84 lines
3 KiB
Python
84 lines
3 KiB
Python
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#!/usr/bin/env python3
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"""Raw-seed fail breakdown: proportion-aware split sizing A/B (homemaker-py-leu.2).
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Builds the *constructive* seed (operators.constructive_topology, single-stage,
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adjacency-aware) with proportion-aware split sizing OFF then ON, scores each raw
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seed with native fitness BEFORE the inner loop, and tallies fails by family. The
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claim under test (DESIGN.md §12.2): sizing cuts from target areas drops the
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geometry family (size/width/proportion/crinkliness) at the raw seed without
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regressing the adjacency/access family that §11.6/§11.7 fixed.
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Usage:
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URB_NO_OCCLUSION=1 python3 experiments/measure_seed_geometry.py <programme_dir> [n_seeds]
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"""
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from __future__ import annotations
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import copy
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import sys
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from pathlib import Path
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import numpy as np
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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, operators, programme # noqa: E402
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GEOM = ("perpendicular", "proportion", "size", "width", "crinkliness")
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def _categorise(fails: tuple[str, ...]) -> dict[str, int]:
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cats = {"geometry": 0, "access_adj": 0, "missing": 0, "other": 0}
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for f in fails:
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if f.endswith(GEOM) or "edge too long" in f:
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cats["geometry"] += 1
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elif "access" in f or "inaccessible" in f or "adjacent" in f or "adjacency" in f:
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cats["access_adj"] += 1
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elif "missing" in f:
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cats["missing"] += 1
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else:
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cats["other"] += 1
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return cats
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def main() -> int:
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programme_dir = Path(sys.argv[1])
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n_seeds = int(sys.argv[2]) if len(sys.argv) > 2 else 10
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reqs = programme.load_programme_dir(programme_dir)
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types = sorted(reqs) + ["C", "O"]
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conf, cost = fitness.load_config(programme_dir)
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fit = fitness.Fitness(conf, cost)
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seed_file = programme_dir / "init.dom"
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seed_root = dom.load(str(seed_file))
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print(f"programme : {programme_dir.name} ({len(reqs)} codes)")
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print(f"seeds : {n_seeds} (single-stage constructive, adjacency-aware)\n")
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agg = {0: {"total": 0, "geometry": 0, "access_adj": 0, "missing": 0, "other": 0},
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1: {"total": 0, "geometry": 0, "access_adj": 0, "missing": 0, "other": 0}}
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for s in range(n_seeds):
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for prop in (False, True):
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rng = np.random.default_rng(s)
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topo = operators.constructive_topology(
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seed_root, reqs, rng, types,
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adjacency_aware=True, proportion_aware=prop)
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_score, fails = fit.score_with_fails(copy.deepcopy(topo))
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cats = _categorise(fails)
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agg[int(prop)]["total"] += len(fails)
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for k, v in cats.items():
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agg[int(prop)][k] += v
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def _avg(d, k):
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return d[k] / n_seeds
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print(f"{'family':<12} {'PROP=0 (before)':>16} {'PROP=1 (after)':>16}")
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for k in ("geometry", "access_adj", "missing", "other", "total"):
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print(f"{k:<12} {_avg(agg[0], k):>16.1f} {_avg(agg[1], k):>16.1f}")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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