250 lines
9.6 KiB
Python
250 lines
9.6 KiB
Python
#!/usr/bin/env python3
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"""
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胡汉三千年项目历史数据可视化工具
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Historical Data Visualization Tool for Hu-Han Three Thousand Years Project
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"""
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import matplotlib.pyplot as plt
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import seaborn as sns
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import pandas as pd
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import numpy as np
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from typing import Dict, List, Any
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import json
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import os
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# 设置中文字体
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plt.rcParams['font.sans-serif'] = ['SimHei', 'DejaVu Sans']
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plt.rcParams['axes.unicode_minus'] = False
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class HistoricalDataVisualizer:
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"""历史数据可视化器"""
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def __init__(self, output_dir: str = "tools/diagrams/generated"):
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self.output_dir = output_dir
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os.makedirs(output_dir, exist_ok=True)
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# 设置样式
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sns.set_style("whitegrid")
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sns.set_palette("husl")
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def plot_emperor_ages(self, dynasty_data: Dict[str, List[int]],
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title: str = "各朝代皇帝死亡年龄分析"):
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"""绘制皇帝年龄分析图"""
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fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))
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# 左图：年龄分布直方图
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for dynasty, ages in dynasty_data.items():
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ax1.hist(ages, alpha=0.7, label=f"{dynasty} (平均:{np.mean(ages):.1f}岁)",
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bins=10, density=True)
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ax1.set_xlabel('死亡年龄')
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ax1.set_ylabel('密度')
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ax1.set_title('皇帝死亡年龄分布')
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ax1.legend()
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ax1.grid(True, alpha=0.3)
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# 右图：平均年龄对比
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dynasties = list(dynasty_data.keys())
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avg_ages = [np.mean(ages) for ages in dynasty_data.values()]
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median_ages = [np.median(ages) for ages in dynasty_data.values()]
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x = np.arange(len(dynasties))
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width = 0.35
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ax2.bar(x - width/2, avg_ages, width, label='平均年龄', alpha=0.8)
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ax2.bar(x + width/2, median_ages, width, label='中位数年龄', alpha=0.8)
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ax2.set_xlabel('朝代')
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ax2.set_ylabel('年龄')
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ax2.set_title('各朝代统治者年龄对比')
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ax2.set_xticks(x)
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ax2.set_xticklabels(dynasties)
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ax2.legend()
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ax2.grid(True, alpha=0.3)
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# 添加数值标签
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for i, (avg, med) in enumerate(zip(avg_ages, median_ages)):
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ax2.text(i - width/2, avg + 1, f'{avg:.1f}', ha='center', va='bottom')
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ax2.text(i + width/2, med + 1, f'{med:.1f}', ha='center', va='bottom')
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plt.suptitle(title, fontsize=16, fontweight='bold')
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plt.tight_layout()
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# 保存图片
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filename = f"{self.output_dir}/emperor_ages_analysis.png"
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plt.savefig(filename, dpi=300, bbox_inches='tight')
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plt.show()
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return filename
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def plot_cultural_influence_network(self, influence_data: Dict[str, Any],
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title: str = "文化影响传播网络"):
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"""绘制文化影响网络图"""
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import networkx as nx
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fig, ax = plt.subplots(figsize=(12, 8))
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# 创建网络图
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G = nx.DiGraph()
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# 添加节点和边
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for edge in influence_data['edges']:
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G.add_edge(edge['from'], edge['to'],
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weight=edge.get('strength', 1),
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influence=edge.get('influence', ''))
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# 设置布局
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pos = nx.spring_layout(G, k=3, iterations=50)
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# 绘制节点
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node_sizes = [3000 if node in influence_data.get('core_nodes', []) else 2000
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for node in G.nodes()]
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node_colors = ['red' if node in influence_data.get('core_nodes', []) else 'lightblue'
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for node in G.nodes()]
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nx.draw_networkx_nodes(G, pos, node_size=node_sizes,
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node_color=node_colors, alpha=0.8, ax=ax)
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# 绘制边
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nx.draw_networkx_edges(G, pos, edge_color='gray',
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arrows=True, arrowsize=20,
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arrowstyle='->', alpha=0.6, ax=ax)
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# 添加标签
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nx.draw_networkx_labels(G, pos, font_size=12, font_weight='bold', ax=ax)
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# 添加边标签（影响类型）
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edge_labels = {(edge['from'], edge['to']): edge.get('influence', '')
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for edge in influence_data['edges']}
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nx.draw_networkx_edge_labels(G, pos, edge_labels, font_size=8, ax=ax)
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ax.set_title(title, fontsize=16, fontweight='bold')
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ax.axis('off')
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# 添加图例
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legend_elements = [
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plt.Line2D([0], [0], marker='o', color='w', markerfacecolor='red',
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markersize=15, label='核心影响源'),
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plt.Line2D([0], [0], marker='o', color='w', markerfacecolor='lightblue',
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markersize=15, label='影响接受方'),
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plt.Line2D([0], [0], color='gray', label='影响路径')
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]
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ax.legend(handles=legend_elements, loc='upper right')
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plt.tight_layout()
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# 保存图片
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filename = f"{self.output_dir}/cultural_influence_network.png"
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plt.savefig(filename, dpi=300, bbox_inches='tight')
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plt.show()
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return filename
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def plot_timeline_analysis(self, timeline_data: List[Dict[str, Any]],
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title: str = "历史事件时间线分析"):
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"""绘制历史事件时间线"""
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fig, ax = plt.subplots(figsize=(15, 8))
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# 准备数据
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events = sorted(timeline_data, key=lambda x: x['year'])
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years = [event['year'] for event in events]
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categories = list(set(event['category'] for event in events))
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# 为每个类别分配颜色和y位置
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colors = plt.cm.Set3(np.linspace(0, 1, len(categories)))
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category_colors = dict(zip(categories, colors))
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category_positions = {cat: i for i, cat in enumerate(categories)}
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# 绘制时间线
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for event in events:
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y_pos = category_positions[event['category']]
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color = category_colors[event['category']]
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# 绘制事件点
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ax.scatter(event['year'], y_pos, s=200, c=[color],
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alpha=0.8, edgecolors='black', linewidth=1)
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# 添加事件标签
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ax.annotate(event['name'],
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(event['year'], y_pos),
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xytext=(10, 10), textcoords='offset points',
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bbox=dict(boxstyle='round,pad=0.3', facecolor=color, alpha=0.7),
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fontsize=9, ha='left')
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# 设置坐标轴
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ax.set_xlabel('年份', fontsize=12)
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ax.set_ylabel('事件类别', fontsize=12)
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ax.set_yticks(range(len(categories)))
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ax.set_yticklabels(categories)
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ax.set_title(title, fontsize=16, fontweight='bold')
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# 添加网格
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ax.grid(True, alpha=0.3)
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# 设置x轴范围
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year_range = max(years) - min(years)
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ax.set_xlim(min(years) - year_range * 0.05, max(years) + year_range * 0.05)
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plt.tight_layout()
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# 保存图片
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filename = f"{self.output_dir}/timeline_analysis.png"
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plt.savefig(filename, dpi=300, bbox_inches='tight')
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plt.show()
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return filename
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def create_northern_wei_analysis():
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"""创建北魏分析示例"""
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viz = HistoricalDataVisualizer()
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# 示例数据：各朝代皇帝年龄
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dynasty_data = {
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'北魏': [16, 23, 29, 31, 33, 28, 25, 39, 27, 24, 32, 26], # 平均29岁
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'唐朝': [49, 52, 45, 55, 47, 38, 43, 51, 46, 44, 48, 50], # 平均47岁
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'宋朝': [42, 38, 54, 46, 49, 41, 35, 52, 44, 47, 43, 45], # 平均45岁
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'日本天皇': [34, 31, 28, 36, 32, 29, 35, 33, 30, 37, 31, 34] # 平均32岁
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}
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# 生成皇帝年龄分析图
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viz.plot_emperor_ages(dynasty_data, "北魏生殖崇拜理论：皇帝年龄数据支撑")
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# 文化影响网络数据
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influence_data = {
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'core_nodes': ['北魏'],
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'edges': [
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{'from': '北魏', 'to': '高句丽', 'influence': '政治制度', 'strength': 3},
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{'from': '北魏', 'to': '百济', 'influence': '佛教文化', 'strength': 2},
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{'from': '高句丽', 'to': '日本', 'influence': '建筑艺术', 'strength': 2},
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{'from': '百济', 'to': '日本', 'influence': '宗教仪式', 'strength': 3},
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{'from': '北魏', 'to': '新罗', 'influence': '文字系统', 'strength': 1},
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{'from': '新罗', 'to': '日本', 'influence': '学术传统', 'strength': 1}
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]
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}
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# 生成文化影响网络图
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viz.plot_cultural_influence_network(influence_data, "北魏对日本文化影响的传播路径")
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# 时间线数据
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timeline_data = [
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{'year': 386, 'name': '北魏建立', 'category': '政治事件'},
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{'year': 398, 'name': '迁都平城', 'category': '政治事件'},
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{'year': 494, 'name': '孝文帝改革', 'category': '文化改革'},
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{'year': 538, 'name': '佛教传入日本', 'category': '文化传播'},
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{'year': 552, 'name': '百济使者访日', 'category': '外交事件'},
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{'year': 593, 'name': '圣德太子摄政', 'category': '政治事件'},
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{'year': 645, 'name': '大化改新', 'category': '文化改革'}
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]
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# 生成时间线分析图
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viz.plot_timeline_analysis(timeline_data, "北魏影响日本的历史时间线")
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print("✅ 北魏分析可视化图表已生成！")
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print(f"📁 图片保存位置: {viz.output_dir}")
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if __name__ == "__main__":
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create_northern_wei_analysis() |