126 lines
4.4 KiB
Python
126 lines
4.4 KiB
Python
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#!/usr/bin/env python3
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"""Dissect the edge-too-long fails in the harbor probe best (§13.7 follow-up).
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Tests three hypotheses for why edge-too-long is now harbor's top fail class:
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(1) COMBINED leaf — a shared leaf (share>1) holds k rooms, so it is ~k× a
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room's area and its walls run long; would vanish if actually subdivided.
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(2) CORRIDOR — a circulation leaf, long+thin; long edge inevitable.
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(3) NARROW ROOM — a non-shared room at/near target AREA but high aspect
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(one wall >8m because the room is too narrow); a real layout problem.
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(4) OVERSIZE ROOM — a non-shared room well above target area.
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For each flagged leaf prints: type, circ?, share k, area vs (k×)target,
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narrowest width, the long edge length(s), aspect, and a verdict tag.
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"""
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from __future__ import annotations
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import copy, sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "src"))
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from homemaker_layout import dom, fitness, geometry # noqa: E402
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from homemaker_layout import graph as graph_mod # noqa: E402
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from homemaker_layout import dom as dom_mod # noqa: E402
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REPO = Path(__file__).resolve().parents[1]
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HARBOR = REPO / "examples" / "harbor-house"
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BEST = REPO / "scratch" / "harbor_floor_probe" / "harbor_fullstack_s0.dom"
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# same relaxed-config injection the probe used, so fails match
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_orig = fitness.load_config
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def _load(d):
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c, k = _orig(d); c = dict(c); c["leaf_sharing"] = True; c["max_share"] = 3
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return c, k
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fitness.load_config = _load
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conf, cost = fitness.load_config(HARBOR)
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fit = fitness.Fitness(conf, cost)
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root = dom.load(str(BEST))
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score, fails = fit.score_with_fails(copy.deepcopy(root))
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edge_fails = [f for f in fails if "edge too long" in f]
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print(f"{BEST.name}: {len(fails)} fails, {len(edge_fails)} edge-too-long\n")
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for f in edge_fails:
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print(" ", f)
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print()
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# rebuild merged tree + base graphs exactly as _evaluate_full does
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work = copy.deepcopy(root)
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fit2 = fitness.Fitness(conf, cost)
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fit2.preprocess_building(work)
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geometry.clear_cache(); dom_mod.merge_divided(work); geometry.clear_cache()
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door_w = fit2.conf("door_width") or 1.2
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graph_base = graph_mod.build_graphs(work, door_w)
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lvls = dom_mod.levels(work)
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by_id = {} # 'level/id' -> (leaf, level)
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for li, lvl in enumerate(lvls):
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for leaf in lvl.leaves():
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by_id[f"{li}/{leaf.id}"] = (leaf, li)
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def edges(leaf):
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return [geometry.edge_length(leaf, e) for e in range(4)]
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def t0(leaf):
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return (leaf.type or "?")[0].lower()
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def target_area(leaf):
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try:
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p = fit2.get_space_params(leaf.type, "size")
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return p[0]
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except Exception:
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return None
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def describe(leaf, li):
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ty = leaf.type or "?"
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circ = dom_mod.is_circulation(leaf)
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out = dom_mod.is_outside(leaf)
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share = graph_mod.leaf_share(leaf, 3)
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area = geometry.area(leaf)
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narrow = geometry.length_narrowest(leaf)
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es = edges(leaf)
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longest = max(es)
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aspect = longest / narrow if narrow else float("inf")
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tgt = target_area(leaf)
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ke = share if share > 1 else 1
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tgt_eff = (tgt * ke) if tgt else None
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# classify
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if share > 1:
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tag = f"COMBINED (share={share})"
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elif circ:
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tag = "CORRIDOR (circulation)"
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elif tgt and area >= 0.85 * tgt and aspect > 1.8:
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tag = "NARROW ROOM (area ok, aspect bad)"
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elif tgt and area > 1.3 * tgt:
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tag = "OVERSIZE ROOM"
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else:
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tag = "other"
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ts = f"{tgt:.0f}" if tgt else "n/a"
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tes = f"{tgt_eff:.0f}" if tgt_eff else "n/a"
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print(f" {li}/{leaf.id:10s} type={ty:5s} circ={int(circ)} out={int(out)} "
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f"share={share} area={area:5.1f} (tgt {ts}, k*tgt {tes})")
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print(f" narrowest={narrow:4.1f} edges={[round(x,1) for x in es]} "
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f"longest={longest:4.1f} aspect={aspect:4.1f} -> {tag}")
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return tag
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tags = []
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seen = set()
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for f in edge_fails:
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outside = "outside edge too long" in f
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parts = f.split()
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key = parts[0] # 'level/id'
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if outside:
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ent = by_id.get(key)
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if ent:
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tags.append(describe(*ent))
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else:
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# '{level}/{a.id} {b.id} edge too long' — both leaves border the long wall
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li_a = key
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b_id = parts[1]
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li = li_a.split("/")[0]
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for k in (li_a, f"{li}/{b_id}"):
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if k in by_id and k not in seen:
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seen.add(k)
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tags.append(describe(*by_id[k]))
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print("\n=== classification tally ===")
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from collections import Counter
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for tag, n in Counter(tags).most_common():
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print(f" {n:2d} {tag}")
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