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