Research-Stack/5-Applications/scripts/swarm_codon_otom_improvement_suggestions.py

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#!/usr/bin/env python3
"""
Swarm Improvement Suggestions for CodonOTOM Module
Queries the swarm for specific improvement suggestions to make the
CodonOTOM module 100% complete.
"""
import sqlite3
import json
from datetime import datetime
from typing import Dict, List, Any
# Database path
DB_PATH = "/home/allaun/Documents/Research Stack/data/math_entities.db"
def get_codon_otom_entry() -> Dict[str, Any]:
"""Get the CodonOTOM entry from the database."""
conn = sqlite3.connect(DB_PATH)
conn.row_factory = sqlite3.Row
cursor = conn.cursor()
cursor.execute("""
SELECT entity_id, subject, secondary_subjects, name, statement, proof_status, formal_status,
lean_module, dependencies, citations, complexity_score, year
FROM math_entities
WHERE entity_id = 'codon_fitness_001'
""")
result = cursor.fetchone()
conn.close()
if result:
return dict(result)
return None
def analyze_current_state(entry: Dict[str, Any]) -> Dict[str, Any]:
"""Analyze the current state of CodonOTOM."""
analysis = {
"entity_id": entry["entity_id"],
"name": entry["name"],
"proof_status": entry["proof_status"],
"formal_status": entry["formal_status"],
"complexity_score": entry["complexity_score"],
"completeness": 0.0,
"gaps": []
}
# Assess completeness
if entry["proof_status"] == "theorems":
analysis["completeness"] = 0.9
elif entry["proof_status"] == "definitions":
analysis["completeness"] = 0.5
analysis["gaps"].append("Add theorems proving key properties")
else:
analysis["completeness"] = 0.3
if entry["formal_status"] == "noncomputable":
analysis["completeness"] *= 0.8
analysis["gaps"].append("Consider Q16_16 fixed-point for hardware extraction")
return analysis
def generate_swarm_improvement_suggestions(analysis: Dict[str, Any]) -> List[str]:
"""Generate swarm improvement suggestions based on analysis."""
suggestions = []
# Overall completeness assessment
if analysis["completeness"] < 0.8:
suggestions.append(f"OVERALL: Current completeness {analysis['completeness']:.1%} - target 100%")
# Specific suggestions
if analysis["proof_status"] == "definitions":
suggestions.append("Add theorem: phiCodon is bounded when denomSafe holds")
suggestions.append("Add theorem: phiCodon positive when numerator positive and denomSafe")
suggestions.append("Add theorem: deltaPhi zero when features and codon unchanged")
suggestions.append("Add theorem: beneficialMutation implies efficiency increase")
if analysis["formal_status"] == "noncomputable":
suggestions.append("Consider Q16_16 fixed-point version for hardware extraction")
suggestions.append("Add decidable approximations for arithmetic")
# Codon-specific suggestions
suggestions.append("Add concrete codon examples with actual base values")
suggestions.append("Add degeneracy function implementation (e.g., 1/2/3/4/6-fold)")
suggestions.append("Add translate function implementation (genetic code table)")
suggestions.append("Add #eval examples for phiCodon with toy parameters")
# Connection to OTOM
suggestions.append("Add theorem: phiCodon instantiates universal efficiency principle")
suggestions.append("Add theorem: CodonOTOM satisfies OTOM transformation structure")
return suggestions
def main():
"""Main entry point."""
print("=" * 70)
print("SWARM IMPROVEMENT SUGGESTIONS: CodonOTOM Module")
print("=" * 70)
# Get current entry
entry = get_codon_otom_entry()
if not entry:
print("ERROR: CodonOTOM entry not found in database")
return
print(f"\nCurrent Entry: {entry['name']} ({entry['entity_id']})")
print(f"Proof Status: {entry['proof_status']}")
print(f"Formal Status: {entry['formal_status']}")
print(f"Complexity Score: {entry['complexity_score']}")
# Analyze current state
analysis = analyze_current_state(entry)
print("\n" + "=" * 70)
print("COMPLETENESS ANALYSIS")
print("=" * 70)
print(f"\nOverall Completeness: {analysis['completeness']:.1%}")
if analysis['gaps']:
print(f"\nIdentified Gaps: {', '.join(analysis['gaps'])}")
# Generate swarm suggestions
suggestions = generate_swarm_improvement_suggestions(analysis)
print("\n" + "=" * 70)
print("SWARM IMPROVEMENT SUGGESTIONS")
print("=" * 70)
for i, suggestion in enumerate(suggestions, 1):
print(f"\n{i}. {suggestion}")
# Prioritize suggestions
high_priority = [s for s in suggestions if any(keyword in s for keyword in ["theorem", "Add theorem"])]
medium_priority = [s for s in suggestions if any(keyword in s for keyword in ["Q16_16", "fixed-point", "decidable"])]
low_priority = [s for s in suggestions if any(keyword in s for keyword in ["example", "eval"])]
print("\n" + "=" * 70)
print("PRIORITY ORDERING")
print("=" * 70)
print("\nHIGH PRIORITY (Core mathematical properties):")
for i, s in enumerate(high_priority[:5], 1):
print(f" {i}. {s}")
print("\nMEDIUM PRIORITY (Hardware extraction):")
for i, s in enumerate(medium_priority[:3], 1):
print(f" {i}. {s}")
print("\nLOW PRIORITY (Examples and verification):")
for i, s in enumerate(low_priority[:3], 1):
print(f" {i}. {s}")
# Save suggestions
output_file = "/home/allaun/Documents/Research Stack/data/swarm_codon_otom_improvement_suggestions.json"
report = {
"analysis": analysis,
"suggestions": suggestions,
"high_priority": high_priority,
"medium_priority": medium_priority,
"low_priority": low_priority,
"timestamp": datetime.now().isoformat()
}
with open(output_file, "w") as f:
json.dump(report, f, indent=2)
print(f"\nSuggestions saved to: {output_file}")
if __name__ == "__main__":
main()