chore(rebar): Pier_T_rebar 작업 폴더 초기 구성 및 외부 의존 파일 통합
- Code\rebar_pipeline, review_pipeline, pier-program을 정션에서 실제 폴더로 전환 - Code\rhino_mcp 및 CLAUDE_rhino배경.md 추가, .mcp.json은 PYTHONPATH로 새 위치 사용 - pier-program 내부 .git 제거(이력은 backup\pier-program_20261028.bundle에 보관) - worktree 가이드 반영(CLAUDE.local.md, HANDOFF.md) - D:\Rhino-MCP 경로 참조를 새 위치로 치환 Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
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"""Out-of-table dimension finding (stage C of the 입력 묶음 확인·확정 개편, first part, 2026-10-19).
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Anchors: for a modelled pier (params / expected known) the app records where each numeric field was read from the drawing — every dimension / EL
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text (layer, sheet, position) whose value equals the field value. For a NEW drawing of the same series the anchors are followed: the shift between
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the two drawings is estimated per view from the texts both drawings share (R5), the candidate is the dimension text of the same layer and kind
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nearest to the predicted position (R1 EL texts, scalar dimension texts). Several instances of one dimension (front / side / plan) vote.
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Trust grades (기획서 4.2): A >= 2 instances followed and all agree, small shift spread -> candidate with evidence, may be applied
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B agreement of >= 2 instances, or a single instance -> candidate with a warning
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C instances disagree -> list only, applying needs a reason
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none: nothing found -> "근거 없음", no candidate is invented.
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R2: dimension chains `n@pitch=total` are parsed and checked (n x pitch = total).
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Validation on the real series (tools/test_anchors.py): grade A had no wrong candidate; B and C are measured and shown as such.
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"""
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import re
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import statistics
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from collections import defaultdict
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from engine import variability
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VERSION = "2"
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MIN_MM = 1000 # values below one metre are too common as texts to be anchored
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MAX_HITS = 6 # a value found in more places is not a specific dimension
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RADIUS = 1200.0 # search radius around the predicted position (drawing units, mm)
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K_LANDMARKS = 5
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MIN_COVERAGE = 0.70 # share of the anchors' landmark texts found again in the new drawing
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A_SPREAD = 400.0
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TABLE_RULE = "single" # "single": a candidate whose only followed instance is ONE table cell is demoted to C (2026-10-20); "none": table cells never grade; "off": old behaviour.
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# Measured on the verified Ungok P3 / P4 values: grade B wrong 10/65 (off) -> 2/39 (single) vs 3/29 (none); grade A unchanged (0 wrong)
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MARK = re.compile(r"^[A-Z]{1,2}\d{1,2}$")
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NUM = re.compile(r"^-?\d[\d,]*\.?\d*$")
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CHAIN = re.compile(r"^(\d+)\s*@\s*(\d[\d,]*(?:\.\d+)?)\s*=\s*(\d[\d,]*(?:\.\d+)?)\s*(?:\(.*\))?$")
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SKIP = {("expected", "planned_fail"), ("expected", "rebar_palette"), ("expected", "tol_mm")}
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def text_val(t):
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"""(value mm, kind) of a dimension / EL text: 'EL. 38.916' -> (38916, EL), '7.800' -> (7800, m), '7800' -> (7800, mm); else None."""
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s = t.strip().replace(" ", "")
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m = re.match(r"^EL\.?(\d+\.\d{3})$", s)
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if m:
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return round(float(m.group(1)) * 1000, 3), "EL"
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if NUM.match(s):
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x = s.replace(",", "")
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try:
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f = float(x)
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except ValueError:
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return None
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if re.match(r"^\d+\.\d{3}$", x):
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return round(f * 1000, 3), "m"
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if re.match(r"^\d+$", x):
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return f, "mm"
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return None
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def leaves(params, expected, max_list=40):
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"""(field, value) of every anchorable numeric leaf: bundles of grade V1 / V2 only, no sources / notes, no human decision records."""
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for which, doc in (("params", params), ("expected", expected)):
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for k, v in doc.items():
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m = variability.classify(which, k, v)
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if m["info"] or m["grade"] in ("F", "V3") or (which, k) in SKIP:
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continue
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stack = [((k,), v)]
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while stack:
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path, x = stack.pop()
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if isinstance(x, dict):
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for a, b in x.items():
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if a in ("src", "_note") or a.endswith("_src"):
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continue
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stack.append((path + (str(a),), b))
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elif isinstance(x, list):
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if len(x) <= max_list:
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stack.extend((path + (str(i),), b) for i, b in enumerate(x))
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elif isinstance(x, (int, float)) and not isinstance(x, bool):
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yield f"{which}:" + ".".join(path), x
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def _unique_labels(texts):
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out = defaultdict(list)
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for t in texts:
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s = t["text"].strip()
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if len(s) > 1 and not NUM.match(s.replace(" ", "")) and not CHAIN.match(s):
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out[(t["dwg"], s)].append(t)
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return {k: v[0] for k, v in out.items() if len(v) == 1}
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def learn(params, expected, texts, sources=()):
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"""Anchors of a modelled pier. `sources` = sha256 of its DWG files (to recognise a pier that follows its own drawing)."""
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by = defaultdict(list)
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for t in texts:
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v = text_val(t["text"])
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if v:
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by[round(v[0])].append({"text": t["text"].strip(), "x": t["x"], "y": t["y"], "layer": t["layer"], "dwg": t["dwg"], "kind": v[1]})
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fields = {}
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owners = defaultdict(set) # same value, same file, different bundle / leaf name -> which field the text belongs to is unknown
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cand = []
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for field, v in leaves(params, expected):
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key = round(abs(v))
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if key >= MIN_MM and 1 <= len(by.get(key, [])) <= MAX_HITS:
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which, path = field.split(":", 1)
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parts = [q for q in path.split(".") if not q.isdigit() and not MARK.match(q)] # mark rows (P3, C1 ...) are instances of one dimension kind
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owners[(which, key)].add((path.split(".")[0], re.sub(r"_(x|y|z|left|right|front|rear|top|bottom)$", "", parts[-1])))
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cand.append((field, v, key))
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for field, v, key in cand:
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which = field.split(":", 1)[0]
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fields[field] = {"v": v, "hits": by[key], "shared": len(owners[(which, key)])}
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lm = [{"text": s, "x": t["x"], "y": t["y"], "dwg": d} for (d, s), t in _unique_labels(texts).items()]
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return {"version": VERSION, "sources": list(sources), "fields": fields, "landmarks": lm}
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def _shift(anchor, common, dwg, x, y):
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near = sorted((c for c in common if c[4] == dwg), key=lambda c: (c[0] - x) ** 2 + (c[1] - y) ** 2)[:K_LANDMARKS]
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if not near:
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return None
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dx, dy = statistics.median(c[2] for c in near), statistics.median(c[3] for c in near)
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return dx, dy, max(abs(c[2] - dx) for c in near) + max(abs(c[3] - dy) for c in near)
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def follow(anchors, texts, own_sources=()):
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"""Candidates for a new drawing: {field: {value, grade, followed, agree, spread, text, x, y, dwg, layer, all, self_source}}."""
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new = _unique_labels(texts)
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common = []
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for lm in anchors.get("landmarks", []):
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t = new.get((lm["dwg"], lm["text"]))
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if t:
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common.append((lm["x"], lm["y"], t["x"] - lm["x"], t["y"] - lm["y"], lm["dwg"]))
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by_layer = defaultdict(list)
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for t in texts:
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v = text_val(t["text"])
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if v:
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by_layer[(t["dwg"], t["layer"], v[1])].append((v[0], t))
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self_source = bool(set(anchors.get("sources", [])) & set(own_sources))
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coverage = len(common) / len(anchors["landmarks"]) if anchors.get("landmarks") else 0.0
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out = {}
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for field, a in anchors.get("fields", {}).items():
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res = []
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for h in a["hits"]:
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sh = _shift(a, common, h["dwg"], h["x"], h["y"])
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if not sh:
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continue
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px, py = h["x"] + sh[0], h["y"] + sh[1]
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best = None
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for val, t in by_layer.get((h["dwg"], h["layer"], h["kind"]), []):
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d = ((t["x"] - px) ** 2 + (t["y"] - py) ** 2) ** 0.5
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if d <= RADIUS and (best is None or d < best[0]):
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best = (d, val, t)
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if best:
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res.append({"value": round(best[1]), "dist": round(best[0], 1), "spread": round(sh[2], 1), "text": best[2]["text"].strip(),
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"x": best[2]["x"], "y": best[2]["y"], "dwg": best[2]["dwg"], "layer": best[2]["layer"],
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"table_cell": "TABL" in best[2]["layer"]})
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if not res:
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continue
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# improvement #34-4 (2026-10-20): a text that sits in a schedule / table is found again by POSITION, but the rows of a table move when the pier's
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# bar list differs (Ungok P3 / P4: the length cell '3.800' of S1 was followed as the end of a rebar chain, grade B). Table cells are the job of the
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# table candidates (engine/reader, check C2). A candidate whose only followed instance is one table cell is therefore demoted to C.
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free = [r for r in res if not r["table_cell"]]
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if TABLE_RULE == "none":
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table_only = not free
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if free:
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res = free
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elif TABLE_RULE == "single":
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table_only = not free and len(res) == 1
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else:
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table_only = False
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vals = [r["value"] for r in res]
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cons = max(set(vals), key=lambda v: (vals.count(v), -abs(v)))
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agree = vals.count(cons)
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spread = max(r["spread"] for r in res)
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if table_only:
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grade = "C"
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elif len(res) >= 2 and agree == len(res) and spread < A_SPREAD and a.get("shared", 1) == 1:
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grade = "A"
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elif agree >= 2 or len(res) == 1:
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grade = "B"
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else:
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grade = "C"
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if coverage < MIN_COVERAGE and grade != "C":
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grade = "C" # the drawing frame differs from the one the anchors come from
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pos = min((r for r in res if r["value"] == cons), key=lambda r: r["dist"])
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out[field] = {"value": cons if a["v"] >= 0 else -cons, "grade": grade, "followed": len(res), "agree": agree, "spread": spread,
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"text": pos["text"], "x": pos["x"], "y": pos["y"], "dwg": pos["dwg"], "layer": pos["layer"],
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"all": sorted(set(vals)), "source_value": a["v"], "self_source": self_source, "coverage": round(coverage, 2),
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"shared": a.get("shared", 1), "table_only": table_only}
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return out
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def table_values(proposal_rows):
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"""{field: value} of the table candidates (engine.reader.proposals rows); list candidates are expanded per index (schedule [L, n])."""
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out = {}
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for r in proposal_rows:
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field = f"{r['file']}:" + ".".join(str(x) for x in r["path"])
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c = r["candidate"]
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if isinstance(c, (list, tuple)):
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for i, v in enumerate(c):
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if isinstance(v, (int, float)) and not isinstance(v, bool):
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out[f"{field}.{i}"] = v
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elif isinstance(c, (int, float)) and not isinstance(c, bool):
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out[field] = c
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return out
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def cross_check(cand, table):
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"""Confirm / correct anchor candidates with table values of the same field: equal -> grade A (table_confirmed), different -> grade C with
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`table` = the table value. Fields without a table value keep their grade. Works on the dict returned by follow()."""
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for f, c in cand.items():
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t = table.get(f)
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if t is None:
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continue
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c["table"] = t
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if abs(abs(t) - abs(c["value"])) <= 1.5:
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c["grade"], c["table_confirmed"] = "A", True
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else:
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c["grade"], c["table_confirmed"] = "C", False
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return cand
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def chains(texts):
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"""R2: dimension chains `n@pitch=total` with the check n x pitch = total: [{text, dwg, x, y, n, pitch, total, ok}]."""
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def mm(s):
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s = s.replace(",", "")
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return round(float(s) * 1000) if re.fullmatch(r"\d+\.\d{3}", s) else round(float(s))
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out = []
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for t in texts:
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m = CHAIN.match(t["text"].strip())
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if m:
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n, p, tot = int(m.group(1)), mm(m.group(2)), mm(m.group(3))
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out.append({"text": t["text"].strip(), "dwg": t["dwg"], "x": t["x"], "y": t["y"], "n": n, "pitch": p, "total": tot, "ok": abs(n * p - tot) <= 1})
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return out
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