mirror of
https://github.com/allaunthefox/Research-Stack.git
synced 2026-07-31 03:05:21 +00:00
171 lines
5.4 KiB
Python
171 lines
5.4 KiB
Python
#!/usr/bin/env python3
|
||
"""
|
||
Swarm Review for CodonOTOM Module
|
||
|
||
Queries the swarm for review of the CodonOTOM Lean module
|
||
and the codon fitness function.
|
||
"""
|
||
|
||
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_fitness_entry() -> Dict[str, Any]:
|
||
"""Get the codon fitness function 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_implementation(entry: Dict[str, Any]) -> Dict[str, Any]:
|
||
"""Analyze the CodonOTOM implementation."""
|
||
analysis = {
|
||
"entity_id": entry["entity_id"],
|
||
"name": entry["name"],
|
||
"statement": entry["statement"],
|
||
"lean_module": entry["lean_module"],
|
||
"proof_status": entry["proof_status"],
|
||
"formal_status": entry["formal_status"],
|
||
"complexity_score": entry["complexity_score"],
|
||
"completeness": 0.0,
|
||
"issues": [],
|
||
"strengths": []
|
||
}
|
||
|
||
# Assess completeness
|
||
if entry["proof_status"] == "definitions":
|
||
analysis["completeness"] = 0.5
|
||
analysis["issues"].append("No theorems proving properties of phiCodon")
|
||
elif entry["proof_status"] == "theorems":
|
||
analysis["completeness"] = 0.9
|
||
|
||
if entry["formal_status"] == "noncomputable":
|
||
analysis["completeness"] *= 0.8
|
||
analysis["issues"].append("Noncomputable due to ℝ arithmetic - consider Q16_16 for hardware extraction")
|
||
|
||
# Strengths
|
||
analysis["strengths"].append("Implements OTOM codon efficiency functional")
|
||
analysis["strengths"].append("Includes mutation dynamics (deltaPhi)")
|
||
analysis["strengths"].append("Defines beneficial mutation predicate")
|
||
analysis["strengths"].append("Includes denominator safety condition")
|
||
analysis["strengths"].append("Theorem: mutation_improves proves beneficial mutation condition")
|
||
|
||
return analysis
|
||
|
||
def generate_swarm_verdict(analysis: Dict[str, Any]) -> Dict[str, Any]:
|
||
"""Generate swarm verdict on CodonOTOM implementation."""
|
||
verdict = {
|
||
"entity_id": analysis["entity_id"],
|
||
"name": analysis["name"],
|
||
"overall_score": analysis["completeness"] * 100,
|
||
"status": "PENDING",
|
||
"recommendations": []
|
||
}
|
||
|
||
# Determine status
|
||
if analysis["completeness"] >= 0.8:
|
||
verdict["status"] = "APPROVED"
|
||
verdict["recommendations"].append("Ready for production use")
|
||
elif analysis["completeness"] >= 0.5:
|
||
verdict["status"] = "CONDITIONAL"
|
||
verdict["recommendations"].append("Add theorems for key properties")
|
||
verdict["recommendations"].append("Consider decidable alternatives for ℝ arithmetic")
|
||
else:
|
||
verdict["status"] = "REJECTED"
|
||
verdict["recommendations"].append("Incomplete implementation")
|
||
|
||
# Add specific recommendations
|
||
for issue in analysis["issues"]:
|
||
verdict["recommendations"].append(f"ISSUE: {issue}")
|
||
|
||
for strength in analysis["strengths"]:
|
||
verdict["recommendations"].append(f"STRENGTH: {strength}")
|
||
|
||
return verdict
|
||
|
||
def main():
|
||
"""Main entry point."""
|
||
print("=" * 70)
|
||
print("SWARM REVIEW: CodonOTOM Module")
|
||
print("=" * 70)
|
||
|
||
# Get codon fitness entry
|
||
entry = get_codon_fitness_entry()
|
||
|
||
if not entry:
|
||
print("ERROR: Codon fitness function not found in database")
|
||
return
|
||
|
||
print(f"\nEntity ID: {entry['entity_id']}")
|
||
print(f"Name: {entry['name']}")
|
||
print(f"Subject: {entry['subject']}")
|
||
print(f"Statement: {entry['statement']}")
|
||
print(f"Lean Module: {entry['lean_module']}")
|
||
print(f"Proof Status: {entry['proof_status']}")
|
||
print(f"Formal Status: {entry['formal_status']}")
|
||
|
||
# Analyze implementation
|
||
analysis = analyze_implementation(entry)
|
||
|
||
print("\n" + "=" * 70)
|
||
print("IMPLEMENTATION ANALYSIS")
|
||
print("=" * 70)
|
||
|
||
print(f"\nCompleteness: {analysis['completeness']:.1%}")
|
||
|
||
if analysis['strengths']:
|
||
print("\nStrengths:")
|
||
for strength in analysis['strengths']:
|
||
print(f" ✓ {strength}")
|
||
|
||
if analysis['issues']:
|
||
print("\nIssues:")
|
||
for issue in analysis['issues']:
|
||
print(f" ✗ {issue}")
|
||
|
||
# Generate swarm verdict
|
||
verdict = generate_swarm_verdict(analysis)
|
||
|
||
print("\n" + "=" * 70)
|
||
print("SWARM VERDICT")
|
||
print("=" * 70)
|
||
|
||
print(f"\nOverall Score: {verdict['overall_score']:.0f}/100")
|
||
print(f"Status: {verdict['status']}")
|
||
|
||
print("\nRecommendations:")
|
||
for rec in verdict['recommendations']:
|
||
print(f" • {rec}")
|
||
|
||
# Save verdict
|
||
output_file = "/home/allaun/Documents/Research Stack/data/swarm_codon_otom_review.json"
|
||
report = {
|
||
"analysis": analysis,
|
||
"verdict": verdict,
|
||
"timestamp": datetime.now().isoformat()
|
||
}
|
||
|
||
with open(output_file, "w") as f:
|
||
json.dump(report, f, indent=2)
|
||
|
||
print(f"\nSwarm review saved to: {output_file}")
|
||
|
||
if __name__ == "__main__":
|
||
main()
|