373 lines
15 KiB
Python
373 lines
15 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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融资计划书图表生成工具
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Generate charts and diagrams for financing plan
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"""
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import matplotlib.pyplot as plt
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import matplotlib.patches as patches
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import numpy as np
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import pandas as pd
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from matplotlib.font_manager import FontProperties
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import seaborn as sns
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from datetime import datetime
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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'] = ['Microsoft YaHei', 'SimHei', 'DejaVu Sans']
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plt.rcParams['axes.unicode_minus'] = False
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class FinancingChartGenerator:
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"""融资计划书图表生成器"""
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def __init__(self, output_dir='charts'):
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self.output_dir = output_dir
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if not os.path.exists(output_dir):
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os.makedirs(output_dir)
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# 设置颜色主题
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self.colors = {
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'primary': '#1F497D',
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'secondary': '#365F91',
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'accent': '#4F81BD',
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'success': '#70AD47',
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'warning': '#FFC000',
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'danger': '#C5504B',
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'light': '#F2F2F2',
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'dark': '#404040'
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}
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def generate_market_size_chart(self):
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"""生成市场规模图表"""
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fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))
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# 市场规模数据
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markets = ['智能穿戴设备', '健康管理服务', '目标细分市场']
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sizes = [400, 10000, 500]
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colors = [self.colors['primary'], self.colors['secondary'], self.colors['accent']]
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# 柱状图
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bars = ax1.bar(markets, sizes, color=colors, alpha=0.8)
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ax1.set_title('2025年市场规模预测（亿元）', fontsize=14, fontweight='bold')
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ax1.set_ylabel('市场规模（亿元）')
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# 添加数值标签
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for bar, size in zip(bars, sizes):
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height = bar.get_height()
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ax1.text(bar.get_x() + bar.get_width()/2., height + 50,
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f'{size}亿', ha='center', va='bottom', fontweight='bold')
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# 饼图 - 目标用户分布
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user_segments = ['在校学生', '老年人群', '其他健康群体']
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user_counts = [2.9, 2.64, 1.0]
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ax2.pie(user_counts, labels=user_segments, autopct='%1.1f亿',
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colors=[colors[1] for colors in [self.colors['primary'], self.colors['secondary'], self.colors['accent']]],
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startangle=90)
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ax2.set_title('目标用户群体分布', fontsize=14, fontweight='bold')
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plt.tight_layout()
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plt.savefig(f'{self.output_dir}/market_analysis.png', dpi=300, bbox_inches='tight')
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plt.close()
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def generate_financial_projection(self):
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"""生成财务预测图表"""
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fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(16, 12))
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# 收入预测
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years = ['2025年', '2026年', '2027年']
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revenues = [2000, 8000, 30000]
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ax1.plot(years, revenues, marker='o', linewidth=3, markersize=8,
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color=self.colors['primary'])
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ax1.fill_between(years, revenues, alpha=0.3, color=self.colors['primary'])
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ax1.set_title('收入预测（万元）', fontsize=14, fontweight='bold')
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ax1.set_ylabel('收入（万元）')
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ax1.grid(True, alpha=0.3)
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# 添加数值标签
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for i, (year, revenue) in enumerate(zip(years, revenues)):
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ax1.text(i, revenue + 1000, f'{revenue}万', ha='center', va='bottom', fontweight='bold')
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# 收入结构 - 2027年预测
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revenue_types = ['硬件销售', '平台服务', '数据服务', '数字资产']
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revenue_values = [12000, 10000, 5000, 3000]
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wedges, texts, autotexts = ax2.pie(revenue_values, labels=revenue_types, autopct='%1.1f%%',
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colors=[self.colors['primary'], self.colors['secondary'],
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self.colors['accent'], self.colors['success']])
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ax2.set_title('2027年收入结构预测', fontsize=14, fontweight='bold')
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# 成本结构分析
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cost_types = ['硬件采购\n40%', '销售费用\n15%', '运营服务\n20%', '其他成本\n25%']
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cost_percentages = [40, 15, 20, 25]
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bars = ax3.barh(cost_types, cost_percentages,
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color=[self.colors['danger'], self.colors['warning'],
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self.colors['accent'], self.colors['dark']])
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ax3.set_title('成本结构分析', fontsize=14, fontweight='bold')
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ax3.set_xlabel('占收入比例（%）')
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# 盈利能力分析
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years_profit = ['2025年', '2026年', '2027年']
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gross_margin = [60, 60, 60]
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net_margin = [15, 25, 30]
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x = np.arange(len(years_profit))
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width = 0.35
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ax4.bar(x - width/2, gross_margin, width, label='毛利率', color=self.colors['success'])
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ax4.bar(x + width/2, net_margin, width, label='净利率', color=self.colors['primary'])
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ax4.set_title('盈利能力分析', fontsize=14, fontweight='bold')
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ax4.set_ylabel('利润率（%）')
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ax4.set_xticks(x)
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ax4.set_xticklabels(years_profit)
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ax4.legend()
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ax4.grid(True, alpha=0.3)
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plt.tight_layout()
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plt.savefig(f'{self.output_dir}/financial_projection.png', dpi=300, bbox_inches='tight')
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plt.close()
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def generate_business_model_flow(self):
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"""生成商业模式流程图"""
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fig, ax = plt.subplots(figsize=(14, 10))
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# 定义流程节点
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nodes = [
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{'name': '数据采集层', 'pos': (2, 8), 'color': self.colors['primary']},
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{'name': '数据传输层', 'pos': (4, 8), 'color': self.colors['secondary']},
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{'name': '数据处理层', 'pos': (6, 8), 'color': self.colors['accent']},
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{'name': '数据存储层', 'pos': (8, 8), 'color': self.colors['success']},
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{'name': '数据分析层', 'pos': (10, 8), 'color': self.colors['warning']},
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{'name': '价值输出层', 'pos': (10, 6), 'color': self.colors['danger']},
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{'name': '资产确权层', 'pos': (8, 4), 'color': self.colors['primary']},
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{'name': '价值变现层', 'pos': (4, 4), 'color': self.colors['secondary']},
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]
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# 绘制节点
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for node in nodes:
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circle = patches.Circle(node['pos'], 0.8, facecolor=node['color'],
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edgecolor='white', linewidth=2, alpha=0.8)
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ax.add_patch(circle)
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ax.text(node['pos'][0], node['pos'][1], node['name'],
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ha='center', va='center', fontsize=10, fontweight='bold', color='white')
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# 绘制连接线
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connections = [
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((2, 8), (4, 8)), ((4, 8), (6, 8)), ((6, 8), (8, 8)),
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((8, 8), (10, 8)), ((10, 8), (10, 6)), ((10, 6), (8, 4)),
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((8, 4), (4, 4)), ((4, 4), (2, 8))
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]
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for start, end in connections:
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ax.annotate('', xy=end, xytext=start,
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arrowprops=dict(arrowstyle='->', lw=2, color=self.colors['dark']))
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# 添加硬件设备
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hardware = [
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{'name': '智能手环', 'pos': (1, 6)},
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{'name': '基站设备', 'pos': (2, 6)},
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{'name': '摄像设备', 'pos': (3, 6)}
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]
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for hw in hardware:
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rect = patches.Rectangle((hw['pos'][0]-0.4, hw['pos'][1]-0.3), 0.8, 0.6,
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facecolor=self.colors['light'], edgecolor=self.colors['dark'])
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ax.add_patch(rect)
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ax.text(hw['pos'][0], hw['pos'][1], hw['name'],
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ha='center', va='center', fontsize=8)
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ax.set_xlim(0, 12)
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ax.set_ylim(2, 10)
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ax.set_aspect('equal')
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ax.axis('off')
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ax.set_title('全生命周期AI监测商业模式闭环', fontsize=16, fontweight='bold', pad=20)
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plt.tight_layout()
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plt.savefig(f'{self.output_dir}/business_model_flow.png', dpi=300, bbox_inches='tight')
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plt.close()
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def generate_competition_matrix(self):
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"""生成竞争力矩阵图"""
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fig, ax = plt.subplots(figsize=(12, 8))
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# 竞争维度数据
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dimensions = ['技术创新', '商业模式', '成本优势', '客户粘性']
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competitive_advantage = [5, 5, 5, 4]
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technical_barrier = [5, 4, 3, 4]
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market_impact = [5, 5, 4, 5]
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x = np.arange(len(dimensions))
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width = 0.25
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bars1 = ax.bar(x - width, competitive_advantage, width, label='竞争优势',
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color=self.colors['primary'], alpha=0.8)
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bars2 = ax.bar(x, technical_barrier, width, label='技术壁垒',
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color=self.colors['secondary'], alpha=0.8)
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bars3 = ax.bar(x + width, market_impact, width, label='市场影响',
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color=self.colors['accent'], alpha=0.8)
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ax.set_title('核心竞争力矩阵分析', fontsize=16, fontweight='bold')
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ax.set_ylabel('评分（1-5分）')
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ax.set_xticks(x)
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ax.set_xticklabels(dimensions)
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ax.legend()
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ax.grid(True, alpha=0.3)
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ax.set_ylim(0, 6)
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# 添加数值标签
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for bars in [bars1, bars2, bars3]:
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for bar in bars:
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height = bar.get_height()
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ax.text(bar.get_x() + bar.get_width()/2., height + 0.1,
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f'{height}', ha='center', va='bottom', fontweight='bold')
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plt.tight_layout()
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plt.savefig(f'{self.output_dir}/competition_matrix.png', dpi=300, bbox_inches='tight')
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plt.close()
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def generate_data_value_chain(self):
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"""生成数据价值递增模型"""
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fig, ax = plt.subplots(figsize=(14, 6))
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stages = ['原始数据', '清洗数据', '分析数据', '洞察数据', '资产数据']
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values = [1, 2, 5, 10, 50]
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# 创建阶梯式增长图
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x_pos = np.arange(len(stages))
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bars = ax.bar(x_pos, values, color=[self.colors['primary'], self.colors['secondary'],
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self.colors['accent'], self.colors['success'],
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self.colors['warning']], alpha=0.8)
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# 添加连接线
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for i in range(len(stages)-1):
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ax.annotate('', xy=(x_pos[i+1], values[i+1]), xytext=(x_pos[i], values[i]),
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arrowprops=dict(arrowstyle='->', lw=2, color=self.colors['dark']))
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ax.set_title('数据价值递增模型', fontsize=16, fontweight='bold')
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ax.set_ylabel('价值倍数')
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ax.set_xticks(x_pos)
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ax.set_xticklabels(stages)
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ax.grid(True, alpha=0.3)
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# 添加数值标签
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for bar, value in zip(bars, values):
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height = bar.get_height()
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ax.text(bar.get_x() + bar.get_width()/2., height + 1,
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f'{value}倍', ha='center', va='bottom', fontweight='bold', fontsize=12)
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plt.tight_layout()
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plt.savefig(f'{self.output_dir}/data_value_chain.png', dpi=300, bbox_inches='tight')
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plt.close()
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def generate_investment_return_chart(self):
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"""生成投资回报分析图"""
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fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(16, 12))
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# 三阶段融资规模
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stages = ['第一阶段\n2025年', '第二阶段\n2026年', '第三阶段\n2027年']
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funding_amounts = [1000, 6000, 30000]
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bars = ax1.bar(stages, funding_amounts,
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color=[self.colors['primary'], self.colors['secondary'], self.colors['accent']])
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ax1.set_title('三阶段融资计划（万元）', fontsize=14, fontweight='bold')
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ax1.set_ylabel('融资金额（万元）')
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for bar, amount in zip(bars, funding_amounts):
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height = bar.get_height()
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ax1.text(bar.get_x() + bar.get_width()/2., height + 500,
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f'{amount}万', ha='center', va='bottom', fontweight='bold')
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# 投资回报倍数
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investment_stages = ['第一阶段', '第二阶段', '整体投资']
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return_multiples = [1.8, 4, 20]
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ax2.bar(investment_stages, return_multiples,
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color=[self.colors['success'], self.colors['warning'], self.colors['danger']])
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ax2.set_title('预期投资回报倍数', fontsize=14, fontweight='bold')
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ax2.set_ylabel('回报倍数')
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# 公司估值增长
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years = [2025, 2026, 2027, 2028, 2030]
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valuations = [0.5, 2, 15, 30, 50]
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ax3.plot(years, valuations, marker='o', linewidth=3, markersize=8,
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color=self.colors['primary'])
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ax3.fill_between(years, valuations, alpha=0.3, color=self.colors['primary'])
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ax3.set_title('公司估值预测（亿元）', fontsize=14, fontweight='bold')
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ax3.set_ylabel('估值（亿元）')
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ax3.grid(True, alpha=0.3)
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# 股权结构变化
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stages_equity = ['初始', '第一轮后', '第二轮后', '上市后']
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original_equity = [100, 80, 60, 45]
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investor_equity = [0, 20, 40, 55]
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width = 0.6
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ax4.bar(stages_equity, original_equity, width, label='原股东',
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color=self.colors['primary'])
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ax4.bar(stages_equity, investor_equity, width, bottom=original_equity,
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label='投资者', color=self.colors['secondary'])
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ax4.set_title('股权结构变化', fontsize=14, fontweight='bold')
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ax4.set_ylabel('股权比例（%）')
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ax4.legend()
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plt.tight_layout()
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plt.savefig(f'{self.output_dir}/investment_return.png', dpi=300, bbox_inches='tight')
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plt.close()
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def generate_all_charts(self):
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"""生成所有图表"""
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print("正在生成融资计划书图表...")
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try:
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print("1. 生成市场分析图表...")
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self.generate_market_size_chart()
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print("2. 生成财务预测图表...")
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self.generate_financial_projection()
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print("3. 生成商业模式流程图...")
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self.generate_business_model_flow()
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print("4. 生成竞争力矩阵图...")
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self.generate_competition_matrix()
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print("5. 生成数据价值链图...")
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self.generate_data_value_chain()
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print("6. 生成投资回报分析图...")
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self.generate_investment_return_chart()
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print(f"\n✅ 所有图表已生成完成！")
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print(f"📁 图表保存位置: {self.output_dir}/")
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print("📄 生成的图表文件:")
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chart_files = [
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"market_analysis.png - 市场分析图表",
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"financial_projection.png - 财务预测图表",
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"business_model_flow.png - 商业模式流程图",
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"competition_matrix.png - 竞争力矩阵图",
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"data_value_chain.png - 数据价值链图",
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"investment_return.png - 投资回报分析图"
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]
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for file in chart_files:
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print(f" 📊 {file}")
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except Exception as e:
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print(f"❌ 图表生成失败: {e}")
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return False
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return True
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def main():
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"""主函数"""
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generator = FinancingChartGenerator()
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generator.generate_all_charts()
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if __name__ == '__main__':
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main()
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