lead/frame_plot/show_frame.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Polygon\n",
    "import matplotlib.font_manager as fm\n",
    "\n",
    "# 设置中文字体\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号\n",
    "\n",
    "# 生成随机种群\n",
    "np.random.seed(42)\n",
    "n_points = 50\n",
    "points = np.random.rand(n_points, 2) * 10\n",
    "\n",
    "# 识别帕累托前沿\n",
    "def is_pareto_efficient(costs):\n",
    "    is_efficient = np.ones(costs.shape[0], dtype=bool)\n",
    "    for i, c in enumerate(costs):\n",
    "        if is_efficient[i]:\n",
    "            is_efficient[is_efficient] = np.any(costs[is_efficient] < c, axis=1)  # Remove dominated points\n",
    "            is_efficient[i] = True\n",
    "    return is_efficient\n",
    "\n",
    "# 获取帕累托前沿点\n",
    "pareto_front_mask = is_pareto_efficient(points)\n",
    "pareto_front = points[pareto_front_mask]\n",
    "\n",
    "# 创建图形\n",
    "plt.figure(figsize=(10, 8))\n",
    "\n",
    "# 绘制非帕累托前沿点\n",
    "plt.scatter(points[~pareto_front_mask, 0], points[~pareto_front_mask, 1], \n",
    "           c='lightgray', s=100, label='种群个体')\n",
    "\n",
    "# 绘制帕累托前沿点\n",
    "plt.scatter(pareto_front[:, 0], pareto_front[:, 1], \n",
    "           c='red', s=100, label='帕累托前沿个体')\n",
    "\n",
    "# 连接帕累托前沿点\n",
    "sorted_front = pareto_front[np.argsort(pareto_front[:, 0])]\n",
    "plt.plot(sorted_front[:, 0], sorted_front[:, 1], 'r--', alpha=0.5)\n",
    "\n",
    "# 添加密度分布示意\n",
    "for point in pareto_front:\n",
    "    circle = plt.Circle(point, 0.5, color='blue', fill=False, alpha=0.2)\n",
    "    plt.gca().add_patch(circle)\n",
    "\n",
    "# 添加箭头和标注\n",
    "plt.arrow(8, 8, -0.5, -0.5, head_width=0.2, head_length=0.2, fc='k', ec='k')\n",
    "plt.text(8.2, 8.2, '优化方向', fontsize=20)\n",
    "\n",
    "# 设置标题和标签\n",
    "# plt.title('帕累托前沿维护策略示意图', fontsize=14, pad=20)\n",
    "plt.xlabel('算法性能指标', fontsize=20)\n",
    "plt.ylabel('运行时间', fontsize=20)\n",
    "\n",
    "# 添加图例\n",
    "plt.legend(loc='upper right', fontsize=20)\n",
    "\n",
    "# 添加网格\n",
    "plt.grid(True, linestyle='--', alpha=0.3)\n",
    "\n",
    "# 设置坐标轴范围\n",
    "plt.xlim(-0.5, 11)\n",
    "plt.ylim(-0.5, 11)\n",
    "\n",
    "# 保存图片\n",
    "plt.savefig('pareto_front_strategy.png', dpi=300, bbox_inches='tight')\n",
    "plt.close() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "text1 = '''贪心\n",
    "回溯\n",
    "高度优先\n",
    "图着色\n",
    "饱和度\n",
    "回溯\n",
    "相邻约束\n",
    "图着色\n",
    "贪心\n",
    "回溯\n",
    "高度优先\n",
    "优先队列\n",
    "使用次数\n",
    "颜色选择\n",
    "贪心\n",
    "相邻未着色\n",
    "颜色选择\n",
    "冲突减少\n",
    "饱和度\n",
    "动态更新\n",
    "可用颜色\n",
    "优先队列\n",
    "相邻约束\n",
    "饱和度\n",
    "度数选择\n",
    "相邻约束\n",
    "颜色使用\n",
    "Welsh-Powell\n",
    "Welsh-Powell\n",
    "动态更新\n",
    "可用颜色\n",
    "相邻冲突\n",
    "颜色选择\n",
    "饱和度\n",
    "动态更新\n",
    "相邻约束\n",
    "颜色选择\n",
    "'''\n",
    "text2 = '''\n",
    "贪心\n",
    "度数优先\n",
    "颜色分配\n",
    "图着色\n",
    "最低可用颜色\n",
    "优化\n",
    "优先队列\n",
    "颜色分配\n",
    "贪心\n",
    "图着色\n",
    "度数优先\n",
    "邻居历史\n",
    "最小颜色\n",
    "图着色\n",
    "贪心\n",
    "贪心\n",
    "邻居历史\n",
    "颜色最小化\n",
    "图着色\n",
    "颜色选择\n",
    "Welsh-Powell\n",
    "度数优先\n",
    "颜色分配\n",
    "贪心\n",
    "图着色\n",
    "贪心\n",
    "迭代着色\n",
    "相邻约束\n",
    "图着色\n",
    "颜色选择\n",
    "Welsh-Powell\n",
    "贪心\n",
    "降序着色\n",
    "图着色\n",
    "颜色分配\n",
    "贪心\n",
    "度数优先\n",
    "最小颜色\n",
    "相邻约束\n",
    "图着色'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号\n",
    "plt.rcParams['font.size'] = 16  # 设置更大的字号\n",
    "\n",
    "# 定义要删除的关键词\n",
    "keywords = ['着色', '颜色', '图着色',' ','优化']\n",
    "\n",
    "# 预处理文本,删除包含关键词的行\n",
    "text1_lines = text1.strip().split('\\n')\n",
    "text2_lines = text2.strip().split('\\n')\n",
    "\n",
    "text1_filtered = []\n",
    "text2_filtered = []\n",
    "\n",
    "for line in text1_lines:\n",
    "    if not any(keyword in line for keyword in keywords):\n",
    "        text1_filtered.append(line)\n",
    "        \n",
    "for line in text2_lines:\n",
    "    if not any(keyword in line for keyword in keywords):\n",
    "        text2_filtered.append(line)\n",
    "\n",
    "text1 = '\\n'.join(text1_filtered)\n",
    "text2 = '\\n'.join(text2_filtered)\n",
    "\n",
    "\n",
    "\n",
    "# 统计text1和text2中的词频\n",
    "text1_words = text1.strip().split('\\n')\n",
    "text2_words = text2.strip().split('\\n')\n",
    "\n",
    "# 获取所有唯一的词\n",
    "all_words = sorted(set(text1_words + text2_words))\n",
    "\n",
    "# 统计词频\n",
    "text1_freq = {word: text1_words.count(word) for word in all_words}\n",
    "text2_freq = {word: text2_words.count(word) for word in all_words}\n",
    "\n",
    "# 创建雷达图\n",
    "plt.figure(figsize=(12, 8))\n",
    "\n",
    "# 计算角度\n",
    "angles = np.linspace(0, 2*np.pi, len(all_words), endpoint=False)\n",
    "\n",
    "# 闭合雷达图\n",
    "values1 = list(text1_freq.values())\n",
    "values2 = list(text2_freq.values())\n",
    "values1.append(values1[0])\n",
    "values2.append(values2[0])\n",
    "angles = np.concatenate((angles, [angles[0]]))\n",
    "\n",
    "# 绘制雷达图\n",
    "ax = plt.subplot(111, projection='polar')\n",
    "ax.plot(angles, values1, 'o-', linewidth=2, label='AAD', color='skyblue', alpha=0.7)\n",
    "ax.fill(angles, values1, alpha=0.25, color='skyblue')\n",
    "ax.plot(angles, values2, 'o-', linewidth=2, label='EoH', color='red', alpha=0.7)\n",
    "ax.fill(angles, values2, alpha=0.25, color='red')\n",
    "\n",
    "# 设置刻度标签\n",
    "ax.set_xticks(angles[:-1])\n",
    "ax.set_xticklabels(all_words, fontsize=20)\n",
    "\n",
    "# 添加图例和标题\n",
    "plt.legend(loc='upper right', bbox_to_anchor=(0.05, 0.05),fontsize=22)\n",
    "# plt.title('词频分布雷达图对比', pad=20)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('rador.png', dpi=300)\n",
    "plt.show()"
   ]
  }
 ],
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   "display_name": "lead",
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