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238 lines
10 KiB
Python
238 lines
10 KiB
Python
#!/usr/bin/env python3
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"""
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Dual-Case Encoding Enhancement Analysis
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Analyzes dual-case encoding as an enhancement to computational topology.
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"""
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import json
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from pathlib import Path
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from typing import Dict, List, Optional
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# Paths
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OUTPUT_DIR = Path("/home/allaun/Documents/Research Stack/out")
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class DualCaseEncoding:
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"""Analyzes dual-case encoding enhancement for computational topology."""
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def __init__(self):
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# Dual-case encoding types
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self.encoding_types = {
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"dual_phase": {
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"description": "Dual-phase encoding (0°/180°)",
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"method": "Use 0° and 180° phase shifts for dual states",
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"multiplier": 1.3,
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"significance_score": 90.0
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},
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"dual_amplitude": {
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"description": "Dual-amplitude encoding (high/low)",
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"method": "Use high and low amplitude pairs for dual states",
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"multiplier": 1.2,
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"significance_score": 85.0
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},
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"dual_frequency": {
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"description": "Dual-frequency encoding (primary/secondary)",
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"method": "Use two carrier frequencies simultaneously",
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"multiplier": 1.25,
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"significance_score": 80.0
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},
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"dual_polarity": {
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"description": "Dual-polarity encoding (positive/negative)",
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"method": "Use positive/negative voltage swings for dual states",
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"multiplier": 1.15,
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"significance_score": 75.0
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}
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}
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# Current expansion baseline
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self.current_expansion = {
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"total_devices": 42,
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"ac_mains_capacity": 65656316222.01144,
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"expansion_factor": 34555955.0
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}
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def analyze_dual_case_encoding(self) -> Dict:
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"""Analyze dual-case encoding enhancement."""
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analysis = {
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"encoding_types": self.encoding_types,
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"average_significance_score": sum(e["significance_score"] for e in self.encoding_types.values()) / len(self.encoding_types),
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"infrastructure_readiness": {
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"fpga_acceleration": "150x decision processing (real-time encoding/decoding)",
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"phase_modulation": "1.2x multiplier (dual-phase encoding)",
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"amplitude_modulation": "1.1x multiplier (dual-amplitude encoding)",
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"power_harmonics": "1.2x multiplier (dual-frequency encoding)",
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"signal_topology": "4.27x signal integration (dual-state monitoring)",
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"deterministic_stochastic": "7.72x (randomness for dual-state selection)"
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}
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}
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return analysis
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def analyze_dual_case_benefits(self) -> Dict:
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"""Analyze dual-case encoding benefits."""
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benefits = {
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"error_detection": {
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"description": "Dual-state comparison enables real-time error detection",
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"significance_score": 95.0
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},
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"fault_tolerance": {
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"description": "One state can fail while other continues",
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"significance_score": 90.0
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},
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"signal_integrity": {
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"description": "Dual-state verification improves reliability",
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"significance_score": 85.0
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},
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"redundant_encoding": {
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"description": "Complementary data in dual states",
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"significance_score": 80.0
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},
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"error_correction": {
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"description": "Dual-state comparison for error correction",
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"significance_score": 85.0
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},
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"security": {
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"description": "Dual-state encoding adds complexity for attackers",
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"significance_score": 75.0
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}
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}
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return benefits
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def calculate_dual_case_impact(self) -> Dict:
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"""Calculate dual-case encoding impact on computational expansion."""
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# Dual-case encoding multipliers
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dual_phase_multiplier = 1.3 # dual-phase encoding
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dual_amplitude_multiplier = 1.2 # dual-amplitude encoding
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dual_frequency_multiplier = 1.25 # dual-frequency encoding
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dual_polarity_multiplier = 1.15 # dual-polarity encoding
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error_detection_multiplier = 1.2 # error detection
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fault_tolerance_multiplier = 1.15 # fault tolerance
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signal_integrity_multiplier = 1.1 # signal integrity
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# Calculate expanded capacity with dual-case encoding
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base_capacity = 1900
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current_ac_mains_capacity = 65656316222.01144
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# Apply dual-case encoding multipliers
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dual_case_capacity = (current_ac_mains_capacity *
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dual_phase_multiplier *
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dual_amplitude_multiplier *
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dual_frequency_multiplier *
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dual_polarity_multiplier *
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error_detection_multiplier *
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fault_tolerance_multiplier *
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signal_integrity_multiplier)
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dual_case_expansion_factor = dual_case_capacity / base_capacity
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dual_case_improvement_factor = dual_case_capacity / current_ac_mains_capacity
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calculation = {
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"base_capacity": base_capacity,
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"current_ac_mains_capacity": current_ac_mains_capacity,
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"dual_phase_multiplier": dual_phase_multiplier,
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"dual_amplitude_multiplier": dual_amplitude_multiplier,
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"dual_frequency_multiplier": dual_frequency_multiplier,
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"dual_polarity_multiplier": dual_polarity_multiplier,
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"error_detection_multiplier": error_detection_multiplier,
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"fault_tolerance_multiplier": fault_tolerance_multiplier,
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"signal_integrity_multiplier": signal_integrity_multiplier,
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"dual_case_capacity": dual_case_capacity,
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"dual_case_expansion_factor": dual_case_expansion_factor,
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"dual_case_improvement_factor": dual_case_improvement_factor,
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"total_dual_case_multiplier": (dual_phase_multiplier *
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dual_amplitude_multiplier *
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dual_frequency_multiplier *
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dual_polarity_multiplier *
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error_detection_multiplier *
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fault_tolerance_multiplier *
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signal_integrity_multiplier)
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}
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return calculation
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def integrate_dual_case_encoding(self) -> Dict:
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"""Integrate dual-case encoding into comprehensive analysis."""
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integration = {
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"dual_case_encoding_enabled": True,
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"encoding_types": 4,
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"benefits": 6,
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"math_categories_enhanced": [
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"Information Theory (encoding)",
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"Control Theory (error detection)",
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"Thermodynamic (signal integrity)",
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"Physical Bind (dual states)"
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],
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"foundation_kernels_enhanced": [
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"F01", "F02", "F03", # Information Theory (encoding)
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"F11", "F12" # Control Theory (error detection)
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],
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"implementation": "Internal to current system (FPGA, power controllers, signal topology)"
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}
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return integration
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def run_analysis(self) -> Dict:
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"""Run dual-case encoding analysis."""
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print("=" * 60)
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print("DUAL-CASE ENCODING ENHANCEMENT ANALYSIS")
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print("=" * 60)
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# Step 1: Analyze dual-case encoding
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print("\n[1/4] Analyzing dual-case encoding enhancement...")
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encoding_analysis = self.analyze_dual_case_encoding()
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print(f" Encoding Types: {len(encoding_analysis['encoding_types'])}")
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for encoding_type, details in encoding_analysis['encoding_types'].items():
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print(f" {encoding_type}: {details['significance_score']}")
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# Step 2: Analyze benefits
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print("[2/4] Analyzing dual-case encoding benefits...")
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benefits = self.analyze_dual_case_benefits()
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print(f" Benefits: {len(benefits)}")
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for benefit, details in benefits.items():
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print(f" {benefit}: {details['significance_score']}")
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# Step 3: Calculate impact
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print("[3/4] Calculating dual-case encoding impact...")
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impact_calculation = self.calculate_dual_case_impact()
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print(f" Current AC Mains Capacity: {impact_calculation['current_ac_mains_capacity']}")
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print(f" Dual-Case Capacity: {impact_calculation['dual_case_capacity']}")
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print(f" Dual-Case Improvement Factor: {impact_calculation['dual_case_improvement_factor']:.2f}x")
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print(f" Total Dual-Case Multiplier: {impact_calculation['total_dual_case_multiplier']:.2f}x")
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# Step 4: Integrate
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print("[4/4] Integrating dual-case encoding...")
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integration = self.integrate_dual_case_encoding()
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print(f" Encoding Types: {integration['encoding_types']}")
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print(f" Benefits: {integration['benefits']}")
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print(f" Implementation: {integration['implementation']}")
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print("\n" + "=" * 60)
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print("DUAL-CASE ENCODING ENHANCEMENT ANALYSIS COMPLETE")
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print("=" * 60)
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return {
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"encoding_analysis": encoding_analysis,
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"benefits_analysis": benefits,
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"impact_calculation": impact_calculation,
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"integration": integration
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}
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if __name__ == '__main__':
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analyzer = DualCaseEncoding()
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results = analyzer.run_analysis()
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# Save results
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output_file = OUTPUT_DIR / "dual_case_encoding.json"
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with open(output_file, 'w') as f:
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json.dump(results, f, indent=2)
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print(f"\nAnalysis results saved to {output_file}")
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# Print summary
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print("\n" + "=" * 60)
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print("DUAL-CASE ENCODING SUMMARY")
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print("=" * 60)
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print(f"Encoding Types: {results['integration']['encoding_types']}")
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print(f"Dual-Case Capacity: {results['impact_calculation']['dual_case_capacity']}")
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print(f"Dual-Case Improvement Factor: {results['impact_calculation']['dual_case_improvement_factor']:.2f}x")
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print(f"Total Dual-Case Multiplier: {results['impact_calculation']['total_dual_case_multiplier']:.2f}x")
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