typed with a Cyrillic Т (U+0422) is the layout's Latin T4100.
|
||||
cyrillic = {("Т" + tag[1:] if tag == "T4100" else tag): xy for tag, xy in PLAN.items()}
|
||||
matched = match_tags(snapshot(tags(cyrillic, "A")), snapshot(tags(PLAN, "B")))
|
||||
assert "T4100" in matched["matched"]
|
||||
assert len(matched["matched"]) == 6
|
||||
|
||||
|
||||
def test_fewer_than_three_matched_tags_is_insufficient():
|
||||
two = {k: PLAN[k] for k in ("T4100", "T4200")}
|
||||
result = scale_check(snapshot(tags(two, "A")), snapshot(tags(PLAN, "B")))
|
||||
assert result["verdict"] == "insufficient"
|
||||
assert result["factor"] is None
|
||||
assert result["pair_count"] == 1
|
||||
|
||||
|
||||
def test_pairs_closer_than_the_floor_on_the_reference_are_left_out():
|
||||
# With a 13 m floor, the pairs of PLAN at least 13 000 apart on the
|
||||
# reference are T4100-T4300 (15 000), T4100-T4600 (25 000), T4200-T4600
|
||||
# (hypot(8000, 15000) = 17 000), T4400-T4600 (hypot(20000, 6000) = 20 881),
|
||||
# T4500-T4600 (hypot(14000, 11000) = 17 804), T4200-T4400 (15 000): six.
|
||||
result = scale_check(
|
||||
snapshot(tags(PLAN, "A", 0.5)), snapshot(tags(PLAN, "B")), min_pair_mm=13000.0
|
||||
)
|
||||
assert result["pair_count"] == 6
|
||||
assert result["pairs_below_floor"] == 9
|
||||
assert result["verdict"] == "to_scale"
|
||||
|
||||
|
||||
@pytest.mark.parametrize("floor", [0.0, -5.0, float("nan"), float("inf")])
|
||||
def test_a_floor_that_is_not_a_positive_number_is_refused(floor):
|
||||
with pytest.raises(ValueError, match="min_pair_mm: must be a positive number"):
|
||||
scale_check(snapshot(tags(PLAN, "A")), snapshot(tags(PLAN, "B")), min_pair_mm=floor)
|
||||
|
||||
|
||||
def test_an_unknown_cluster_is_refused_with_the_ids_the_drawing_has():
|
||||
with pytest.raises(ValueError, match=r"cluster_b: no cluster 'C99'"):
|
||||
match_tags(snapshot(tags(PLAN, "A")), snapshot(tags(PLAN, "B")), cluster_b="C99")
|
||||
|
||||
|
||||
def test_the_synthetic_pid_is_schematic_against_its_layout(tmp_path):
|
||||
truth = build_plant_pair(tmp_path)
|
||||
result = scale_check(read_snapshot(truth["pid"]), read_snapshot(truth["layout"]))
|
||||
assert result["verdict"] == truth["scale_verdict"]
|
||||
assert len(result["matched"]) >= 3
|
||||
# The layout's two plan copies: the check must pick one of them.
|
||||
assert result["scope"]["cluster_b"] is not None
|
||||
@@ -0,0 +1,100 @@
|
||||
"""drawing_scale_check over the MCP wire, on a fresh headless document."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import ezdxf
|
||||
import pytest
|
||||
import pytest_asyncio
|
||||
from fastmcp import Client
|
||||
|
||||
import server
|
||||
from tests.fixtures.plant_pair import build_plant_pair
|
||||
|
||||
pytestmark = pytest.mark.asyncio
|
||||
|
||||
#: Six tags of one plant in millimetres; the closest pair is 7 211 apart.
|
||||
PLAN = {
|
||||
"T4100": (0.0, 0.0),
|
||||
"T4200": (12000.0, 0.0),
|
||||
"T4300": (12000.0, 9000.0),
|
||||
"T4400": (0.0, 9000.0),
|
||||
"T4500": (6000.0, 4000.0),
|
||||
"T4600": (20000.0, 15000.0),
|
||||
}
|
||||
|
||||
|
||||
@pytest_asyncio.fixture
|
||||
async def client(monkeypatch):
|
||||
"""In-memory client on a fresh headless document - never the operator's AutoCAD."""
|
||||
monkeypatch.setenv("AUTOCAD_MCP_BACKEND", "ezdxf")
|
||||
async with Client(server.mcp) as connected:
|
||||
status = (await connected.call_tool("system_status", {})).structured_content or {}
|
||||
assert status.get("backend") == "ezdxf", "these tests must never touch live AutoCAD"
|
||||
await connected.call_tool("drawing_new", {})
|
||||
yield connected
|
||||
|
||||
|
||||
def reference_file(tmp_path):
|
||||
"""The plan's tags at full size in a millimetre DXF (INSUNITS 4)."""
|
||||
doc = ezdxf.new(dxfversion="R2010", units=4)
|
||||
msp = doc.modelspace()
|
||||
for tag, (x, y) in PLAN.items():
|
||||
msp.add_text(tag, height=250.0, dxfattribs={"insert": (x, y), "layer": "TAGS"})
|
||||
path = tmp_path / "reference.dxf"
|
||||
doc.saveas(path)
|
||||
return str(path)
|
||||
|
||||
|
||||
async def test_the_synthetic_pid_is_schematic_against_its_layout(client, tmp_path):
|
||||
truth = build_plant_pair(tmp_path)
|
||||
result = await client.call_tool(
|
||||
"drawing_scale_check", {"path": truth["pid"], "reference": truth["layout"]}
|
||||
)
|
||||
assert result.structured_content["verdict"] == truth["scale_verdict"]
|
||||
|
||||
|
||||
async def test_the_current_document_at_half_scale_is_to_scale_with_factor_one_half(
|
||||
client, tmp_path
|
||||
):
|
||||
# The same tags at half the coordinates in the current document. Its
|
||||
# header says metres (drawing_new keeps ezdxf's default INSUNITS 6), but
|
||||
# 250-unit text and a 10 000-unit spread read as millimetres, and the
|
||||
# check converts by the inferred unit: the factor stays 0.5.
|
||||
for tag, (x, y) in PLAN.items():
|
||||
await client.call_tool(
|
||||
"entity_create_text",
|
||||
{"text": tag, "x": x * 0.5, "y": y * 0.5, "height": 250.0, "layer": "TAGS"},
|
||||
)
|
||||
before = (await client.call_tool("analysis_entity_stats", {})).structured_content
|
||||
result = await client.call_tool("drawing_scale_check", {"reference": reference_file(tmp_path)})
|
||||
after = (await client.call_tool("analysis_entity_stats", {})).structured_content
|
||||
assert after == before
|
||||
report = result.structured_content
|
||||
assert report["units"]["a"]["unit"] == report["units"]["b"]["unit"] == "mm"
|
||||
assert report["verdict"] == "to_scale"
|
||||
assert report["factor"] == pytest.approx(0.5, abs=1e-12)
|
||||
assert report["pair_count"] == 15
|
||||
assert report["ambiguous"] == []
|
||||
|
||||
|
||||
async def test_a_missing_reference_is_refused_by_name(client, tmp_path):
|
||||
result = await client.call_tool(
|
||||
"drawing_scale_check", {"reference": str(tmp_path / "none.dxf")}, raise_on_error=False
|
||||
)
|
||||
assert result.is_error is True
|
||||
assert "reference: no such file" in result.content[0].text
|
||||
|
||||
|
||||
async def test_a_non_positive_floor_is_refused(client, tmp_path):
|
||||
result = await client.call_tool(
|
||||
"drawing_scale_check",
|
||||
{"reference": reference_file(tmp_path), "min_pair_mm": 0.0},
|
||||
raise_on_error=False,
|
||||
)
|
||||
assert result.is_error is True
|
||||
assert "min_pair_mm" in result.content[0].text
|
||||
|
||||
|
||||
async def test_drawing_scale_check_is_advertised_read_only(client):
|
||||
tools = {tool.name: tool for tool in await client.list_tools()}
|
||||
assert tools["drawing_scale_check"].annotations.readOnlyHint is True
|
||||
Reference in New Issue
Block a user