code/_compute_within_arch_perm.py

"""Within-architecture permutation tests on the 24-config sweep — top-3 vs bot-3
PosDis within discrete-only and within continuous-only subsets.

Addresses R2's flag that the pooled top-5 vs bot-5 comparison is partially confounded
with discrete-vs-continuous (top-5 are all discrete; continuous tops at PosDis 0.40).
"""
import numpy as np

# 24 configs from Table 6 (paper.tex)
# (name, kind, posdis, cross192)
configs = [
    ("disc_L2_V5",   "disc", 0.20, 43.9),
    ("disc_L2_V10",  "disc", 0.25, 41.7),
    ("disc_L3_V5",   "disc", 0.13, 42.8),
    ("disc_L3_V10",  "disc", 0.12, 45.6),
    ("disc_L4_V5",   "disc", 0.10, 42.2),
    ("disc_L4_V10",  "disc", 0.08, 45.0),
    ("disc_L5_V5",   "disc", 0.07, 43.9),
    ("cont_dim2",    "cont", 0.15, 54.4),
    ("cont_dim3",    "cont", 0.15, 41.1),
    ("cont_dim5",    "cont", 0.06, 43.9),
    ("cont_dim10",   "cont", 0.04, 48.3),
    ("cont_dim20",   "cont", 0.02, 55.0),
    ("disc_multi_L3_V5",        "disc", 0.51, 46.1),
    ("disc_multi_L4_V10",       "disc", 0.48, 50.6),
    ("cont_multi_dim3",         "cont", 0.40, 55.0),
    ("disc_multi5_L2_V5",       "disc", 0.82, 52.2),
    ("disc_multi5_L3_V5",       "disc", 0.83, 46.1),
    ("disc_multi5_L4_V5",       "disc", 0.70, 47.8),
    ("disc_multi5_L2_V10_e250", "disc", 0.70, 55.6),
    ("disc_multi5_L3_V10_e250", "disc", 0.81, 43.3),
    ("disc_multi5_L4_V10_e250", "disc", 0.70, 41.7),
    ("disc_multi5_L2_V5_e200",  "disc", 0.83, 51.1),
    ("disc_multi5_L4_V5_e250",  "disc", 0.91, 46.7),
    ("disc_multi_L5_V5_3cls",   "disc", 0.73, 42.2),
]

posdis = np.array([c[2] for c in configs])
cross  = np.array([c[3] for c in configs])
kind   = np.array([c[1] for c in configs])

n_perm = 100_000

def run_perm(label, mask, k):
    p = posdis[mask]; c = cross[mask]
    n = len(p)
    if n < 2 * k:
        print(f"  {label}: n={n} too small for top-{k}/bot-{k}")
        return
    order = np.argsort(p)
    top_idx = order[-k:]
    bot_idx = order[:k]
    obs_diff = c[top_idx].mean() - c[bot_idx].mean()
    obs_abs = abs(obs_diff)
    rng = np.random.default_rng(42)
    null_abs = []
    for _ in range(n_perm):
        cp = rng.permutation(c)
        null_abs.append(abs(cp[top_idx].mean() - cp[bot_idx].mean()))
    null_abs = np.array(null_abs)
    p_two = float(np.mean(null_abs >= obs_abs))
    print(f"  {label} (n={n}, k={k}): obs |top-{k} - bot-{k}| = {obs_abs:.2f}pp, two-sided p = {p_two:.3f}")
    print(f"    top-{k} PosDis range: {p[top_idx].min():.2f}-{p[top_idx].max():.2f}, cross: {sorted(c[top_idx].tolist())}")
    print(f"    bot-{k} PosDis range: {p[bot_idx].min():.2f}-{p[bot_idx].max():.2f}, cross: {sorted(c[bot_idx].tolist())}")

print("=" * 60)
print("Within-architecture permutation tests (n_perm=10^5)")
print("=" * 60)

print("\n--- All 24 configs (pooled, for reference) ---")
for k in [3, 5]:
    run_perm(f"All", np.ones(24, dtype=bool), k)

print("\n--- Discrete-only (n=19) ---")
disc_mask = (kind == "disc")
print(f"  Total disc configs: {disc_mask.sum()}, PosDis range: {posdis[disc_mask].min():.2f}-{posdis[disc_mask].max():.2f}")
for k in [3, 4, 5]:
    run_perm(f"Disc top-{k}/bot-{k}", disc_mask, k)

print("\n--- Continuous-only (n=6) ---")
cont_mask = (kind == "cont")
print(f"  Total cont configs: {cont_mask.sum()}, PosDis range: {posdis[cont_mask].min():.2f}-{posdis[cont_mask].max():.2f}")
for k in [2, 3]:
    run_perm(f"Cont top-{k}/bot-{k}", cont_mask, k)