#!/usr/bin/env python3
"""
Script 39c: Mid/Small-Firm Signature-Level Dip Test
====================================================
Companion to Script 39b. 39b showed every Big-4 firm rejects
unimodality on the dHash signature marginal (p < 5e-4 in each
of A/B/C/D) while every Big-4 firm fails to reject unimodality
on the cosine marginal. This script asks the same questions of
the mid/small-firm population (non-Big-4):

  1. Does the pooled mid/small-firm signature cloud show the same
     dHash multimodality?
  2. Within individual mid/small firms (those with enough
     signatures to support the test), does the dHash multimodality
     hold firm-internally as it does in Big-4?

If yes, the dHash signature-level multimodality is corpus-universal
and the Big-4 scope restriction of v4.0 is not necessary on dHash
grounds (cf §III-G item 2 which currently rests on Big-4-level
multimodality). The cosine axis is reported alongside for
completeness, but no v4.0 claim turns on cosine multimodality
outside Big-4.

Outputs:
  reports/v4_big4/midsmall_signature_diptest/
    midsmall_diptest_results.json
    midsmall_diptest_report.md
"""

import json
import sqlite3
import numpy as np
import diptest
from pathlib import Path
from datetime import datetime
from scipy import stats
from scipy.signal import find_peaks

DB = '/Volumes/NV2/PDF-Processing/signature-analysis/signature_analysis.db'
OUT = Path('/Volumes/NV2/PDF-Processing/signature-analysis/reports/'
           'v4_big4/midsmall_signature_diptest')
OUT.mkdir(parents=True, exist_ok=True)

BIG4 = ('勤業眾信聯合', '安侯建業聯合', '資誠聯合', '安永聯合')
N_BOOT = 2000
SINGLE_FIRM_MIN_SIG = 500  # minimum signature count to run a per-firm dip test


def load_non_big4_signatures():
    conn = sqlite3.connect(DB)
    cur = conn.cursor()
    cur.execute('''
        SELECT a.firm,
               s.max_similarity_to_same_accountant,
               CAST(s.min_dhash_independent AS REAL)
        FROM signatures s
        JOIN accountants a ON s.assigned_accountant = a.name
        WHERE s.assigned_accountant IS NOT NULL
          AND s.max_similarity_to_same_accountant IS NOT NULL
          AND s.min_dhash_independent IS NOT NULL
          AND a.firm IS NOT NULL
          AND a.firm NOT IN (?, ?, ?, ?)
    ''', BIG4)
    rows = cur.fetchall()
    conn.close()
    return rows


def kde_dip(values, n_boot=N_BOOT):
    arr = np.asarray(values, dtype=float)
    arr = arr[np.isfinite(arr)]
    if len(arr) < 10:
        return {'n': int(len(arr)), 'skipped': 'too few points'}
    dip, pval = diptest.diptest(arr, boot_pval=True, n_boot=n_boot)
    kde = stats.gaussian_kde(arr, bw_method='silverman')
    xs = np.linspace(arr.min(), arr.max(), 2000)
    density = kde(xs)
    peaks, _ = find_peaks(density, prominence=density.max() * 0.02)
    antimodes = []
    for i in range(len(peaks) - 1):
        seg = density[peaks[i]:peaks[i + 1]]
        if not len(seg):
            continue
        local = peaks[i] + int(np.argmin(seg))
        antimodes.append(float(xs[local]))
    return {
        'n': int(len(arr)),
        'dip': float(dip),
        'dip_pvalue': float(pval),
        'unimodal_alpha05': bool(pval > 0.05),
        'n_modes': int(len(peaks)),
        'mode_locations': [float(xs[p]) for p in peaks],
        'antimodes': antimodes,
        'n_boot': int(n_boot),
    }


def _fmt_p(p):
    if p == 0.0:
        return '< 5e-4'
    return f'{p:.4g}'


def main():
    print('=' * 72)
    print('Script 39c: Mid/Small-Firm Signature-Level Dip Test')
    print('=' * 72)
    rows = load_non_big4_signatures()
    cos_all = np.array([r[1] for r in rows], dtype=float)
    dh_all = np.array([r[2] for r in rows], dtype=float)
    firms = np.array([r[0] for r in rows])
    n_total = len(rows)
    print(f'\nLoaded {n_total:,} non-Big-4 signatures across '
          f'{len(set(firms))} firms')

    # Firm size table
    firm_counts = {}
    for f in firms:
        firm_counts[f] = firm_counts.get(f, 0) + 1
    top = sorted(firm_counts.items(), key=lambda x: -x[1])
    print('\nTop firms by signature count:')
    for f, n in top[:10]:
        print(f'  {f}: {n:,}')

    results = {
        'meta': {
            'script': '39c',
            'timestamp': datetime.now().isoformat(timespec='seconds'),
            'n_total': int(n_total),
            'n_firms': int(len(firm_counts)),
            'n_boot': N_BOOT,
            'single_firm_min_sig': SINGLE_FIRM_MIN_SIG,
        },
        'pooled': {},
        'per_firm_eligible': {},
        'firm_counts': dict(firm_counts),
    }

    # A. Pooled non-Big-4
    print('\n[A] Pooled non-Big-4')
    for desc, arr in [('cos', cos_all), ('dh_indep', dh_all)]:
        r = kde_dip(arr)
        results['pooled'][desc] = r
        print(f'  {desc}: n={r["n"]:,}, dip={r["dip"]:.5f}, '
              f'p={_fmt_p(r["dip_pvalue"])}, n_modes={r["n_modes"]}')

    # B. Per-firm (only firms with >= SINGLE_FIRM_MIN_SIG signatures)
    eligible = [f for f, n in firm_counts.items() if n >= SINGLE_FIRM_MIN_SIG]
    print(f'\n[B] Per-firm dip test '
          f'(firms with >= {SINGLE_FIRM_MIN_SIG} signatures: {len(eligible)})')
    for f in sorted(eligible, key=lambda x: -firm_counts[x]):
        mask = firms == f
        results['per_firm_eligible'][f] = {'n': int(mask.sum())}
        for desc, arr in [('cos', cos_all[mask]), ('dh_indep', dh_all[mask])]:
            r = kde_dip(arr)
            results['per_firm_eligible'][f][desc] = r
            print(f'  {f[:20]:<22s} {desc}: n={r["n"]:,}, dip={r["dip"]:.5f}, '
                  f'p={_fmt_p(r["dip_pvalue"])}, n_modes={r["n_modes"]}')

    json_path = OUT / 'midsmall_diptest_results.json'
    json_path.write_text(json.dumps(results, indent=2, ensure_ascii=False),
                         encoding='utf-8')
    print(f'\n[json] {json_path}')

    md = ['# Mid/Small-Firm Signature-Level Dip Test (Script 39c)',
          '',
          f'Generated: {results["meta"]["timestamp"]}',
          f'Bootstrap replicates: {N_BOOT}',
          '',
          '## A. Pooled non-Big-4 signature cloud',
          '',
          f'n = {n_total:,} signatures across '
          f'{results["meta"]["n_firms"]} firms',
          '',
          '| Marginal | dip | p (boot) | n_modes | unimodal @0.05 |',
          '|---|---|---|---|---|']
    for desc in ['cos', 'dh_indep']:
        r = results['pooled'][desc]
        md.append(f'| {desc} | {r["dip"]:.5f} | {_fmt_p(r["dip_pvalue"])} | '
                  f'{r["n_modes"]} | {r["unimodal_alpha05"]} |')

    md += ['', f'## B. Single mid/small firms (>= {SINGLE_FIRM_MIN_SIG} '
              f'signatures), {len(eligible)} qualify', '',
           '| Firm | Marginal | n | dip | p (boot) | n_modes | unimodal @0.05 |',
           '|---|---|---|---|---|---|---|']
    for f in sorted(eligible, key=lambda x: -firm_counts[x]):
        for desc in ['cos', 'dh_indep']:
            r = results['per_firm_eligible'][f][desc]
            md.append(f'| {f[:20]} | {desc} | {r["n"]:,} | {r["dip"]:.5f} | '
                      f'{_fmt_p(r["dip_pvalue"])} | {r["n_modes"]} | '
                      f'{r["unimodal_alpha05"]} |')

    md += ['',
           '## Reading guide',
           '',
           ('If the pooled-non-Big-4 dHash marginal rejects unimodality '
            'AND the qualifying individual mid/small firms also reject, '
            'the dHash within-firm replication regime structure is '
            'corpus-universal and not Big-4-specific. In that case the '
            'Big-4 scope of v4.0 is justified on cosine-axis grounds '
            '(Firm-A composition; §III-G item 1) and accountant-level '
            'LOOO reproducibility (§III-G item 3), but not on dHash '
            'multimodality grounds (§III-G item 2 should be re-scoped or '
            'qualified). If the per-firm dHash tests instead fail to '
            'reject inside mid/small firms, the dHash multimodality is '
            'Big-4-specific and §III-G item 2 holds as stated.'),
           '']
    md_path = OUT / 'midsmall_diptest_report.md'
    md_path.write_text('\n'.join(md), encoding='utf-8')
    print(f'[md  ] {md_path}')


if __name__ == '__main__':
    main()