#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ 行为模式识别模块 - 人物画像技能 分析行为在时间线上的规律 创建时间：2026-04-03 开发者：瞰宇 (Kàn Yǔ) """ import json from typing import Dict, List, Tuple, Optional from dataclasses import dataclass from collections import defaultdict from datetime import datetime @dataclass class ActionPattern: """行动模式""" radical_degree: str # 激进程度（低/中/高） confrontational: bool # 对抗性 exposure_preference: str # 曝光偏好（低调/高调） cooperation_style: str # 合作模式（共赢/零和） @dataclass class Adaptation: """适应性分析""" failure_response: str # 面对失败的反应 success_response: str # 面对成功的反应 criticism_response: str # 面对批评的反应 class BehaviorAnalyzer: """ 行为模式识别器 分析行为在时间线上的规律 """ def __init__(self): """初始化行为模式识别器""" self.behaviors = [] self.decisions = [] self.crisis_responses = [] def load_behaviors(self, behaviors: List[Dict]): """ 加载行为记录 Args: behaviors: 行为记录列表 """ self.behaviors = behaviors def load_decisions(self, decisions: List[Dict]): """ 加载决策案例 Args: decisions: 决策案例列表 """ self.decisions = decisions def load_crisis_responses(self, responses: List[Dict]): """ 加载危机应对记录 Args: responses: 危机应对记录列表 """ self.crisis_responses = responses def analyze_action_patterns(self) -> ActionPattern: """ 分析行动模式 Returns: ActionPattern对象 """ if not self.behaviors: return ActionPattern("中", False, "高调", "共赢") # 统计激进程度 radical_count = sum( 1 for b in self.behaviors if "激进" in b.get("description", "") or "突破" in b.get("description", "") ) moderate_count = sum( 1 for b in self.behaviors if "渐进" in b.get("description", "") or "稳健" in b.get("description", "") ) # 判断激进程度 if radical_count > moderate_count: radical_degree = "高" elif moderate_count > radical_count: radical_degree = "低" else: radical_degree = "中" # 判断对抗性 confrontational_keywords = ["对抗", "冲突", "抵制", "强硬"] confrontational_count = sum( 1 for b in self.behaviors if any(kw in b.get("description", "") for kw in confrontational_keywords) ) confrontational = confrontational_count > len(self.behaviors) * 0.4 # 判断曝光偏好 high_profile_keywords = ["演讲", "声明", "社媒", "采访", "发布会"] high_profile_count = sum( 1 for b in self.behaviors if any(kw in b.get("type", "") for kw in high_profile_keywords) ) exposure_preference = "高调" if high_profile_count > len(self.behaviors) * 0.5 else "低调" # 判断合作模式 cooperation_keywords = ["合作", "协商", "妥协", "双赢"] zero_sum_keywords = ["击败", "赢", "胜利", "压制"] cooperation_count = sum( 1 for b in self.behaviors if any(kw in b.get("description", "") for kw in cooperation_keywords) ) zero_sum_count = sum( 1 for b in self.behaviors if any(kw in b.get("description", "") for kw in zero_sum_keywords) ) if zero_sum_count > cooperation_count: cooperation_style = "零和" else: cooperation_style = "共赢" return ActionPattern( radical_degree=radical_degree, confrontational=confrontational, exposure_preference=exposure_preference, cooperation_style=cooperation_style ) def analyze_adaptation(self) -> Adaptation: """ 分析适应性 Returns: Adaptation对象 """ if not self.crisis_responses: return Adaptation("数据不足", "数据不足", "数据不足") # 面对失败的反应 failure_responses = [ r for r in self.crisis_responses if r.get("outcome") == "failure" or "失败" in r.get("outcome", "") ] if failure_responses: # 分析归因模式 external_blame_count = sum( 1 for r in failure_responses if "他人" in r.get("response", "") or "外部" in r.get("response", "") ) if external_blame_count > len(failure_responses) * 0.6: failure_response = "外归因（归咎于他人）" else: failure_response = "自我反思或承担" else: failure_response = "数据不足" # 面对成功的反应 success_responses = [ r for r in self.crisis_responses if r.get("outcome") == "success" or "成功" in r.get("outcome", "") ] if success_responses: self_attribution_count = sum( 1 for r in success_responses if "我" in r.get("response", "") or "个人" in r.get("response", "") ) if self_attribution_count > len(success_responses) * 0.6: success_response = "自归因（归功于个人）" else: success_response = "团队归因" else: success_response = "数据不足" # 面对批评的反应 criticism_responses = [ r for r in self.crisis_responses if "批评" in r.get("context", "") or "质疑" in r.get("context", "") ] if criticism_responses: confrontational_count = sum( 1 for r in criticism_responses if "反击" in r.get("response", "") or "否认" in r.get("response", "") ) if confrontational_count > len(criticism_responses) * 0.5: criticism_response = "对抗性回应" else: criticism_response = "协调性回应或忽略" else: criticism_response = "数据不足" return Adaptation( failure_response=failure_response, success_response=success_response, criticism_response=criticism_response ) def generate_behavior_report(self) -> Dict: """ 生成行为模式识别报告 Returns: 分析报告字典 """ # 分析行动模式 action_patterns = self.analyze_action_patterns() # 分析适应性 adaptation = self.analyze_adaptation() report = { "行动模式": { "激进程度": action_patterns.radical_degree, "对抗性": "是" if action_patterns.confrontational else "否", "曝光偏好": action_patterns.exposure_preference, "合作模式": action_patterns.cooperation_style }, "适应性分析": { "面对失败的反应": adaptation.failure_response, "面对成功的反应": adaptation.success_response, "面对批评的反应": adaptation.criticism_response }, "决策案例分析": [ { "决策": d.get("description", ""), "时间": d.get("date", ""), "影响": d.get("impact", "") } for d in self.decisions[:5] ] } return report def main(): """测试行为模式识别器""" analyzer = BehaviorAnalyzer() # 示例行为数据 behaviors = [ {"type": "演讲", "description": "发表突破性改革演讲", "date": "2024-01-01"}, {"type": "声明", "description": "对抗性声明，强硬回应", "date": "2024-02-15"}, {"type": "行动", "description": "渐进式政策调整", "date": "2024-03-10"} ] # 示例危机应对数据 crisis_responses = [ { "context": "政策失败", "outcome": "failure", "response": "归咎于前政府和外部环境" }, { "context": "项目成功", "outcome": "success", "response": "这是我的功劳，我领导了整个项目" }, { "context": "遭到媒体批评", "outcome": "neutral", "response": "反击媒体，称其为假新闻" } ] analyzer.load_behaviors(behaviors) analyzer.load_crisis_responses(crisis_responses) # 生成报告 print("=== 行为模式识别报告 ===") report = analyzer.generate_behavior_report() print(json.dumps(report, ensure_ascii=False, indent=2)) if __name__ == "__main__": main()