# fuzzy_logic implementation FUZZY LOGIC system
import logging
from typing import Any, Dict, List, Callable

# Configure logging
logger = logging.getLogger(__name__)

class FUZZY_LOGIC:
    def __init__(self, input_vars: Dict[str, Callable[[int], Dict[str, float]]], 
                 output_vars: Dict[str, Callable[[Dict[str, float]], float]], 
                 rules: List[Callable[[Dict[str, float]], Dict[str, float]]]):
        """
        Initialize the Fuzzy Logic System with custom inputs, outputs, and rules.

        Parameters:
        - input_vars (Dict[str, Callable]): Dictionary of input variable names and their fuzzification functions.
        - output_vars (Dict[str, Callable]): Dictionary of output variable names and their defuzzification functions.
        - rules (List[Callable]): List of functions representing the fuzzy rules.
        """
        self.input_vars = input_vars
        self.output_vars = output_vars
        self.rules = rules
        logger.info("Fuzzy Logic System initialized with custom inputs, outputs, and rules.")

    def evaluate(self, input_values: Dict[str, int]) -> Dict[str, float]:
        """
        Evaluate the fuzzy logic system based on input values.

        Parameters:
        - input_values (Dict[str, int]): Dictionary with input variable names and their values.

        Returns:
        - Dict[str, float]: Dictionary with the defuzzified output values.
        """
        logger.info("Evaluating Fuzzy Logic System.")
        try:
            # Fuzzify inputs
            fuzzy_inputs = {var: self.input_vars[var](value) for var, value in input_values.items()}

            # Apply rules
            fuzzy_outputs = {}
            for rule in self.rules:
                rule_output = rule(fuzzy_inputs)
                for key, value in rule_output.items():
                    if key not in fuzzy_outputs:
                        fuzzy_outputs[key] = value
                    else:
                        fuzzy_outputs[key] = max(fuzzy_outputs[key], value)

            # Defuzzify outputs
            defuzzified_outputs = {var: self.output_vars[var](fuzzy_outputs) for var in self.output_vars}
            logger.info(f"Fuzzy Logic evaluation result: {defuzzified_outputs}")
            return defuzzified_outputs
        except Exception as e:
            logger.error(f"Error in Fuzzy Logic evaluation: {e}")
            return {}

    def recommend(self, input_values: Dict[str, int], top_n: int = 10) -> List[int]:
        """
        Recommend actions based on fuzzy logic evaluation.

        Parameters:
        - input_values (Dict[str, int]): Dictionary with input values for fuzzy evaluation.
        - top_n (int): Number of top recommendations to return.

        Returns:
        - List[int]: List of recommended actions (placeholder for actual implementation).
        """
        logger.info("Generating recommendations using Fuzzy Logic System.")
        evaluation = self.evaluate(input_values)
        # Example: Recommend actions based on evaluation
        # This requires a mapping from evaluation results to actions; here we return an empty list as a placeholder
        recommendations = []  # Implement logic based on the application
        logger.info(f"Top {top_n} recommendations generated using Fuzzy Logic.")
        return recommendations[:top_n]
