Merge branch 'dev' of https://github.com/MaiM-with-u/MaiBot into dev
This commit is contained in:
SengokuCola
@@ -1,37 +1,38 @@
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import json
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import os
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from pathlib import Path
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import numpy as np
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from sklearn.feature_extraction.text import TfidfVectorizer
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from sklearn.metrics.pairwise import cosine_similarity
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import matplotlib.pyplot as plt
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import seaborn as sns
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import networkx as nx
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import matplotlib as mpl
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import sqlite3
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# 设置中文字体
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plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] # 使用微软雅黑
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plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号
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plt.rcParams['font.family'] = 'sans-serif'
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plt.rcParams["font.sans-serif"] = ["Microsoft YaHei"] # 使用微软雅黑
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plt.rcParams["axes.unicode_minus"] = False # 用来正常显示负号
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plt.rcParams["font.family"] = "sans-serif"
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# 获取脚本所在目录
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SCRIPT_DIR = Path(__file__).parent
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def get_group_name(stream_id):
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"""从数据库中获取群组名称"""
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conn = sqlite3.connect('data/maibot.db')
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conn = sqlite3.connect("data/maibot.db")
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cursor = conn.cursor()
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cursor.execute('''
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cursor.execute(
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"""
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SELECT group_name, user_nickname, platform
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FROM chat_streams
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WHERE stream_id = ?
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''', (stream_id,))
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""",
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(stream_id,),
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)
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result = cursor.fetchone()
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conn.close()
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if result:
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group_name, user_nickname, platform = result
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if group_name:
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@@ -42,139 +43,148 @@ def get_group_name(stream_id):
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return f"{platform}-{stream_id[:8]}"
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return stream_id
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def load_group_data(group_dir):
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"""加载单个群组的数据"""
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json_path = Path(group_dir) / "expressions.json"
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if not json_path.exists():
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return [], [], []
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with open(json_path, 'r', encoding='utf-8') as f:
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with open(json_path, "r", encoding="utf-8") as f:
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data = json.load(f)
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situations = []
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styles = []
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combined = []
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for item in data:
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count = item['count']
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situations.extend([item['situation']] * count)
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styles.extend([item['style']] * count)
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count = item["count"]
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situations.extend([item["situation"]] * count)
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styles.extend([item["style"]] * count)
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combined.extend([f"{item['situation']} {item['style']}"] * count)
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return situations, styles, combined
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def analyze_group_similarity():
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# 获取所有群组目录
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base_dir = Path("data/expression/learnt_style")
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group_dirs = [d for d in base_dir.iterdir() if d.is_dir()]
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group_ids = [d.name for d in group_dirs]
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# 获取群组名称
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group_names = [get_group_name(group_id) for group_id in group_ids]
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# 加载所有群组的数据
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group_situations = []
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group_styles = []
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group_combined = []
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for d in group_dirs:
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situations, styles, combined = load_group_data(d)
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group_situations.append(' '.join(situations))
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group_styles.append(' '.join(styles))
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group_combined.append(' '.join(combined))
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group_situations.append(" ".join(situations))
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group_styles.append(" ".join(styles))
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group_combined.append(" ".join(combined))
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# 创建TF-IDF向量化器
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vectorizer = TfidfVectorizer()
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# 计算三种相似度矩阵
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situation_matrix = cosine_similarity(vectorizer.fit_transform(group_situations))
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style_matrix = cosine_similarity(vectorizer.fit_transform(group_styles))
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combined_matrix = cosine_similarity(vectorizer.fit_transform(group_combined))
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# 对相似度矩阵进行对数变换
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log_situation_matrix = np.log1p(situation_matrix)
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log_style_matrix = np.log1p(style_matrix)
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log_combined_matrix = np.log1p(combined_matrix)
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# 创建一个大图，包含三个子图
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plt.figure(figsize=(45, 12))
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# 场景相似度热力图
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plt.subplot(1, 3, 1)
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sns.heatmap(log_situation_matrix,
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xticklabels=group_names,
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yticklabels=group_names,
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cmap='YlOrRd',
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annot=True,
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fmt='.2f',
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vmin=0,
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vmax=np.log1p(0.2))
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plt.title('群组场景相似度热力图 (对数变换)')
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plt.xticks(rotation=45, ha='right')
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sns.heatmap(
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log_situation_matrix,
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xticklabels=group_names,
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yticklabels=group_names,
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cmap="YlOrRd",
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annot=True,
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fmt=".2f",
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vmin=0,
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vmax=np.log1p(0.2),
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)
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plt.title("群组场景相似度热力图 (对数变换)")
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plt.xticks(rotation=45, ha="right")
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# 表达方式相似度热力图
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plt.subplot(1, 3, 2)
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sns.heatmap(log_style_matrix,
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xticklabels=group_names,
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yticklabels=group_names,
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cmap='YlOrRd',
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annot=True,
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fmt='.2f',
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vmin=0,
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vmax=np.log1p(0.2))
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plt.title('群组表达方式相似度热力图 (对数变换)')
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plt.xticks(rotation=45, ha='right')
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sns.heatmap(
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log_style_matrix,
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xticklabels=group_names,
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yticklabels=group_names,
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cmap="YlOrRd",
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annot=True,
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fmt=".2f",
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vmin=0,
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vmax=np.log1p(0.2),
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)
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plt.title("群组表达方式相似度热力图 (对数变换)")
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plt.xticks(rotation=45, ha="right")
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# 组合相似度热力图
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plt.subplot(1, 3, 3)
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sns.heatmap(log_combined_matrix,
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xticklabels=group_names,
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yticklabels=group_names,
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cmap='YlOrRd',
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annot=True,
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fmt='.2f',
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vmin=0,
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vmax=np.log1p(0.2))
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plt.title('群组场景+表达方式相似度热力图 (对数变换)')
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plt.xticks(rotation=45, ha='right')
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sns.heatmap(
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log_combined_matrix,
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xticklabels=group_names,
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yticklabels=group_names,
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cmap="YlOrRd",
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annot=True,
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fmt=".2f",
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vmin=0,
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vmax=np.log1p(0.2),
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)
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plt.title("群组场景+表达方式相似度热力图 (对数变换)")
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plt.xticks(rotation=45, ha="right")
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plt.tight_layout()
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plt.savefig(SCRIPT_DIR / 'group_similarity_heatmaps.png', dpi=300, bbox_inches='tight')
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plt.savefig(SCRIPT_DIR / "group_similarity_heatmaps.png", dpi=300, bbox_inches="tight")
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plt.close()
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# 保存匹配详情到文本文件
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with open(SCRIPT_DIR / 'group_similarity_details.txt', 'w', encoding='utf-8') as f:
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f.write('群组相似度详情\n')
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f.write('=' * 50 + '\n\n')
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with open(SCRIPT_DIR / "group_similarity_details.txt", "w", encoding="utf-8") as f:
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f.write("群组相似度详情\n")
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f.write("=" * 50 + "\n\n")
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for i in range(len(group_ids)):
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for j in range(i+1, len(group_ids)):
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for j in range(i + 1, len(group_ids)):
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if log_combined_matrix[i][j] > np.log1p(0.05):
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f.write(f'群组1: {group_names[i]}\n')
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f.write(f'群组2: {group_names[j]}\n')
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f.write(f'场景相似度: {situation_matrix[i][j]:.4f}\n')
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f.write(f'表达方式相似度: {style_matrix[i][j]:.4f}\n')
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f.write(f'组合相似度: {combined_matrix[i][j]:.4f}\n')
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f.write(f"群组1: {group_names[i]}\n")
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f.write(f"群组2: {group_names[j]}\n")
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f.write(f"场景相似度: {situation_matrix[i][j]:.4f}\n")
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f.write(f"表达方式相似度: {style_matrix[i][j]:.4f}\n")
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f.write(f"组合相似度: {combined_matrix[i][j]:.4f}\n")
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# 获取两个群组的数据
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situations1, styles1, _ = load_group_data(group_dirs[i])
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situations2, styles2, _ = load_group_data(group_dirs[j])
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# 找出共同的场景
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common_situations = set(situations1) & set(situations2)
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if common_situations:
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f.write('\n共同场景:\n')
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f.write("\n共同场景:\n")
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for situation in common_situations:
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f.write(f'- {situation}\n')
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f.write(f"- {situation}\n")
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# 找出共同的表达方式
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common_styles = set(styles1) & set(styles2)
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if common_styles:
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f.write('\n共同表达方式:\n')
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f.write("\n共同表达方式:\n")
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for style in common_styles:
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f.write(f'- {style}\n')
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f.write('\n' + '-' * 50 + '\n\n')
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f.write(f"- {style}\n")
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f.write("\n" + "-" * 50 + "\n\n")
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if __name__ == "__main__":
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analyze_group_similarity()
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@@ -32,7 +32,6 @@ from rich.panel import Panel
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from src.common.database.database import db
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from src.common.database.database_model import (
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ChatStreams,
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LLMUsage,
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Emoji,
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Messages,
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Images,
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@@ -8,162 +8,174 @@ import matplotlib.pyplot as plt
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from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
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from sklearn.feature_extraction.text import TfidfVectorizer
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from sklearn.metrics.pairwise import cosine_similarity
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import numpy as np
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from collections import defaultdict
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class ExpressionViewer:
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def __init__(self, root):
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self.root = root
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self.root.title("表达方式预览器")
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self.root.geometry("1200x800")
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# 创建主框架
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self.main_frame = ttk.Frame(root)
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self.main_frame.pack(fill=tk.BOTH, expand=True, padx=10, pady=10)
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# 创建左侧控制面板
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self.control_frame = ttk.Frame(self.main_frame)
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self.control_frame.pack(side=tk.LEFT, fill=tk.Y, padx=(0, 10))
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# 创建搜索框
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self.search_frame = ttk.Frame(self.control_frame)
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self.search_frame.pack(fill=tk.X, pady=(0, 10))
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self.search_var = tk.StringVar()
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self.search_var.trace('w', self.filter_expressions)
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self.search_var.trace("w", self.filter_expressions)
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self.search_entry = ttk.Entry(self.search_frame, textvariable=self.search_var)
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self.search_entry.pack(side=tk.LEFT, fill=tk.X, expand=True)
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ttk.Label(self.search_frame, text="搜索:").pack(side=tk.LEFT, padx=(0, 5))
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# 创建文件选择下拉框
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self.file_var = tk.StringVar()
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self.file_combo = ttk.Combobox(self.search_frame, textvariable=self.file_var)
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self.file_combo.pack(side=tk.LEFT, padx=5)
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self.file_combo.bind('<<ComboboxSelected>>', self.load_file)
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self.file_combo.bind("<<ComboboxSelected>>", self.load_file)
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# 创建排序选项
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self.sort_frame = ttk.LabelFrame(self.control_frame, text="排序选项")
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self.sort_frame.pack(fill=tk.X, pady=5)
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self.sort_var = tk.StringVar(value="count")
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ttk.Radiobutton(self.sort_frame, text="按计数排序", variable=self.sort_var,
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value="count", command=self.apply_sort).pack(anchor=tk.W)
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ttk.Radiobutton(self.sort_frame, text="按情境排序", variable=self.sort_var,
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value="situation", command=self.apply_sort).pack(anchor=tk.W)
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ttk.Radiobutton(self.sort_frame, text="按风格排序", variable=self.sort_var,
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value="style", command=self.apply_sort).pack(anchor=tk.W)
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ttk.Radiobutton(
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self.sort_frame, text="按计数排序", variable=self.sort_var, value="count", command=self.apply_sort
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).pack(anchor=tk.W)
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ttk.Radiobutton(
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self.sort_frame, text="按情境排序", variable=self.sort_var, value="situation", command=self.apply_sort
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).pack(anchor=tk.W)
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ttk.Radiobutton(
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self.sort_frame, text="按风格排序", variable=self.sort_var, value="style", command=self.apply_sort
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).pack(anchor=tk.W)
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# 创建分群选项
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self.group_frame = ttk.LabelFrame(self.control_frame, text="分群选项")
|
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self.group_frame.pack(fill=tk.X, pady=5)
|
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|
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self.group_var = tk.StringVar(value="none")
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ttk.Radiobutton(self.group_frame, text="不分群", variable=self.group_var,
|
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value="none", command=self.apply_grouping).pack(anchor=tk.W)
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ttk.Radiobutton(self.group_frame, text="按情境分群", variable=self.group_var,
|
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value="situation", command=self.apply_grouping).pack(anchor=tk.W)
|
||||
ttk.Radiobutton(self.group_frame, text="按风格分群", variable=self.group_var,
|
||||
value="style", command=self.apply_grouping).pack(anchor=tk.W)
|
||||
|
||||
ttk.Radiobutton(
|
||||
self.group_frame, text="不分群", variable=self.group_var, value="none", command=self.apply_grouping
|
||||
).pack(anchor=tk.W)
|
||||
ttk.Radiobutton(
|
||||
self.group_frame, text="按情境分群", variable=self.group_var, value="situation", command=self.apply_grouping
|
||||
).pack(anchor=tk.W)
|
||||
ttk.Radiobutton(
|
||||
self.group_frame, text="按风格分群", variable=self.group_var, value="style", command=self.apply_grouping
|
||||
).pack(anchor=tk.W)
|
||||
|
||||
# 创建相似度阈值滑块
|
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self.similarity_frame = ttk.LabelFrame(self.control_frame, text="相似度设置")
|
||||
self.similarity_frame.pack(fill=tk.X, pady=5)
|
||||
|
||||
|
||||
self.similarity_var = tk.DoubleVar(value=0.5)
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self.similarity_scale = ttk.Scale(self.similarity_frame, from_=0.0, to=1.0,
|
||||
variable=self.similarity_var, orient=tk.HORIZONTAL,
|
||||
command=self.update_similarity)
|
||||
self.similarity_scale = ttk.Scale(
|
||||
self.similarity_frame,
|
||||
from_=0.0,
|
||||
to=1.0,
|
||||
variable=self.similarity_var,
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||||
orient=tk.HORIZONTAL,
|
||||
command=self.update_similarity,
|
||||
)
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||||
self.similarity_scale.pack(fill=tk.X, padx=5, pady=5)
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||||
ttk.Label(self.similarity_frame, text="相似度阈值: 0.5").pack()
|
||||
|
||||
|
||||
# 创建显示选项
|
||||
self.view_frame = ttk.LabelFrame(self.control_frame, text="显示选项")
|
||||
self.view_frame.pack(fill=tk.X, pady=5)
|
||||
|
||||
|
||||
self.show_graph_var = tk.BooleanVar(value=True)
|
||||
ttk.Checkbutton(self.view_frame, text="显示关系图", variable=self.show_graph_var,
|
||||
command=self.toggle_graph).pack(anchor=tk.W)
|
||||
|
||||
ttk.Checkbutton(
|
||||
self.view_frame, text="显示关系图", variable=self.show_graph_var, command=self.toggle_graph
|
||||
).pack(anchor=tk.W)
|
||||
|
||||
# 创建右侧内容区域
|
||||
self.content_frame = ttk.Frame(self.main_frame)
|
||||
self.content_frame.pack(side=tk.LEFT, fill=tk.BOTH, expand=True)
|
||||
|
||||
|
||||
# 创建文本显示区域
|
||||
self.text_area = tk.Text(self.content_frame, wrap=tk.WORD)
|
||||
self.text_area.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
|
||||
|
||||
|
||||
# 添加滚动条
|
||||
scrollbar = ttk.Scrollbar(self.text_area, command=self.text_area.yview)
|
||||
scrollbar.pack(side=tk.RIGHT, fill=tk.Y)
|
||||
self.text_area.config(yscrollcommand=scrollbar.set)
|
||||
|
||||
|
||||
# 创建图形显示区域
|
||||
self.graph_frame = ttk.Frame(self.content_frame)
|
||||
self.graph_frame.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
|
||||
|
||||
|
||||
# 初始化数据
|
||||
self.current_data = []
|
||||
self.graph = nx.Graph()
|
||||
self.canvas = None
|
||||
|
||||
|
||||
# 加载文件列表
|
||||
self.load_file_list()
|
||||
|
||||
|
||||
def load_file_list(self):
|
||||
expression_dir = Path("data/expression")
|
||||
files = []
|
||||
for root, _, filenames in os.walk(expression_dir):
|
||||
for filename in filenames:
|
||||
if filename.endswith('.json'):
|
||||
if filename.endswith(".json"):
|
||||
rel_path = os.path.relpath(os.path.join(root, filename), expression_dir)
|
||||
files.append(rel_path)
|
||||
|
||||
self.file_combo['values'] = files
|
||||
|
||||
self.file_combo["values"] = files
|
||||
if files:
|
||||
self.file_combo.set(files[0])
|
||||
self.load_file(None)
|
||||
|
||||
|
||||
def load_file(self, event):
|
||||
selected_file = self.file_var.get()
|
||||
if not selected_file:
|
||||
return
|
||||
|
||||
|
||||
file_path = os.path.join("data/expression", selected_file)
|
||||
try:
|
||||
with open(file_path, 'r', encoding='utf-8') as f:
|
||||
with open(file_path, "r", encoding="utf-8") as f:
|
||||
self.current_data = json.load(f)
|
||||
|
||||
|
||||
self.apply_sort()
|
||||
self.update_similarity()
|
||||
|
||||
|
||||
except Exception as e:
|
||||
self.text_area.delete(1.0, tk.END)
|
||||
self.text_area.insert(tk.END, f"加载文件时出错: {str(e)}")
|
||||
|
||||
|
||||
def apply_sort(self):
|
||||
if not self.current_data:
|
||||
return
|
||||
|
||||
|
||||
sort_key = self.sort_var.get()
|
||||
reverse = sort_key == "count"
|
||||
|
||||
|
||||
self.current_data.sort(key=lambda x: x.get(sort_key, ""), reverse=reverse)
|
||||
self.apply_grouping()
|
||||
|
||||
|
||||
def apply_grouping(self):
|
||||
if not self.current_data:
|
||||
return
|
||||
|
||||
|
||||
group_key = self.group_var.get()
|
||||
if group_key == "none":
|
||||
self.display_data(self.current_data)
|
||||
return
|
||||
|
||||
|
||||
grouped_data = defaultdict(list)
|
||||
for item in self.current_data:
|
||||
key = item.get(group_key, "未分类")
|
||||
grouped_data[key].append(item)
|
||||
|
||||
|
||||
self.text_area.delete(1.0, tk.END)
|
||||
for group, items in grouped_data.items():
|
||||
self.text_area.insert(tk.END, f"\n=== {group} ===\n\n")
|
||||
@@ -172,7 +184,7 @@ class ExpressionViewer:
|
||||
self.text_area.insert(tk.END, f"风格: {item.get('style', 'N/A')}\n")
|
||||
self.text_area.insert(tk.END, f"计数: {item.get('count', 'N/A')}\n")
|
||||
self.text_area.insert(tk.END, "-" * 50 + "\n")
|
||||
|
||||
|
||||
def display_data(self, data):
|
||||
self.text_area.delete(1.0, tk.END)
|
||||
for item in data:
|
||||
@@ -180,59 +192,58 @@ class ExpressionViewer:
|
||||
self.text_area.insert(tk.END, f"风格: {item.get('style', 'N/A')}\n")
|
||||
self.text_area.insert(tk.END, f"计数: {item.get('count', 'N/A')}\n")
|
||||
self.text_area.insert(tk.END, "-" * 50 + "\n")
|
||||
|
||||
|
||||
def update_similarity(self, *args):
|
||||
if not self.current_data:
|
||||
return
|
||||
|
||||
|
||||
threshold = self.similarity_var.get()
|
||||
self.similarity_frame.winfo_children()[-1].config(text=f"相似度阈值: {threshold:.2f}")
|
||||
|
||||
|
||||
# 计算相似度
|
||||
texts = [f"{item['situation']} {item['style']}" for item in self.current_data]
|
||||
vectorizer = TfidfVectorizer()
|
||||
tfidf_matrix = vectorizer.fit_transform(texts)
|
||||
similarity_matrix = cosine_similarity(tfidf_matrix)
|
||||
|
||||
|
||||
# 创建图
|
||||
self.graph.clear()
|
||||
for i, item in enumerate(self.current_data):
|
||||
self.graph.add_node(i, label=f"{item['situation']}\n{item['style']}")
|
||||
|
||||
|
||||
# 添加边
|
||||
for i in range(len(self.current_data)):
|
||||
for j in range(i + 1, len(self.current_data)):
|
||||
if similarity_matrix[i, j] > threshold:
|
||||
self.graph.add_edge(i, j, weight=similarity_matrix[i, j])
|
||||
|
||||
|
||||
if self.show_graph_var.get():
|
||||
self.draw_graph()
|
||||
|
||||
|
||||
def draw_graph(self):
|
||||
if self.canvas:
|
||||
self.canvas.get_tk_widget().destroy()
|
||||
|
||||
|
||||
fig = plt.figure(figsize=(8, 6))
|
||||
pos = nx.spring_layout(self.graph)
|
||||
|
||||
|
||||
# 绘制节点
|
||||
nx.draw_networkx_nodes(self.graph, pos, node_color='lightblue',
|
||||
node_size=1000, alpha=0.6)
|
||||
|
||||
nx.draw_networkx_nodes(self.graph, pos, node_color="lightblue", node_size=1000, alpha=0.6)
|
||||
|
||||
# 绘制边
|
||||
nx.draw_networkx_edges(self.graph, pos, alpha=0.4)
|
||||
|
||||
|
||||
# 添加标签
|
||||
labels = nx.get_node_attributes(self.graph, 'label')
|
||||
labels = nx.get_node_attributes(self.graph, "label")
|
||||
nx.draw_networkx_labels(self.graph, pos, labels, font_size=8)
|
||||
|
||||
|
||||
plt.title("表达方式关系图")
|
||||
plt.axis('off')
|
||||
|
||||
plt.axis("off")
|
||||
|
||||
self.canvas = FigureCanvasTkAgg(fig, master=self.graph_frame)
|
||||
self.canvas.draw()
|
||||
self.canvas.get_tk_widget().pack(fill=tk.BOTH, expand=True)
|
||||
|
||||
|
||||
def toggle_graph(self):
|
||||
if self.show_graph_var.get():
|
||||
self.draw_graph()
|
||||
@@ -240,26 +251,28 @@ class ExpressionViewer:
|
||||
if self.canvas:
|
||||
self.canvas.get_tk_widget().destroy()
|
||||
self.canvas = None
|
||||
|
||||
|
||||
def filter_expressions(self, *args):
|
||||
search_text = self.search_var.get().lower()
|
||||
if not search_text:
|
||||
self.apply_sort()
|
||||
return
|
||||
|
||||
|
||||
filtered_data = []
|
||||
for item in self.current_data:
|
||||
situation = item.get('situation', '').lower()
|
||||
style = item.get('style', '').lower()
|
||||
situation = item.get("situation", "").lower()
|
||||
style = item.get("style", "").lower()
|
||||
if search_text in situation or search_text in style:
|
||||
filtered_data.append(item)
|
||||
|
||||
|
||||
self.display_data(filtered_data)
|
||||
|
||||
|
||||
def main():
|
||||
root = tk.Tk()
|
||||
app = ExpressionViewer(root)
|
||||
# app = ExpressionViewer(root)
|
||||
root.mainloop()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
main()
|
||||
|
||||
Reference in New Issue
Block a user