model.py

import hashlib
import time
import numpy as np
from scipy import stats

class TemporalLock:
    """
    Geophysical Cycle-Based Cryptographic Validation
    Applications:
    - Secure log timestamping
    - Event chronology forensics
    """
    def __init__(self):
        self.cycles = {
            'schumann': 7.83,    # Schumann resonance (Hz)
            'solar': 11.2         # Solar cycle (years)
        }
        
    def stamp(self, data: str) -> dict:
        """Generate time-anchored signature"""
        t = time.time()
        moduli = [t % freq for freq in self.cycles.values()]
        return {
            'timestamp': t,
            'hash': hashlib.blake3(
                f"{data}_{t}_{moduli[0]}".encode()
            ).hexdigest(),
            'cycle_alignments': moduli
        }
    
    def validate(self, events: list) -> float:
        """Calculate anomaly confidence (0.0-1.0)"""
        errors = sum(e['errors'] for e in events)
        total = sum(e['observations'] for e in events)
        return min(0.99, 1 - stats.binomtest(
            k=errors, n=total, p=0.05
        ).pvalue)