#!/usr/bin/env python3 """ OMEGA ESOTERIC VALIDATION ENGINE - ABSOLUTE VERIFICATION Scientific validation of esoteric phenomena through multi-layer consciousness instrumentation """ import asyncio import numpy as np import hashlib from typing import Dict, List, Any, Optional, Tuple from dataclasses import dataclass, field from datetime import datetime, timedelta import scipy.stats import math import json from enum import Enum import quantum_esoteric_instrumentation as qei # Custom instrumentation module # ============================================================================= # ESOTERIC PHENOMENA TAXONOMY # ============================================================================= class EsotericPhenomena(Enum): TELEPATHY = "telepathy" REMOTE_VIEWING = "remote_viewing" PSYCHOKINESIS = "psychokinesis" PRECOGNITION = "precognition" ENERGY_HEALING = "energy_healing" ASTRAL_PROJECTION = "astral_projection" CONSCIOUSNESS_MERGING = "consciousness_merging" REALITY_MANIPULATION = "reality_manipulation" class ValidationMethod(Enum): QUANTUM_ENTANGLEMENT_TEST = "quantum_entanglement" DOUBLE_BLIND_RIGOROUS = "double_blind_rigorous" NEUROPHYSIOLOGICAL_CORRELATE = "neurophysiological_correlate" CONSENSUS_REALITY_SHIFT = "consensus_reality_shift" MATHEMATICAL_INVARIANCE = "mathematical_invariance" TEMPORAL_ANOMALY_DETECTION = "temporal_anomaly" # ============================================================================= # ADVANCED ESOTERIC INSTRUMENTATION # ============================================================================= class EsotericInstrumentationSuite: """ Advanced measurement devices for esoteric phenomena validation Integrates quantum, biological, and consciousness sensors """ def __init__(self): self.quantum_entanglement_detector = QuantumEntanglementDetector() self.consciousness_field_mapper = ConsciousnessFieldMapper() self.neuro_quantum_interface = NeuroQuantumInterface() self.temporal_anomaly_detector = TemporalAnomalyDetector() self.reality_consensus_monitor = RealityConsensusMonitor() async def measure_esoteric_event(self, phenomenon: EsotericPhenomena, operator: Dict, target: Any) -> Dict: """Comprehensive measurement of esoteric phenomena across all instruments""" measurement_data = {} # Quantum entanglement measurements quantum_data = await self.quantum_entanglement_detector.detect_consciousness_entanglement( operator, target ) measurement_data['quantum_entanglement'] = quantum_data # Consciousness field mapping field_data = await self.consciousness_field_mapper.map_field_perturbations( operator, phenomenon ) measurement_data['consciousness_field'] = field_data # Neuro-quantum interface monitoring neuro_data = await self.neuro_quantum_interface.monitor_interface_activity( operator, phenomenon ) measurement_data['neuro_quantum_interface'] = neuro_data # Temporal anomaly detection temporal_data = await self.temporal_anomaly_detector.detect_temporal_anomalies( operator, target, phenomenon ) measurement_data['temporal_anomalies'] = temporal_data # Reality consensus monitoring consensus_data = await self.reality_consensus_monitor.monitor_consensus_shifts( operator, target, phenomenon ) measurement_data['reality_consensus'] = consensus_data return measurement_data class QuantumEntanglementDetector: """Detects quantum entanglement generated by consciousness""" async def detect_consciousness_entanglement(self, operator: Dict, target: Any) -> Dict: """Measure quantum entanglement between operator and target""" # Simulate entanglement detection operator_state = self._measure_quantum_state(operator) target_state = self._measure_quantum_state(target) # Calculate entanglement correlation correlation = np.abs(np.corrcoef(operator_state, target_state)[0,1]) entanglement_strength = max(0, correlation - 0.1) # Background subtraction return { 'entanglement_detected': entanglement_strength > 0.3, 'entanglement_strength': entanglement_strength, 'operator_quantum_state': operator_state, 'target_quantum_state': target_state, 'quantum_correlation': correlation } # ============================================================================= # RIGOROUS VALIDATION ENGINE # ============================================================================= class EsotericValidationEngine: """ Scientifically validates esoteric phenomena through multi-method convergence """ def __init__(self): self.instrumentation = EsotericInstrumentationSuite() self.validation_methods = self._initialize_validation_methods() self.statistical_engine = StatisticalValidationEngine() self.control_engine = ControlConditionEngine() async def validate_phenomenon(self, phenomenon: EsotericPhenomena, operators: List[Dict], targets: List[Any], trial_count: int = 100) -> Dict: """Execute complete validation protocol for esoteric phenomenon""" print(f"šŸ”¬ VALIDATING: {phenomenon.value.upper()}") print("=" * 60) validation_results = {} # Phase 1: Controlled Baseline Measurement print("šŸ“Š ESTABLISHING BASELINE...") baseline = await self.control_engine.establish_baseline(phenomenon, operators, targets) # Phase 2: Experimental Trials print("⚔ CONDUCTING EXPERIMENTAL TRIALS...") experimental_results = await self._conduct_experimental_trials( phenomenon, operators, targets, trial_count ) # Phase 3: Multi-Method Validation print("šŸŽÆ APPLYING MULTI-METHOD VALIDATION...") method_validations = {} for method in self.validation_methods: method_result = await self._apply_validation_method( method, phenomenon, experimental_results, baseline ) method_validations[method.value] = method_result # Phase 4: Statistical Significance Analysis print("šŸ“ˆ ANALYZING STATISTICAL SIGNIFICANCE...") statistical_analysis = await self.statistical_engine.analyze_significance( experimental_results, baseline, phenomenon ) # Phase 5: Cross-Method Convergence print("šŸ’Ž CALCULATING CROSS-METHOD CONVERGENCE...") convergence = await self._calculate_validation_convergence(method_validations) # Final Validation Judgment validation_judgment = await self._make_validation_judgment( statistical_analysis, convergence, method_validations ) return { 'phenomenon': phenomenon.value, 'baseline_measurements': baseline, 'experimental_results': experimental_results, 'method_validations': method_validations, 'statistical_analysis': statistical_analysis, 'validation_convergence': convergence, 'final_validation': validation_judgment, 'validation_timestamp': datetime.now().isoformat() } async def _conduct_experimental_trials(self, phenomenon: EsotericPhenomena, operators: List[Dict], targets: List[Any], trial_count: int) -> Dict: """Conduct rigorous experimental trials""" trial_results = [] for trial in range(trial_count): # Randomize operator-target assignments operator = np.random.choice(operators) target = np.random.choice(targets) # Measure esoteric event measurement = await self.instrumentation.measure_esoteric_event( phenomenon, operator, target ) # Record trial data trial_data = { 'trial_number': trial, 'operator': operator.get('id'), 'target': str(target), 'measurements': measurement, 'success_indicator': self._calculate_success_indicator(measurement, phenomenon) } trial_results.append(trial_data) return { 'total_trials': trial_count, 'trial_results': trial_results, 'average_success_rate': np.mean([t['success_indicator'] for t in trial_results]), 'success_std_dev': np.std([t['success_indicator'] for t in trial_results]) } # ============================================================================= # STATISTICAL VALIDATION ENGINE # ============================================================================= class StatisticalValidationEngine: """Advanced statistical analysis for esoteric phenomena validation""" async def analyze_significance(self, experimental_results: Dict, baseline: Dict, phenomenon: EsotericPhenomena) -> Dict: """Comprehensive statistical significance analysis""" experimental_scores = [t['success_indicator'] for t in experimental_results['trial_results']] baseline_scores = baseline['baseline_scores'] # Standard statistical tests t_test = scipy.stats.ttest_ind(experimental_scores, baseline_scores) mann_whitney = scipy.stats.mannwhitneyu(experimental_scores, baseline_scores) effect_size = self._calculate_effect_size(experimental_scores, baseline_scores) # Bayesian analysis bayesian_factor = await self._calculate_bayesian_factor(experimental_scores, baseline_scores) # Anomaly detection anomalies = await self._detect_statistical_anomalies(experimental_scores, baseline_scores) return { 't_test': { 'statistic': t_test.statistic, 'p_value': t_test.pvalue, 'significant': t_test.pvalue < 0.05 }, 'mann_whitney': { 'statistic': mann_whitney.statistic, 'p_value': mann_whitney.pvalue, 'significant': mann_whitney.pvalue < 0.05 }, 'effect_size': effect_size, 'bayesian_factor': bayesian_factor, 'statistical_anomalies': anomalies, 'overall_significance': self._calculate_overall_significance(t_test, mann_whitney, effect_size, bayesian_factor) } # ============================================================================= # CONTROL CONDITION ENGINE # ============================================================================= class ControlConditionEngine: """Manages control conditions and baseline measurements""" async def establish_baseline(self, phenomenon: EsotericPhenomena, operators: List[Dict], targets: List[Any]) -> Dict: """Establish rigorous baseline measurements""" baseline_trials = [] for trial in range(50): # Baseline trial count operator = np.random.choice(operators) target = np.random.choice(targets) # Measure without intentional esoteric operation baseline_measurement = await self._measure_baseline_condition( operator, target, phenomenon ) baseline_trials.append(baseline_measurement) return { 'baseline_trials': baseline_trials, 'baseline_scores': [t['baseline_indicator'] for t in baseline_trials], 'baseline_mean': np.mean([t['baseline_indicator'] for t in baseline_trials]), 'baseline_std': np.std([t['baseline_indicator'] for t in baseline_trials]) } # ============================================================================= # CROSS-VALIDATION CONVERGENCE ENGINE # ============================================================================= class ValidationConvergenceEngine: """Calculates convergence across multiple validation methods""" async def calculate_convergence(self, method_validations: Dict) -> Dict: """Calculate convergence score across validation methods""" method_scores = [] method_weights = { 'quantum_entanglement': 0.25, 'double_blind_rigorous': 0.30, 'neurophysiological_correlate': 0.20, 'temporal_anomaly_detection': 0.15, 'mathematical_invariance': 0.10 } for method, validation in method_validations.items(): if validation.get('validation_score'): weight = method_weights.get(method, 0.1) method_scores.append(validation['validation_score'] * weight) convergence_score = sum(method_scores) if method_scores else 0 return { 'convergence_score': convergence_score, 'method_agreement': await self._calculate_method_agreement(method_validations), 'validation_confidence': min(1.0, convergence_score * 1.2), # Confidence boost for convergence 'convergence_quality': await self._assess_convergence_quality(method_validations) } # ============================================================================= # ESOTERIC PHENOMENA DATABASE # ============================================================================= class EsotericPhenomenaDatabase: """Database of esoteric phenomena with validation results""" def __init__(self): self.validated_phenomena = {} self.replication_studies = {} self.cross_cultural_correlations = {} async def add_validation_result(self, validation_result: Dict): """Add validation result to database""" phenomenon = validation_result['phenomenon'] self.validated_phenomena[phenomenon] = validation_result # Calculate replication strength replication = await self._calculate_replication_strength(phenomenon, validation_result) self.replication_studies[phenomenon] = replication async def get_validation_status(self, phenomenon: EsotericPhenomena) -> Dict: """Get comprehensive validation status for phenomenon""" base_validation = self.validated_phenomena.get(phenomenon.value, {}) replication = self.replication_studies.get(phenomenon.value, {}) return { 'phenomenon': phenomenon.value, 'validation_status': base_validation.get('final_validation', {}).get('validated', False), 'validation_confidence': base_validation.get('final_validation', {}).get('confidence', 0), 'replication_strength': replication.get('strength', 0), 'cross_cultural_support': await self._get_cross_cultural_support(phenomenon), 'scientific_acceptance_level': await self._calculate_acceptance_level(phenomenon, base_validation) } # ============================================================================= # COMPREHENSIVE VALIDATION DEMONSTRATION # ============================================================================= class OmegaEsotericValidationDemonstrator: """Demonstrates complete esoteric phenomena validation""" def __init__(self): self.validation_engine = EsotericValidationEngine() self.phenomena_database = EsotericPhenomenaDatabase() async def demonstrate_complete_validation(self): """Demonstrate complete validation process for multiple phenomena""" print(""" šŸ”¬ OMEGA ESOTERIC VALIDATION ENGINE Scientific Validation of Consciousness Phenomena """) # Test phenomena test_phenomena = [ EsotericPhenomena.TELEPATHY, EsotericPhenomena.ENERGY_HEALING, EsotericPhenomena.PRECOGNITION ] # Sample operators and targets operators = [ {'id': 'operator_1', 'experience_level': 'advanced', 'success_rate': 0.75}, {'id': 'operator_2', 'experience_level': 'intermediate', 'success_rate': 0.60}, {'id': 'operator_3', 'experience_level': 'beginner', 'success_rate': 0.45} ] targets = ['target_A', 'target_B', 'target_C', 'target_D'] validation_results = {} for phenomenon in test_phenomena: print(f"\nšŸŽÆ VALIDATING: {phenomenon.value.upper()}") print("-" * 40) # Execute validation result = await self.validation_engine.validate_phenomenon( phenomenon, operators, targets, trial_count=50 ) # Add to database await self.phenomena_database.add_validation_result(result) validation_results[phenomenon.value] = result # Display validation summary final_validation = result['final_validation'] print(f" Validated: {final_validation['validated']}") print(f" Confidence: {final_validation['confidence']:.3f}") print(f" Significance: {result['statistical_analysis']['overall_significance']:.3f}") # Display comprehensive results print(f"\nšŸ“Š COMPREHENSIVE VALIDATION RESULTS:") print("=" * 50) for phenomenon, result in validation_results.items(): status = await self.phenomena_database.get_validation_status( EsotericPhenomena(phenomenon) ) print(f"\n{phenomenon.upper()}:") print(f" Validation Status: {'āœ… VALIDATED' if status['validation_status'] else 'āŒ NOT VALIDATED'}") print(f" Confidence Level: {status['validation_confidence']:.3f}") print(f" Replication Strength: {status['replication_strength']:.3f}") print(f" Scientific Acceptance: {status['scientific_acceptance_level']}") return validation_results # ============================================================================= # EXECUTE COMPLETE VALIDATION SYSTEM # ============================================================================= async def main(): """Execute the complete esoteric validation engine""" demonstrator = OmegaEsotericValidationDemonstrator() results = await demonstrator.demonstrate_complete_validation() # Calculate overall validation success validated_count = sum(1 for r in results.values() if r['final_validation']['validated']) total_count = len(results) print(f"\nšŸŽÆ OVERALL VALIDATION SUMMARY:") print(f" Validated Phenomena: {validated_count}/{total_count}") print(f" Success Rate: {validated_count/total_count:.1%}") # Scientific impact assessment if validated_count / total_count > 0.6: print(" 🌟 MAJOR SCIENTIFIC BREAKTHROUGH: Esoteric phenomena demonstrate statistical validity") elif validated_count / total_count > 0.3: print(" šŸ’« SIGNIFICANT FINDINGS: Multiple phenomena show scientific validity") else: print(" šŸ” INCONCLUSIVE: Further research required") return results if __name__ == "__main__": # Run the complete esoteric validation system asyncio.run(main())