161_艺术创作：LLM辅助音乐与绘画 - 2025年跨模态生成的创意链分析与实现技术研究

class CrossModalArtCreationSystem:
    """
    跨模态艺术创作系统的核心框架
    整合LLM、音乐生成和视觉生成技术
    """
    def __init__(self, llm_model_name="gpt-5", music_generator="musicgen-3", 
                 visual_generator="dalle-4"):
        """
        初始化跨模态艺术创作系统
        
        参数:
        llm_model_name: 使用的LLM模型名称
        music_generator: 音乐生成模型名称
        visual_generator: 视觉生成模型名称
        """
        # 初始化LLM模型
        self.llm = self._load_llm_model(llm_model_name)
        
        # 初始化音乐生成器
        self.music_generator = self._load_music_generator(music_generator)
        
        # 初始化视觉生成器
        self.visual_generator = self._load_visual_generator(visual_generator)
        
        # 初始化模态映射模块
        self.modal_mapper = self._initialize_modal_mapper()
        
        # 初始化创意链管理器
        self.creative_chain_manager = CreativeChainManager()
        
        print(f"跨模态艺术创作系统已初始化\n" 
              f"LLM模型: {llm_model_name}\n" 
              f"音乐生成器: {music_generator}\n" 
              f"视觉生成器: {visual_generator}")
    
    def _load_llm_model(self, model_name):
        """
        加载LLM模型
        
        参数:
        model_name: 模型名称
        
        返回:
        初始化的LLM模型实例
        """
        # 示例实现，实际应用中需要根据具体模型API进行适配
        print(f"加载LLM模型: {model_name}")
        # 模拟LLM模型加载
        return type('LLMModel', (), {
            'generate': lambda self, prompt, **kwargs: f"生成内容基于提示: {prompt}",
            'embed': lambda self, text: [0.1] * 1024  # 模拟嵌入向量
        })()
    
    def _load_music_generator(self, generator_name):
        """
        加载音乐生成器
        
        参数:
        generator_name: 生成器名称
        
        返回:
        初始化的音乐生成器实例
        """
        print(f"加载音乐生成器: {generator_name}")
        # 模拟音乐生成器加载
        return type('MusicGenerator', (), {
            'generate_from_text': lambda self, text_prompt, duration=30: 
                f"音乐生成基于文本提示: {text_prompt}, 时长: {duration}秒",
            'generate_from_image': lambda self, image, duration=30: 
                f"音乐生成基于图像, 时长: {duration}秒",
            'analyze_music': lambda self, music_data: {
                'emotion': 'happy',
                'style': 'classical',
                'tempo': 120,
                'key': 'C major'
            }
        })()
    
    def _load_visual_generator(self, generator_name):
        """
        加载视觉生成器
        
        参数:
        generator_name: 生成器名称
        
        返回:
        初始化的视觉生成器实例
        """
        print(f"加载视觉生成器: {generator_name}")
        # 模拟视觉生成器加载
        return type('VisualGenerator', (), {
            'generate_from_text': lambda self, text_prompt, style=None: 
                f"图像生成基于文本提示: {text_prompt}, 风格: {style}",
            'generate_from_music': lambda self, music_data, style=None: 
                f"图像生成基于音乐数据, 风格: {style}",
            'analyze_image': lambda self, image_data: {
                'emotion': 'serene',
                'style': 'impressionist',
                'color_palette': ['#87CEEB', '#90EE90', '#F0E68C'],
                'composition': 'landscape'
            }
        })()
    
    def _initialize_modal_mapper(self):
        """
        初始化模态映射模块
        
        返回:
        模态映射模块实例
        """
        # 模拟模态映射模块初始化
        return type('ModalMapper', (), {
            'music_to_visual': lambda self, music_features: {
                'emotion': music_features['emotion'],
                'color_palette': self._map_emotion_to_colors(music_features['emotion']),
                'composition': self._map_music_style_to_composition(music_features['style'])
            },
            'visual_to_music': lambda self, visual_features: {
                'emotion': visual_features['emotion'],
                'style': self._map_visual_style_to_music_style(visual_features['style']),
                'tempo': self._map_colors_to_tempo(visual_features['color_palette'])
            },
            '_map_emotion_to_colors': lambda self, emotion: {
                'happy': ['#FFD700', '#FF6347', '#4682B4'],
                'sad': ['#6A5ACD', '#708090', '#B0C4DE'],
                'angry': ['#FF0000', '#FF4500', '#DC143C'],
                'calm': ['#00CED1', '#98FB98', '#87CEEB']
            }.get(emotion, ['#808080', '#A9A9A9', '#C0C0C0']),
            '_map_music_style_to_composition': lambda self, style: {
                'classical': 'symmetrical',
                'jazz': 'improvisational',
                'rock': 'dynamic',
                'electronic': 'abstract'
            }.get(style, 'balanced'),
            '_map_visual_style_to_music_style': lambda self, style: {
                'impressionist': 'classical',
                'cubist': 'jazz',
                'expressionist': 'rock',
                'abstract': 'electronic'
            }.get(style, 'contemporary'),
            '_map_colors_to_tempo': lambda self, colors: {
                'warm': 120,
                'cool': 80,
                'neutral': 100
            }[self._classify_color_temperature(colors)],
            '_classify_color_temperature': lambda self, colors: 'neutral'  # 简化实现
        })()
    
    def music_to_visual(self, music_input, style=None, iterations=1):
        """
        音乐到视觉的跨模态生成
        
        参数:
        music_input: 音乐输入(可以是音频数据或音乐描述)
        style: 目标视觉风格
        iterations: 创意迭代次数
        
        返回:
        生成的视觉内容和创意链记录
        """
        # 1. 分析音乐特征
        music_features = self.music_generator.analyze_music(music_input)
        
        # 2. 映射到视觉特征
        visual_features = self.modal_mapper.music_to_visual(music_features)
        
        # 3. 使用LLM生成详细的视觉描述
        llm_prompt = f"基于以下音乐特征创建详细的视觉艺术描述:\n"
        llm_prompt += f"音乐情感: {music_features['emotion']}\n"
        llm_prompt += f"音乐风格: {music_features['style']}\n"
        llm_prompt += f"音乐节奏: {music_features['tempo']} BPM\n"
        llm_prompt += f"建议色彩: {', '.join(visual_features['color_palette'])}\n"
        llm_prompt += f"建议构图: {visual_features['composition']}\n"
        if style:
            llm_prompt += f"指定风格: {style}\n"
        
        visual_description = self.llm.generate(llm_prompt)
        
        # 4. 使用视觉生成器创建图像
        generated_image = self.visual_generator.generate_from_text(
            visual_description, style=style
        )
        
        # 5. 记录创意链
        creative_chain = {
            'input_type': 'music',
            'input_data': str(music_input),
            'music_features': music_features,
            'visual_features': visual_features,
            'llm_prompt': llm_prompt,
            'visual_description': visual_description,
            'output_image': generated_image,
            'timestamp': datetime.now().isoformat()
        }
        
        self.creative_chain_manager.add_chain(creative_chain)
        
        return generated_image, creative_chain
    
    def visual_to_music(self, visual_input, duration=30, style=None, iterations=1):
        """
        视觉到音乐的跨模态生成
        
        参数:
        visual_input: 视觉输入(可以是图像数据或图像描述)
        duration: 生成音乐的时长(秒)
        style: 目标音乐风格
        iterations: 创意迭代次数
        
        返回:
        生成的音乐内容和创意链记录
        """
        # 1. 分析视觉特征
        visual_features = self.visual_generator.analyze_image(visual_input)
        
        # 2. 映射到音乐特征
        music_features = self.modal_mapper.visual_to_music(visual_features)
        
        # 3. 使用LLM生成详细的音乐描述
        llm_prompt = f"基于以下视觉特征创建详细的音乐创作描述:\n"
        llm_prompt += f"视觉情感: {visual_features['emotion']}\n"
        llm_prompt += f"视觉风格: {visual_features['style']}\n"
        llm_prompt += f"色彩 palette: {', '.join(visual_features['color_palette'])}\n"
        llm_prompt += f"构图类型: {visual_features['composition']}\n"
        llm_prompt += f"建议音乐情感: {music_features['emotion']}\n"
        if style:
            llm_prompt += f"指定音乐风格: {style}\n"
        else:
            llm_prompt += f"建议音乐风格: {music_features['style']}\n"
        llm_prompt += f"建议节奏: {music_features['tempo']} BPM\n"
        llm_prompt += f"音乐时长: {duration}秒\n"
        
        music_description = self.llm.generate(llm_prompt)
        
        # 4. 使用音乐生成器创建音乐
        generated_music = self.music_generator.generate_from_text(
            music_description, duration=duration
        )
        
        # 5. 记录创意链
        creative_chain = {
            'input_type': 'visual',
            'input_data': str(visual_input),
            'visual_features': visual_features,
            'music_features': music_features,
            'llm_prompt': llm_prompt,
            'music_description': music_description,
            'output_music': generated_music,
            'timestamp': datetime.now().isoformat()
        }
        
        self.creative_chain_manager.add_chain(creative_chain)
        
        return generated_music, creative_chain
    
    def interactive_creative_process(self, initial_input, modality='music', 
                                     iterations=3, style_evolution=True):
        """
        交互式创意演化过程
        
        参数:
        initial_input: 初始输入内容
        modality: 初始输入模态('music'或'visual')
        iterations: 交互迭代次数
        style_evolution: 是否启用风格演化
        
        返回:
        创意演化过程中的所有作品和创意链记录
        """
        results = []
        current_input = initial_input
        current_modality = modality
        
        for i in range(iterations):
            print(f"\n创意迭代 {i+1}/{iterations}")
            
            if current_modality == 'music':
                # 音乐到视觉
                output, chain = self.music_to_visual(
                    current_input,
                    style=StyleEvolution.get_next_style(i) if style_evolution else None
                )
                current_modality = 'visual'
            else:
                # 视觉到音乐
                output, chain = self.visual_to_music(
                    current_input,
                    duration=30,
                    style=StyleEvolution.get_next_style(i) if style_evolution else None
                )
                current_modality = 'music'
            
            results.append({
                'iteration': i+1,
                'input_modality': 'music' if current_modality == 'visual' else 'visual',
                'output_modality': current_modality,
                'output': output,
                'chain': chain
            })
            
            current_input = output
        
        return results

class CreativeChainManager:
    """
    创意链管理器，负责记录和管理跨模态创意过程
    """
    def __init__(self):
        """
        初始化创意链管理器
        """
        self.chains = []
        self.chain_id_counter = 0
    
    def add_chain(self, chain_data):
        """
        添加创意链记录
        
        参数:
        chain_data: 创意链数据
        
        返回:
        创意链ID
        """
        chain_id = f"chain_{self.chain_id_counter}"
        chain_data['chain_id'] = chain_id
        self.chains.append(chain_data)
        self.chain_id_counter += 1
        return chain_id
    
    def get_chain(self, chain_id):
        """
        获取特定创意链记录
        
        参数:
        chain_id: 创意链ID
        
        返回:
        创意链数据或None
        """
        for chain in self.chains:
            if chain.get('chain_id') == chain_id:
                return chain
        return None
    
    def get_all_chains(self):
        """
        获取所有创意链记录
        
        返回:
        创意链列表
        """
        return self.chains
    
## 3. 音乐与绘画的跨模态语义映射

### 3.1 情感映射机制研究

情感是音乐和绘画创作中最核心的表达方式之一，也是跨模态映射中最基础的桥梁。2025年的研究表明，成功的跨模态艺术创作很大程度上依赖于精准的情感映射机制。

#### 3.1.1 情感空间模型

为了实现音乐和绘画之间的情感映射，我们需要建立一个统一的情感空间模型。这一模型通常基于以下几个维度：

1. **效价-唤醒度模型(PAD模型)**：
   - 效价(Pleasure)：情感的积极或消极程度
   - 唤醒度(Arousal)：情感的强度或激活程度
   - 支配度(Dominance)：情感的控制或被控制程度

2. **基础情感分类**：
   - 基本情感：快乐、悲伤、愤怒、恐惧、惊讶、厌恶等
   - 复合情感：通过基础情感组合而成的复杂情感状态

3. **情感强度量化**：
   - 使用数值范围(如0-10或-5到+5)量化情感强度
   - 考虑情感的动态变化和时间维度

#### 3.1.2 音乐情感特征提取

音乐情感特征的提取是情感映射的第一步，主要涉及以下技术：

```python
class MusicEmotionExtractor:
    """
    音乐情感特征提取器
    负责从音乐中提取情感相关特征
    """
    def __init__(self):
        """
        初始化音乐情感提取器
        """
        # 加载预训练的音频特征提取模型
        self.audio_feature_extractor = self._load_audio_feature_extractor()
        # 加载情感分类器
        self.emotion_classifier = self._load_emotion_classifier()
        # 加载情感强度回归器
        self.emotion_intensity_regressor = self._load_emotion_intensity_regressor()
    
    def _load_audio_feature_extractor(self):
        """
        加载音频特征提取器
        
        返回:
        音频特征提取器实例
        """
        # 模拟音频特征提取器
        return type('AudioFeatureExtractor', (), {
            'extract': lambda self, audio_data: {
                'tempo': 120,  # 速度
                'key': 'C major',  # 调性
                'energy': 0.7,  # 能量
                'valence': 0.8,  # 积极度
                'danceability': 0.6,  # 舞曲性
                'acousticness': 0.4,  # 原声性
                'instrumentalness': 0.9,  # 器乐性
                'liveness': 0.2,  # 现场感
                'speechiness': 0.1,  # 语音性
                'spectral_centroid': 2500,  # 频谱中心
                'spectral_bandwidth': 3000,  # 频谱带宽
                'spectral_rolloff': 4000,  # 频谱衰减点
                'mfcc': [0.1, 0.2, -0.3, 0.4, -0.5, 0.6, -0.7, 0.8, -0.9, 1.0]  # MFCC系数
            }
        })()
    
    def _load_emotion_classifier(self):
        """
        加载情感分类器
        
        返回:
        情感分类器实例
        """
        # 模拟情感分类器
        return type('EmotionClassifier', (), {
            'classify': lambda self, features: {
                'primary_emotion': 'happy',
                'secondary_emotion': 'excited',
                'confidence': 0.92
            }
        })()
    
    def _load_emotion_intensity_regressor(self):
        """
        加载情感强度回归器
        
        返回:
        情感强度回归器实例
        """
        # 模拟情感强度回归器
        return type('EmotionIntensityRegressor', (), {
            'predict': lambda self, features: {
                'pleasure': 8.2,  # 效价: 0-10
                'arousal': 7.5,   # 唤醒度: 0-10
                'dominance': 6.8  # 支配度: 0-10
            }
        })()
    
    def extract_emotion_features(self, music_data):
        """
        从音乐数据中提取情感特征
        
        参数:
        music_data: 音乐数据(音频文件路径或音频流)
        
        返回:
        情感特征字典
        """
        # 1. 提取音频特征
        audio_features = self.audio_feature_extractor.extract(music_data)
        
        # 2. 情感分类
        emotion_classification = self.emotion_classifier.classify(audio_features)
        
        # 3. 情感强度预测
        emotion_intensity = self.emotion_intensity_regressor.predict(audio_features)
        
        # 4. 综合特征
        emotion_features = {
            **audio_features,
            **emotion_classification,
            **emotion_intensity,
            'timestamp': datetime.now().isoformat()
        }
        
        return emotion_features
    
    def extract_temporal_emotion(self, music_data, segment_length=30):
        """
        提取音乐的时间序列情感变化
        
        参数:
        music_data: 音乐数据
        segment_length: 分段长度(秒)
        
        返回:
        时间序列情感特征列表
        """
        # 模拟时间序列情感提取
        temporal_emotions = []
        # 假设音乐时长为180秒(3分钟)
        for i in range(0, 180, segment_length):
            # 为每个时间段提取特征
            segment_features = self.extract_emotion_features(music_data)
            segment_features['time_segment'] = f"{i}-{i+segment_length}s"
            temporal_emotions.append(segment_features)
        
        return temporal_emotions

class VisualEmotionExtractor:
    """
    视觉情感特征提取器
    负责从图像中提取情感相关特征
    """
    def __init__(self):
        """
        初始化视觉情感提取器
        """
        # 加载预训练的视觉特征提取模型
        self.visual_feature_extractor = self._load_visual_feature_extractor()
        # 加载情感分类器
        self.emotion_classifier = self._load_emotion_classifier()
        # 加载情感强度回归器
        self.emotion_intensity_regressor = self._load_emotion_intensity_regressor()
        # 加载色彩分析器
        self.color_analyzer = self._load_color_analyzer()
    
    def _load_visual_feature_extractor(self):
        """
        加载视觉特征提取器
        
        返回:
        视觉特征提取器实例
        """
        # 模拟视觉特征提取器
        return type('VisualFeatureExtractor', (), {
            'extract': lambda self, image_data: {
                'composition_balance': 0.7,  # 构图平衡度
                'complexity': 0.6,            # 复杂度
                'contrast': 0.8,              # 对比度
                'brightness': 0.7,            # 亮度
                'sharpness': 0.8,             # 清晰度
                'symmetry': 0.6,              # 对称性
                'dynamic_range': 0.7,         # 动态范围
                'edges': 450,                 # 边缘数量
                'textures': ['smooth', 'rough'],  # 纹理类型
                'subject_focus': 0.9,         # 主体聚焦度
                'depth_perception': 0.8       # 深度感知
            }
        })()
    
    def _load_emotion_classifier(self):
        """
        加载情感分类器
        
        返回:
        情感分类器实例
        """
        # 模拟情感分类器
        return type('EmotionClassifier', (), {
            'classify': lambda self, features: {
                'primary_emotion': 'serene',
                'secondary_emotion': 'peaceful',
                'confidence': 0.88
            }
        })()
    
    def _load_emotion_intensity_regressor(self):
        """
        加载情感强度回归器
        
        返回:
        情感强度回归器实例
        """
        # 模拟情感强度回归器
        return type('EmotionIntensityRegressor', (), {
            'predict': lambda self, features: {
                'pleasure': 7.8,  # 效价: 0-10
                'arousal': 4.5,   # 唤醒度: 0-10
                'dominance': 6.2  # 支配度: 0-10
            }
        })()
    
    def _load_color_analyzer(self):
        """
        加载色彩分析器
        
        返回:
        色彩分析器实例
        """
        # 模拟色彩分析器
        return type('ColorAnalyzer', (), {
            'analyze': lambda self, image_data: {
                'dominant_colors': ['#4682B4', '#00CED1', '#87CEEB'],  # 主色调
                'color_palette': {
                    'warm_colors': ['#FFD700', '#FF6347'],
                    'cool_colors': ['#4682B4', '#00CED1', '#87CEEB'],
                    'neutral_colors': ['#F5F5DC', '#A9A9A9']
                },
                'hue_distribution': {
                    'red': 0.1,
                    'orange': 0.05,
                    'yellow': 0.1,
                    'green': 0.15,
                    'blue': 0.4,
                    'indigo': 0.1,
                    'violet': 0.05,
                    'neutral': 0.05
                },
                'saturation': 0.6,  # 饱和度
                'brightness': 0.7,  # 亮度
                'contrast': 0.75,   # 对比度
                'color_harmony': 'complementary'  # 色彩和谐类型
            }
        })()
    
    def extract_emotion_features(self, image_data):
        """
        从图像数据中提取情感特征
        
        参数:
        image_data: 图像数据(文件路径或图像流)
        
        返回:
        情感特征字典
        """
        # 1. 提取视觉特征
        visual_features = self.visual_feature_extractor.extract(image_data)
        
        # 2. 分析色彩特征
        color_features = self.color_analyzer.analyze(image_data)
        
        # 3. 情感分类
        emotion_classification = self.emotion_classifier.classify({
            **visual_features,
            **color_features
        })
        
        # 4. 情感强度预测
        emotion_intensity = self.emotion_intensity_regressor.predict({
            **visual_features,
            **color_features
        })
        
        # 5. 综合特征
        emotion_features = {
            **visual_features,
            **color_features,
            **emotion_classification,
            **emotion_intensity,
            'timestamp': datetime.now().isoformat()
        }
        
        return emotion_features

class CrossModalEmotionMapper:
    """
    跨模态情感映射器
    实现音乐和视觉艺术之间的情感转换
    """
    def __init__(self):
        """
        初始化跨模态情感映射器
        """
        # 初始化音乐情感提取器
        self.music_emotion_extractor = MusicEmotionExtractor()
        # 初始化视觉情感提取器
        self.visual_emotion_extractor = VisualEmotionExtractor()
        # 加载跨模态映射矩阵
        self.emotion_mapping_matrix = self._load_emotion_mapping_matrix()
        # 初始化LLM用于生成详细描述
        self.llm = self._load_llm()
    
    def _load_emotion_mapping_matrix(self):
        """
        加载情感映射矩阵
        这是一个预定义的矩阵，用于指导不同模态间的情感映射
        
        返回:
        情感映射矩阵
        """
        # 简化的情感映射矩阵
        return {
            # 音乐情感到视觉表达的映射
            'music_to_visual': {
                'happy': {
                    'colors': ['#FFD700', '#FF6347', '#FFA500'],
                    'composition': 'dynamic',
                    'lighting': 'bright',
                    'subjects': ['nature', 'people', 'abstract']
                },
                'sad': {
                    'colors': ['#6A5ACD', '#708090', '#B0C4DE'],
                    'composition': 'asymmetrical',
                    'lighting': 'dim',
                    'subjects': ['landscape', 'water', 'alone']
                },
                'angry': {
                    'colors': ['#FF0000', '#FF4500', '#DC143C'],
                    'composition': 'chaotic',
                    'lighting': 'high contrast',
                    'subjects': ['fire', 'storm', 'conflict']
                },
                'calm': {
                    'colors': ['#00CED1', '#98FB98', '#87CEEB'],
                    'composition': 'balanced',
                    'lighting': 'soft',
                    'subjects': ['water', 'sky', 'nature']
                }
                # 可以扩展更多情感映射
            },
            # 视觉情感到音乐表达的映射
            'visual_to_music': {
                'serene': {
                    'tempo': 'slow',  # 60-80 BPM
                    'key': 'major',
                    'instrumentation': ['piano', 'violin', 'flute'],
                    'dynamics': 'soft',
                    'rhythm': 'smooth',
                    'genre': 'classical, ambient'
                },
                'excited': {
                    'tempo': 'fast',  # 120-140 BPM
                    'key': 'major',
                    'instrumentation': ['drums', 'guitar', 'brass'],
                    'dynamics': 'loud',
                    'rhythm': 'complex',
                    'genre': 'rock, electronic'
                },
                'melancholy': {
                    'tempo': 'slow',  # 60-80 BPM
                    'key': 'minor',
                    'instrumentation': ['cello', 'acoustic guitar', 'piano'],
                    'dynamics': 'soft',
                    'rhythm': 'simple',
                    'genre': 'classical, folk'
                },
                'dramatic': {
                    'tempo': 'moderate',  # 90-110 BPM
                    'key': 'minor',
                    'instrumentation': ['orchestra', 'choir', 'percussion'],
                    'dynamics': 'varying',
                    'rhythm': 'complex',
                    'genre': 'classical, film score'
                }
                # 可以扩展更多情感映射
            }
        }
    
    def _load_llm(self):
        """
        加载LLM用于生成详细描述
        
        返回:
        LLM实例
        """
        # 模拟LLM
        return type('LLM', (), {
            'generate': lambda self, prompt, **kwargs: 
                f"基于提示生成的详细描述: {prompt[:50]}..."
        })()
    
    def map_music_to_visual_emotion(self, music_data):
        """
        将音乐情感映射到视觉表达
        
        参数:
        music_data: 音乐数据
        
        返回:
        视觉情感表达特征
        """
        # 1. 提取音乐情感特征
        music_emotion = self.music_emotion_extractor.extract_emotion_features(music_data)
        
        # 2. 获取主要情感
        primary_emotion = music_emotion['primary_emotion']
        
        # 3. 查询映射矩阵
        mapping_template = self.emotion_mapping_matrix['music_to_visual'].get(
            primary_emotion, 
            self.emotion_mapping_matrix['music_to_visual']['calm']  # 默认映射
        )
        
        # 4. 调整映射参数基于情感强度
        mapped_features = self._adjust_mapping_based_intensity(
            mapping_template, 
            music_emotion['pleasure'],
            music_emotion['arousal'],
            music_emotion['dominance']
        )
        
        # 5. 使用LLM生成详细描述
        llm_prompt = self._create_visual_prompt(primary_emotion, mapped_features, music_emotion)
        visual_description = self.llm.generate(llm_prompt)
        
        # 6. 返回映射结果
        result = {
            'music_emotion': music_emotion,
            'visual_features': mapped_features,
            'visual_description': visual_description,
            'mapping_strategy': 'emotion_based',
            'confidence': 0.85 + (music_emotion['confidence'] * 0.15)  # 映射可信度
        }
        
        return result
    
    def map_visual_to_music_emotion(self, visual_data):
        """
        将视觉情感映射到音乐表达
        
        参数:
        visual_data: 视觉数据
        
        返回:
        音乐情感表达特征
        """
        # 1. 提取视觉情感特征
        visual_emotion = self.visual_emotion_extractor.extract_emotion_features(visual_data)
        
        # 2. 获取主要情感
        primary_emotion = visual_emotion['primary_emotion']
        
        # 3. 查询映射矩阵
        mapping_template = self.emotion_mapping_matrix['visual_to_music'].get(
            primary_emotion, 
            self.emotion_mapping_matrix['visual_to_music']['serene']  # 默认映射
        )
        
        # 4. 调整映射参数基于情感强度
        mapped_features = self._adjust_mapping_based_intensity(
            mapping_template, 
            visual_emotion['pleasure'],
            visual_emotion['arousal'],
            visual_emotion['dominance']
        )
        
        # 5. 结合色彩特征调整音乐参数
        color_adjusted_features = self._adjust_music_based_on_color(
            mapped_features, 
            visual_emotion['color_palette'],
            visual_emotion['saturation'],
            visual_emotion['brightness']
        )
        
        # 6. 使用LLM生成详细描述
        llm_prompt = self._create_music_prompt(primary_emotion, color_adjusted_features, visual_emotion)
        music_description = self.llm.generate(llm_prompt)
        
        # 7. 返回映射结果
        result = {
            'visual_emotion': visual_emotion,
            'music_features': color_adjusted_features,
            'music_description': music_description,
            'mapping_strategy': 'emotion_and_color_based',
            'confidence': 0.85 + (visual_emotion['confidence'] * 0.15)  # 映射可信度
        }
        
        return result
    
    def _adjust_mapping_based_intensity(self, base_mapping, pleasure, arousal, dominance):
        """
        根据情感强度调整映射参数
        
        参数:
        base_mapping: 基础映射参数
        pleasure: 效价强度(0-10)
        arousal: 唤醒度强度(0-10)
        dominance: 支配度强度(0-10)
        
        返回:
        调整后的映射参数
        """
        # 创建副本以避免修改原始数据
        adjusted = dict(base_mapping)
        
        # 简化示例: 根据唤醒度调整某些参数
        if 'tempo' in adjusted:
            if arousal < 4:  # 低唤醒度
                adjusted['tempo'] = 'slow'
            elif arousal < 7:  # 中等唤醒度
                adjusted['tempo'] = 'moderate'
            else:  # 高唤醒度
                adjusted['tempo'] = 'fast'
        
        # 根据效价调整色彩(如果适用)
        if 'colors' in adjusted:
            # 简单模拟: 效价高时选择更明亮的颜色变体
            if pleasure > 7:
                # 这里应该实现具体的颜色亮度调整
                pass
        
        # 添加情感强度信息
        adjusted['emotion_intensity'] = {
            'pleasure': pleasure,
            'arousal': arousal,
            'dominance': dominance
        }
        
        return adjusted
    
    def _adjust_music_based_on_color(self, music_features, color_palette, saturation, brightness):
        """
        根据色彩特征调整音乐参数
        
        参数:
        music_features: 音乐特征
        color_palette: 色彩调色板
        saturation: 色彩饱和度
        brightness: 色彩亮度
        
        返回:
        调整后的音乐特征
        """
        # 创建副本以避免修改原始数据
        adjusted = dict(music_features)
        
        # 简化示例: 根据色彩温度调整音乐特性
        has_warm_colors = len(color_palette.get('warm_colors', [])) > 0
        has_cool_colors = len(color_palette.get('cool_colors', [])) > 0
        
        if has_warm_colors and not has_cool_colors:
            # 暖色调: 可能更适合欢快、活泼的音乐
            if 'dynamics' in adjusted:
                adjusted['dynamics'] = 'bright'
            if 'instrumentation' in adjusted and isinstance(adjusted['instrumentation'], list):
                # 确保包含明亮的乐器
                for instrument in ['trumpet', 'saxophone', 'piano']:
                    if instrument not in adjusted['instrumentation']:
                        adjusted['instrumentation'].append(instrument)
        elif has_cool_colors and not has_warm_colors:
            # 冷色调: 可能更适合平静、沉思的音乐
            if 'dynamics' in adjusted:
                adjusted['dynamics'] = 'soft'
            if 'instrumentation' in adjusted and isinstance(adjusted['instrumentation'], list):
                # 确保包含柔和的乐器
                for instrument in ['flute', 'cello', 'ambient pads']:
                    if instrument not in adjusted['instrumentation']:
                        adjusted['instrumentation'].append(instrument)
        
        # 根据饱和度调整复杂度
        if saturation > 0.7:
            if 'rhythm' in adjusted:
                adjusted['rhythm'] = 'complex'
        elif saturation < 0.3:
            if 'rhythm' in adjusted:
                adjusted['rhythm'] = 'simple'
        
        return adjusted
    
    def _create_visual_prompt(self, emotion, visual_features, music_context):
        """
        创建视觉描述提示
        
        参数:
        emotion: 情感类型
        visual_features: 视觉特征
        music_context: 音乐上下文信息
        
        返回:
        详细的视觉描述提示
        """
        prompt = f"创建一幅表达'{emotion}'情感的视觉艺术作品。"
        prompt += f"作品应该体现以下特征：\n"
        
        if 'colors' in visual_features:
            prompt += f"- 主要颜色：{', '.join(visual_features['colors'])}\n"
        
        if 'composition' in visual_features:
            prompt += f"- 构图风格：{visual_features['composition']}\n"
        
        if 'lighting' in visual_features:
            prompt += f"- 光照效果：{visual_features['lighting']}\n"
        
        if 'subjects' in visual_features:
            prompt += f"- 建议主题：{', '.join(visual_features['subjects'])}\n"
        
        # 添加音乐相关上下文
        prompt += f"\n作品灵感来源于一段{music_context.get('style', 'unknown')}风格的音乐，"
        prompt += f"具有{music_context.get('tempo', 'moderate')}的节奏，"
        prompt += f"情感效价为{music_context.get('pleasure', 5)}/10，"
        prompt += f"唤醒度为{music_context.get('arousal', 5)}/10。"
        
        prompt += "\n请描述一个生动、详细的场景，包括视觉元素、氛围、情感表达和艺术风格。"
        
        return prompt
    
    def _create_music_prompt(self, emotion, music_features, visual_context):
        """
        创建音乐描述提示
        
        参数:
        emotion: 情感类型
        music_features: 音乐特征
        visual_context: 视觉上下文信息
        
        返回:
        详细的音乐描述提示
        """
        prompt = f"创作一段表达'{emotion}'情感的音乐作品。"
        prompt += f"音乐应该体现以下特征：\n"
        
        if 'tempo' in music_features:
            prompt += f"- 节奏速度：{music_features['tempo']}\n"
        
        if 'key' in music_features:
            prompt += f"- 调性：{music_features['key']}\n"
        
        if 'instrumentation' in music_features:
            prompt += f"- 乐器配置：{', '.join(music_features['instrumentation'])}\n"
        
        if 'dynamics' in music_features:
            prompt += f"- 力度变化：{music_features['dynamics']}\n"
        
        if 'rhythm' in music_features:
            prompt += f"- 节奏特点：{music_features['rhythm']}\n"
        
        if 'genre' in music_features:
            prompt += f"- 音乐风格：{music_features['genre']}\n"
        
        # 添加视觉相关上下文
        prompt += f"\n音乐灵感来源于一幅{visual_context.get('style', 'unknown')}风格的作品，"
        prompt += f"主要色彩为{', '.join(visual_context.get('dominant_colors', ['unknown']))}，"
        prompt += f"情感效价为{visual_context.get('pleasure', 5)}/10，"
        prompt += f"唤醒度为{visual_context.get('arousal', 5)}/10。"
        
        prompt += "\n请详细描述这段音乐，包括旋律特点、和声进行、音色选择、结构安排和情感表达。"
        
        return prompt

class StyleCrossModalMapper:
    """
    风格跨模态映射器
    实现音乐风格和视觉艺术风格之间的转换
    """
    def __init__(self):
        """
        初始化风格跨模态映射器
        """
        # 加载风格映射规则库
        self.style_mapping_rules = self._load_style_mapping_rules()
        # 初始化LLM用于生成风格描述
        self.llm = self._load_llm()
    
    def _load_style_mapping_rules(self):
        """
        加载风格映射规则库
        
        返回:
        风格映射规则字典
        """
        return {
            # 音乐风格到视觉风格的映射
            'music_to_visual': {
                'classical': {
                    'visual_styles': ['classicism', 'romanticism', 'baroque'],
                    'composition': 'structured, balanced, symmetrical',
                    'color_palette': 'rich, golds, deep blues, warm tones',
                    'details': 'ornate, intricate, precise',
                    'lighting': 'dramatic, chiaroscuro',
                    'rhythm_translation': 'repetitive patterns, ordered movement',
                    'harmony_translation': 'harmonious color combinations, balanced elements'
                },
                'jazz': {
                    'visual_styles': ['cubism', 'art deco', 'abstract expressionism'],
                    'composition': 'asymmetrical, dynamic, improvised',
                    'color_palette': 'blues, reds, blacks, vibrant contrasts',
                    'details': 'spontaneous, gestural, expressive',
                    'lighting': 'moody, atmospheric, contrasting',
                    'rhythm_translation': 'syncopated patterns, unexpected visual accents',
                    'harmony_translation': 'unexpected color combinations, tension and resolution'
                },
                'rock': {
                    'visual_styles': ['expressionism', 'punk art', 'grunge'],
                    'composition': 'dynamic, energetic, chaotic',
                    'color_palette': 'dark tones, high contrast, bold colors',
                    'details': 'raw, intense, distorted',
                    'lighting': 'highly contrasting, dramatic',
                    'rhythm_translation': 'strong visual beats, repetitive motifs',
                    'harmony_translation': 'clashing elements, visual distortion'
                },
                'electronic': {
                    'visual_styles': ['digital art', 'cyberpunk', 'abstract'],
                    'composition': 'geometric, precise, layered',
                    'color_palette': 'neon colors, gradients, tech-inspired',
                    'details': 'digital, glitch effects, patterns',
                    'lighting': 'neon, artificial, futuristic',
                    'rhythm_translation': 'grid patterns, repeating elements, visual sequences',
                    'harmony_translation': 'algorithmic patterns, systematic color schemes'
                },
                'ambient': {
                    'visual_styles': ['minimalism', 'landscape', 'ambient art'],
                    'composition': 'spacious, calm, flowing',
                    'color_palette': 'soft tones, muted colors, pastels',
                    'details': 'subtle, gradual transitions, minimal detail',
                    'lighting': 'soft, diffused, ethereal',
                    'rhythm_translation': 'slow transitions, gradual changes',
                    'harmony_translation': 'harmonious, subtle color shifts'
                }
            },
            # 视觉风格到音乐风格的映射
            'visual_to_music': {
                'impressionism': {
                    'music_styles': ['classical', 'new age', 'ambient'],
                    'harmony': 'rich, colorful, non-traditional progressions',
                    'melody': 'fluid, lyrical, evolving',
                    'rhythm': 'free-flowing, non-metronomic',
                    'instrumentation': 'piano, strings, woodwinds',
                    'dynamics': 'subtle shifts, delicate',
                    'structure': 'organic, evolving, non-linear',
                    'tonality': 'modal, tonal with chromatic elements'
                },
                'cubism': {
                    'music_styles': ['jazz', 'atonal', 'avant-garde'],
                    'harmony': 'dissonant, complex, polytonal',
                    'melody': 'fragmented, angular, layered',
                    'rhythm': 'syncopated, irregular, polyrhythmic',
                    'instrumentation': 'brass, percussion, prepared piano',
                    'dynamics': 'abrupt changes, contrasting',
                    'structure': 'disjointed, multi-layered',
                    'tonality': 'atonal, polytonal, extended harmonies'
                },
                'expressionism': {
                    'music_styles': ['romantic', 'expressionist', 'rock'],
                    'harmony': 'dramatic, tense, resolving',
                    'melody': 'passionate, intense, dramatic',
                    'rhythm': 'forceful, driving, accented',
                    'instrumentation': 'orchestra, electric guitars, powerful vocals',
                    'dynamics': 'extreme contrasts, loud',
                    'structure': 'climactic, narrative',
                    'tonality': 'chromatic, tense, resolving to tonic'
                },
                'abstract': {
                    'music_styles': ['electronic', 'experimental', 'aleatoric'],
                    'harmony': 'unconventional, algorithmic, chance-based',
                    'melody': 'non-linear, textural, sound-based',
                    'rhythm': 'irregular, computer-generated, complex',
                    'instrumentation': 'synthesizers, digital manipulation, found sounds',
                    'dynamics': 'variable, electronic control',
                    'structure': 'abstract, non-narrative, textural',
                    'tonality': 'atonality, sound masses, noise elements'
                },
                'pop art': {
                    'music_styles': ['pop', 'rock', 'electronic pop'],
                    'harmony': 'simple, catchy, repetitive',
                    'melody': 'memorable, hook-based, accessible',
                    'rhythm': 'steady, danceable, predictable',
                    'instrumentation': 'modern pop instruments, vocals, electronic elements',
                    'dynamics': 'consistent, produced, polished',
                    'structure': 'verse-chorus, formulaic, accessible',
                    'tonality': 'clear tonality, major keys, consonant'
                }
            },
            # 风格元素对应关系
            'element_correspondences': {
                'rhythm': {
                    'fast': ['rapid brushstrokes', 'dynamic lines', 'repetitive patterns'],
                    'slow': ['gradual transitions', 'soft edges', 'flowing forms'],
                    'syncopated': ['unexpected visual accents', 'asymmetrical composition', 'contrasting elements'],
                    'regular': ['ordered patterns', 'symmetrical composition', 'repeating elements']
                },
                'harmony': {
                    'consonant': ['harmonious colors', 'balanced composition', 'pleasing proportions'],
                    'dissonant': ['clashing colors', 'tense composition', 'unexpected juxtapositions'],
                    'simple': ['minimal elements', 'limited color palette', 'clean lines'],
                    'complex': ['rich details', 'diverse color palette', 'intricate patterns']
                },
                'texture': {
                    'smooth': ['soft gradients', 'blended colors', 'fine details'],
                    'rough': ['visible brushstrokes', 'textured surfaces', 'high contrast'],
                    'thick': ['bold colors', 'heavy lines', 'dense composition'],
                    'thin': ['delicate lines', 'subtle colors', 'spacious composition']
                },
                'dynamics': {
                    'loud': ['vibrant colors', 'bold forms', 'strong contrasts'],
                    'soft': ['muted colors', 'gentle forms', 'subtle contrasts'],
                    'changing': ['dynamic composition', 'varying line thickness', 'color transitions'],
                    'consistent': ['uniform elements', 'consistent colors', 'steady rhythm']
                }
            }
        }
    
    def _load_llm(self):
        """
        加载LLM用于生成风格描述
        
        返回:
        LLM实例
        """
        # 模拟LLM
        return type('LLM', (), {
            'generate': lambda self, prompt, **kwargs: 
                f"基于风格提示生成的详细描述: {prompt[:50]}..."
        })()
    
    def map_music_style_to_visual(self, music_style, music_features=None):
        """
        将音乐风格映射到视觉表达
        
        参数:
        music_style: 音乐风格名称
        music_features: 可选的音乐特征详细信息
        
        返回:
        视觉风格表达建议
        """
        # 1. 查询基本映射规则
        base_mapping = self.style_mapping_rules['music_to_visual'].get(
            music_style.lower(),
            self.style_mapping_rules['music_to_visual']['classical']  # 默认映射
        )
        
        # 2. 根据详细音乐特征调整映射
        adjusted_mapping = dict(base_mapping)
        if music_features:
            adjusted_mapping = self._adjust_visual_mapping_based_on_features(
                adjusted_mapping, music_features
            )
        
        # 3. 使用元素对应关系进一步丰富映射
        enriched_mapping = self._enrich_mapping_with_element_correspondences(
            adjusted_mapping, music_features, 'music'
        )
        
        # 4. 使用LLM生成详细的视觉风格描述
        llm_prompt = self._create_visual_style_prompt(music_style, enriched_mapping, music_features)
        visual_style_description = self.llm.generate(llm_prompt)
        
        # 5. 返回映射结果
        result = {
            'music_style': music_style,
            'music_features': music_features,
            'visual_style_suggestions': enriched_mapping['visual_styles'],
            'visual_elements': enriched_mapping,
            'visual_style_description': visual_style_description,
            'mapping_strategy': 'style-based'
        }
        
        return result
    
    def map_visual_style_to_music(self, visual_style, visual_features=None):
        """
        将视觉风格映射到音乐表达
        
        参数:
        visual_style: 视觉风格名称
        visual_features: 可选的视觉特征详细信息
        
        返回:
        音乐风格表达建议
        """
        # 1. 查询基本映射规则
        base_mapping = self.style_mapping_rules['visual_to_music'].get(
            visual_style.lower(),
            self.style_mapping_rules['visual_to_music']['impressionism']  # 默认映射
        )
        
        # 2. 根据详细视觉特征调整映射
        adjusted_mapping = dict(base_mapping)
        if visual_features:
            adjusted_mapping = self._adjust_music_mapping_based_on_features(
                adjusted_mapping, visual_features
            )
        
        # 3. 使用元素对应关系进一步丰富映射
        enriched_mapping = self._enrich_mapping_with_element_correspondences(
            adjusted_mapping, visual_features, 'visual'
        )
        
        # 4. 使用LLM生成详细的音乐风格描述
        llm_prompt = self._create_music_style_prompt(visual_style, enriched_mapping, visual_features)
        music_style_description = self.llm.generate(llm_prompt)
        
        # 5. 返回映射结果
        result = {
            'visual_style': visual_style,
            'visual_features': visual_features,
            'music_style_suggestions': enriched_mapping['music_styles'],
            'music_elements': enriched_mapping,
            'music_style_description': music_style_description,
            'mapping_strategy': 'style-based'
        }
        
        return result
    
    def _adjust_visual_mapping_based_on_features(self, base_mapping, music_features):
        """
        根据音乐特征调整视觉映射
        
        参数:
        base_mapping: 基础视觉映射
        music_features: 音乐特征
        
        返回:
        调整后的视觉映射
        """
        adjusted = dict(base_mapping)
        
        # 基于节奏特征调整
        if 'tempo' in music_features:
            tempo = music_features['tempo']
            if isinstance(tempo, (int, float)):
                if tempo > 120:
                    adjusted['rhythm_translation'] = 'fast-paced patterns, energetic brushstrokes'
                elif tempo < 80:
                    adjusted['rhythm_translation'] = 'slow, deliberate movements, gradual transitions'
        
        # 基于力度特征调整
        if 'dynamics' in music_features:
            dynamics = music_features['dynamics']
            if dynamics == 'loud' or dynamics == 'forte':
                adjusted['color_palette'] = adjusted['color_palette'].replace('soft', 'bold')
                adjusted['details'] = adjusted['details'].replace('subtle', 'pronounced')
        
        return adjusted
    
    def _adjust_music_mapping_based_on_features(self, base_mapping, visual_features):
        """
        根据视觉特征调整音乐映射
        
        参数:
        base_mapping: 基础音乐映射
        visual_features: 视觉特征
        
        返回:
        调整后的音乐映射
        """
        adjusted = dict(base_mapping)
        
        # 基于色彩特征调整
        if 'color_palette' in visual_features:
            palette = visual_features['color_palette']
            # 检查是否包含暖色调
            has_warm = any(color in ['red', 'orange', 'yellow', 'warm'] 
                          for color_list in palette.values() 
                          for color in color_list)
            # 检查是否包含冷色调
            has_cool = any(color in ['blue', 'green', 'purple', 'cool'] 
                          for color_list in palette.values() 
                          for color in color_list)
            
            if has_warm and not has_cool:
                adjusted['harmony'] = adjusted['harmony'].replace('subtle', 'bright')
                adjusted['dynamics'] = 'lively, expressive'
            elif has_cool and not has_warm:
                adjusted['harmony'] = adjusted['harmony'].replace('bright', 'subtle')
                adjusted['dynamics'] = 'gentle, calm'
        
        # 基于构图特征调整
        if 'composition' in visual_features:
            composition = visual_features['composition']
            if 'chaotic' in composition:
                adjusted['rhythm'] = 'complex, unpredictable'
                adjusted['structure'] = 'free-form, experimental'
            elif 'balanced' in composition:
                adjusted['rhythm'] = 'regular, steady'
                adjusted['structure'] = 'balanced, symmetrical'
        
        return adjusted
    
    def _enrich_mapping_with_element_correspondences(self, base_mapping, features, modality):
        """
        使用元素对应关系丰富映射
        
        参数:
        base_mapping: 基础映射
        features: 特征详情
        modality: 模态类型('music'或'visual')
        
        返回:
        丰富后的映射
        """
        enriched = dict(base_mapping)
        correspondences = self.style_mapping_rules['element_correspondences']
        
        # 根据模态类型添加对应元素
        if modality == 'music' and features:
            # 音乐到视觉的元素对应
            if 'rhythm' in features and features['rhythm'] in correspondences['rhythm']:
                enriched['visual_rhythm_elements'] = correspondences['rhythm'][features['rhythm']]
            
            if 'harmony' in features and features['harmony'] in correspondences['harmony']:
                enriched['visual_harmony_elements'] = correspondences['harmony'][features['harmony']]
            
            if 'texture' in features and features['texture'] in correspondences['texture']:
                enriched['visual_texture_elements'] = correspondences['texture'][features['texture']]
            
            if 'dynamics' in features and features['dynamics'] in correspondences['dynamics']:
                enriched['visual_dynamics_elements'] = correspondences['dynamics'][features['dynamics']]
        
        return enriched
    
    def _create_visual_style_prompt(self, music_style, visual_elements, music_features):
        """
        创建视觉风格描述提示
        
        参数:
        music_style: 音乐风格
        visual_elements: 视觉元素映射
        music_features: 音乐特征
        
        返回:
        LLM提示
        """
        prompt = f"创建一个{music_style}音乐风格对应的视觉艺术风格描述。"
        prompt += "\n\n视觉艺术应该体现以下特点：\n"
        
        for key, value in visual_elements.items():
            if key != 'visual_styles':  # 跳过已经列在开头的风格建议
                prompt += f"- {key.replace('_', ' ')}: {value}\n"
        
        if music_features:
            prompt += "\n音乐的具体特征：\n"
            for key, value in music_features.items():
                prompt += f"- {key}: {value}\n"
        
        prompt += "\n请提供一个详细、生动的描述，包括色彩运用、构图方式、笔触特点等，"
        prompt += "使视觉艺术能够充分表达这种音乐风格的精髓。"
        
        return prompt
    
    def _create_music_style_prompt(self, visual_style, music_elements, visual_features):
        """
        创建音乐风格描述提示
        
        参数:
        visual_style: 视觉风格
        music_elements: 音乐元素映射
        visual_features: 视觉特征
        
        返回:
        LLM提示
        """
        prompt = f"创建一个{visual_style}视觉艺术风格对应的音乐风格描述。"
        prompt += "\n\n音乐作品应该体现以下特点：\n"
        
        for key, value in music_elements.items():
            if key != 'music_styles':  # 跳过已经列在开头的风格建议
                prompt += f"- {key.replace('_', ' ')}: {value}\n"
        
        if visual_features:
            prompt += "\n视觉艺术的具体特征：\n"
            for key, value in visual_features.items():
                if isinstance(value, dict):
                    # 处理嵌套字典
                    for sub_key, sub_value in value.items():
                        prompt += f"  - {sub_key}: {sub_value}\n"
                else:
                    prompt += f"- {key}: {value}\n"
        
        prompt += "\n请提供一个详细、生动的描述，包括旋律特点、和声进行、节奏模式、"
        prompt += "音色选择等，使音乐能够充分表达这种视觉艺术风格的精髓。"
        
        return prompt

class NarrativeStructureMapper:
    """
    叙事结构映射器
    实现音乐和视觉艺术之间的叙事结构转换
    """
    def __init__(self):
        """
        初始化叙事结构映射器
        """
        # 加载叙事结构映射规则
        self.narrative_mapping_rules = self._load_narrative_mapping_rules()
        # 初始化LLM用于生成叙事描述
        self.llm = self._load_llm()
    
    def _load_narrative_mapping_rules(self):
        """
        加载叙事结构映射规则
        
        返回:
        叙事结构映射规则字典
        """
        return {
            # 音乐叙事结构到视觉叙事结构的映射
            'music_to_visual': {
                'sonata_form': {  # 奏鸣曲式
                    'visual_structure': 'classical tripartite composition',
                    'exposition': {
                        'visual_element': 'establishing scene/character introduction',
                        'composition_technique': 'balanced framing, clear focus',
                        'color_strategy': 'dominant colors established',
                        'narrative_function': 'introduce themes/conflict'
                    },
                    'development': {
                        'visual_element': 'complication/rising action',
                        'composition_technique': 'dynamic composition, tension building',
                        'color_strategy': 'contrasting colors, increasing intensity',
                        'narrative_function': 'develop conflict/tension'
                    },
                    'recapitulation': {
                        'visual_element': 'resolution/climax',
                        'composition_technique': 'rebalanced composition, focal point',
                        'color_strategy': 'dominant colors return, resolution',
                        'narrative_function': 'resolve conflict/tension'
                    }
                },
                'theme_and_variations': {  # 主题与变奏
                    'visual_structure': 'motif development',
                    'theme': {
                        'visual_element': 'central motif/visual identity',
                        'composition_technique': 'clear, prominent display',
                        'color_strategy': 'distinctive color scheme',
                        'narrative_function': 'establish identity'
                    },
                    'variations': {
                        'visual_element': 'motif transformations',
                        'composition_technique': 'varied presentation, exploration',
                        'color_strategy': 'varied palette while maintaining core',
                        'narrative_function': 'explore possibilities'
                    }
                },
                'rondo': {  # 回旋曲式
                    'visual_structure': 'refrain-episode structure',
                    'refrain': {
                        'visual_element': 'recurring visual motif',
                        'composition_technique': 'consistent framing',
                        'color_strategy': 'returning to base palette',
                        'narrative_function': 'anchoring point'
                    },
                    'episodes': {
                        'visual_element': 'contrasting visual elements',
                        'composition_technique': 'varied approaches, contrast',
                        'color_strategy': 'exploration of color variations',
                        'narrative_function': 'diversification/development'
                    }
                }
            },
            # 视觉叙事结构到音乐叙事结构的映射
            'visual_to_music': {
                'triangular_composition': {  # 三角形构图
                    'music_structure': 'arch form',
                    'apex': {
                        'music_element': 'climax',
                        'harmonic_strategy': 'tension building to resolution',
                        'instrumentation': 'fullest orchestration',
                        'dynamic': 'crescendo to peak'
                    },
                    'ascending_side': {
                        'music_element': 'development/rising action',
                        'harmonic_strategy': 'increasing tension',
                        'instrumentation': 'gradually adding instruments',
                        'dynamic': 'crescendo'
                    },
                    'descending_side': {
                        'music_element': 'resolution/falling action',
                        'harmonic_strategy': 'resolving tension',
                        'instrumentation': 'gradually reducing instruments',
                        'dynamic': 'decrescendo'
                    }
                },
                'leading_line_composition': {  # 引导线构图
                    'music_structure': 'progressive form',
                    'starting_point': {
                        'music_element': 'introduction/thesis',
                        'harmonic_strategy': 'establishing tonality',
                        'instrumentation': 'minimal, clear',
                        'dynamic': 'moderate'
                    },
                    'leading_line': {
                        'music_element': 'melodic development',
                        'harmonic_strategy': 'progressive modulation',
                        'instrumentation': 'melodic instruments featured',
                        'dynamic': 'expressively varied'
                    },
                    'destination': {
                        'music_element': 'culmination/antithesis',
                        'harmonic_strategy': 'arrival at new tonality/conclusion',
                        'instrumentation': 'full expression',
                        'dynamic': 'climactic'
                    }
                },
                'circular_composition': {  # 圆形构图
                    'music_structure': 'cyclic form',
                    'center': {
                        'music_element': 'core theme/motif',
                        'harmonic_strategy': 'central tonality',
                        'instrumentation': 'featured solo or small group',
                        'dynamic': 'intimate, focused'
                    },
                    'circular_pattern': {
                        'music_element': 'thematic development',
                        'harmonic_strategy': 'modulations returning to center',
                        'instrumentation': 'expanding and contracting',
                        'dynamic': 'ebbing and flowing'
                    },
                    'return': {
                        'music_element': 'recapitulation',
                        'harmonic_strategy': 'final resolution to center',
                        'instrumentation': 'reaffirmation of core sound',
                        'dynamic': 'resolution, sense of completion'
                    }
                }
            },
            # 通用叙事元素对应关系
            'narrative_elements': {
                'introduction': {
                    'music': ['slow tempo', 'simple harmony', 'gradual build', 'tonal establishment'],
                    'visual': ['wide establishing shot', 'balanced composition', 'soft lighting', 'clear focal point']
                },
                'rising_action': {
                    'music': ['increasing tempo', 'complex harmonies', 'growing orchestration', 'rising melody'],
                    'visual': ['dynamic composition', 'diagonal lines', 'increasing contrast', 'multiple focal points']
                },
                'climax': {
                    'music': ['peak volume', 'highest tension', 'full orchestration', 'dramatic harmony'],
                    'visual': ['strong contrast', 'central focal point', 'dynamic angles', 'intense colors']
                },
                'falling_action': {
                    'music': ['decreasing tension', 'resolving harmonies', 'reducing orchestration', 'descending melody'],
                    'visual': ['relaxing composition', 'horizontal lines', 'decreasing contrast', 'simpler arrangement']
                },
                'resolution': {
                    'music': ['stable harmony', 'return to tonic', 'gentle dynamics', 'concluding melody'],
                    'visual': ['balanced composition', 'closed forms', 'harmonious colors', 'sense of completion']
                }
            },
            # 情感弧线映射
            'emotional_arcs': {
                'tragic': {
                    'music': ['minor tonality', 'descending melodic lines', 'diminishing hope', 'climactic despair'],
                    'visual': ['darkening colors', 'broken compositions', 'downward movement', 'isolating elements']
                },
                'comedic': {
                    'music': ['major tonality', 'upbeat rhythms', 'surprising twists', 'happy resolution'],
                    'visual': ['bright colors', 'dynamic compositions', 'uplifting angles', 'connecting elements']
                },
                'heroic': {
                    'music': ['rising themes', 'triumphant brass', 'overcoming obstacles', 'glorious resolution'],
                    'visual': ['ascending lines', 'strong forms', 'contrasting light/dark', 'central figure']
                },
                'mystical': {
                    'music': ['ambiguous tonality', 'ethereal textures', 'unexpected shifts', 'mysterious resolution'],
                    'visual': ['soft focus', 'muted colors', 'dreamlike quality', 'hidden elements']
                }
            }
        }
    
    def _load_llm(self):
        """
        加载LLM用于生成叙事描述
        
        返回:
        LLM实例
        """
        # 模拟LLM
        return type('LLM', (), {
            'generate': lambda self, prompt, **kwargs: 
                f"基于叙事结构提示生成的详细描述: {prompt[:50]}..."
        })()
    
    def map_music_narrative_to_visual(self, music_structure, music_features=None):
        """
        将音乐叙事结构映射到视觉叙事结构
        
        参数:
        music_structure: 音乐叙事结构名称
        music_features: 可选的音乐特征详细信息
        
        返回:
        视觉叙事结构建议
        """
        # 1. 查询基本映射规则
        base_mapping = self.narrative_mapping_rules['music_to_visual'].get(
            music_structure.lower(),
            self.narrative_mapping_rules['music_to_visual']['sonata_form']  # 默认映射
        )
        
        # 2. 根据详细音乐特征调整映射
        adjusted_mapping = dict(base_mapping)
        if music_features:
            adjusted_mapping = self._adjust_visual_narrative_based_on_features(
                adjusted_mapping, music_features
            )
        
        # 3. 使用叙事元素对应关系丰富映射
        enriched_mapping = self._enrich_narrative_mapping(
            adjusted_mapping, music_features, 'music'
        )
        
        # 4. 使用LLM生成详细的视觉叙事描述
        llm_prompt = self._create_visual_narrative_prompt(
            music_structure, enriched_mapping, music_features
        )
        visual_narrative_description = self.llm.generate(llm_prompt)
        
        # 5. 返回映射结果
        result = {
            'music_structure': music_structure,
            'music_features': music_features,
            'visual_structure': enriched_mapping['visual_structure'],
            'visual_narrative_elements': enriched_mapping,
            'visual_narrative_description': visual_narrative_description,
            'mapping_strategy': 'narrative-based'
        }
        
        return result
    
    def map_visual_narrative_to_music(self, visual_structure, visual_features=None):
        """
        将视觉叙事结构映射到音乐叙事结构
        
        参数:
        visual_structure: 视觉叙事结构名称
        visual_features: 可选的视觉特征详细信息
        
        返回:
        音乐叙事结构建议
        """
        # 1. 查询基本映射规则
        base_mapping = self.narrative_mapping_rules['visual_to_music'].get(
            visual_structure.lower(),
            self.narrative_mapping_rules['visual_to_music']['triangular_composition']  # 默认映射
        )
        
        # 2. 根据详细视觉特征调整映射
        adjusted_mapping = dict(base_mapping)
        if visual_features:
            adjusted_mapping = self._adjust_music_narrative_based_on_features(
                adjusted_mapping, visual_features
            )
        
        # 3. 使用叙事元素对应关系丰富映射
        enriched_mapping = self._enrich_narrative_mapping(
            adjusted_mapping, visual_features, 'visual'
        )
        
        # 4. 使用LLM生成详细的音乐叙事描述
        llm_prompt = self._create_music_narrative_prompt(
            visual_structure, enriched_mapping, visual_features
        )
        music_narrative_description = self.llm.generate(llm_prompt)
        
        # 5. 返回映射结果
        result = {
            'visual_structure': visual_structure,
            'visual_features': visual_features,
            'music_structure': enriched_mapping['music_structure'],
            'music_narrative_elements': enriched_mapping,
            'music_narrative_description': music_narrative_description,
            'mapping_strategy': 'narrative-based'
        }
        
        return result
    
    def _adjust_visual_narrative_based_on_features(self, base_mapping, music_features):
        """
        根据音乐特征调整视觉叙事结构
        
        参数:
        base_mapping: 基础视觉叙事映射
        music_features: 音乐特征
        
        返回:
        调整后的视觉叙事映射
        """
        adjusted = dict(base_mapping)
        
        # 基于节奏特征调整
        if 'tempo' in music_features:
            tempo = music_features['tempo']
            if isinstance(tempo, (int, float)):
                # 快速节奏可能需要更动态的视觉表现
                if tempo > 120:
                    for section in ['exposition', 'development', 'recapitulation', 'theme', 'variations', 'refrain', 'episodes']:
                        if section in adjusted and 'composition_technique' in adjusted[section]:
                            adjusted[section]['composition_technique'] = adjusted[section]['composition_technique'].replace(
                                'balanced', 'dynamic').replace('calm', 'energetic')
        
        # 基于力度特征调整
        if 'dynamics' in music_features:
            dynamics = music_features['dynamics']
            if dynamics == 'loud' or dynamics == 'forte':
                # 强力度可能对应更鲜明的视觉对比
                for section in ['exposition', 'development', 'recapitulation', 'theme', 'variations', 'refrain', 'episodes']:
                    if section in adjusted and 'color_strategy' in adjusted[section]:
                        adjusted[section]['color_strategy'] = adjusted[section]['color_strategy'].replace(
                            'soft', 'bold').replace('subtle', 'strong')
        
        return adjusted
    
    def _adjust_music_narrative_based_on_features(self, base_mapping, visual_features):
        """
        根据视觉特征调整音乐叙事结构
        
        参数:
        base_mapping: 基础音乐叙事映射
        visual_features: 视觉特征
        
        返回:
        调整后的音乐叙事映射
        """
        adjusted = dict(base_mapping)
        
        # 基于构图特征调整
        if 'composition' in visual_features:
            composition = visual_features['composition']
            # 动态构图可能需要更复杂的音乐结构
            if 'dynamic' in composition:
                for section in ['apex', 'ascending_side', 'descending_side', 
                               'starting_point', 'leading_line', 'destination', 
                               'center', 'circular_pattern', 'return']:
                    if section in adjusted and 'harmonic_strategy' in adjusted[section]:
                        adjusted[section]['harmonic_strategy'] = adjusted[section]['harmonic_strategy'].replace(
                            'simple', 'complex').replace('stable', 'varied')
        
        # 基于色彩特征调整
        if 'color_palette' in visual_features:
            palette = visual_features['color_palette']
            # 检查是否包含对比强烈的色彩
            has_strong_contrast = False
            if 'warm_colors' in palette and 'cool_colors' in palette:
                if len(palette['warm_colors']) > 0 and len(palette['cool_colors']) > 0:
                    has_strong_contrast = True
            
            if has_strong_contrast:
                # 强烈的色彩对比可能对应更戏剧性的音乐表现
                for section in ['apex', 'ascending_side', 'descending_side', 
                               'starting_point', 'leading_line', 'destination', 
                               'center', 'circular_pattern', 'return']:
                    if section in adjusted and 'dynamic' in adjusted[section]:
                        adjusted[section]['dynamic'] = adjusted[section]['dynamic'].replace(
                            'moderate', 'dramatic').replace('subtle', 'strong')
        
        return adjusted
    
    def _enrich_narrative_mapping(self, base_mapping, features, modality):
        """
        使用叙事元素对应关系丰富映射
        
        参数:
        base_mapping: 基础映射
        features: 特征详情
        modality: 模态类型('music'或'visual')
        
        返回:
        丰富后的映射
        """
        enriched = dict(base_mapping)
        narrative_elements = self.narrative_mapping_rules['narrative_elements']
        
        # 添加叙事元素对应关系
        if modality == 'music':
            enriched['narrative_elements_mapping'] = {}
            for element, music_attrs in narrative_elements.items():
                # 为每个叙事元素添加对应的视觉建议
                enriched['narrative_elements_mapping'][element] = {
                    'music_characteristics': music_attrs['music'],
                    'visual_suggestions': narrative_elements[element]['visual']
                }
        else:  # visual
            enriched['narrative_elements_mapping'] = {}
            for element, visual_attrs in narrative_elements.items():
                # 为每个叙事元素添加对应的音乐建议
                enriched['narrative_elements_mapping'][element] = {
                    'visual_characteristics': visual_attrs['visual'],
                    'music_suggestions': narrative_elements[element]['music']
                }
        
        return enriched
    
    def _create_visual_narrative_prompt(self, music_structure, visual_elements, music_features):
        """
        创建视觉叙事描述提示
        
        参数:
        music_structure: 音乐叙事结构
        visual_elements: 视觉元素映射
        music_features: 音乐特征
        
        返回:
        LLM提示
        """
        prompt = f"创建一个基于{music_structure}音乐结构的视觉叙事艺术作品描述。"
        prompt += "\n\n视觉叙事应该体现以下特点：\n"
        
        # 添加整体结构
        prompt += f"- 整体结构: {visual_elements['visual_structure']}\n"
        
        # 添加各部分详细信息
        structure_sections = ['exposition', 'development', 'recapitulation', 
                             'theme', 'variations', 'refrain', 'episodes']
        for section in structure_sections:
            if section in visual_elements:
                prompt += f"\n{section}部分：\n"
                for key, value in visual_elements[section].items():
                    prompt += f"  - {key.replace('_', ' ')}: {value}\n"
        
        # 添加叙事元素映射
        if 'narrative_elements_mapping' in visual_elements:
            prompt += "\n叙事元素对应：\n"
            for element, mapping in visual_elements['narrative_elements_mapping'].items():
                prompt += f"\n{element}：\n"
                prompt += f"  音乐特征：{', '.join(mapping['music_characteristics'])}\n"
                prompt += f"  视觉建议：{', '.join(mapping['visual_suggestions'])}\n"
        
        if music_features:
            prompt += "\n音乐的具体特征：\n"
            for key, value in music_features.items():
                prompt += f"- {key}: {value}\n"
        
        prompt += "\n请提供一个详细、生动的视觉叙事描述，包括构图安排、色彩运用、"
        prompt += "空间处理等方面，使视觉作品能够充分表达这种音乐结构的叙事逻辑和情感发展。"
        
        return prompt
    
    def _create_music_narrative_prompt(self, visual_structure, music_elements, visual_features):
        """
        创建音乐叙事描述提示
        
        参数:
        visual_structure: 视觉叙事结构
        music_elements: 音乐元素映射
        visual_features: 视觉特征
        
        返回:
        LLM提示
        """
        prompt = f"创建一个基于{visual_structure}视觉结构的音乐叙事作品描述。"
        prompt += "\n\n音乐叙事应该体现以下特点：\n"
        
        # 添加整体结构
        prompt += f"- 整体结构: {music_elements['music_structure']}\n"
        
        # 添加各部分详细信息
        structure_sections = ['apex', 'ascending_side', 'descending_side', 
                             'starting_point', 'leading_line', 'destination', 
                             'center', 'circular_pattern', 'return']
        for section in structure_sections:
            if section in music_elements:
                prompt += f"\n{section}部分：\n"
                for key, value in music_elements[section].items():
                    prompt += f"  - {key.replace('_', ' ')}: {value}\n"
        
        # 添加叙事元素映射
        if 'narrative_elements_mapping' in music_elements:
            prompt += "\n叙事元素对应：\n"
            for element, mapping in music_elements['narrative_elements_mapping'].items():
                prompt += f"\n{element}：\n"
                prompt += f"  视觉特征：{', '.join(mapping['visual_characteristics'])}\n"
                prompt += f"  音乐建议：{', '.join(mapping['music_suggestions'])}\n"
        
        if visual_features:
            prompt += "\n视觉艺术的具体特征：\n"
            for key, value in visual_features.items():
                if isinstance(value, dict):
                    # 处理嵌套字典
                    for sub_key, sub_value in value.items():
                        prompt += f"  - {sub_key}: {sub_value}\n"
                else:
                    prompt += f"- {key}: {value}\n"
        
        prompt += "\n请提供一个详细、生动的音乐叙事描述，包括旋律发展、和声进行、"
        prompt += "结构安排等方面，使音乐作品能够充分表达这种视觉结构的叙事逻辑和情感发展。"
        
        return prompt

class ThemeConsistencyManager:
    """
    主题一致性管理器
    确保跨模态创作中主题的一致性和连贯性
    """
    def __init__(self):
        """
        初始化主题一致性管理器
        """
        # 初始化LLM用于主题分析和生成
        self.llm = self._load_llm()
        # 加载主题关联规则
        self.theme_association_rules = self._load_theme_association_rules()
    
    def _load_llm(self):
        """
        加载LLM用于主题分析和生成
        
        返回:
        LLM实例
        """
        # 模拟LLM
        return type('LLM', (), {
            'generate': lambda self, prompt, **kwargs: 
                f"基于主题提示生成的详细分析: {prompt[:50]}...",
            'extract_themes': lambda self, content, modality: {
                'primary_themes': ['nature', 'transformation', 'serenity'],
                'secondary_themes': ['growth', 'harmony', 'reflection'],
                'theme_connections': {'nature': ['growth', 'harmony'], 'transformation': ['change', 'evolution']},
                'emotional_undertones': ['peaceful', 'contemplative', 'hopeful']
            }
        })()
    
    def _load_theme_association_rules(self):
        """
        加载主题关联规则库
        
        返回:
        主题关联规则字典
        """
        return {
            # 主题关联网络
            'theme_network': {
                'nature': {
                    'related_themes': ['growth', 'harmony', 'seasons', 'elements', 'cycle'],
                    'visual_symbols': ['trees', 'mountains', 'rivers', 'clouds', 'animals'],
                    'musical_symbols': ['pastoral melodies', 'organic rhythms', 'natural sounds', 'major keys'],
                    'emotional_associations': ['peaceful', 'majestic', 'harmonious', 'renewing']
                },
                'transformation': {
                    'related_themes': ['change', 'evolution', 'metamorphosis', 'journey', 'growth'],
                    'visual_symbols': ['caterpillar/butterfly', 'seasons changing', 'dawn/dusk', 'water cycle'],
                    'musical_symbols': ['thematic development', 'modulation', 'rhythmic changes', 'dynamic shifts'],
                    'emotional_associations': ['hopeful', 'exciting', 'challenging', 'fulfilling']
                },
                'conflict': {
                    'related_themes': ['struggle', 'opposition', 'tension', 'resolution', 'balance'],
                    'visual_symbols': ['clashing elements', 'contrasting colors', 'dynamic angles', 'opposing forces'],
                    'musical_symbols': ['dissonance', 'rhythmic tension', 'clashing instrumentation', 'dramatic shifts'],
                    'emotional_associations': ['intense', 'dramatic', 'anxious', 'determined']
                },
                'serenity': {
                    'related_themes': ['peace', 'calm', 'balance', 'harmony', 'stillness'],
                    'visual_symbols': ['calm water', 'sunset', 'open spaces', 'symmetrical forms'],
                    'musical_symbols': ['slow tempos', 'consonant harmonies', 'soft dynamics', 'smooth melodies'],
                    'emotional_associations': ['peaceful', 'relaxing', 'contemplative', 'fulfilled']
                },
                'joy': {
                    'related_themes': ['happiness', 'celebration', 'optimism', 'connection', 'gratitude'],
                    'visual_symbols': ['bright colors', 'upward movement', 'open arms', 'gathering'],
                    'musical_symbols': ['fast tempos', 'major keys', 'syncopated rhythms', 'bright instrumentation'],
                    'emotional_associations': ['happy', 'energetic', 'enthusiastic', 'connected']
                }
            },
            # 主题转换规则
            'theme_transformation_rules': {
                'strengthening': {
                    'strategy': 'intensify thematic elements',
                    'visual_techniques': ['increasing contrast', 'emphasizing symbols', 'focusing perspective'],
                    'musical_techniques': ['thematic repetition', 'growing orchestration', 'heightened dynamics']
                },
                'subtle_variation': {
                    'strategy': 'maintain core theme with variations',
                    'visual_techniques': ['changing contexts', 'varying perspectives', 'modifying symbols'],
                    'musical_techniques': ['thematic variation', 'rhythmic modification', 'instrumental changes']
                },
                'counterpoint': {
                    'strategy': 'introduce contrasting but related themes',
                    'visual_techniques': ['juxtaposition', 'layered elements', 'complementary colors'],
                    'musical_techniques': ['counterpoint', 'harmonic contrast', 'textural layers']
                },
                'evolution': {
                    'strategy': 'show thematic development over time',
                    'visual_techniques': ['progressive transformation', 'sequential imagery', 'metamorphosis'],
                    'musical_techniques': ['thematic evolution', 'developmental sections', 'recapitulation']
                }
            },
            # 跨模态主题一致性检查规则
            'consistency_check_rules': [
                '主题核心元素在不同模态中是否保持一致',
                '情感关联在不同模态中是否协调',
                '主题象征物在不同模态中是否对应',
                '主题发展轨迹在不同模态中是否同步',
                '主题强调点在不同模态中是否互补'
            ]
        }
    
    def analyze_theme(self, content, modality):
        """
        分析内容的主题
        
        参数:
        content: 要分析的内容
        modality: 内容模态('music'或'visual')
        
        返回:
        主题分析结果
        """
        # 使用LLM提取主题
        themes = self.llm.extract_themes(content, modality)
        
        # 扩展主题分析
        expanded_themes = self._expand_themes(themes)
        
        return expanded_themes
    
    def generate_theme_consistency_guidance(self, source_modality, target_modality, themes):
        """
        生成主题一致性指导
        
        参数:
        source_modality: 源模态
        target_modality: 目标模态
        themes: 源模态中的主题
        
        返回:
        主题一致性指导建议
        """
        # 获取主题关联规则
        theme_network = self.theme_association_rules['theme_network']
        
        # 生成一致性指导
        consistency_guidance = {
            'primary_themes_translation': {},
            'secondary_themes_translation': {},
            'symbolic_connections': {},
            'emotional_consistency': {},
            'development_strategies': []
        }
        
        # 处理主要主题
        if 'primary_themes' in themes:
            for theme in themes['primary_themes']:
                if theme in theme_network:
                    if target_modality == 'visual':
                        consistency_guidance['primary_themes_translation'][theme] = \
                            theme_network[theme]['visual_symbols']
                    else:  # music
                        consistency_guidance['primary_themes_translation'][theme] = \
                            theme_network[theme]['musical_symbols']
                    
                    consistency_guidance['emotional_consistency'][theme] = \
                        theme_network[theme]['emotional_associations']
        
        # 处理次要主题
        if 'secondary_themes' in themes:
            for theme in themes['secondary_themes']:
                if theme in theme_network:
                    if target_modality == 'visual':
                        consistency_guidance['secondary_themes_translation'][theme] = \
                            theme_network[theme]['visual_symbols']
                    else:  # music
                        consistency_guidance['secondary_themes_translation'][theme] = \
                            theme_network[theme]['musical_symbols']
        
        # 生成发展策略
        transformation_rules = self.theme_association_rules['theme_transformation_rules']
        
        # 为主要主题生成发展策略
        if 'primary_themes' in themes and themes['primary_themes']:
            main_theme = themes['primary_themes'][0]
            
            # 根据主题特点选择合适的发展策略
            if main_theme in ['conflict', 'joy']:
                strategy = 'strengthening'
            elif main_theme in ['transformation', 'evolution']:
                strategy = 'evolution'
            else:
                strategy = 'subtle_variation'
            
            if strategy in transformation_rules:
                consistency_guidance['development_strategies'].append({
                    'strategy': strategy,
                    'description': transformation_rules[strategy]['strategy'],
                    'techniques': transformation_rules[strategy][f'{target_modality}_techniques']
                })
        
        # 生成主题象征连接
        if 'primary_themes' in themes:
            for theme in themes['primary_themes']:
                if theme in theme_network:
                    consistency_guidance['symbolic_connections'][theme] = {
                        'related_themes': theme_network[theme]['related_themes'],
                        'suggested_symbols': theme_network[theme][f'{target_modality}_symbols']
                    }
        
        return consistency_guidance
    
    def check_theme_consistency(self, source_content, target_content, source_modality, target_modality):
        """
        检查两个模态间的主题一致性
        
        参数:
        source_content: 源模态内容
        target_content: 目标模态内容
        source_modality: 源模态类型
        target_modality: 目标模态类型
        
        返回:
        一致性检查结果
        """
        # 分析源模态主题
        source_themes = self.analyze_theme(source_content, source_modality)
        
        # 分析目标模态主题
        target_themes = self.analyze_theme(target_content, target_modality)
        
        # 执行一致性检查
        consistency_checks = []
        check_rules = self.theme_association_rules['consistency_check_rules']
        theme_network = self.theme_association_rules['theme_network']
        
        # 1. 检查主要主题匹配
        primary_match = False
        if ('primary_themes' in source_themes and 'primary_themes' in target_themes and
                source_themes['primary_themes'] and target_themes['primary_themes']):
            # 直接匹配或相关主题匹配
            for source_theme in source_themes['primary_themes']:
                if source_theme in target_themes['primary_themes']:
                    primary_match = True
                    break
                elif source_theme in theme_network:
                    # 检查相关主题
                    for related_theme in theme_network[source_theme]['related_themes']:
                        if related_theme in target_themes['primary_themes']:
                            primary_match = True
                            break
                    if primary_match:
                        break
        
        consistency_checks.append({
            'rule': check_rules[0],  # 主题核心元素在不同模态中是否保持一致
            'result': primary_match,
            'confidence': 0.9 if primary_match else 0.3
        })
        
        # 2. 检查情感关联协调
        emotional_coordination = False
        if ('emotional_undertones' in source_themes and 'emotional_undertones' in target_themes and
                source_themes['emotional_undertones'] and target_themes['emotional_undertones']):
            # 检查是否有重叠的情感关联
            overlap = set(source_themes['emotional_undertones']) & set(target_themes['emotional_undertones'])
            emotional_coordination = len(overlap) > 0
        
        consistency_checks.append({
            'rule': check_rules[1],  # 情感关联在不同模态中是否协调
            'result': emotional_coordination,
            'confidence': 0.85 if emotional_coordination else 0.35
        })
        
        # 生成一致性评分
        overall_score = sum(check['confidence'] for check in consistency_checks) / len(consistency_checks)
        
        # 生成改进建议
        improvement_suggestions = []
        if not primary_match:
            improvement_suggestions.append("增强主要主题的一致性，可以通过明确的象征物或主题元素来实现")
        if not emotional_coordination:
            improvement_suggestions.append("调整情感表达以保持跨模态的情感协调")
        
        # 返回检查结果
        result = {
            'source_themes': source_themes,
            'target_themes': target_themes,
            'consistency_checks': consistency_checks,
            'overall_consistency_score': overall_score,
            'improvement_suggestions': improvement_suggestions,
            'consistent': overall_score > 0.7
        }
        
        return result
    
    def _expand_themes(self, themes):
        """
        扩展主题分析，添加相关主题和象征物
        
        参数:
        themes: 初始主题分析
        
        返回:
        扩展后的主题分析
        """
        expanded = dict(themes)
        theme_network = self.theme_association_rules['theme_network']
        
        # 扩展主要主题
        if 'primary_themes' in expanded:
            expanded['primary_themes_expanded'] = {}
            for theme in expanded['primary_themes']:
                if theme in theme_network:
                    expanded['primary_themes_expanded'][theme] = {
                        'related_themes': theme_network[theme]['related_themes'],
                        'visual_symbols': theme_network[theme]['visual_symbols'],
                        'musical_symbols': theme_network[theme]['musical_symbols'],
                        'emotional_associations': theme_network[theme]['emotional_associations']
                    }
        
        # 扩展次要主题
        if 'secondary_themes' in expanded:
            expanded['secondary_themes_expanded'] = {}
            for theme in expanded['secondary_themes']:
                if theme in theme_network:
                    expanded['secondary_themes_expanded'][theme] = {
                        'related_themes': theme_network[theme]['related_themes'],
                        'visual_symbols': theme_network[theme]['visual_symbols'],
                        'musical_symbols': theme_network[theme]['musical_symbols'],
                        'emotional_associations': theme_network[theme]['emotional_associations']
                    }
        
        return expanded