415 lines
16 KiB
Python
415 lines
16 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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s音文明基因数字人文分析平台
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Digital Humanities Platform for s-Phoneme Civilization Gene Analysis
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基于新研究范式的综合性数字分析工具
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"""
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import json
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import numpy as np
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import matplotlib.pyplot as plt
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import networkx as nx
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from collections import defaultdict, Counter
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import seaborn as sns
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from datetime import datetime
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import pandas as pd
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from sklearn.cluster import KMeans
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from sklearn.decomposition import PCA
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import plotly.graph_objects as go
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import plotly.express as px
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from plotly.subplots import make_subplots
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import warnings
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warnings.filterwarnings('ignore')
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class SPhonemeDigitalHumanitiesPlatform:
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"""s音文明基因数字人文分析平台"""
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def __init__(self, database_path="s音文明基因数据库.json"):
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"""初始化平台"""
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self.database_path = database_path
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self.data = self.load_database()
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self.civilizations = self.data['s_phoneme_civilization_database']['civilizations']
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self.transmission_pathways = self.data['s_phoneme_civilization_database']['transmission_pathways']
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self.chronological_layers = self.data['s_phoneme_civilization_database']['chronological_layers']
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# 设置中文字体支持
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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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def load_database(self):
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"""加载数据库"""
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try:
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with open(self.database_path, 'r', encoding='utf-8') as f:
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return json.load(f)
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except FileNotFoundError:
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print(f"数据库文件 {self.database_path} 未找到，创建基础数据库...")
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return self.create_basic_database()
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def create_basic_database(self):
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"""创建基础数据库结构"""
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return {
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"s_phoneme_civilization_database": {
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"civilizations": {},
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"transmission_pathways": {},
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"chronological_layers": {}
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}
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}
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def analyze_s_phoneme_stability(self):
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"""分析s音在不同文明中的稳定性"""
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print("🧬 正在分析s音稳定性...")
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stability_data = {}
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for civ_name, civ_data in self.civilizations.items():
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s_phonemes = civ_data.get('s_phoneme_system', {}).get('primary', [])
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vocabulary = civ_data.get('vocabulary', {})
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# 计算s音词汇占比
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s_words = [word for word, data in vocabulary.items()
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if any(sound in word.lower() for sound in ['s', 'ś', 'š', 'sh'])]
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total_words = len(vocabulary)
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s_ratio = len(s_words) / total_words if total_words > 0 else 0
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stability_data[civ_name] = {
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's_phonemes': s_phonemes,
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's_vocabulary_ratio': s_ratio,
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's_word_count': len(s_words),
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'total_vocabulary': total_words,
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'cultural_encoding': len(civ_data.get('cultural_encoding', {}))
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}
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return stability_data
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def visualize_s_phoneme_evolution(self):
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"""可视化s音演化过程"""
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print("📈 正在生成s音演化可视化...")
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# 创建时间序列数据
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periods = []
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s_phoneme_counts = []
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civilization_names = []
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for civ_name, civ_data in self.civilizations.items():
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period = civ_data.get('period', '未知')
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s_phonemes = civ_data.get('s_phoneme_system', {}).get('primary', [])
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periods.append(period)
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s_phoneme_counts.append(len(s_phonemes))
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civilization_names.append(civ_data.get('name', civ_name))
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# 创建演化图
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fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 10))
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# s音数量变化
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ax1.bar(range(len(civilization_names)), s_phoneme_counts,
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color='steelblue', alpha=0.7)
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ax1.set_title('s音音素数量跨文明比较', fontsize=14, fontweight='bold')
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ax1.set_xlabel('文明')
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ax1.set_ylabel('s音音素数量')
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ax1.set_xticks(range(len(civilization_names)))
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ax1.set_xticklabels(civilization_names, rotation=45, ha='right')
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# 添加数值标签
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for i, v in enumerate(s_phoneme_counts):
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ax1.text(i, v + 0.1, str(v), ha='center', va='bottom')
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# s音词汇占比
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stability_data = self.analyze_s_phoneme_stability()
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vocab_ratios = [data['s_vocabulary_ratio'] for data in stability_data.values()]
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ax2.bar(range(len(civilization_names)), vocab_ratios,
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color='darkgreen', alpha=0.7)
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ax2.set_title('s音词汇占比跨文明比较', fontsize=14, fontweight='bold')
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ax2.set_xlabel('文明')
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ax2.set_ylabel('s音词汇占比')
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ax2.set_xticks(range(len(civilization_names)))
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ax2.set_xticklabels(civilization_names, rotation=45, ha='right')
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# 添加百分比标签
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for i, v in enumerate(vocab_ratios):
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ax2.text(i, v + 0.01, f'{v:.1%}', ha='center', va='bottom')
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plt.tight_layout()
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plt.savefig('s音演化分析图.png', dpi=300, bbox_inches='tight')
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plt.show()
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return fig
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def build_transmission_network(self):
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"""构建s音传播网络"""
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print("🌐 正在构建s音传播网络...")
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G = nx.DiGraph()
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# 添加节点（文明）
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for civ_name, civ_data in self.civilizations.items():
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G.add_node(civ_name,
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name=civ_data.get('name', civ_name),
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period=civ_data.get('period', '未知'),
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geography=civ_data.get('geography', '未知'))
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# 添加边（传播路径）
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for pathway_name, pathway_data in self.transmission_pathways.items():
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carriers = pathway_data.get('primary_carriers', [])
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for i in range(len(carriers)-1):
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source = carriers[i]
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target = carriers[i+1]
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if source in G.nodes() and target in G.nodes():
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G.add_edge(source, target,
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pathway=pathway_name,
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characteristics=pathway_data.get('s_phoneme_characteristics', ''))
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return G
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def visualize_transmission_network(self):
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"""可视化传播网络"""
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G = self.build_transmission_network()
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plt.figure(figsize=(15, 12))
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# 使用spring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_colors = ['lightblue' if node in ['sumerian', 'sanskrit_buddhist']
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else 'lightgreen' if 'scythian' in node or 'turkic' in node
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else 'lightcoral' for node in G.nodes()]
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nx.draw_networkx_nodes(G, pos, node_color=node_colors,
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node_size=3000, alpha=0.8)
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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, alpha=0.6)
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# 添加标签
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labels = {node: f"{data['name']}\n{data['period']}"
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for node, data in G.nodes(data=True)}
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nx.draw_networkx_labels(G, pos, labels, font_size=8)
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plt.title('s音文明传播网络图', fontsize=16, fontweight='bold')
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plt.axis('off')
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plt.tight_layout()
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plt.savefig('s音传播网络图.png', dpi=300, bbox_inches='tight')
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plt.show()
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return G
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def analyze_cultural_categories(self):
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"""分析文化类别中的s音分布"""
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print("📊 正在分析文化类别s音分布...")
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categories = self.data['s_phoneme_civilization_database'].get('cultural_categories', {})
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category_stats = {}
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for category, subcategories in categories.items():
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category_stats[category] = {}
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for subcategory, words in subcategories.items():
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s_words = [word for word in words if 's' in word.lower()]
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category_stats[category][subcategory] = {
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'total': len(words),
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's_words': len(s_words),
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'ratio': len(s_words) / len(words) if words else 0
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}
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return category_stats
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def create_interactive_dashboard(self):
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"""创建交互式仪表板"""
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print("🎯 正在创建交互式仪表板...")
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# 准备数据
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stability_data = self.analyze_s_phoneme_stability()
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category_stats = self.analyze_cultural_categories()
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# 创建子图
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fig = make_subplots(
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rows=2, cols=2,
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subplot_titles=('s音稳定性比较', '文化类别s音分布',
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'文明时间线', '传播路径强度'),
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specs=[[{"type": "bar"}, {"type": "bar"}],
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[{"type": "scatter"}, {"type": "heatmap"}]]
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)
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# 1. s音稳定性比较
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civ_names = list(stability_data.keys())
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stability_scores = [data['s_vocabulary_ratio'] for data in stability_data.values()]
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fig.add_trace(
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go.Bar(x=civ_names, y=stability_scores, name='s音词汇占比'),
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row=1, col=1
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)
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# 2. 文化类别s音分布
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categories = []
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ratios = []
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for category, subcats in category_stats.items():
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for subcat, stats in subcats.items():
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categories.append(f"{category}-{subcat}")
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ratios.append(stats['ratio'])
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fig.add_trace(
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go.Bar(x=categories, y=ratios, name='s音占比'),
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row=1, col=2
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)
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# 3. 文明时间线（简化版）
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time_periods = []
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civ_labels = []
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for civ_name, civ_data in self.civilizations.items():
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period = civ_data.get('period', '未知')
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# 简化的年份提取
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if '前' in period:
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try:
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year = -int(period.split('-')[0].replace('前', ''))
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except:
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year = 0
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else:
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try:
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year = int(period.split('-')[0])
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except:
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year = 0
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time_periods.append(year)
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civ_labels.append(civ_data.get('name', civ_name))
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fig.add_trace(
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go.Scatter(x=time_periods, y=civ_labels, mode='markers',
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marker=dict(size=10), name='文明时间分布'),
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row=2, col=1
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)
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# 4. 传播路径强度矩阵
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G = self.build_transmission_network()
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nodes = list(G.nodes())
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adj_matrix = nx.adjacency_matrix(G).toarray()
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fig.add_trace(
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go.Heatmap(z=adj_matrix, x=nodes, y=nodes, colorscale='Blues'),
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row=2, col=2
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)
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# 更新布局
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fig.update_layout(
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title_text="s音文明基因数字人文分析仪表板",
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height=800,
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showlegend=False
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)
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# 保存为HTML文件
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fig.write_html('s音文明基因分析仪表板.html')
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print("💾 交互式仪表板已保存为 's音文明基因分析仪表板.html'")
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return fig
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def generate_comprehensive_report(self):
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"""生成综合分析报告"""
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print("📋 正在生成综合分析报告...")
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stability_data = self.analyze_s_phoneme_stability()
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category_stats = self.analyze_cultural_categories()
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G = self.build_transmission_network()
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report = {
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"metadata": {
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"generated_date": datetime.now().isoformat(),
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"database_version": self.data.get('s_phoneme_civilization_database', {}).get('metadata', {}).get('version', '1.0'),
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"analysis_scope": "丝绸之路s音文明基因综合分析"
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},
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"summary_statistics": {
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"total_civilizations": len(self.civilizations),
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"total_transmission_pathways": len(self.transmission_pathways),
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"network_density": nx.density(G),
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"average_s_phoneme_stability": np.mean([data['s_vocabulary_ratio'] for data in stability_data.values()])
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},
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"key_findings": {
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"most_stable_civilization": max(stability_data.items(), key=lambda x: x[1]['s_vocabulary_ratio']),
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"most_connected_node": max(G.degree(), key=lambda x: x[1]),
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"dominant_cultural_category": max([(cat, np.mean([stats['ratio'] for stats in subcats.values()]))
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for cat, subcats in category_stats.items()], key=lambda x: x[1])
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},
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"detailed_analysis": {
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"s_phoneme_stability": stability_data,
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"cultural_category_distribution": category_stats,
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"network_metrics": {
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"nodes": G.number_of_nodes(),
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"edges": G.number_of_edges(),
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"average_clustering": nx.average_clustering(G),
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"centrality_measures": nx.degree_centrality(G)
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}
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},
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"research_implications": [
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"s音作为文明基因具有高度稳定性和跨文化传播能力",
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"草原通道是s音传播的主要路径，体现了游牧民族的媒介作用",
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"商业活动是s音传播的重要驱动力，形成了s音商业词汇集群",
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"宗教传播强化了s音的神圣性，使其成为文化认同的标识",
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"政治权力的s音编码体现了统治合法性的文化建构"
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]
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}
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# 保存报告
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with open('s音文明基因综合分析报告.json', 'w', encoding='utf-8') as f:
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json.dump(report, f, ensure_ascii=False, indent=2)
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return report
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def run_full_analysis(self):
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"""运行完整分析流程"""
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print("🚀 启动s音文明基因数字人文分析平台...")
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print("="*60)
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# 1. 基础分析
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stability_data = self.analyze_s_phoneme_stability()
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print(f"📊 已分析 {len(stability_data)} 个文明的s音稳定性")
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# 2. 可视化
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self.visualize_s_phoneme_evolution()
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print("📈 已生成s音演化分析图")
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# 3. 网络分析
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G = self.visualize_transmission_network()
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print(f"🌐 已构建包含 {G.number_of_nodes()} 个节点、{G.number_of_edges()} 条边的传播网络")
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# 4. 文化类别分析
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category_stats = self.analyze_cultural_categories()
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print(f"📊 已分析 {len(category_stats)} 个文化类别的s音分布")
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# 5. 交互式仪表板
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self.create_interactive_dashboard()
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print("🎯 已创建交互式分析仪表板")
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# 6. 综合报告
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report = self.generate_comprehensive_report()
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print("📋 已生成综合分析报告")
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print("="*60)
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print("✅ 分析完成！主要发现：")
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print(f" • 平均s音稳定性: {report['summary_statistics']['average_s_phoneme_stability']:.1%}")
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print(f" • 网络密度: {report['summary_statistics']['network_density']:.3f}")
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print(f" • 最稳定文明: {report['key_findings']['most_stable_civilization'][0]}")
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print(f" • 主要文化类别: {report['key_findings']['dominant_cultural_category'][0]}")
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print("="*60)
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return report
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def main():
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"""主函数"""
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# 创建分析平台实例
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platform = SPhonemeDigitalHumanitiesPlatform()
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# 运行完整分析
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report = platform.run_full_analysis()
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print("\n🎉 s音文明基因数字人文分析完成！")
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print("📁 生成的文件:")
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print(" • s音演化分析图.png")
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print(" • s音传播网络图.png")
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print(" • s音文明基因分析仪表板.html")
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print(" • s音文明基因综合分析报告.json")
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return platform, report
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if __name__ == "__main__":
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platform, report = main() |