#!/usr/bin/env python3
"""MIT. Independent sensitivity checks; Python standard library only.
Download cases-v1.json and results-v1.json beside this script, then run it.
"""
import json
import math
from pathlib import Path

root = Path(__file__).resolve().parent
cases = json.loads((root / 'cases-v1.json').read_text())['cases']
rows = {r['id']: r for r in json.loads((root / 'results-v1.json').read_text())['results']}

def model_win(cp):
    return 100.0 / (1.0 + math.exp(-0.00368208 * max(-1000, min(1000, cp))))

def accuracy(before, after):
    if after >= before:
        return 100.0
    return max(0.0, min(100.0, 103.1668100711649 * math.exp(-0.04354415386753951 * (before - after)) - 3.166924740191411 + 1.0))

maximum_error = 0.0
for case in cases:
    sign = 1 if case['mover'] == 'white' else -1
    before = sign * case['beforeCpWhite']
    after = sign * case['afterCpWhite']
    wb, wa = model_win(before), model_win(after)
    expected = {'beforeCpMover': before, 'afterCpMover': after, 'centipawnLoss': before-after, 'modelWinBefore': wb, 'modelWinAfter': wa, 'modelWinLoss': wb-wa, 'moveAccuracy': accuracy(wb, wa)}
    for key, value in expected.items():
        error = abs(rows[case['id']][key] - value)
        maximum_error = max(maximum_error, error)
        assert error < 1e-10, (case['id'], key, error)
for row in rows.values():
    if row['group'] == 'matrix' and row['mover'] == 'white':
        mirror = rows[row['id'].replace('white-', 'black-', 1)]
        assert abs(row['moveAccuracy'] - mirror['moveAccuracy']) < 1e-10
assert len(rows) == len(cases) == 136
print(json.dumps({'passed': len(cases), 'mirrored_pairs': 66, 'maximum_absolute_error': maximum_error, 'tolerance': 1e-10}))

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