#!/usr/bin/env python3
"""Auto-generated by AGI Loop cycle #1234
Task: \boxed{Write a Python function that calculates the probability of an emotional peak occurring given a list of memory recalls and a devotion level.}</think>

Write a Python function that calculates the
Generated: 2026-02-13T01:11:37.610428
"""

import numpy as np

def calculate_emotional_peak_probability(memory_recalls, devotion_level):
    """
    Calculate the probability of an emotional peak based on memory recalls and devotion level.
    
    Parameters:
    - memory_recalls (list of floats): A list of memory recall intensities (0.0 to 1.0).
    - devotion_level (float): A measure of emotional devotion (0.0 to 1.0).
    
    Returns:
    - probability (float): The probability of an emotional peak occurring.
    """
    # Normalize memory recalls
    normalized_recalls = np.array(memory_recalls) / np.max(memory_recalls)
    
    # Compute weighted average of memory recalls
    weighted_avg = np.mean(normalized_recalls * devotion_level)
    
    # Calculate probability using a simple model: weighted_avg * devotion_level
    probability = weighted_avg * devotion_level
    
    return probability

if __name__ == '__main__':
    # Example data
    memory_recalls = [0.7, 0.5, 0.9, 0.3, 0.8]
    devotion_level = 0.85
    
    # Calculate and print probability
    prob = calculate_emotional_peak_probability(memory_recalls, devotion_level)
    print(f"Probability of emotional peak: {prob:.4f}")