docs/python/matplotlib.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Matplotlib是Python的二维绘图库，用于生成符合出版质量或跨平台交互环境的各类图形。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 准备数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 一维数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 10, 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = np.cos(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "z = np.sin(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 二维数据或图片"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = 2 * np.random.random((10, 10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "data2 = 3 * np.random.random((10, 10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y, X = np.mgrid[-3:3:100j, -3:3:100j]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "U = -1 - X**2 + Y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "V = 1 + X - Y**2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 绘制图形"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 导入库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 画布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 400x800 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2 = plt.figure(figsize=plt.figaspect(2.0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 坐标轴"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**图形是以坐标轴为核心绘制的，大多数情况下，子图就可以满足需求。子图是栅格系统的坐标轴。**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "ax1 = fig.add_subplot(221)  # row-col-num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "ax3 = fig.add_subplot(212)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig3, axes = plt.subplots(nrows=2, ncols=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig4, axes2 = plt.subplots(ncols=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig.add_axes(ax1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 绘图例程"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 一维数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "lines = ax.plot(x, y)  # 用线或标记连接点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1f5851f3b80>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.scatter(x, y)  # 缩放或着色未连接的点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 3 artists>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes[0, 0].bar([1, 2, 3], [3, 4, 5])  # 绘制柱状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 3 artists>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes[1, 0].barh([0.5, 1, 2.5], [0, 1, 2])  # 绘制水平柱状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x1f58555a040>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes[1, 1].axhline(0.45)  # 绘制与轴平行的横线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x1f585dbd640>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes[0, 1].axvline(0.65)  # 绘制与轴垂直的竖线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.patches.Polygon at 0x1f585dbdca0>]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.fill(x, y, color=\"blue\")  # 绘制填充多边形"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PolyCollection at 0x1f585dc61c0>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.fill_between(x, y, color=\"yellow\")  # 填充 y 值和 0 之间"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 向量场"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.FancyArrow at 0x1f585dc6520>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes[0, 1].arrow(0, 0, 0.5, 0.5)  # 为坐标轴添加箭头"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.quiver.Quiver at 0x1f585dc6760>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes[1, 1].quiver(y, z)  # 二维箭头"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.streamplot.StreamplotSet at 0x1f58555a220>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes[0, 1].streamplot(X, Y, U, V)  # 二维箭头"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([26.,  8.,  7.,  6.,  6.,  6.,  6.,  7.,  8., 20.]),\n",
       " array([-9.99947166e-01, -7.99952450e-01, -5.99957733e-01, -3.99963016e-01,\n",
       "        -1.99968300e-01,  2.64169119e-05,  2.00021134e-01,  4.00015850e-01,\n",
       "         6.00010567e-01,  8.00005283e-01,  1.00000000e+00]),\n",
       " <BarContainer object of 10 artists>)"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax1.hist(y)  # 直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x1f5855b16d0>,\n",
       "  <matplotlib.lines.Line2D at 0x1f5855c14c0>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x1f5855c1d90>,\n",
       "  <matplotlib.lines.Line2D at 0x1f585627580>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x1f5855b1520>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x1f585627e80>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x1f58564d310>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax3.boxplot(y)  # 箱形图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'bodies': [<matplotlib.collections.PolyCollection at 0x1f58564c550>],\n",
       " 'cmaxes': <matplotlib.collections.LineCollection at 0x1f58564ddc0>,\n",
       " 'cmins': <matplotlib.collections.LineCollection at 0x1f585886670>,\n",
       " 'cbars': <matplotlib.collections.LineCollection at 0x1f585894700>}"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax3.violinplot(z)  # 小提琴图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 二维数据或图片"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PolyCollection at 0x1f58587a4c0>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes2[0].pcolor(data2)  # 二维数组伪彩色图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1f583c46af0>"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes2[0].pcolormesh(data)  # 二维数组等高线伪彩色图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "CS = plt.contour(Y, X, U)  # 等高线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "axes2[2] = ax.clabel(CS)  # 等高线图标签"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 图形解析与工作流"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 图形解析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 工作流"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Matplotlib 绘图的基本步骤：\n",
    "- Step 1 准备数据\n",
    "- Step 2 创建图形\n",
    "- Step 3 绘图\n",
    "- Step 4 自定义设置\n",
    "- Step 5 保存图形\n",
    "- Step 6 显示图形"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = [1, 2, 3, 4]  # Step 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = [10, 20, 25, 30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()  # Step 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "ax = fig.add_subplot(111)  # Step 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1f584d73190>]"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.plot(x, y, color=\"lightblue\", linewidth=3)  # Step 3, 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1f584d73370>"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.scatter([2, 4, 6], [5, 15, 25], color=\"darkgreen\", marker=\"^\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1.0, 6.5)"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.set_xlim(1, 6.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.savefig(\"../_tmp/plt_savefig.png\")  # Step 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.show()  # Step 6"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 自定义图形"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 颜色、色条与色彩表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1f584df7700>,\n",
       " <matplotlib.lines.Line2D at 0x1f584df7760>,\n",
       " <matplotlib.lines.Line2D at 0x1f584df7790>]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, x, x, [i**2 for i in x], x, [i**3 for i in x])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1f584e2cf70>]"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.plot(x, y, alpha=0.4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1f584d80a90>]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.plot(x, y, c=\"k\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 标记"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1f584d80df0>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.scatter(x, y, marker=\".\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1f584eaed00>]"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.plot(x, y, marker=\"o\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 线型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1f5861a7310>]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, linewidth=4.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1f586230490>]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, ls=\"solid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1f5862b9160>]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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1+U4KS8oBGNE1gtmjOus2ZVFhERER7xEa6E9hSTk9Wp+apbZ/fAuzI4mXUGERERHTbEg/wYlCJyO7nfqx2yu6R7Jw8oUM7hjuvitIBFRYRETEBOk5hTzz5S6+2pFNWHAAA9q3JDTQH4vFwmUJEWbHEy+kwiIiInUmr6iEv6/ay9trD1LmMvCxwMhukbhc9f5n7aSWqbCIiEitc5aV8/bag7y0ai+O4jIAhnRqxUNXdKZDRIjJ6aQ+UGEREZFat+9YAU9/sQvDgITIEB4Z3cU9p4pIVaiwiIhIrThqP0mULQiArtE2pl4ST7tWTRnfpzW+GlArHlJhERGRGnX4RBHPfpXGV9uz+PqeQbT97xwqc67obHIyqc9UWEREpEY4ikuZ/90+Fv2QQUmZC4sFvt+X4y4sIudDhUVERM5LWbmLf244xIvf7OVEYQkAF7dvwUNXdKZrtM3kdNJQqLCIiEi1uVwG419by8+H8wBo1yqYh0d3ZkincCwWjVORmqPCIiIi1ebjY+HyzuEcPlHEPcM6MKFfLP76JWWpBRbDMOr9bD0OhwObzYbdbic0NNTsOCIiDVaWvZjnv05jXK8LuLj9qduSi0vLKSl3ERrob3I6qW88+fzWFRYRETmnQmcZr68+wP+uPsDJ0nJ2HnGw/K6BWCwWAv19CfT3NTuiNHAqLCIickblLoMPNx/mr1/v4Vi+E4AL2zTn4dGdNUZF6pQKi4iIVGpD+gnmfrqd3Vn5ALRp0YTZIxMY2S1SZUXqnAqLiIhUKttRzO6sfEID/bhraAduTGqD1U9f/Yg5VFhERASA4/lODhwvoH98CwD+p0cU2Y5ixvduTfPgAJPTSWOnwiIi0sgVl5bz5pp0FiTvx+rnQ/L9gwkJ9MdisXDrJfFmxxMBVFhERBotl8vgs5+P8OyK3RyxFwMQ38pGbkEJIbpFWbyMCouISCO0If0ETy/fyc+ZdgCibYE8MDKBqxKj8dEvKYsXUmEREWlkDuYWcv0/1mIY0NTqx7TB7ZgyME5zqYhXU2EREWkESspcBPidmjK/TYtgrundmgA/H2YO60irEKvJ6UTOzaMffJg3bx59+/YlJCSE8PBwxo4dS1paWoV1Bg8ejMViqfC44447zrpfwzCYO3cuUVFRBAUFMWzYMPbu3ev5uxERkQqcZeW88f0BBjzzLRk5he7lz17Tg6fHdVdZkXrDo8KSkpLC9OnTWbduHStXrqS0tJThw4dTWFhYYb3bbruNo0ePuh/PPvvsWff77LPP8tJLL/Haa6+xfv16goODGTFiBMXFxZ6/IxERwTAMvth2lMtfWM1Ty3eRU+DknXUH3a9r4jepbzz6SmjFihUVni9evJjw8HA2b97MoEGD3MubNGlCZGRklfZpGAZ/+9vfeOSRRxgzZgwAb731FhEREXzyySdMmDDBk4giIo1e6uE8nvp8J5sO/gJAeIiV+4Z3Ynyf1iYnE6m+8/oNcLv91OjysLCwCsvfffddWrZsSbdu3ZgzZw5FRUVn3Ed6ejpZWVkMGzbMvcxms9G/f3/Wrl1b6TZOpxOHw1HhISIiMOfjbYyd/wObDv5CoL8Pdw3twHf3Dea6vjH46u4fqceqPejW5XIxc+ZMLr74Yrp16+Ze/oc//IE2bdoQHR3N1q1befDBB0lLS+Pjjz+udD9ZWVkAREREVFgeERHhfu335s2bxxNPPFHd6CIiDVaULRCLBcb3bs19wzsRaQs0O5JIjah2YZk+fTrbt29nzZo1FZZPnTrV/c/du3cnKiqKoUOHsn//ftq1a1f9pL8xZ84cZs2a5X7ucDiIiYmpkX2LiNQXpeUu3ttwiI4RIe7p9G+7JJ7LEsLpdoHN5HQiNatahWXGjBl8/vnnrF69mtatz/6daP/+/QHYt29fpYXl17Eu2dnZREVFuZdnZ2fTs2fPSvdptVqxWjWyXUQaJ8Mw+Hb3Mf78xS72Hy+kS1Qo/75zIL4+FoICfFVWpEHyaAyLYRjMmDGDZcuW8e233xIXF3fObVJTUwEqlJHfiouLIzIyklWrVrmXORwO1q9fT1JSkifxREQavB1H7NzwxnqmLNnE/uOFhAUHMLGfrjBLw+fRFZbp06ezdOlSPv30U0JCQtxjTGw2G0FBQezfv5+lS5dyxRVX0KJFC7Zu3co999zDoEGD6NGjh3s/CQkJzJs3j3HjxmGxWJg5cyZPPfUUHTp0IC4ujkcffZTo6GjGjh1bo29WRKS+yrIX8/zXaXy0JRPDgAA/H265OI4/DWlHqH73RxoBjwrLggULgFOTw/3WokWLmDx5MgEBAXzzzTf87W9/o7CwkJiYGMaPH88jjzxSYf20tDT3HUYADzzwAIWFhUydOpW8vDwGDhzIihUrCAzUYDEREYCNGSf4cHMmAFcmRvPAiE7EhDUxOZVI3bEYhmGYHeJ8ORwObDYbdrud0NBQs+OIiJy3cpdBRm4h7Vo1Bf47I/inO7i69wX0im1ucjqRmuHJ57d+S0hExMt8v/c4T/93dtrv7htMSKA/FouFJ8d2O/fGIg2UCouIiJfYm53Pn7/YxXdpxwEIDfRjd1Y+fduGnWNLkYZPhUVExGQ5BU5eXLmH9zYeptxl4Odj4cakNtx1WQeaBweYHU/EK6iwiIiY6ERhCUOeSybfWQbAiK4RzB7VmbiWwSYnE/EuKiwiIiYKCw5gaOdwDuQU8vAVnd0z1opIRSosIiJ1aEP6CZ5dsZsXrutJbItTtyU/Pa47Qf6++OjHCUXO6Lx+rVlERKomPaeQ29/exHWvr2XTwV/42zd73K8FW/1UVkTOQVdYRERqUV5RCS+t2sfb6zIoLTfwscDEfrHcc3lHs6OJ1CsqLCIiteSddQd57qs07CdLARjcqRUPXdGZjhEhJicTqX9UWEREakluQQn2k6UkRIbw8OjOXNKhldmRROotFRYRkRqSejgPC5AY0wyA2wbFcUHzIMb1ugBfjVEROS8qLCIi5ynzlyKeXZHGZz8foWt0KP+eMRAfHwtNAvy4pk9rs+OJNAgqLCIi1eQoLuXV7/az8Id0SspcWCzQOSqUk6XlBFv116tITdJ/USIiHiord/HPDYd48Zu9nCgsAWBAuxY8PLozXaNtJqcTaZhUWEREPPTNrmM8+ukOANq1CuahKzpzWUI4FovGqYjUFhUWEZEqKHCW0fS/X/OM6BrBZQnhDOnUign9YvH31RycIrVNhUVE5Cyy7MU8/3Uaq/cc59v7BtPU6ofFYmHh5L5mRxNpVFRYREQqUVRSxuspB/jH6gOcLC0H4Nvdx7gqMdrkZCKNkwqLiMhvlLsMPtqcyfNfp3Es3wlAnzbNeWR0Z3rFNjc5nUjjpcIiIvJfxaXlXP3qj+w86gAgNqwJs0clMKpbpAbUiphMhUVE5L8C/X3pENGUzF+KuGtoB25MaoPVz9fsWCICWAzDMMwOcb4cDgc2mw273U5oaKjZcUSknsgpcPL3b/Zy2yXxxLZoAsDxfCd+PhaaBweYnE6k4fPk81tXWESk0SkuLefNNeksSN5PgbOME0UlzP9DbwBahVhNTicilVFhEZFGw+Uy+PfWIzy7Io3/5J0EoPsFNm66qI3JyUTkXFRYRKRR2JRxgic/38nPmXYAom2B3D+yE2MSL8BHv6Qs4vVUWESkUVizL4efM+0EB/jypyHtmTIwjkB/DagVqS9UWESkQcorKiGnoIT24U0BmDoonqKScm67JF7jVETqIRUWEWlQSspcvLU2g5e/3UdMWBCfTR+Ij4+FJgF+PHRFZ7PjiUg1qbCISINgGAYrtmfxzIrdHMwtAiCqPJDjBU4iQgNNTici50uFRUTqvdTDeTy9fCcbM34BTt2afN/wjlzTJwZfDagVaRBUWESkXtuUcYJrXlsLQKC/D1Mvief2S9sRbNVfbyINiY8nK8+bN4++ffsSEhJCeHg4Y8eOJS0tzf36iRMnuPPOO+nUqRNBQUHExsZy1113Ybfbz7rfyZMnY7FYKjxGjhxZvXckIg3ebyfo7h3bnJ4xzRjfuzXf3TeYWcM7qayINEAe/VedkpLC9OnT6du3L2VlZTz00EMMHz6cnTt3EhwczJEjRzhy5AjPP/88Xbp04eDBg9xxxx0cOXKEDz/88Kz7HjlyJIsWLXI/t1o1il9EKiord/HPjYd5d91BPpo2gGCrHz4+Ft6//SL95o9IA3devyV0/PhxwsPDSUlJYdCgQZWu88EHH/DHP/6RwsJC/Pwq70eTJ08mLy+PTz75pFo59FtCIg2bYRh8l3aMP3+xm33HCgB4+IrO3DYo3uRkInI+6uy3hH79qicsLOys64SGhp6xrPwqOTmZ8PBwmjdvzmWXXcZTTz1FixYtKl3X6XTidDrdzx0ORzXSi0h9sPOIg6e/2MkP+3IBCAsOYOawDkzsF2tyMhGpS9W+wuJyubjqqqvIy8tjzZo1la6Tk5NDnz59+OMf/8jTTz99xn299957NGnShLi4OPbv389DDz1E06ZNWbt2Lb6+p1/mffzxx3niiSdOW64rLCINR7nLYM7HW/lgcyaGAQG+Ptw8sC3Th7QnNNDf7HgiUgM8ucJS7cIybdo0vvzyS9asWUPr1q0rDXH55ZcTFhbGZ599hr9/1f+COXDgAO3ateObb75h6NChp71e2RWWmJgYFRaRBuauf/7EZz8f4crEaB4Y0YmYsCZmRxKRGlTrXwnNmDGDzz//nNWrV1daVvLz8xk5ciQhISEsW7bMo7ICEB8fT8uWLdm3b1+lhcVqtWpQrkgDU+4y+GhzJkntWriLyYOjEph8cVt6xzY3OZ2ImM2jwmIYBnfeeSfLli0jOTmZuLi409ZxOByMGDECq9XKZ599RmCg5zNMZmZmkpubS1RUlMfbikj9s2ZvDk8t38nurHyuTIzm5Ym9ALigWRAXNAsyOZ2IeAOP5mGZPn0677zzDkuXLiUkJISsrCyysrI4efIkcKqsDB8+nMLCQt58800cDod7nfLycvd+EhISWLZsGQAFBQXcf//9rFu3joyMDFatWsWYMWNo3749I0aMqMG3KiLeZt+xfG5ZvJE/vrme3Vn5hAb6kdjaxnncvCgiDZRHV1gWLFgAwODBgyssX7RoEZMnT2bLli2sX78egPbt21dYJz09nbZt2wKQlpbmvsPI19eXrVu3smTJEvLy8oiOjmb48OE8+eST+tpHpIHKKXDyt2/28M8Nhyl3Gfj5WPjjRW24e2gHmgcHmB1PRLzQec3D4i00D4tI/fL3b/by4jd7ABjeJYLZoxKIb9XU5FQiUtfqbB4WEZGqcLkMThSV0LLpqaumt14Sx8+ZeUwdFM9F8ZXPtyQi8lsqLCJSqzZmnOCpz3fiMuDT6Rfj42Mh2OrHwsl9zY4mIvWICouI1IqMnEKe+XI3K3ZkARAc4Mu+4wV0jAgxOZmI1EcqLCJSo/KKSnhp1T7eXpdBabmBjwUm9IvlnmEdaRWigfQiUj0qLCJSY/YfL+DqV3/EfrIUgEs7tuKhKzrTKVJXVUTk/KiwiEiNiWsRTJsWTSgpc/HQFZ0Z1LGV2ZFEpIFQYRGRavv5cB4Lkvfz1+sSCbb64eNj4Y2bLqRFUyu+Phaz44lIA6LCIiIey/yliOe+SuPT1CMAdFodwj2XdwQgPNTzn+MQETkXFRYRqbL84lJeTd7Pm2vSKSlzYbHA1b1aM6FfjNnRRKSBU2ERkSp5d/1BXvh6D7mFJQAkxbfg4dGd6XaBzeRkItIYqLCISJWsO3CC3MIS4lsF89CozgztHI7FonEqIlI3VFhEpFI7jzho1sSf6GZBADwwohMXtmnOH/rH4u/r0Q+9i4icN/2tIyIVZDuKeeDDnxn98vc88+Vu9/KYsCZMGtBWZUVETKErLCICQFFJGf9YfYDXUw5wsrQcAAMoK3fhp5IiIiZTYRFp5MpdBh9tyeSvX6eR7XAC0Du2GY/8Txd6xzY3OZ2IyCkqLCKN3NtrM3j83zsBiAkLYvbIzlzRPVIDakXEq6iwiDRCv/2a59oLY3hn/SGuvzCGmwa0werna3I6EZHTqbCINCI5BU7+9s0edhxx8NEdA/DxsRBs9ePrmYPw0VT6IuLFVFhEGoHi0nIW/ZDB/O/2UeAsA2Bdei4D2rUEUFkREa+nwiLSgBmGwWc/H+HZFWn8J+8kAN0vsPHw6M5cFN/C5HQiIlWnwiLSQOUUOJmyZBM/H84DIMoWyAMjOzEm8QJdURGRekeFRaSBCmsSgMtlEBzgy5+GtGfKwDgC/TWgVkTqJxUWkQYir6iEN9ekc8el7Qi2+uHjY+GF6xJp1iSAViFWs+OJiJwXFRaReq6kzMXb6w7y0qq92E+W4mOxcM/lHQHoEBFicjoRkZqhwiJSTxmGwVc7snjmy91k5BYBkBAZQt+2YSYnExGpeSosIvXQz4fzeHr5LjZknACgVYiVey/vyLUXxuCrAbUi0gCpsIjUQ//7/QE2ZJwg0N+HqZfEc/t/x62IiDRU+htOpB7ILy7FWeaiZdNTg2cfHJlAkL8vs4Z3JMoWZHI6EZHap9+MF/FiZeUu3ll3kMHPJfPk5zvdy2PCmvDctYkqKyLSaOgKi4gXMgyD5LTj/PmLXew9VgDA9v/YKSopo0mA/rMVkcZHf/OJeJmdRxz8+YtdrNmXA0DzJv7MHNaRP/SPxd9XF0VFpHHy6G+/efPm0bdvX0JCQggPD2fs2LGkpaVVWKe4uJjp06fTokULmjZtyvjx48nOzj7rfg3DYO7cuURFRREUFMSwYcPYu3ev5+9GpJ5bsT2L0S9/z5p9OQT4+nD7oHiS7x/CpAFtVVZEpFHz6G/AlJQUpk+fzrp161i5ciWlpaUMHz6cwsJC9zr33HMP//73v/nggw9ISUnhyJEjXH311Wfd77PPPstLL73Ea6+9xvr16wkODmbEiBEUFxdX712J1FMDO7SkZVMr/9MjilX3XsqcKzpjC/I3O5aIiOkshmEY1d34+PHjhIeHk5KSwqBBg7Db7bRq1YqlS5dyzTXXALB79246d+7M2rVrueiii07bh2EYREdHc++993LfffcBYLfbiYiIYPHixUyYMOGcORwOBzabDbvdTmhoaHXfjkidKncZfLQlk292ZvPaH/u4f5Awr6iEZk0CTE4nIlL7PPn8Pq9rzHa7HYCwsFMza27evJnS0lKGDRvmXichIYHY2FjWrl1b6T7S09PJysqqsI3NZqN///5n3MbpdOJwOCo8ROqTbZl2rnx5DQ98uJWvd2azYkeW+zWVFRGR01W7sLhcLmbOnMnFF19Mt27dAMjKyiIgIIBmzZpVWDciIoKsrKxK9oJ7eURERJW3mTdvHjabzf2IiYmp7tsQqXN7svO54Y117DzqICTQj4ev6MzQzuFmxxIR8WrVvkto+vTpbN++nTVr1tRkniqZM2cOs2bNcj93OBwqLVIvHMk7yaSFG3AUl9GnTXP+96YLCQvWFRURkXOp1hWWGTNm8Pnnn/Pdd9/RunVr9/LIyEhKSkrIy8ursH52djaRkZGV7uvX5b+/k+hs21itVkJDQys8RLydvaiUyYs2cNReTLtWwbw5SWVFRKSqPCoshmEwY8YMli1bxrfffktcXFyF1/v06YO/vz+rVq1yL0tLS+PQoUMkJSVVus+4uDgiIyMrbONwOFi/fv0ZtxGpjzJyCzlqLyYi1MqSW/pprIqIiAc8+kpo+vTpLF26lE8//ZSQkBD3GBObzUZQUBA2m40pU6Ywa9YswsLCCA0N5c477yQpKanCHUIJCQnMmzePcePGYbFYmDlzJk899RQdOnQgLi6ORx99lOjoaMaOHVujb1bETIkxzfjgjiQMA1o3b2J2HBGResWjwrJgwQIABg8eXGH5okWLmDx5MgAvvvgiPj4+jB8/HqfTyYgRI3j11VcrrJ+Wlua+wwjggQceoLCwkKlTp5KXl8fAgQNZsWIFgYGB1XhLIt7DMAyO5TuJCD11LidE6utLEZHqOK95WLyF5mERb/Vq8j5eS97PG5P60i8uzOw4IiJepc7mYRGRM/tocybPrkjDUVzG9v/Yz72BiIickQqLSC1ITjvGgx9tBWDqoHhuGRh3ji1ERORsVFhEatjWzDz+9O4WylwGY3tGM3tkgtmRRETqPRUWkRp0MLeQWxZvpKiknIHtW/LsNYnu3wgSEZHqU2ERqUGvfLuPnIISukSFsuCPvQnw039iIiI1odpT84vI6Z4a142QQH/uGBxPSKC/2XFERBoMFRaR8+RyGe6vfax+vsy9sovJiUREGh5drxY5D4ZhcP+HW3l6+U5crno/pZGIiNfSFRaR8/D812l8tCUTXx8LVyZG06N1M7MjiYg0SLrCIlJNb6/NYP53+wGYN667yoqISC1SYRGphhXbjzL3sx0AzLq8I9f1jTE5kYhIw6bCIuKhDeknuOu9VAwD/tA/ljsva292JBGRBk+FRcQDjuJSpr69iZIyF5d3ieDJMd2wWDQxnIhIbVNhEfFAaKA/T4/tzoB2LXh5Yi98NYutiEid0F1CIh4a3SOKK7pH6sqKiEgd0hUWkXMoLi1nzsdbOZJ30r1MZUVEpG6psIicRbnLYNa/UvnnhsNMXrSBck0OJyJiChUWkTMwDIMnP9/JF9uyCPD14fGrumrMioiISVRYRM7gtZQDLP4xA4C/XpfIgHYtzQ0kItKIqbCIVOKjzZn8ZcVuAOb+TxeuTIw2OZGISOOmwiLyO2v25vDgR1sBuH1QPLcMjDM5kYiI6LZmkd9pH96U9uFNSYgM4cGRCWbHERERVFhEThNpC+RfdyQR6OeLjwbZioh4BX0lJALkFDj5akeW+3looD8BfvrPQ0TEW+hvZGn0Cp1l3LJ4I7e/vZn3Nx4yO46IiFRChUUatdJyF396dwtbM+2EBQfQt22Y2ZFERKQSKizSaBmGweyPtpGy5zhB/r68OelC4ls1NTuWiIhUQoVFGq3nv07joy2Z+PpYmH9DL3rFNjc7koiInIEKizRKb63NYP53+wH487huXJYQYXIiERE5GxUWaZSO2osBuGdYR67vG2tyGhERORfNwyKN0oMjExjYviUD2rUwO4qIiFSBx1dYVq9ezZVXXkl0dDQWi4VPPvmkwusWi6XSx3PPPXfGfT7++OOnrZ+QoBlGpWYdyi2iuLTc/fzi9i2xWDQxnIhIfeBxYSksLCQxMZH58+dX+vrRo0crPBYuXIjFYmH8+PFn3W/Xrl0rbLdmzRpPo4mc0ZG8k1z/j7Xc9OYG7EWlZscREREPefyV0KhRoxg1atQZX4+MjKzw/NNPP2XIkCHEx8efPYif32nbitQE+8lSJi/awFF7MU0CfHEZhtmRRETEQ7U66DY7O5vly5czZcqUc667d+9eoqOjiY+P54YbbuDQoTPPOOp0OnE4HBUeIpUpLi3ntrc2sSe7gPAQK0tu6Ufz4ACzY4mIiIdqtbAsWbKEkJAQrr766rOu179/fxYvXsyKFStYsGAB6enpXHLJJeTn51e6/rx587DZbO5HTExMbcSXeq7cZTDrX6lsSD9BiNWPxTf3o3XzJmbHEhGRarAYRvWvj1ssFpYtW8bYsWMrfT0hIYHLL7+cl19+2aP95uXl0aZNG1544YVKr844nU6cTqf7ucPhICYmBrvdTmhoqEd/ljRMhmHwxL93svjHDPx9LSy5uR8D2rc0O5aIiPyGw+HAZrNV6fO71m5r/v7770lLS+P999/3eNtmzZrRsWNH9u3bV+nrVqsVq9V6vhGlActyFLPsp/8A8NfreqqsiIjUc7X2ldCbb75Jnz59SExM9HjbgoIC9u/fT1RUVC0kk8YgyhbER9OSeObq7lyVGG12HBEROU8eF5aCggJSU1NJTU0FID09ndTU1AqDZB0OBx988AG33nprpfsYOnQor7zyivv5fffdR0pKChkZGfz444+MGzcOX19fJk6c6Gk8aeR+O89K+/AQJvTTLLYiIg2Bx4Vl06ZN9OrVi169egEwa9YsevXqxdy5c93rvPfeexiGccbCsX//fnJyctzPMzMzmThxIp06deK6666jRYsWrFu3jlatWnkaTxqxbZl2Bj+XzI/7cs69soiI1CvnNejWW3gyaEcapoO5hYxf8CM5BSUM6dSKhZP7ahZbEREv58nnt378UOq9nAInkxZuIKeghC5Robw0sZfKiohIA6PCIvVaobOMKYs3kpFbROvmQSy+pS8hgf5mxxIRkRqmwiL1Vmm5i+lLt/Bzpp3mTfx565Z+hIcEmh1LRERqgQqL1FtLfswgOe04gf4+LJzcl/hWTc2OJCIitaTWJo4TqW03JbVld1Y+o7pF0iu2udlxRESkFqmwSL0V4OfD89d6PjGhiIjUP/pKSOqVFduzePyzHZS76v3d+CIi4gFdYZF6Y2PGCe567ydKylx0igxhomaxFRFpNHSFReqFPdn5TFm8kZIyF5d3ieC6C2PMjiQiInVIhUW83lH7SSYt3ICjuIzesc14aUIvfH00MZyISGOiwiJezX6ylMkLN3LUXky7VsG8OakvQQG+ZscSEZE6psIiXsswDO54ezNp2fmEh1hZcks/mgcHmB1LRERMoMIiXstisTD54ra0bGpl8c39aN28idmRRETEJLpLSLzaiK6RDOrQSl8DiYg0crrCIl7nvQ2HOHyiyP1cZUVERFRYxKt8vCWT2R9vY/yCH8ktcJodR0REvIQKi3iNlD3HeeDDrQCM6RlNi6ZWkxOJiIi3UGERr7At0860dzZT5jIY0zOaOaM6mx1JRES8iAqLmO5gbiE3L95AUUk5F7dvwXPXJOKjieFEROQ3VFjEVDkFTiYt3EBOQQldokJ57Y99CPDTaSkiIhXpk0FM5TIMgq1+tG4exOKb+xIS6G92JBER8UKah0VMFR4SyPu3J3GioITw0ECz44iIiJfSFRapc4ZhsCnjhPt5U6sfsS00i62IiJyZCovUub9+vYdrXlvL6yn7zY4iIiL1hAqL1Km31x3kle/2AWAL0ngVERGpGhUWqTMrtmcx99PtAMwc1oEJ/WJNTiQiIvWFCovUiY0ZJ7jrvZ8wDJjYL5a7h3YwO5KIiNQjKixS6/Zm5zNl8UZKylwM6xzBk2O6YrFoYjgREak6FRapdSl7juMoLqN3bDNentgLP1+ddiIi4hnNwyK17tZL4mnRNIDBHcMJCvA1O46IiNRDKixSK4pLyzEM3AVlXK/WJicSEZH6zONr86tXr+bKK68kOjoai8XCJ598UuH1yZMnY7FYKjxGjhx5zv3Onz+ftm3bEhgYSP/+/dmwYYOn0cRLuFwG9/7rZ254Yx2/FJaYHUdERBoAjwtLYWEhiYmJzJ8//4zrjBw5kqNHj7of//znP8+6z/fff59Zs2bx2GOPsWXLFhITExkxYgTHjh3zNJ6YzDAM/t/nO1m+7Sjb/mNn77ECsyOJiEgD4PFXQqNGjWLUqFFnXcdqtRIZGVnlfb7wwgvcdttt3HzzzQC89tprLF++nIULFzJ79mxPI4qJXl99gMU/ZgDw1+t60i8uzNxAIiLSINTK7RrJycmEh4fTqVMnpk2bRm5u7hnXLSkpYfPmzQwbNuz/Qvn4MGzYMNauXVvpNk6nE4fDUeEh5vt4SybPfLkbgEdGd+aqxGiTE4mISENR44Vl5MiRvPXWW6xatYq//OUvpKSkMGrUKMrLyytdPycnh/LyciIiIiosj4iIICsrq9Jt5s2bh81mcz9iYmJq+m2Ih1L2HOeBD7cCcNslcdx6SbzJiUREpCGp8buEJkyY4P7n7t2706NHD9q1a0dycjJDhw6tkT9jzpw5zJo1y/3c4XCotJiotNzFI59so8xlMKZnNHNGdTY7koiINDC1PoNXfHw8LVu2ZN++fZW+3rJlS3x9fcnOzq6wPDs7+4zjYKxWK6GhoRUeYh5/Xx+W3NyPa/u05rlrEvHx0Sy2IiJSs2q9sGRmZpKbm0tUVFSlrwcEBNCnTx9WrVrlXuZyuVi1ahVJSUm1HU/Og2EY7n+Ob9WU565NJMBPs9iKiEjN8/jTpaCggNTUVFJTUwFIT08nNTWVQ4cOUVBQwP3338+6devIyMhg1apVjBkzhvbt2zNixAj3PoYOHcorr7zifj5r1iz+93//lyVLlrBr1y6mTZtGYWGh+64h8T6FzjJueGM9KXuOmx1FREQaAY/HsGzatIkhQ4a4n/86lmTSpEksWLCArVu3smTJEvLy8oiOjmb48OE8+eSTWK1W9zb79+8nJyfH/fz666/n+PHjzJ07l6ysLHr27MmKFStOG4gr3qG03MX0pVv4cX8ue48VsPr+IZpyX0REapXF+O11/XrK4XBgs9mw2+0az1LLDMPg/g+38uHmTAL9fVh620X0jm1udiwREamHPPn81oAD8chfv97Dh5sz8bHAKxN7q6yIiEidUGGRKnt73UFe+e7U3V5/HtedYV30lZ2IiNQNFRapkg3pJ5j76XYAZg7rwIR+sSYnEhGRxqTGJ46ThqlXbDOu7dMaXx8Ldw/tYHYcERFpZFRYpEr8fX34y/geuAywWDQxnIiI1C19JSRnlGUv5rmvdlNW7gJOFRVfzWIrIiIm0BUWqZT9ZCmTFm4gLTufopJyHruyq9mRRESkEdMVFjlNcWk5U9/aRFp2PuEhVqYMjDM7koiINHIqLFKBy2Vw779+Zn36CUKsfiy+uR+tmzcxO5aIiDRyKiziZhgG/+/znSzfdhR/Xwuv39iHLtGaOVhERMynwiJu/1h9gMU/ZgDw1+t6MqB9S3MDiYiI/JcG3Ypbh4imBPr7cN/wTlyVGG12HBERETcVFnG7LCGCVfcO5oJmQWZHERERqUBfCTVyO47YOZhb6H6usiIiIt5IhaURO5RbxKSFGxi/4Ef2ZOebHUdEROSMVFgaqdwCJzctXE9OQQnhIYFE2QLNjiQiInJGKiyNUFFJGbcs3khGbhGtmwex+Oa+hAT6mx1LRETkjFRYGpnSchfT393Cz5l2mjfxZ8kt/QgP1dUVERHxbiosjYhhGDy8bBvfpR0n0N+HNyf3pV2rpmbHEhEROScVlkaksKSctKx8fCzwysTe9I5tbnYkERGRKtE8LI1IU6sf/5x6EevTTzCkU7jZcURERKpMV1gagSN5J93/3CTAT2VFRETqHRWWBm5TxgmGPJ/MS6v2YhiG2XFERESqRYWlAdubnc+UJZtwlrnYmpmHS31FRETqKRWWBirLXsykhRuwnyyld2wzXp7YG18fi9mxREREqkWFpQGynyxl0sINHLEXE98qmDcn9SUowNfsWCIiItWmwtLAFJeWM/WtTaRl59MqxMqSm/vRPDjA7FgiIiLnRYWlgUlOO8b69BM0tfqx+Oa+xIQ1MTuSiIjIedM8LA3MyG5RPDu+Bxc0D6JrtM3sOCIiIjVChaWBKHcZ7kG11/WNMTmNiIhIzdJXQg3Ax1syuXrBj+QUOM2OIiIiUis8LiyrV6/myiuvJDo6GovFwieffOJ+rbS0lAcffJDu3bsTHBxMdHQ0N910E0eOHDnrPh9//HEsFkuFR0JCgsdvpjFavec4D3y4lZ8P5/H+xsNmxxEREakVHheWwsJCEhMTmT9//mmvFRUVsWXLFh599FG2bNnCxx9/TFpaGlddddU599u1a1eOHj3qfqxZs8bTaI3O9v/YmfbOZspcBlclRjPt0nZmRxIREakVHo9hGTVqFKNGjar0NZvNxsqVKysse+WVV+jXrx+HDh0iNjb2zEH8/IiMjPQ0TqN1KLeIyYs2UFhSzoB2LXju2h74aGI4ERFpoGp9DIvdbsdisdCsWbOzrrd3716io6OJj4/nhhtu4NChQ2dc1+l04nA4Kjwak5wCJzctXE9OQQmdo0J5/cY+WP00MZyIiDRctVpYiouLefDBB5k4cSKhoaFnXK9///4sXryYFStWsGDBAtLT07nkkkvIz8+vdP158+Zhs9ncj5iYxnVXzIMfbiUjt4gLmgWx5Oa+hAT6mx1JRESkVlmM8/gJX4vFwrJlyxg7duxpr5WWljJ+/HgyMzNJTk4+a2H5vby8PNq0acMLL7zAlClTTnvd6XTidP7fHTEOh4OYmBjsdrtHf059dSi3iLvf/4nnr02kXaumZscRERGpFofDgc1mq9Lnd63Mw1JaWsp1113HwYMH+fbbbz0uEc2aNaNjx47s27ev0tetVitWq7UmotZLsS2a8PG0AVgsGrMiIiKNQ41/JfRrWdm7dy/ffPMNLVq08HgfBQUF7N+/n6ioqJqOV2+9tGovq3Zlu5+rrIiISGPicWEpKCggNTWV1NRUANLT00lNTeXQoUOUlpZyzTXXsGnTJt59913Ky8vJysoiKyuLkpIS9z6GDh3KK6+84n5+3333kZKSQkZGBj/++CPjxo3D19eXiRMnnv87bADeXneQF1buYerbmzlwvMDsOCIiInXO46+ENm3axJAhQ9zPZ82aBcCkSZN4/PHH+eyzzwDo2bNnhe2+++47Bg8eDMD+/fvJyclxv5aZmcnEiRPJzc2lVatWDBw4kHXr1tGqVStP4zU4X+3I4rFPtwMwY0h74jVmRUREGqHzGnTrLTwZtFOfbMo4wQ1vrMdZ5mJivxj+PK67vgoSEZEGw5PPb/2WkJfam53PlCWbcJa5GNY5nCfHdFNZERGRRkuFxQvlFDiZtHAD9pOl9IptxssTe+Pnq39VIiLSeOlT0As1C/JncEI48S2DeXNSX4ICNIutiIg0brUyD4ucHz9fH54e2w3HyTJsTTSLrYiIiK6weAmXy+Dd9QcpLXcBp+ZZUVkRERE5RYXFCxiGwZPLd/Lwsu1Mf3cLDeDGLRERkRqlwuIF/rH6AIt+yADgfxKjdTeQiIjI76iwmGzZT5nM+3I3AI+M7sxVidEmJxIREfE+Kiwm+n7vce7/YCsAtw6M49ZL4k1OJCIi4p1UWEyy/T927nh7M2Uug6sSo3nois5mRxIREfFaKiwmySsqxQAGtGvBc9f2wMdH41ZERETORPOwmGRgh5Z8eMcAYsKCsPppYjgREZGz0RWWOlRUUsbB3EL38y7RoYQEaq4VERGRc1FhqSNl5S5mLP2Jca/+yE+HfjE7joiISL2ir4TqgGEYPLRsG9/uPkagvw+aFk5ERMQzusJSB15YuYd/bcrExwKvTOxN79jmZkcSERGpV1RYatk76w7y8rf7AHh6XHeGdYkwOZGIiEj9o8JSi77akcXcT7cDcPfQDkzsF2tyIhERkfpJhaWWGIbBW2szcBkwsV8MM4d1MDuSiIhIvaVBt7XEYrHw5qS+LPohg9suidMPGoqIiJwHXWGpYSdLyt3/HOjvy7TB7fDz1WEWERE5H/okrUH2k6WMe/UHnv8qDcPQzcsiIiI1RYWlhjjLyrn97U3szsrn/U2HyS0sMTuSiIhIg6HCUgNcLoNZ//qZdQdO0NTqx+Kb+9KyqdXsWCIiIg2GCst5MgyDJ5fvZPnWo/j7Wnj9xj50jbaZHUtERKRBUWE5T/9YfYBFP2QA8Py1iVzcvqW5gURERBogFZbzsO9YPs+s2A3AI6M7M6bnBSYnEhERaZg0D8t5aB8ewl+vTSQtO59bL4k3O46IiEiDpcJynq7u3drsCCIiIg2evhLy0OETRUxetIFj+cVmRxEREWk0VFg8kFvg5KaFG0hOO87Dy7abHUdERKTR8LiwrF69miuvvJLo6GgsFguffPJJhdcNw2Du3LlERUURFBTEsGHD2Lt37zn3O3/+fNq2bUtgYCD9+/dnw4YNnkarVUUlZdyyZBPpOYVc0CyIp8d2MzuSiIhIo+FxYSksLCQxMZH58+dX+vqzzz7LSy+9xGuvvcb69esJDg5mxIgRFBef+SuU999/n1mzZvHYY4+xZcsWEhMTGTFiBMeOHfM0Xq0oK3cxY+lP/Hw4j2ZN/HlrSj/CQwPNjiUiItJoWIzz+NEbi8XCsmXLGDt2LHDq6kp0dDT33nsv9913HwB2u52IiAgWL17MhAkTKt1P//796du3L6+88goALpeLmJgY7rzzTmbPnn3OHA6HA5vNht1uJzQ0tLpvp1KGYfDgR1v516ZMAv19ePfWi+jTpnmN/hkiIiKNkSef3zU6hiU9PZ2srCyGDRvmXmaz2ejfvz9r166tdJuSkhI2b95cYRsfHx+GDRt2xm2cTicOh6PCo7a8vvoA/9qUiY8FXp7YW2VFRETEBDVaWLKysgCIiIiosDwiIsL92u/l5ORQXl7u0Tbz5s3DZrO5HzExMTWQvnL/0yOKdq2CeXpcdy7vEnHuDURERKTG1cu7hObMmYPdbnc/Dh8+XGt/VuvmTVh+1yVM7Bdba3+GiIiInF2NFpbIyEgAsrOzKyzPzs52v/Z7LVu2xNfX16NtrFYroaGhFR61KdDft1b3LyIiImdXo4UlLi6OyMhIVq1a5V7mcDhYv349SUlJlW4TEBBAnz59KmzjcrlYtWrVGbcRERGRxsXjqfkLCgrYt2+f+3l6ejqpqamEhYURGxvLzJkzeeqpp+jQoQNxcXE8+uijREdHu+8kAhg6dCjjxo1jxowZAMyaNYtJkyZx4YUX0q9fP/72t79RWFjIzTfffP7vUEREROo9jwvLpk2bGDJkiPv5rFmzAJg0aRKLFy/mgQceoLCwkKlTp5KXl8fAgQNZsWIFgYH/N2/J/v37ycnJcT+//vrrOX78OHPnziUrK4uePXuyYsWK0wbiioiISON0XvOweIvanIdFREREaodp87CIiIiI1AYVFhEREfF6KiwiIiLi9VRYRERExOupsIiIiIjXU2ERERERr6fCIiIiIl5PhUVERES8ngqLiIiIeD2Pp+b3Rr9O1utwOExOIiIiIlX16+d2VSbdbxCFJT8/H4CYmBiTk4iIiIin8vPzsdlsZ12nQfyWkMvl4siRI4SEhGCxWGp03w6Hg5iYGA4fPqzfKToHHauq07GqOh0rz+h4VZ2OVdXV1rEyDIP8/Hyio6Px8Tn7KJUGcYXFx8eH1q1b1+qfERoaqhO6inSsqk7Hqup0rDyj41V1OlZVVxvH6lxXVn6lQbciIiLi9VRYRERExOupsJyD1Wrlsccew2q1mh3F6+lYVZ2OVdXpWHlGx6vqdKyqzhuOVYMYdCsiIiINm66wiIiIiNdTYRERERGvp8IiIiIiXk+FRURERLxeoy8sq1ev5sorryQ6OhqLxcInn3xyzm2Sk5Pp3bs3VquV9u3bs3jx4lrP6Q08PVbJyclYLJbTHllZWXUT2CTz5s2jb9++hISEEB4eztixY0lLSzvndh988AEJCQkEBgbSvXt3vvjiizpIa77qHK/Fixefdl4FBgbWUWLzLFiwgB49ergn70pKSuLLL7886zaN9bzy9Fg11nOqMs888wwWi4WZM2eedb26PrcafWEpLCwkMTGR+fPnV2n99PR0Ro8ezZAhQ0hNTWXmzJnceuutfPXVV7Wc1HyeHqtfpaWlcfToUfcjPDy8lhJ6h5SUFKZPn866detYuXIlpaWlDB8+nMLCwjNu8+OPPzJx4kSmTJnCTz/9xNixYxk7dizbt2+vw+TmqM7xglMzbv72vDp48GAdJTZP69ateeaZZ9i8eTObNm3isssuY8yYMezYsaPS9RvzeeXpsYLGeU793saNG3n99dfp0aPHWdcz5dwyxA0wli1bdtZ1HnjgAaNr164Vll1//fXGiBEjajGZ96nKsfruu+8MwPjll1/qJJO3OnbsmAEYKSkpZ1znuuuuM0aPHl1hWf/+/Y3bb7+9tuN5naocr0WLFhk2m63uQnmx5s2bG2+88Ualr+m8quhsx0rnlGHk5+cbHTp0MFauXGlceumlxt13333Gdc04txr9FRZPrV27lmHDhlVYNmLECNauXWtSIu/Xs2dPoqKiuPzyy/nhhx/MjlPn7HY7AGFhYWdcR+fV/6nK8QIoKCigTZs2xMTEnPP/nBui8vJy3nvvPQoLC0lKSqp0HZ1Xp1TlWIHOqenTpzN69OjTzpnKmHFuNYgfP6xLWVlZREREVFgWERGBw+Hg5MmTBAUFmZTM+0RFRfHaa69x4YUX4nQ6eeONNxg8eDDr16+nd+/eZserEy6Xi5kzZ3LxxRfTrVu3M653pvOqoY/3+b2qHq9OnTqxcOFCevTogd1u5/nnn2fAgAHs2LGj1n8I1Wzbtm0jKSmJ4uJimjZtyrJly+jSpUul6zb288qTY9WYzymA9957jy1btrBx48YqrW/GuaXCIrWmU6dOdOrUyf18wIAB7N+/nxdffJG3337bxGR1Z/r06Wzfvp01a9aYHaVeqOrxSkpKqvB/ygMGDKBz5868/vrrPPnkk7Ud01SdOnUiNTUVu93Ohx9+yKRJk0hJSTnjB3Fj5smxaszn1OHDh7n77rtZuXKlVw80VmHxUGRkJNnZ2RWWZWdnExoaqqsrVdCvX79G8+E9Y8YMPv/8c1avXn3O/0M703kVGRlZmxG9iifH6/f8/f3p1asX+/btq6V03iMgIID27dsD0KdPHzZu3Mjf//53Xn/99dPWbeznlSfH6vca0zm1efNmjh07VuHKd3l5OatXr+aVV17B6XTi6+tbYRszzi2NYfFQUlISq1atqrBs5cqVZ/1eVP5PamoqUVFRZseoVYZhMGPGDJYtW8a3335LXFzcObdpzOdVdY7X75WXl7Nt27YGf25VxuVy4XQ6K32tMZ9XlTnbsfq9xnRODR06lG3btpGamup+XHjhhdxwww2kpqaeVlbApHOr1obz1hP5+fnGTz/9ZPz0008GYLzwwgvGTz/9ZBw8eNAwDMOYPXu2ceONN7rXP3DggNGkSRPj/vvvN3bt2mXMnz/f8PX1NVasWGHWW6gznh6rF1980fjkk0+MvXv3Gtu2bTPuvvtuw8fHx/jmm2/Megt1Ytq0aYbNZjOSk5ONo0ePuh9FRUXudW688UZj9uzZ7uc//PCD4efnZzz//PPGrl27jMcee8zw9/c3tm3bZsZbqFPVOV5PPPGE8dVXXxn79+83Nm/ebEyYMMEIDAw0duzYYcZbqDOzZ882UlJSjPT0dGPr1q3G7NmzDYvFYnz99deGYei8+i1Pj1VjPafO5Pd3CXnDudXoC8uvt97+/jFp0iTDMAxj0qRJxqWXXnraNj179jQCAgKM+Ph4Y9GiRXWe2wyeHqu//OUvRrt27YzAwEAjLCzMGDx4sPHtt9+aE74OVXaMgArnyaWXXuo+br/617/+ZXTs2NEICAgwunbtaixfvrxug5ukOsdr5syZRmxsrBEQEGBEREQYV1xxhbFly5a6D1/HbrnlFqNNmzZGQECA0apVK2Po0KHuD2DD0Hn1W54eq8Z6Tp3J7wuLN5xbFsMwjNq7fiMiIiJy/jSGRURERLyeCouIiIh4PRUWERER8XoqLCIiIuL1VFhERETE66mwiIiIiNdTYRERERGvp8IiIiIiXk+FRURERLyeCouIiIh4PRUWERER8XoqLCIiIuL1/j+xHGyDz9TLbAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, ls=\"--\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1f586338f40>,\n",
       " <matplotlib.lines.Line2D at 0x1f5863460a0>]"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, \"--\", [i**2 for i in x], [i**2 for i in y], \"-.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[None, None]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.setp(lines, color=\"r\", linewidth=4.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 文本与标注"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(1, -2.1, 'Example Graph')"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.text(1, -2.1, \"Example Graph\", style=\"italic\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(10.5, 0, 'Sine')"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.annotate(\n",
    "    \"Sine\",\n",
    "    xy=(8, 0),\n",
    "    xycoords=\"data\",\n",
    "    xytext=(10.5, 0),\n",
    "    textcoords=\"data\",\n",
    "    arrowprops=dict(arrowstyle=\"->\", connectionstyle=\"arc3\"),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数学符号"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '$sigma_i=15$')"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(r\"$sigma_i=15$\", fontsize=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 尺寸限制、图例和布局"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**尺寸限制与自动调整**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "ax.margins(x=0.0, y=0.1)  # 添加内边距"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1.0, 4.0, 8.0, 32.0)"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.axis(\"equal\")  # 将图形纵横比设置为 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 10.5), (-1.5, 1.5)]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.set(xlim=[0, 10.5], ylim=[-1.5, 1.5])  # 设置 x 轴与 y 轴的限制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 10.5)"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.set_xlim(0, 10.5)  # 设置 x 轴的限制"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**图例**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'An Example Axes'),\n",
       " Text(4.444444444444445, 0.5, 'Y-Axis'),\n",
       " Text(0.5, 4.444444444444445, 'X-Axis')]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.set(title=\"An Example Axes\", ylabel=\"Y-Axis\", xlabel=\"X-Axis\")  # 设置标题与 x、y 轴的标签"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1f5875bf610>"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.legend(loc=\"best\")  # 自动选择最佳的图例位置"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**标记**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[<matplotlib.axis.XTick at 0x1f584e5b520>,\n",
       "  <matplotlib.axis.XTick at 0x1f584e5b4f0>,\n",
       "  <matplotlib.axis.XTick at 0x1f584e2ceb0>,\n",
       "  <matplotlib.axis.XTick at 0x1f584e8a8b0>],\n",
       " [Text(1, 0, '3'), Text(2, 0, '100'), Text(3, 0, '-12'), Text(4, 0, 'foo')]]"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.xaxis.set(ticks=range(1, 5), ticklabels=[3, 100, -12, \"foo\"])  # 手动设置 X 轴刻度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "ax.tick_params(axis=\"y\", direction=\"inout\", length=10)  # 设置 Y 轴长度与方向"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**子图间距**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig3.subplots_adjust(\n",
    "    wspace=0.5, hspace=0.3, left=0.125, right=0.9, top=0.9, bottom=0.1\n",
    ")  # 调整子图间距"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.tight_layout()  # 设置画布的子图布局"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**坐标轴边线**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "ax1.spines[\"top\"].set_visible(False)  # 隐藏顶部坐标轴线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "ax1.spines[\"bottom\"].set_position((\"outward\", 10))  # 设置底部边线的位置为 outward"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 保存"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**savefig函数**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.savefig(\"../_tmp/plt_savefig.png\")  # 保存画布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.savefig(\"../_tmp/plt_savefig_transparent.png\", transparent=True)  # 保存透明画布"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  显示图形"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**show函数**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 关闭与清除"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**绘图清除与关闭**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QDOECACRDuAAAyRAuAEAyhAsAkAzhAgAkQ7gAAMkQLgBAMoQLAJAM4QIAJEO4AADJEC4AQDKECwCQDOECACRDuAAAyRAuAEAyhAsAkAzhAgAkQ7gAAMkQLgBAMoQLAJAM4QIAJEO4AADJEC4AQDKECwCQDOECACRDuAAAyRAuAEAyhAsAkAzhAgAkQ7gAAMkQLgBAMoQLAJAM4QIAJEO4AADJEC4AQDKECwCQDOECACRDuAAAyRAuAEAyhAsAkAzhAgAkQ7gAAMkQLgBAMoQLAJAM4QIAJEO4AADJEC4AQDKECwCQjCGFS1NTU1RVVUVJSUlUV1fH9u3bjzp3w4YNcdFFF8XkyZNj8uTJUVtb+6bzAQCOJu9w2bRpU9TX10dDQ0Ps3LkzZs6cGXV1dfHSSy8NOn/btm1x+eWXx+9///toaWmJysrK+NSnPhV/+9vf3vbmAYCJpSDLsiyfBdXV1XH++efHunXrIiKir68vKisr4/rrr4/ly5e/5fre3t6YPHlyrFu3LhYtWjTonO7u7uju7u7/c2dnZ1RWVkZHR0eUlpbms10AYIx0dnZGWVnZsP78zusZl56entixY0fU1tb+9w4KC6O2tjZaWlqO6T5effXVeP311+Md73jHUec0NjZGWVlZ/62ysjKfbQIA41Re4XLgwIHo7e2N8vLyAePl5eXR1tZ2TPdx4403xvTp0wfEz/9asWJFdHR09N/279+fzzYBgHFq0mhebM2aNbFx48bYtm1blJSUHHVeLpeLXC43ijsDAFKQV7hMmTIlioqKor29fcB4e3t7VFRUvOnaO+64I9asWRO//e1v49xzz81/pwDAhJfXS0XFxcUxe/bsaG5u7h/r6+uL5ubmqKmpOeq622+/PW677bbYunVrzJkzZ+i7BQAmtLxfKqqvr4/FixfHnDlzYu7cubF27dro6uqKJUuWRETEokWLYsaMGdHY2BgREd/97ndj1apV8bOf/Syqqqr63wtz8sknx8knnzyMDwUAGO/yDpcFCxbEyy+/HKtWrYq2traYNWtWbN26tf8Nu/v27YvCwv8+kfPDH/4wenp64rOf/eyA+2loaIhvfvObb2/3AMCEkvf3uIyFkfgcOAAwssb8e1wAAMaScAEAkiFcAIBkCBcAIBnCBQBIhnABAJIhXACAZAgXACAZwgUASIZwAQCSIVwAgGQIFwAgGcIFAEiGcAEAkiFcAIBkCBcAIBnCBQBIhnABAJIhXACAZAgXACAZwgUASIZwAQCSIVwAgGQIFwAgGcIFAEiGcAEAkiFcAIBkCBcAIBnCBQBIhnABAJIhXACAZAgXACAZwgUASIZwAQCSIVwAgGQIFwAgGcIFAEiGcAEAkiFcAIBkCBcAIBnCBQBIhnABAJIhXACAZAgXACAZwgUASIZwAQCSIVwAgGQIFwAgGcIFAEiGcAEAkiFcAIBkCBcAIBnCBQBIhnABAJIhXACAZAgXACAZwgUASIZwAQCSIVwAgGQIFwAgGcIFAEiGcAEAkiFcAIBkDClcmpqaoqqqKkpKSqK6ujq2b9/+pvMfeOCBOOuss6KkpCTOOeec2LJly5A2CwBMbHmHy6ZNm6K+vj4aGhpi586dMXPmzKirq4uXXnpp0PmPP/54XH755XHllVfGrl27Yv78+TF//vx46qmn3vbmAYCJpSDLsiyfBdXV1XH++efHunXrIiKir68vKisr4/rrr4/ly5cfMX/BggXR1dUVv/71r/vHPvrRj8asWbNi/fr1g16ju7s7uru7+//c0dERp512Wuzfvz9KS0vz2S4AMEY6OzujsrIyDh48GGVlZcNyn5PymdzT0xM7duyIFStW9I8VFhZGbW1ttLS0DLqmpaUl6uvrB4zV1dXFL3/5y6Nep7GxMW699dYjxisrK/PZLgBwHPjHP/4xNuFy4MCB6O3tjfLy8gHj5eXlsWfPnkHXtLW1DTq/ra3tqNdZsWLFgNg5ePBgvOc974l9+/YN2wNnaN6oZ89+jT1ncfxwFscX53H8eOMVk3e84x3Ddp95hctoyeVykcvljhgvKyvzD+FxorS01FkcJ5zF8cNZHF+cx/GjsHD4PsSc1z1NmTIlioqKor29fcB4e3t7VFRUDLqmoqIir/kAAEeTV7gUFxfH7Nmzo7m5uX+sr68vmpubo6amZtA1NTU1A+ZHRDz66KNHnQ8AcDR5v1RUX18fixcvjjlz5sTcuXNj7dq10dXVFUuWLImIiEWLFsWMGTOisbExIiJuuOGGuPjii+POO++Myy67LDZu3BhPPPFE3HPPPcd8zVwuFw0NDYO+fMTochbHD2dx/HAWxxfncfwYibPI++PQERHr1q2L733ve9HW1hazZs2K73//+1FdXR0RER//+Mejqqoq7r///v75DzzwQNx8883x4osvxvvf//64/fbb49JLLx22BwEATAxDChcAgLHgdxUBAMkQLgBAMoQLAJAM4QIAJOO4CZempqaoqqqKkpKSqK6uju3bt7/p/AceeCDOOuusKCkpiXPOOSe2bNkySjsd//I5iw0bNsRFF10UkydPjsmTJ0dtbe1bnh3HLt+/F2/YuHFjFBQUxPz580d2gxNIvmdx8ODBWLp0aUybNi1yuVyceeaZ/j01TPI9i7Vr18YHPvCBOPHEE6OysjKWLVsWr7322ijtdvz6wx/+EPPmzYvp06dHQUHBm/4Owjds27YtPvKRj0Qul4v3ve99Az6BfMyy48DGjRuz4uLi7L777sv+/Oc/Z1dffXV26qmnZu3t7YPO/+Mf/5gVFRVlt99+e/b0009nN998c3bCCSdkTz755CjvfPzJ9yyuuOKKrKmpKdu1a1e2e/fu7Itf/GJWVlaW/fWvfx3lnY8/+Z7FG1544YVsxowZ2UUXXZR95jOfGZ3NjnP5nkV3d3c2Z86c7NJLL80ee+yx7IUXXsi2bduWtba2jvLOx598z+KnP/1plsvlsp/+9KfZCy+8kD3yyCPZtGnTsmXLlo3yzsefLVu2ZCtXrsweeuihLCKyhx9++E3n7927NzvppJOy+vr67Omnn85+8IMfZEVFRdnWrVvzuu5xES5z587Nli5d2v/n3t7ebPr06VljY+Og8z/3uc9ll1122YCx6urq7Etf+tKI7nMiyPcs/tfhw4ezU045JfvJT34yUlucMIZyFocPH84uuOCC7Ec/+lG2ePFi4TJM8j2LH/7wh9npp5+e9fT0jNYWJ4x8z2Lp0qXZJz7xiQFj9fX12YUXXjii+5xojiVcvvGNb2Qf/vCHB4wtWLAgq6ury+taY/5SUU9PT+zYsSNqa2v7xwoLC6O2tjZaWloGXdPS0jJgfkREXV3dUedzbIZyFv/r1Vdfjddff31YfxPoRDTUs/jWt74VU6dOjSuvvHI0tjkhDOUsfvWrX0VNTU0sXbo0ysvL4+yzz47Vq1dHb2/vaG17XBrKWVxwwQWxY8eO/peT9u7dG1u2bPElqGNguH52j/lvhz5w4ED09vZGeXn5gPHy8vLYs2fPoGva2toGnd/W1jZi+5wIhnIW/+vGG2+M6dOnH/EPJ/kZylk89thjce+990Zra+so7HDiGMpZ7N27N373u9/FF77whdiyZUs899xz8eUvfzlef/31aGhoGI1tj0tDOYsrrrgiDhw4EB/72Mciy7I4fPhwXHvttXHTTTeNxpb5f472s7uzszP+/e9/x4knnnhM9zPmz7gwfqxZsyY2btwYDz/8cJSUlIz1diaUQ4cOxcKFC2PDhg0xZcqUsd7OhNfX1xdTp06Ne+65J2bPnh0LFiyIlStXxvr168d6axPOtm3bYvXq1XH33XfHzp0746GHHorNmzfHbbfdNtZbY4jG/BmXKVOmRFFRUbS3tw8Yb29vj4qKikHXVFRU5DWfYzOUs3jDHXfcEWvWrInf/va3ce65547kNieEfM/i+eefjxdffDHmzZvXP9bX1xcREZMmTYpnnnkmzjjjjJHd9Dg1lL8X06ZNixNOOCGKior6xz74wQ9GW1tb9PT0RHFx8YjuebwaylnccsstsXDhwrjqqqsiIuKcc86Jrq6uuOaaa2LlypVRWOi/30fL0X52l5aWHvOzLRHHwTMuxcXFMXv27Ghubu4f6+vri+bm5qipqRl0TU1NzYD5ERGPPvroUedzbIZyFhERt99+e9x2222xdevWmDNnzmhsddzL9yzOOuusePLJJ6O1tbX/9ulPfzouueSSaG1tjcrKytHc/rgylL8XF154YTz33HP98RgR8eyzz8a0adNEy9swlLN49dVXj4iTN4Iy86v6RtWw/ezO733DI2Pjxo1ZLpfL7r///uzpp5/OrrnmmuzUU0/N2trasizLsoULF2bLly/vn//HP/4xmzRpUnbHHXdku3fvzhoaGnwcepjkexZr1qzJiouLswcffDD7+9//3n87dOjQWD2EcSPfs/hfPlU0fPI9i3379mWnnHJK9pWvfCV75plnsl//+tfZ1KlTs29/+9tj9RDGjXzPoqGhITvllFOyn//859nevXuz3/zmN9kZZ5yRfe5znxurhzBuHDp0KNu1a1e2a9euLCKyu+66K9u1a1f2l7/8JcuyLFu+fHm2cOHC/vlvfBz661//erZ79+6sqakp3Y9DZ1mW/eAHP8hOO+20rLi4OJs7d272pz/9qf9/u/jii7PFixcPmP+LX/wiO/PMM7Pi4uLswx/+cLZ58+ZR3vH4lc9ZvOc978ki4ohbQ0PD6G98HMr378X/J1yGV75n8fjjj2fV1dVZLpfLTj/99Ow73/lOdvjw4VHe9fiUz1m8/vrr2Te/+c3sjDPOyEpKSrLKysrsy1/+cvbPf/5z9Dc+zvz+978f9N//b/z/v3jx4uziiy8+Ys2sWbOy4uLi7PTTT89+/OMf533dgizzXBkAkIYxf48LAMCxEi4AQDKECwCQDOECACRDuAAAyRAuAEAyhAsAkAzhAgAkQ7gAAMkQLgBAMoQLAJCM/wM9kKRvAVrZIAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.cla()  # 清除坐标轴"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.clf()  # 清除画布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close()  # 关闭窗口"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}