Umut CANandClaude Opus 5
e246b5e86a
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01FKFStjEFzpGyLq5bMpWxTd
566 lines
21 KiB
Python
566 lines
21 KiB
Python
"""Read a P&ID back as a graph: nodes (symbols), edges (lines), junctions, dangling ends.
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Rules the reader keeps (spec §9.4): it never modifies the drawing, it reads
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geometry from the drawing rather than the catalogue, and confidence is the
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minimum of its inputs — never raised by agreement between heuristics.
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"""
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from __future__ import annotations
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import math
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import re
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from dataclasses import dataclass, field
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from typing import TYPE_CHECKING
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from .lines import LAYER_TO_CLASS, PID_LINE_LAYERS
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from .symbols import Port, transform_port
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from .tags import parse_tag
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from .xdata import read_payload
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if TYPE_CHECKING:
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from backends.base import AutoCADBackend, EntityInfo
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INSERT_TYPES = {"INSERT", "BLOCKREFERENCE"}
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# Same set ``drawlines`` keeps: ezdxf says LWPOLYLINE, the COM engine derives
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# POLYLINE (AcDbPolyline) / 2DPOLYLINE from the ActiveX ObjectName.
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POLY_TYPES = {"LWPOLYLINE", "POLYLINE", "2DPOLYLINE"}
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LINE_TYPES = {"LINE"}
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TEXT_TYPES = {"TEXT", "MTEXT"}
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ATTRIBUTE_TAGS = ("TAG", "TAGNO", "TAGNUMBER", "EQUIP_TAG", "EQUIPMENT_TAG", "INST_TAG", "INSTTAG")
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# Block-name keywords (spec §9.2 step 2), matched as whole tokens of the name
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# split on non-letters: ``GATE_VALVE`` → VALVE, ``P101PUMP`` → PUMP, but
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# ``COMPANY_LOGO`` is a logo, not a compressor — a substring match would file
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# every title block and logo as equipment at 0.6.
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KEYWORDS = {
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"VALVE": "valve",
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"VLV": "valve",
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"PUMP": "equipment",
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"TANK": "equipment",
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"VESSEL": "equipment",
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"DRUM": "equipment",
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"INST": "instrument",
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"INSTRUMENT": "instrument",
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"BUBBLE": "instrument",
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"HX": "equipment",
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"EXCH": "equipment",
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"EXCHANGER": "equipment",
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"FILTER": "equipment",
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"COMP": "equipment",
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"COMPRESSOR": "equipment",
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}
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_TOKEN_RE = re.compile(r"[A-Z]+")
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FAMILY_KIND = {"instrument": "instrument", "valve": "valve", "connector": "connector"}
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LINE_NUMBER_RE = re.compile(r'^\d+(?:"|MM)?-[A-Z]{1,4}-\d+', re.IGNORECASE)
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CONFIDENCE = {"catalog": 1.0, "xdata": 0.95, "heuristic": 0.6, "inferred": 0.3}
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_PAGE = 1000
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@dataclass
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class _Node:
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id: str
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kind: str
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block_name: str
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family: str | None
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symbol: str | None
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x: float
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y: float
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rotation_deg: float
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scale: float
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layer: str
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space: str
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bbox: tuple[float, float, float, float] | None
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source: str
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confidence: float
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attributes: dict
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ports: dict = field(default_factory=dict)
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tag: str | None = None
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tag_source: str | None = None
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def to_dict(self) -> dict:
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parsed = None
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if self.tag:
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parsed = parse_tag(self.tag, kind="instrument" if self.kind == "instrument" else "auto")
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return {
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"id": self.id,
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"kind": self.kind,
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"block_name": self.block_name,
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"family": self.family,
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"symbol": self.symbol,
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"tag": self.tag,
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"tag_parsed": parsed,
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"tag_source": self.tag_source,
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"x": self.x,
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"y": self.y,
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"rotation_deg": self.rotation_deg,
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"scale": self.scale,
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"layer": self.layer,
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"space": self.space,
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"ports": self.ports,
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"description": self.attributes.get("DESC") or None,
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"source": self.source,
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"confidence": self.confidence,
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}
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@dataclass
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class _Edge:
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id: str
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vertices: list[tuple[float, float]]
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layer: str
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linetype: str
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space: str
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payload: dict | None
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source: str
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line_class: str | None = None
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class_source: str | None = None
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line_number: str | None = None
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number_source: str | None = None
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from_ref: dict | None = None
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to_ref: dict | None = None
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def to_dict(self, include_geometry: bool) -> dict:
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p = self.payload or {}
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out = {
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"id": self.id,
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"line_class": self.line_class,
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"class_source": self.class_source,
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"line_number": self.line_number,
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"number_source": self.number_source,
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"size": p.get("size"),
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"service": p.get("service"),
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"spec": p.get("spec"),
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"insulation": p.get("insulation"),
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"from": self.from_ref,
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"to": self.to_ref,
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"length": round(
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sum(
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math.dist(a, b) for a, b in zip(self.vertices, self.vertices[1:], strict=False)
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),
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6,
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),
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"layer": self.layer,
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"space": self.space,
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"source": self.source,
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}
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if include_geometry:
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out["vertices"] = [[x, y] for x, y in self.vertices]
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return out
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class _Grid:
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"""Uniform grid for nearest-within-tolerance queries."""
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def __init__(self, cell: float):
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self.cell = cell
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self.cells: dict[tuple[int, int], list] = {}
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def _key(self, x: float, y: float) -> tuple[int, int]:
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return (int(math.floor(x / self.cell)), int(math.floor(y / self.cell)))
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def add(self, x: float, y: float, item) -> None:
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self.cells.setdefault(self._key(x, y), []).append((x, y, item))
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def near(self, x: float, y: float, radius: float):
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kx, ky = self._key(x, y)
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reach = int(math.ceil(radius / self.cell))
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for dx in range(-reach, reach + 1):
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for dy in range(-reach, reach + 1):
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for px, py, item in self.cells.get((kx + dx, ky + dy), []):
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d = math.hypot(px - x, py - y)
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if d <= radius:
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yield d, item
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def _vertices(info: EntityInfo) -> list[tuple[float, float]]:
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if info.type in LINE_TYPES:
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s, e = info.properties["start"], info.properties["end"]
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return [(float(s[0]), float(s[1])), (float(e[0]), float(e[1]))]
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return [(float(p[0]), float(p[1])) for p in info.properties.get("points") or []]
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def _point_segment_distance(p, a, b) -> float:
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ax, ay = a
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bx, by = b
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px, py = p
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dx, dy = bx - ax, by - ay
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if dx == 0 and dy == 0:
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return math.hypot(px - ax, py - ay)
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t = max(0.0, min(1.0, ((px - ax) * dx + (py - ay) * dy) / (dx * dx + dy * dy)))
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return math.hypot(px - (ax + t * dx), py - (ay + t * dy))
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def _keyword_kind(block_name: str) -> str | None:
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"""Kind implied by a foreign block's name, or None when no token is a keyword."""
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for token in _TOKEN_RE.findall(block_name.upper()):
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kind = KEYWORDS.get(token)
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if kind:
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return kind
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return None
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def _bbox(info: EntityInfo):
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bb = info.properties.get("bounding_box")
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if not bb:
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return None
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return (float(bb["min"][0]), float(bb["min"][1]), float(bb["max"][0]), float(bb["max"][1]))
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def _on_bbox_boundary(p, bbox, tolerance) -> bool:
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x, y = p
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xmin, ymin, xmax, ymax = bbox
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inside_x = xmin - tolerance <= x <= xmax + tolerance
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inside_y = ymin - tolerance <= y <= ymax + tolerance
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near_vertical = min(abs(x - xmin), abs(x - xmax)) <= tolerance and inside_y
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near_horizontal = min(abs(y - ymin), abs(y - ymax)) <= tolerance and inside_x
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return near_vertical or near_horizontal
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async def _collect(backend: AutoCADBackend, scope: str) -> list[tuple[EntityInfo, str]]:
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async def page_all(space: str):
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out = []
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offset = 0
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while True:
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page = await backend.entity_list(limit=_PAGE, offset=offset)
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out.extend((info, space) for info in page)
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if len(page) < _PAGE:
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return out
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offset += _PAGE
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layouts = await backend.layout_list()
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current = layouts.get("current") or "Model"
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if scope != "all":
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return await page_all(current)
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entities = []
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try:
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for name in layouts.get("layouts", [current]):
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await backend.layout_set_current(name)
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entities.extend(await page_all(name))
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finally:
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await backend.layout_set_current(current)
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return entities
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async def build_graph(
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backend: AutoCADBackend,
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tolerance: float = 0.5,
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label_search: float = 15.0,
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scope: str = "current_space",
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include_foreign: bool = True,
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include_geometry: bool = False,
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) -> dict:
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if tolerance <= 0:
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raise ValueError("tolerance must be > 0")
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if scope not in ("current_space", "all"):
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raise ValueError("scope must be 'current_space' or 'all'")
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entities = await _collect(backend, scope)
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layer_linetypes = {lyr.name.upper(): lyr.linetype.upper() for lyr in await backend.layer_list()}
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# 1 — classify INSERTs
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nodes: dict[str, _Node] = {}
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candidates: dict[str, _Node] = {} # unknown blocks kept only if a line touches them
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for info, space in entities:
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if info.type not in INSERT_TYPES:
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continue
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name = str(info.properties.get("block_name", ""))
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if name.startswith("PID_MARKER_"):
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continue
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payload = await read_payload(backend, info.handle)
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try:
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attributes = await backend.block_get_attributes(info.handle)
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except Exception:
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attributes = {}
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ins = info.properties.get("insertion", [0.0, 0.0])
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rotation = float(info.properties.get("rotation_deg", 0.0))
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scale = float(info.properties.get("x_scale", 1.0))
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y_scale = float(info.properties.get("y_scale", scale))
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base = dict(
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id=info.handle,
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block_name=name,
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x=float(ins[0]),
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y=float(ins[1]),
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rotation_deg=rotation,
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scale=scale,
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layer=info.layer,
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space=space,
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bbox=_bbox(info),
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attributes=attributes,
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)
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if payload and payload.get("kind") == "symbol":
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source = "catalog" if name.startswith("PID_") else "xdata"
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family = payload.get("family")
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node = _Node(
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kind=FAMILY_KIND.get(family, "equipment"),
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family=family,
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symbol=payload.get("symbol"),
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source=source,
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confidence=CONFIDENCE[source],
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**base,
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)
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for pname, (lx, ly, ldir, kind, radius) in payload.get("ports", {}).items():
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# Measured from the INSERT as it is: a mirrored symbol carries
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# y_scale = -1 and its ports sit on the mirrored geometry.
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local = Port(pname, float(lx), float(ly), ldir, kind, float(radius))
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try:
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port = transform_port(local, node.x, node.y, rotation, scale, y_scale)
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except ValueError:
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# A stretched INSERT (someone scaled one axis by hand): the
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# reader never refuses a drawing, so it measures along the
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# X factor and says so instead of raising.
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port = transform_port(local, node.x, node.y, rotation, scale)
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port["inferred"] = True
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node.ports[pname] = {**port, "edges": []}
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nodes[node.id] = node
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continue
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if not include_foreign:
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continue
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keyword_kind = _keyword_kind(name)
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tag_key = next((k for k in ATTRIBUTE_TAGS if k in attributes), None)
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if keyword_kind or tag_key:
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node = _Node(
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kind=keyword_kind or "equipment",
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family=None,
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symbol=None,
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source="heuristic",
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confidence=CONFIDENCE["heuristic"],
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**base,
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)
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nodes[node.id] = node
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elif base["bbox"] is not None:
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candidates[info.handle] = _Node(
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kind="unknown_block",
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family=None,
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symbol=None,
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source="inferred",
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confidence=CONFIDENCE["inferred"],
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**base,
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)
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# 2 — candidate edges
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edges: dict[str, _Edge] = {}
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foreign_edges: dict[str, _Edge] = {}
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for info, space in entities:
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if info.type not in POLY_TYPES | LINE_TYPES:
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continue
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verts = _vertices(info)
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if len(verts) < 2:
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continue
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payload = await read_payload(backend, info.handle) if info.type in POLY_TYPES else None
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layer = info.layer.upper()
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edge = _Edge(
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id=info.handle,
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vertices=verts,
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layer=info.layer,
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linetype=info.linetype,
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space=space,
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payload=payload if payload and payload.get("kind") == "line" else None,
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source="touch",
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)
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if edge.payload:
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edge.source = "xdata"
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edge.line_class, edge.class_source = edge.payload.get("class"), "xdata"
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edge.line_number = edge.payload.get("number")
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edge.number_source = "xdata" if edge.line_number else None
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edges[edge.id] = edge
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elif layer in PID_LINE_LAYERS:
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edge.source = "layer"
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cls = LAYER_TO_CLASS[layer]
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if cls is None:
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own = (info.linetype or "").upper()
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effective = own if own and own != "BYLAYER" else layer_linetypes.get(layer, "")
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cls = "electric" if "DASH" in effective else "signal_unknown"
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edge.line_class, edge.class_source = cls, "layer"
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edges[edge.id] = edge
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elif include_foreign:
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foreign_edges[edge.id] = edge
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# 3 — spatial index of ports and vertices
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grid = _Grid(cell=10.0 * tolerance)
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radial_ports: list[tuple[str, str, float, float, float]] = []
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for node in nodes.values():
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for pname, port in node.ports.items():
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if port.get("radius", 0.0) > 0:
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# a bubble's line starts on its circle, not at its centre
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radial_ports.append((node.id, pname, port["x"], port["y"], port["radius"]))
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else:
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grid.add(port["x"], port["y"], ("port", node.id, pname))
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all_edges = {**edges, **foreign_edges}
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for edge in all_edges.values():
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for v in edge.vertices:
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grid.add(v[0], v[1], ("vertex", edge.id))
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# 4 — resolve endpoints
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junctions: list[dict] = []
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dangling: list[dict] = []
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def _junction_at(x, y, edge_id, other_id) -> dict:
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for j in junctions:
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if math.hypot(j["x"] - x, j["y"] - y) <= tolerance:
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for e in (edge_id, other_id):
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if e not in j["edges"]:
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j["edges"].append(e)
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return {"junction": j["id"]}
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j = {"id": f"J{len(junctions) + 1}", "x": x, "y": y, "edges": [edge_id, other_id]}
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junctions.append(j)
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return {"junction": j["id"]}
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def _resolve(edge: _Edge, end: str) -> dict | None:
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x, y = edge.vertices[0] if end == "from" else edge.vertices[-1]
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for node_id, pname, cx, cy, r in radial_ports:
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if abs(math.hypot(x - cx, y - cy) - r) <= tolerance:
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nodes[node_id].ports[pname]["edges"].append(edge.id)
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return {"node": node_id, "port": pname}
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best = None
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for d, item in grid.near(x, y, tolerance):
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if item[0] == "port" and (best is None or d < best[0]):
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best = (d, item)
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if best:
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_, (_kind, node_id, pname) = best
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nodes[node_id].ports[pname]["edges"].append(edge.id)
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return {"node": node_id, "port": pname}
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for node in list(nodes.values()) + list(candidates.values()):
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if (
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node.source in ("heuristic", "inferred")
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and node.bbox
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and _on_bbox_boundary((x, y), node.bbox, tolerance)
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):
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if node.id in candidates:
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nodes[node.id] = candidates.pop(node.id)
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pname = f"p{len(node.ports) + 1}"
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node.ports[pname] = {
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"name": pname,
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"x": x,
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"y": y,
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"direction_deg": None,
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"kind": "process",
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"radius": 0.0,
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"inferred": True,
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"edges": [edge.id],
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}
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grid.add(x, y, ("port", node.id, pname))
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return {"node": node.id, "port": pname}
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for _d, item in grid.near(x, y, tolerance):
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if item[0] == "vertex" and item[1] != edge.id:
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return _junction_at(x, y, edge.id, item[1])
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for other in all_edges.values():
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if other.id == edge.id:
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continue
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for a, b in zip(other.vertices, other.vertices[1:], strict=False):
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if _point_segment_distance((x, y), a, b) <= tolerance:
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return _junction_at(x, y, edge.id, other.id)
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nearest = None
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for d, item in grid.near(x, y, 10.0 * tolerance):
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if item[0] == "port" and (nearest is None or d < nearest[0]):
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nearest = (d, item)
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dangling.append(
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{
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"edge": edge.id,
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"end": end,
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"x": x,
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"y": y,
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"nearest": (
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{"node": nearest[1][1], "port": nearest[1][2], "distance": round(nearest[0], 6)}
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if nearest
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else None
|
|
),
|
|
}
|
|
)
|
|
return None
|
|
|
|
for edge in list(edges.values()):
|
|
edge.from_ref = _resolve(edge, "from")
|
|
edge.to_ref = _resolve(edge, "to")
|
|
for edge in list(foreign_edges.values()):
|
|
# a foreign line joins the graph only through a node
|
|
probe_from = _resolve(edge, "from")
|
|
probe_to = _resolve(edge, "to")
|
|
attached = any(ref and "node" in ref for ref in (probe_from, probe_to))
|
|
if attached:
|
|
edge.from_ref, edge.to_ref = probe_from, probe_to
|
|
edges[edge.id] = edge
|
|
else:
|
|
dangling[:] = [d for d in dangling if d["edge"] != edge.id]
|
|
for j in junctions:
|
|
if edge.id in j["edges"]:
|
|
j["edges"].remove(edge.id)
|
|
junctions[:] = [j for j in junctions if len(j["edges"]) >= 2]
|
|
|
|
# 5 — tags and line numbers from attributes or nearby text
|
|
texts = [(info, space) for info, space in entities if info.type in TEXT_TYPES]
|
|
|
|
def _text_near(x, y, radius, pattern=None):
|
|
best = None
|
|
for info, _space in texts:
|
|
ins = info.properties.get("insertion")
|
|
content = str(info.properties.get("text", "")).strip()
|
|
if not ins or not content or (pattern and not pattern.match(content)):
|
|
continue
|
|
d = math.hypot(float(ins[0]) - x, float(ins[1]) - y)
|
|
if d <= radius and (best is None or d < best[0]):
|
|
best = (d, content)
|
|
return best[1] if best else None
|
|
|
|
for node in nodes.values():
|
|
attrs = node.attributes
|
|
if node.kind == "instrument" and attrs.get("FUNC"):
|
|
node.tag = f"{attrs['FUNC']}-{attrs.get('LOOP', '')}".rstrip("-")
|
|
node.tag_source = "attribute"
|
|
else:
|
|
key = next((k for k in ATTRIBUTE_TAGS if attrs.get(k)), None)
|
|
if key:
|
|
node.tag, node.tag_source = str(attrs[key]).strip(), "attribute"
|
|
if node.tag is None:
|
|
radius = max((p.get("radius", 0.0) for p in node.ports.values()), default=0.0)
|
|
if node.kind == "instrument" and radius:
|
|
found = _text_near(node.x, node.y, radius)
|
|
else:
|
|
cx = ((node.bbox[0] + node.bbox[2]) / 2.0) if node.bbox else node.x
|
|
top = node.bbox[3] if node.bbox else node.y
|
|
found = _text_near(cx, top, label_search)
|
|
if found:
|
|
node.tag, node.tag_source = found, "text"
|
|
for edge in edges.values():
|
|
if edge.line_number:
|
|
continue
|
|
a, b = max(zip(edge.vertices, edge.vertices[1:], strict=False), key=lambda s: math.dist(*s))
|
|
found = _text_near((a[0] + b[0]) / 2.0, (a[1] + b[1]) / 2.0, label_search, LINE_NUMBER_RE)
|
|
if found:
|
|
edge.line_number, edge.number_source = found, "label"
|
|
|
|
# 6 — off-page links
|
|
links: dict[str, list[str]] = {}
|
|
for node in nodes.values():
|
|
link = node.attributes.get("LINK")
|
|
if node.kind == "connector" and link:
|
|
links.setdefault(str(link), []).append(node.id)
|
|
offpage_links = [{"link": k, "nodes": sorted(v)} for k, v in sorted(links.items())]
|
|
|
|
# 7 — assemble
|
|
node_rows = [n.to_dict() for n in nodes.values()]
|
|
edge_rows = [e.to_dict(include_geometry) for e in edges.values()]
|
|
by_kind: dict[str, int] = {}
|
|
for n in node_rows:
|
|
by_kind[n["kind"]] = by_kind.get(n["kind"], 0) + 1
|
|
by_class: dict[str, int] = {}
|
|
for e in edge_rows:
|
|
key = e["line_class"] or "unknown"
|
|
by_class[key] = by_class.get(key, 0) + 1
|
|
return {
|
|
"nodes": node_rows,
|
|
"edges": edge_rows,
|
|
"junctions": junctions,
|
|
"dangling": dangling,
|
|
"unclassified": [{"handle": c.id, "block_name": c.block_name} for c in candidates.values()],
|
|
"offpage_links": offpage_links,
|
|
"stats": {
|
|
"nodes_by_kind": dict(sorted(by_kind.items())),
|
|
"edges_by_class": dict(sorted(by_class.items())),
|
|
"dangling": len(dangling),
|
|
"unclassified": len(candidates),
|
|
"confidence_min": min((n["confidence"] for n in node_rows), default=1.0),
|
|
"entities_scanned": len(entities),
|
|
},
|
|
"tolerance": tolerance,
|
|
"scope": scope,
|
|
"backend": backend.name,
|
|
}
|