Atomizer/optimization_engine/plugins/post_extraction/optimization_logger_results.py

"""
Optimization-Level Logger Hook - Results

Appends trial results to the high-level optimization.log file.

Hook Point: post_extraction
"""

from pathlib import Path
from datetime import datetime
from typing import Dict, Any, Optional
import logging

logger = logging.getLogger(__name__)


def log_optimization_results(context: Dict[str, Any]) -> Optional[Dict[str, Any]]:
    """
    Append trial results to the main optimization.log file.

    This hook completes the trial entry in the high-level log with:
    - Objective values
    - Constraint evaluations
    - Trial outcome (feasible/infeasible)

    Args:
        context: Hook context containing:
            - trial_number: Current trial number
            - extracted_results: Dict of all extracted objectives and constraints
            - result_path: Path to result file

    Returns:
        None (logging only)
    """
    trial_num = context.get('trial_number', '?')
    extracted_results = context.get('extracted_results', {})
    result_path = context.get('result_path', '')

    # Get the output directory from context (passed by runner)
    output_dir = Path(context.get('output_dir', 'optimization_results'))
    log_file = output_dir / 'optimization.log'

    if not log_file.exists():
        logger.warning(f"Optimization log file not found: {log_file}")
        return None

    # Find the last line for this trial and append results
    with open(log_file, 'a') as f:
        timestamp = datetime.now().strftime('%H:%M:%S')

        # Extract objective and constraint values
        results_str = " | ".join([f"{name}={value:.3f}" for name, value in extracted_results.items()])

        f.write(f"[{timestamp}] Trial {trial_num:3d} COMPLETE | {results_str}\n")

    return None


def register_hooks(hook_manager):
    """
    Register this plugin's hooks with the manager.

    This function is called automatically when the plugin is loaded.
    """
    hook_manager.register_hook(
        hook_point='post_extraction',
        function=log_optimization_results,
        description='Append trial results to optimization.log',
        name='optimization_logger_results',
        priority=100
    )


# Hook metadata
HOOK_NAME = "optimization_logger_results"
HOOK_POINT = "post_extraction"
ENABLED = True
PRIORITY = 100