assembly-economics/simulations/gadm02/band_probe.py

"""Probe scenarios across the adoption band B1-B4 (ASSEMBLY-WP-0009-T02).

For every scenario and band anchor, compute key readings and classify each as
robust, quantitative shift or qualitative break (research/ScenarioBandMethod.md
§ 5).

Usage: python3 -B simulations/gadm02/band_probe.py
"""

from __future__ import annotations

import itertools
import sys
from pathlib import Path

sys.dont_write_bytecode = True

import gadm03 as g3  # noqa: E402
import gadm04 as g  # noqa: E402
import grounding as gr  # noqa: E402
from scenarios import load_all  # noqa: E402

OUT = Path(__file__).resolve().parent / "results"
ANCHORS = list(gr.BAND)  # B1..B4
FLOORS = {"G": (">=", 0.2), "E": (">=", 0.2), "P": ("<=", 0.7), "A": (">=", 0.2)}
GRID = {"lineage": ({"L": 0.1, "lin_open": 0.1}, {"L": 0.8, "lin_open": 0.8}),
        "membrane": ({"m": 0.2}, {"m": 0.8}),
        "attention": ({"x_att": 0.9}, {"x_att": 0.2})}


def classify(values: list, kind: str) -> str:
    """kind: 'sign' (numbers), 'label' (categorical), 'bool'."""
    if kind == "label" or kind == "bool":
        return "robust" if len(set(values)) == 1 else "QUALITATIVE BREAK"
    signs = {(v > 0) - (v < 0) for v in values}
    if len(signs) > 1:
        return "QUALITATIVE BREAK"
    lo, hi = min(abs(v) for v in values), max(abs(v) for v in values)
    return "quantitative shift" if lo > 0 and hi / lo > 1.5 else "robust"


def shape(traj: list[float]) -> str:
    peak = max(traj)
    if traj[-1] >= 0.9 * peak:
        return "saturating"
    return "peak-and-decline"


def main() -> None:
    OUT.mkdir(exist_ok=True)
    scs = load_all()
    names = list(scs)
    var = {a: gr.variant(gr.BAND[a]) for a in ANCHORS}
    runs = {a: {n: g.simulate({**scs[n]["params"], **var[a][0]}, {**scs[n]["init"], **var[a][1]})
                for n in names} for a in ANCHORS}
    fin = {a: {n: runs[a][n][-1] for n in names} for a in ANCHORS}

    lines = [f"# {g.MODEL_VERSION}: scenarios across the adoption band", "",
             "Generated by `simulations/gadm02/band_probe.py`. Anchors B1–B4 from",
             "`grounding.py` (`research/ScenarioBandMethod.md` § 2). t = 100 years unless noted.", "",
             "## K_Ω path per anchor (baseline)", "", "| Anchor | t 5 | t 10 | t 25 | t 50 | t 100 | shape |",
             "|---|---|---|---|---|---|---|"]
    shapes = []
    for a in ANCHORS:
        tr = [r["Ko"] for r in runs[a]["baseline"]]
        shapes.append(shape(tr))
        lines.append(f"| {a} ({gr.BAND[a]}) | " + " | ".join(f"{tr[t]:.2f}" for t in (5, 10, 25, 50, 100))
                     + f" | {shapes[-1]} |")

    lines += ["", "## Scenario VFAC / P per anchor", "",
              "| Scenario | " + " | ".join(ANCHORS) + " |", "|---|" + "---|" * len(ANCHORS)]
    for n in names:
        lines.append(f"| {scs[n]['title']} | " + " | ".join(
            f"{fin[a][n]['VFAC']:.3f} / {fin[a][n]['P']:.2f}" for a in ANCHORS) + " |")

    readings = []

    def add(name, values, kind, fmt=lambda v: f"{v:+.3f}" if isinstance(v, float) else str(v)):
        readings.append((name, [fmt(v) for v in values], classify(values, kind)))

    order = {a: sorted(names, key=lambda n: -fin[a][n]["VFAC"]) for a in ANCHORS}
    add("best scenario", [scs[order[a][0]]["title"] for a in ANCHORS], "label")
    add("worst scenario", [scs[order[a][-1]]["title"] for a in ANCHORS], "label")
    add("lowest domination", [scs[min(names, key=lambda n: fin[a][n]["P"])]["title"] for a in ANCHORS], "label")
    for n in names:
        if n != "baseline":
            add(f"VFAC {scs[n]['title']} − baseline",
                [fin[a][n]["VFAC"] - fin[a]["baseline"]["VFAC"] for a in ANCHORS], "sign")
    for n in names:
        dom = []
        for a in ANCHORS:
            ch = max(g3.CHANNELS, key=lambda k: fin[a][n][k])
            dom.append(g3.CHANNEL_NAMES[ch])
        add(f"dominant domination channel: {scs[n]['title']}", dom, "label")
    for n in names:
        viol = []
        for a in ANCHORS:
            v = [k for k, (op, lim) in FLOORS.items()
                 if (fin[a][n][k] < lim if op == ">=" else fin[a][n][k] > lim)]
            viol.append(",".join(v) or "none")
        add(f"floor violations at t 100: {scs[n]['title']}", viol, "label")
    eff = {a: [] for a in ANCHORS}
    for a in ANCHORS:
        out = {}
        for lv in itertools.product((0, 1), repeat=3):
            ex = {}
            for ax, l in zip(GRID, lv):
                ex.update(GRID[ax][l])
            out[lv] = g.simulate({**scs["baseline"]["params"], **var[a][0], **ex},
                                 {**scs["baseline"]["init"], **var[a][1]})[-1]["VFAC"]
        eff[a] = [sum((1 if lv[i] else -1) * v for lv, v in out.items()) / 4 for i in range(3)]
    for i, ax in enumerate(GRID):
        add(f"organism lever effect: {ax}", [eff[a][i] for a in ANCHORS], "sign")
    add("lever order lineage > membrane > attention",
        [eff[a][0] > eff[a][1] > eff[a][2] > 0 for a in ANCHORS], "bool")
    mem = scs["generative_concentrated_lineages"]
    p3 = []
    for a in ANCHORS:
        lo = g.simulate({**mem["params"], **var[a][0], "wtax": 0.0}, {**mem["init"], **var[a][1]})[-1]["P"]
        hi = g.simulate({**mem["params"], **var[a][0], "wtax": 1.0}, {**mem["init"], **var[a][1]})[-1]["P"]
        p3.append(hi - lo)
    add("P3: wealth tax ΔP (membrane-dominated)", p3, "sign")
    add("P3 holds (|ΔP| < 0.06)", [abs(x) < 0.06 for x in p3], "bool")
    add("K_Ω trajectory shape (baseline)", shapes, "label")

    lines += ["", "## Readings and robustness class", "",
              "| Reading | " + " | ".join(ANCHORS) + " | class |", "|---|" + "---|" * (len(ANCHORS) + 1)]
    for name, vals, cls in readings:
        lines.append(f"| {name} | " + " | ".join(vals) + f" | {cls} |")
    n_break = sum(1 for _n, _v, c in readings if c == "QUALITATIVE BREAK")
    n_shift = sum(1 for _n, _v, c in readings if c == "quantitative shift")
    lines += ["", f"{len(readings)} readings: {len(readings) - n_break - n_shift} robust, "
              f"{n_shift} quantitative shifts, {n_break} qualitative breaks.", ""]
    (OUT / "band_probe.md").write_text("\n".join(lines))
    print("\n".join(lines))


if __name__ == "__main__":
    main()