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Atomizer/optimization_engine/plugins/post_calculation/safety_factor_hook.py

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2025-11-16 16:33:48 -05:00
"""
Calculate safety factor
Auto-generated lifecycle hook by Atomizer Phase 2.9
Hook Point: post_calculation
Inputs: max_stress, yield_strength
Outputs: safety_factor
"""
import logging
from typing import Dict, Any, Optional
logger = logging.getLogger(__name__)
def safety_factor_hook(context: Dict[str, Any]) -> Optional[Dict[str, Any]]:
"""
Calculate safety factor
Args:
context: Hook context containing:
- trial_number: Current optimization trial
- results: Dictionary with extracted FEA results
- calculations: Dictionary with inline calculation results
Returns:
Dictionary with calculated values to add to context
"""
logger.info(f"Executing safety_factor_hook for trial {context.get('trial_number', 'unknown')}")
# Extract inputs from context
results = context.get('results', {})
calculations = context.get('calculations', {})
max_stress = calculations.get('max_stress') or results.get('max_stress')
if max_stress is None:
logger.error(f"Required input 'max_stress' not found in context")
raise ValueError(f"Missing required input: max_stress")
yield_strength = calculations.get('yield_strength') or results.get('yield_strength')
if yield_strength is None:
logger.error(f"Required input 'yield_strength' not found in context")
raise ValueError(f"Missing required input: yield_strength")
# Calculate using custom formula
safety_factor = yield_strength / max_stress
logger.info(f"safety_factor = {safety_factor:.6f}")
return {
'safety_factor': safety_factor
}
def register_hooks(hook_manager):
"""
Register this hook with the HookManager.
This function is called automatically when the plugin is loaded.
Args:
hook_manager: The HookManager instance
"""
hook_manager.register_hook(
hook_point='post_calculation',
function=safety_factor_hook,
description="Calculate safety factor",
name="safety_factor_hook",
priority=100,
enabled=True
)
logger.info(f"Registered safety_factor_hook at post_calculation")