[SHA Metrics] Extend silence metrics for structural preservation analysis

examples/sha_extended_metrics_demo.py

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+"""Demo: Extended SHA (Silence) Metrics
+
+This demo shows how to use the extended metrics for the SHA operator
+to analyze structural preservation effectiveness in different scenarios.
+
+The extended metrics enable deep analysis of:
+- EPI variance during silence
+- Preservation integrity quality
+- Reactivation readiness assessment
+- Time-to-collapse prediction
+"""
+
+from tnfr.structural import create_nfr
+from tnfr.operators.metrics import silence_metrics
+from tnfr.alias import set_attr
+from tnfr.constants.aliases import ALIAS_VF, ALIAS_EPI
+
+
+def print_metrics(title: str, metrics: dict) -> None:
+    """Pretty print extended metrics."""
+    print(f"\n{'='*60}")
+    print(f"{title}")
+    print(f"{'='*60}")
+    print(f"Operator: {metrics['operator']} ({metrics['glyph']})")
+    print(f"\nCore Metrics:")
+    print(f"  vf_reduction: {metrics['vf_reduction']:.4f}")
+    print(f"  vf_final: {metrics['vf_final']:.4f}")
+    print(f"  epi_preservation: {metrics['epi_preservation']:.4f}")
+    print(f"  is_silent: {metrics['is_silent']}")
+    print(f"\nExtended Metrics:")
+    print(f"  epi_variance: {metrics['epi_variance']:.6f}")
+    print(f"  preservation_integrity: {metrics['preservation_integrity']:.4f}")
+    print(f"  reactivation_readiness: {metrics['reactivation_readiness']:.4f}")
+    time_val = metrics['time_to_collapse']
+    time_str = "infinite" if time_val == float('inf') else f"{time_val:.2f} steps"
+    print(f"  time_to_collapse: {time_str}")
+
+
+def demo_biomedical_use_case():
+    """Biomedical: Sleep consolidation tracking."""
+    print("\n🏥 BIOMEDICAL USE CASE: Sleep Consolidation")
+    print("Tracking HRV signal during 8-hour sleep period")
+
+    # Create node representing HRV signal
+    G, node = create_nfr("hrv_signal", epi=0.6, vf=0.02)
+
+    # Set up silence tracking
+    G.nodes[node]["preserved_epi"] = 0.6
+    G.nodes[node]["silence_duration"] = 8.0  # 8 hours
+    G.nodes[node]["epi_history_during_silence"] = [
+        0.6, 0.602, 0.598, 0.601, 0.599, 0.600
+    ]  # Minimal variance (stable sleep)
+    G.nodes[node]["epi_drift_rate"] = 0.001  # Very slow drift
+
+    metrics = silence_metrics(G, node, vf_before=0.5, epi_before=0.6)
+    print_metrics("Sleep Consolidation Analysis", metrics)
+
+    print("\n📊 Interpretation:")
+    print("  ✓ High preservation integrity (>0.99) = Stable sleep")
+    print("  ✓ Low EPI variance (<0.01) = No sleep disturbances")
+    print("  ✓ Moderate readiness (0.3-0.8) = Natural post-sleep state")
+    print("  ✓ Long time-to-collapse (>100) = Healthy resilience")
+
+
+def demo_cognitive_use_case():
+    """Cognitive: Memory consolidation during incubation."""
+    print("\n🧠 COGNITIVE USE CASE: Memory Consolidation")
+    print("Memory trace during incubation period")
+
+    # Create node representing memory trace
+    G, node = create_nfr("memory_trace", epi=0.7, vf=0.03)
+
+    # Set up perfect preservation
+    G.nodes[node]["preserved_epi"] = 0.7
+    G.nodes[node]["silence_duration"] = 2.0  # Brief pause
+    G.nodes[node]["epi_history_during_silence"] = [0.7, 0.7, 0.7]  # Perfect stability
+    G.nodes[node]["epi_drift_rate"] = 0.0  # No drift
+
+    # Add network support (other memory traces)
+    for i in range(4):
+        G.add_node(f"memory_{i}")
+        set_attr(G.nodes[f"memory_{i}"], ALIAS_VF, 0.5)
+        set_attr(G.nodes[f"memory_{i}"], ALIAS_EPI, 0.6)
+        G.add_edge(node, f"memory_{i}")
+
+    metrics = silence_metrics(G, node, vf_before=0.5, epi_before=0.7)
+    print_metrics("Memory Consolidation Analysis", metrics)
+
+    print("\n📊 Interpretation:")
+    print("  ✓ Perfect integrity (1.0) = Excellent consolidation")
+    print("  ✓ Zero variance = No memory degradation")
+    print("  ✓ High readiness (>0.7) = Ready for recall")
+    print("  ✓ Infinite collapse time = Stable long-term memory")
+
+
+def demo_social_use_case():
+    """Social: Strategic pause in conflict."""
+    print("\n🤝 SOCIAL USE CASE: Strategic Pause in Conflict")
+    print("Conflict state paused for de-escalation")
+
+    # Create node representing conflict state
+    G, node = create_nfr("conflict_state", epi=0.4, vf=0.01)
+
+    # Set up degrading silence (some EPI loss)
+    G.nodes[node]["preserved_epi"] = 0.45
+    G.nodes[node]["silence_duration"] = 15.0  # Long strategic pause
+    G.nodes[node]["epi_history_during_silence"] = [
+        0.45, 0.44, 0.42, 0.41, 0.40
+    ]  # Gradual degradation
+    G.nodes[node]["epi_drift_rate"] = 0.01  # Slow degradation
+
+    metrics = silence_metrics(G, node, vf_before=0.8, epi_before=0.45)
+    print_metrics("Strategic Pause Analysis", metrics)
+
+    print("\n📊 Interpretation:")
+    print("  ⚠ Good integrity (0.85-0.95) = Acceptable degradation")
+    print("  ⚠ Some variance = Tension still present")
+    print("  ⚠ Moderate readiness (<0.6) = Extended pause needed")
+    print("  ⚠ Finite collapse (30-50 steps) = Act before breakdown")
+
+
+def demo_preservation_failure():
+    """Example: Detection of preservation failure."""
+    print("\n⚠️  FAILURE DETECTION: Poor Preservation")
+    print("Node with excessive EPI drift during silence")
+
+    # Create node with poor preservation
+    G, node = create_nfr("unstable_node", epi=0.2, vf=0.05)
+
+    # Set up failing preservation
+    G.nodes[node]["preserved_epi"] = 0.5  # Started at 0.5
+    G.nodes[node]["silence_duration"] = 5.0
+    G.nodes[node]["epi_history_during_silence"] = [
+        0.5, 0.4, 0.3, 0.25, 0.2
+    ]  # Rapid degradation
+    G.nodes[node]["epi_drift_rate"] = 0.06  # High drift
+
+    metrics = silence_metrics(G, node, vf_before=1.0, epi_before=0.5)
+    print_metrics("Preservation Failure Detection", metrics)
+
+    print("\n📊 Interpretation:")
+    print("  ❌ Low integrity (<0.8) = PRESERVATION FAILURE")
+    print("  ❌ High variance = Unstable structure")
+    print("  ❌ Low readiness (<0.3) = RISKY REACTIVATION")
+    print("  ❌ Short collapse time (<10) = IMMINENT COLLAPSE")
+    print("\n⚡ ACTION REQUIRED: Apply IL (Coherence) before reactivation")
+
+
+if __name__ == "__main__":
+    print("╔════════════════════════════════════════════════════════════╗")
+    print("║  Extended SHA Metrics Demo                                 ║")
+    print("║  Analyzing Structural Preservation Effectiveness           ║")
+    print("╚════════════════════════════════════════════════════════════╝")
+
+    # Run all demos
+    demo_biomedical_use_case()
+    demo_cognitive_use_case()
+    demo_social_use_case()
+    demo_preservation_failure()
+
+    print("\n" + "="*60)
+    print("✨ Demo Complete!")
+    print("="*60)
+    print("\nThe extended SHA metrics enable:")
+    print("  • Deep analysis of preservation quality")
+    print("  • Early detection of structural degradation")
+    print("  • Informed reactivation timing decisions")
+    print("  • Cross-domain application (biomedical, cognitive, social)")