diff --git a/第四回:文字图例尽眉目.ipynb b/第四回:文字图例尽眉目.ipynb index 561e844..eea0fb1 100644 --- a/第四回:文字图例尽眉目.ipynb +++ b/第四回:文字图例尽眉目.ipynb @@ -81,6 +81,18 @@ "\n" ] }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib.font_manager import FontProperties\n", + "import numpy as np" + ] + }, { "cell_type": "code", "execution_count": 1, @@ -88,7 +100,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -102,10 +114,9 @@ "source": [ "#fontdict学习的案例\n", "#学习的过程中请尝试更换不同的fontdict字典的内容,以便于更好的掌握\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", "#---------设置字体样式,分别是字体,颜色,宽度,大小\n", - "font1 = {'family': 'Times New Roman',\n", + "font1 = {'family': 'SimSun',#华文楷体\n", + " 'alpha':0.7,#透明度\n", " 'color': 'purple',\n", " 'weight': 'normal',\n", " 'size': 16,\n", @@ -132,7 +143,7 @@ "y = np.cos(2*np.pi*x) * np.exp(-x/3)\n", "#-------绘制图像,添加标注----------\n", "plt.plot(x, y, '--')\n", - "plt.title('Damped exponential decay', fontdict=font1)\n", + "plt.title('震荡曲线', fontdict=font1)\n", "#------添加文本在指定的坐标处------------\n", "plt.text(2, 0.65, r'$\\cos(2 \\pi x) \\exp(-x/3)$', fontdict=font2)\n", "#---------设置坐标标签\n", @@ -169,47 +180,6 @@ "**返回值**:此方法返回作为创建的title实例的文本。" ] }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#该例子展现了如何在title中使用fontdict参数。\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "#---------设置字体样式,分别是字体,透明度,颜色,宽度,大小\n", - "font1 = {'family': 'SimSun',#华文楷体\n", - " 'alpha':0.7,#透明度\n", - " 'color': 'purple',\n", - " 'weight': 'normal',\n", - " 'size': 16,\n", - " }\n", - "x = np.linspace(0.0, 5.0, 100)\n", - "y = np.cos(2*np.pi*x) * np.exp(-x/3)\n", - "#-------绘制图像,添加标注----------\n", - "plt.plot(x, y, '--')\n", - "plt.title('震荡曲线', fontdict=font1,pad=13,loc='right')\n", - "# 调整图像边距\n", - "plt.subplots_adjust(left=0.15)\n", - "plt.show()" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -257,7 +227,8 @@ "xlabel或者ylabel:label的文本 \n", "labelpad:设置label距离轴(axis)的距离 \n", "loc:{'left', 'center', 'right'},默认为center \n", - "\\*\\*kwargs:[文本](https://matplotlib.org/api/text_api.html#matplotlib.text.Text)属性 " + "\\*\\*kwargs:[文本](https://matplotlib.org/api/text_api.html#matplotlib.text.Text)属性 \n", + "**返回值**:此方法返回作为创建的xlabel和ylabel实例的文本。" ] }, { @@ -280,11 +251,8 @@ ], "source": [ "#文本属性的输入一种是通过**kwargs属性这种方式,一种是通过操作 matplotlib.font_manager.FontProperties 方法\n", + "#该案例中对于x_label采用**kwargs调整字体属性,y_label则采用 matplotlib.font_manager.FontProperties 方法调整字体属性\n", "#该链接是FontProperties方法的介绍 https://matplotlib.org/api/font_manager_api.html#matplotlib.font_manager.FontProperties\n", - "from matplotlib.font_manager import FontProperties\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "\n", "x1 = np.linspace(0.0, 5.0, 100)\n", "y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)\n", "\n", @@ -1551,7 +1519,7 @@ "# 直接用字体的名字。\n", "plt.xlabel('x 轴名称参数', fontproperties='Microsoft YaHei', fontsize=16) # 设置x轴名称,采用微软雅黑字体\n", "plt.ylabel('y 轴名称参数', fontproperties='Microsoft YaHei', fontsize=14) # 设置Y轴名称\n", - "plt.title('坐标系的标题', fontproperties='Microsoft YaHei', fontsize=20)\t\t # 设置坐标系标题的字体\n", + "plt.title('坐标系的标题', fontproperties='Microsoft YaHei', fontsize=20) # 设置坐标系标题的字体\n", "plt.legend(loc='lower right', prop={\"family\": 'Microsoft YaHei'}, fontsize=10) # 小示例图的字体设置" ] }, @@ -1600,71 +1568,12 @@ "plt.legend(loc='lower right', prop=my_font1, fontsize=10) # 小示例图的字体设置\n" ] }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#这是以上学习内容的总结案例\n", - "import matplotlib\n", - "import matplotlib.pyplot as plt\n", - "\n", - "fig = plt.figure()\n", - "ax = fig.add_subplot(111)\n", - "fig.subplots_adjust(top=0.85)\n", - "\n", - "# Set titles for the figure and the subplot respectively\n", - "fig.suptitle('bold figure suptitle', fontsize=14, fontweight='bold')\n", - "ax.set_title('axes title')\n", - "\n", - "ax.set_xlabel('xlabel')\n", - "ax.set_ylabel('ylabel')\n", - "\n", - "# Set both x- and y-axis limits to [0, 10] instead of default [0, 1]\n", - "ax.axis([0, 10, 0, 10])\n", - "\n", - "ax.text(3, 8, 'boxed italics text in data coords', style='italic',\n", - " bbox={'facecolor': 'red', 'alpha': 0.5, 'pad': 10})\n", - "\n", - "ax.text(2, 6, r'an equation: $E=mc^2$', fontsize=15)\n", - "font1 = {'family': 'Times New Roman',\n", - " 'color': 'purple',\n", - " 'weight': 'normal',\n", - " 'size': 10,\n", - " }\n", - "ax.text(3, 2, 'unicode: Institut für Festkörperphysik',fontdict=font1)\n", - "ax.text(0.95, 0.01, 'colored text in axes coords',\n", - " verticalalignment='bottom', horizontalalignment='right',\n", - " transform=ax.transAxes,\n", - " color='green', fontsize=15)\n", - "\n", - "ax.plot([2], [1], 'o')\n", - "ax.annotate('annotate', xy=(2, 1), xytext=(3, 4),\n", - " arrowprops=dict(facecolor='black', shrink=0.05))\n", - "\n", - "plt.show()" - ] - }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 8.数学表达式\n", - "在文本标签中使用数学表达式。有关MathText的概述,请参见 [写数学表达式](https://matplotlib.org/tutorials/text/mathtext.html#sphx-glr-tutorials-text-mathtext-py),但由于数学表达式的联系想必我们都在markdown语法和latex语法中多少有接触,故在此不继续展开,愿意深入学习的可以参看官方文档.下面是一个官方案例,供参考了解。" + "在文本标签中使用数学表达式。有关MathText的概述,请参见 [写数学表达式](https://matplotlib.org/tutorials/text/mathtext.html#sphx-glr-tutorials-text-mathtext-py),但由于数学表达式的练习想必我们都在markdown语法和latex语法中多少有接触,故在此不继续展开,愿意深入学习的可以参看官方文档.下面是一个官方案例,供参考了解。" ] }, { @@ -1701,6 +1610,65 @@ "plt.show()" ] }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#这是对前七节学习内容的总结案例\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "\n", + "fig = plt.figure()\n", + "ax = fig.add_subplot(111)\n", + "fig.subplots_adjust(top=0.85)\n", + "\n", + "# 分别在figure和subplot上设置title\n", + "fig.suptitle('bold figure suptitle', fontsize=14, fontweight='bold')\n", + "ax.set_title('axes title')\n", + "\n", + "ax.set_xlabel('xlabel')\n", + "ax.set_ylabel('ylabel')\n", + "\n", + "# 设置x-axis和y-axis的范围都是[0, 10]\n", + "ax.axis([0, 10, 0, 10])\n", + "\n", + "ax.text(3, 8, 'boxed italics text in data coords', style='italic',\n", + " bbox={'facecolor': 'red', 'alpha': 0.5, 'pad': 10})\n", + "\n", + "ax.text(2, 6, r'an equation: $E=mc^2$', fontsize=15)\n", + "font1 = {'family': 'Times New Roman',\n", + " 'color': 'purple',\n", + " 'weight': 'normal',\n", + " 'size': 10,\n", + " }\n", + "ax.text(3, 2, 'unicode: Institut für Festkörperphysik',fontdict=font1)\n", + "ax.text(0.95, 0.01, 'colored text in axes coords',\n", + " verticalalignment='bottom', horizontalalignment='right',\n", + " transform=ax.transAxes,\n", + " color='green', fontsize=15)\n", + "\n", + "ax.plot([2], [1], 'o')\n", + "ax.annotate('annotate', xy=(2, 1), xytext=(3, 4),\n", + " arrowprops=dict(facecolor='black', shrink=0.05))\n", + "\n", + "plt.show()" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -1712,7 +1680,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "设置tick(刻度)和ticklabel(刻度标签)也是可视化中经常需要操作的步骤,matplotlib既提供了自动生成刻度和刻度标签的模式(默认状态),同时也提供了许多让使用者灵活操控手动设置的方式。" + "设置tick(刻度)和ticklabel(刻度标签)也是可视化中经常需要操作的步骤,matplotlib既提供了自动生成刻度和刻度标签的模式(默认状态),同时也提供了许多让使用者灵活设置的方式。" ] }, { @@ -1725,7 +1693,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -1738,12 +1706,12 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1755,7 +1723,7 @@ } ], "source": [ - "# 使用axis的set_ticks方法手动设置标签位置的例子\n", + "# 使用axis的set_ticks方法手动设置标签位置的例子,该案例中由于tick设置过大,所以会影响绘图美观,不建议用此方式进行设置tick\n", "fig, axs = plt.subplots(2, 1, figsize=(5, 3), tight_layout=True)\n", "axs[0].plot(x1, y1)\n", "axs[1].plot(x1, y1)\n", @@ -1765,12 +1733,12 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "image/png": 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0IYHMuLCQfXqKEP0GsNa6VClVq5S6E2jSWpcGoa4BuzAvhf/5Vwk1LU5SYwLzkfJoYwdrDtTwpaUTCbcZ95v7O1flU9HYwfde24fWmjsW5Qz5WF6v5tdrD/Ord0qZkhLFk3cUnnUReSPZLCaWTk5iae9Kc1prnC4vLV0uWrpcmBREOaxEOSyED7AvU4hQMaDORK31o1rrZ0NlCtpHXZzve7jlOyW1ATvH05sqMCs1rMDzB7NJ8bvb5nBRXgrfe20/v37n0JDWEK5v6+YLfyri/94u5fpZGbxy/3khGb5nopQizGYmNcbBlNQoJqVEkRrjIMJukfAVI07oTNobotzkSLLiw1hbXBeQ47c6XawuquSamekBa2EPhsNqZsVn53DjnAx++VYpD7+yl9YBPk1Da82q7ZVc/MgG3jvUwA+uncYjt8zsu41YCBFcI74nXCnFRXkprNx2jK4ej9/DZNX2Sjp6PHz+vPF+Pe5wWMwmfnHzTJKjHPz+3TLeOlDHw1fmccPsjDO2At0eL+sO1vPku+Vsq2hifk48P71xOrnJofdgUyHGkhEfwAAX5SfzzOYKNpc1cFG+/+bneryaZzZXMD8nPqRulwXfQNV/XpHHldNT+e5r+3lo1W5+9fYhFk6IZ8H4BMJsZupanVSd7OKNPdXUtDpJjrLz3zdO59OFWSE5pUeIsWZUBPD88fFE2My8XVzn1wB+60ANVSe7hvW0i0CbkRnLK19azMu7jrNmfw1r9teyqqiq7+cWk+K83ER+cN00LsxLxhpCt4oKMdaNigC2W8wsy0tmzf4afnDtNGwW/4TMUxsryIwL45KpqX45XqCcupPn5rmZeL2a0ro2vF5IjrYTH26T1q4QIWrUNIdumpNBU0cP6w/6ZzBub1UL2yqauGtxTkjeUXQ2JpMiL9W3+EtipF3CV4gQNmoC+IJJSSRG2nlpZ1X/Gw/A4xsOE2W3cMu8LL8cTwghTjdqAthiNnH9rHTWltRx8ix3Sg3U4TrfKlZ3Ls6Rx+gIIQJm1AQwwE1zM3F5NH/bfWJYx/ndujIcFjOfPz90pp4JIUafURXA+WnRTEuP5q87ht4NcbSxg9d2n+C2BeOIj7D5sTohhPi4URXAADfNyWTv8RZKa9uGtP+KDWWYTYovXDDBz5UJIcTHjboAvm5WOhaTYtX2yv43Ps3x5i7+uqOKTxdmBfU5c0KIsWnUBXBCpJ2rZqTx3Naj1LY6B7XvT/5+AJNSfHGptH6FEIE36gIY4BuXTMHj1Tzy5sBXzlxXUsc/9tbwlQtzyYwbGSuDCSFGtlEZwOMSwrljUQ6rd1RysKb/vuCuHg/ffW0fucmR3HvBxCBUKIQQozSAAb68PJcIu4Wf/bO4320fW3uIqpNd/OT6Ar/dxiyEEP0ZtWkTF2Hjy8tzWXewnndL68+63XuHfMs03jw3kwUTEoJYoRBirBu1AQxw5+IcchLC+dJzO1hX8sk1Iv61r5q7nykiNzmS71wZuiueCSFGp1EdwA6rmRe/uIicxAjufnY7f37/KF09vseB//n9o9z//E4KMqJ58d5FxMlNF0KIIFNDeabY2RQWFuqioiK/Hc9fOrrdfGXlLtae1gpeMimR398+19AHbQohRi6l1A6tdeFQ9x8TyRNht/DE7XNZue0Ybd1uEiPsJEfbWTwxUQbdhBCGGRMBDL7V0m43+KnGQgjxUdL8E0IIg/i1D1gpVQ8cHeLuiUCD34oJTWPhPcLYeJ9j4T3C2Hifw3mP2VrrpKGe2K8BPBxKqaLhdGaPBGPhPcLYeJ9j4T3C2HifRr5H6YIQQgiDSAALIYRBQimAnzC6gCAYC+8Rxsb7HAvvEcbG+zTsPYZMH7AQQow1odQCFkKIMUUCWAghDCIBLIQQBgmJAFZKPaiUulMp9VWjawkUpdRipdRfja4jkJRSDqXU55VS1yilfqyUCom/X/6klLIppe5WSt2olPqa0fUEmlJqvFLqt0bXEShKqU1Kqed6/wT9YZCG/wNRSk0C0rTWzwJxSqk8o2sKBK31ZqDd6DoC7HLAo7V+HagGZhlbTkDkA/Fa65eBLKVUvNEFBdgCIMLoIgLoca31Z3v/lAf75KGwGM9yYFvv693AUqDEuHLEMKwHTj1WJA2oMKySANFa71ZK7e390gr0/9DBEUopdRnwT3y/WEerhUqpOGAy8KDW2hvMkxveAsZ3H3Zr7+t2YLS3KEYtrXWz1rpMKZULHNZaNxldU6Aopb4FlGitXUbXEghKqVSgQ2vdYnQtAfZbrfWvgZ3ABcE+eSgEcCMQ1fs6qvdrMUL1/sOdrbV+xuhaAkVr7dVa/xzwKKWuMLqeAJkJWJRSy4BUpVSBseX4n1LKAZzs/bIKSA12DaEQwOuAeb2vZ+L7GCtGoN6/0FdqrVcrpaxKqZlG1+RvSqmFSqnP9n5ZA0w0sp5A0Vqv0Vqv11qvB2q01vuMrikALgdu6X2dBZQGuwDDA1hrXQrUKqXuBJp6vx51lFIXAEuUUtcppZTR9QTIPcBlSqnngLWAx+B6AuEIkK6UuhaYAzxjbDmBo3xuBqb1DpaPNm8CXb3/L6O11juDXYDciiyEEAYxvAUshBBjlQSwEEIYRAJYCCEMIgEshBAGkQAWQgiDSAALIYRBJICFEMIgEsBCCGEQCWAhhDCIBLAQQhhEAlgIIQzi1wXZExMTdU5Ojj8PKYQQIWvHjh0NWuukoe7fbwArpRYDD2mtb+5v25ycHIqKioZaixBCjChKqaPD2b/fLgh/Psuszeniqyt38bfdJ/xxOCGEGNGG3QeslLpXKVWklCqqr68/57YRNgslNa38du1hvF5ZBlMIMbYNO4C11k9orQu11oVJSefuCjGZFF9aNpGDtW2sLakb7qmFEGJEC/osiGtmpJMZF8bv1h9GFoMXQoxlQQ9gi9nEvRdMYOexZrYeGbUPzRVCiH71G8CBeJbZLYVZRNjMvLFHBuOEEGNXv9PQtNbv4ucnvzqsZhZMSGDzYXkCvRBi7DLsTrjFExMob+iguqXLqBKEEMJQBgZwIoC0goUQY5ZhAZyXGkV8hI1NZQ1GlSCEEIYyLIBNJsWi3n5gmY4mhBiLDF0NbXFuAjWtTo40dBhZhhBCGMLYAO7tB95SLv3AQoixx9AAzkkIJybMyt6qFiPLEEIIQxgawEoppmfEsPe4BLAQYuwx/IkYBRkxlNa20e32GF2KEEIEleEBPD0jBpdHc7CmzehShBAiqEIigAH2HW81uBIhhAguwwM4Kz7MNxAn/cBCiDHG8ABWSlGQEc0+CWAhxBhjeACDbyDuYE0bPW6v0aUIIUTQhEQAT8+IocfjpbRWBuKEEGNHSARwQfqpgTjphhBCjB0hEcDj4sMJt5kpkaloQogxJCQC2GRSTE6JkrnAQogxJSQCGCA/LYqSmlZZmlIIMWaETABPSYniZKeL+rZuo0sRQoig6PehnMGSlxYNQHFNG8nRjqCcU2vNqqJKfvFmKVF2C/lp0fz75VPITogIyvmFEGNbyLSA81KjACipDs4tyT1uL/c9t4P/eGkv2fHhTE6J4r1D9dz0+BYOnJDbooUQgRcyARwbbiM12hG0gbgn3i1jzf5a/uPyPFZ9cRErbp/Ly/cvxmpWfPqJLZTVtwelDiHE2BUyAQyQlxZFcRACuLy+ncfWHubK6al8adlETCYFQG5yFKvvW4RJKb61ejcerwwICiECJ6QCeEpqFIfr2nB5AndLstaah1/Zi91i4r+umfaJn2fGhfP9a6ay81gzz2yuCFgdQggRUgGcnxqNy6MD+pDObUeaeL+8iW9eOuWsg303zM7gwrxkfr6mhOPNXQGrRQgxtoVUAE/pHYgrDuBA3J/eP0q0w8IthVln3UYpxY+uL8DrhcfePhSwWoQQY1tIBfDEpEgsJhWwW5JrWpys2VfDp+dlEWYzn3PbjNgwbls4jr/urJIBOSFEQIRUANssJnKTIwM2E+Iv247h0ZrbF+YMaPv7l+Vit5j4v7dKA1KPEGJsC6kABt984EDMBXZ7vKzcdowLpyQzLiF8QPskRdn5/HnjeWNPtWHrVMgayUKMXiFzJ9wpeWnRvPrBCVo6XcSEW/123K1Hmqhv6+bmuZmD2u/u88fz1KYj/G79YR69dbbf6jkbrTVr9tfywvZj7DveSkN7N/ERNnKTIrl+dgbXzEwjyuG/6yKEME7ItYBPDcSV1Pi3Ffz3vdWE28wsm5I8qP3iImzcvjCb13efoCKAszMADta0ce1vNnHfczs4XNfOsilJfO3iSVxekEpzVw8Pv7KX8362lmc3V+AO4FQ9IURwhFwLOD/VtyZESU0bCyYk+OWYbo+Xf+2r4cK85H4H387k7iXjeXpzBSs2lPGzm2b4pabTrdlfw9df/IAIu4VffGom189Kx2L+8Pej1ppdlc388s2DfP9v+1m9o5JHb53NxKTIgNQjhAi8kGsBp0TbiQ23+rUFvPVIE00dPVw1PW1I+ydHObh1XhYv7awKyLzg1UWVfPHPO5iUHMkbXzmfm+dmfix8wTc1bs64OJ67ewG//cwcjp/s4urHNrJqe2XQlvB0ujzsP9HC2wdqee2D47z2wXHWHayjuLoVp8sTlBqEGE0G1AJWSj0INAMxWuvHAlmQUso3EOfHQa839gyt++Gjvrh0Iiu3HWPF+jJ+dH2B32r7x95q/uOlPSyZlMiTdxTisJ67ha6U4qoZaRTmxPHQqg/495f2sK2iiR9dVzCk1n1/9p9o4R97q3m3tIH9J1o4293ZJgW5yZHMzY5j4YQEzstNJDHS7vd6zkVrjdbg1RqzSaGUCur5hRisfgNYKTUJSNNaP6qU+r5SKk9rXRLIovJSo1lVVInXq/vWaRgqj1fz5v4alg+x++GUjNgwbp6bxYvbK3lgeS6pMcNfMnNreSMPvrCL2ePi+P3tc/sN349KiXbwp88v4LF3DvHY2kPsrWrhN5+ZzaSUqGHX1dXj4eVdVTz3/jGKq1sxmxRzxsXy5eW5TEmNJis+jAi7Ba01LV1ujjd3cbiunT1Vzbyxp5qV2yoBmJYezbIpSZyfm8Sc7FjsluH9gmh1ujhU287hujYqGjs51tRJTYuT+rZuWrpctHe7P7Z+h91iIsphIdphJT7CRmKknZRoO8nRDlKiHb7XUQ6SouzEhFkxD/LvWo/bS5vTRavTTWuXi1ani3anm44eD509bpwuD90uLy6vxuP9sM/+htmZ5CZL15EYWAt4ObCt9/VuYCkQ4ACOorPHw7GmTnISh7c27+6qZho7erh0asqw67p/2URWF1WyYkMZ/3XtJ9eRGIyqk5186fmdZMWF89Sd8wi3Db473mxSfP2SyczJjuOhFz/gmt9s5DtXTeW2+eOG9IurqaOHZzZX8OctFZzsdDEtPZofXTeNq2ekExdhO+t+c7Pj+l57vJp9x1vYeLiBDQfrWbGhnN+uK8NhNTEzM5Y52XHkp0WTmxRJWoyDmDBrX61aazp7PNS2OqlucXKkoYMjDR2U1rZxqLadmlZn33ksJkVmXBhpMWHMyoolLtxKhN2C3WJGKXB7Nd0uD23dblo6XTR2dHO4vp3NZQ20Ot2feA9KQUyYlSiHhQibBbvVjNWkUAq82jeO0O320uXy0NHtob3bhdM18IFQs0lx6v/I3Ow4CWABDCyAE4Hy3tftQP5Hf6iUuhe4F2DcuHF+KWpqum8g7kB167ADeG1xHWaTYunkpGHXlRUfzo1zMvjLtmPcs2Q8mXEDm098us4eN1/40w5cHi9P3lk47Ol2Sycn8c8Hl/DQqt1899V9vLbrOD+8rqDvOvanrL6dpzYe4aWdVThdXi6ZmsIXlkxgXk7coD/Gm02KmVmxzMyK5YHlubQ6XWwtb2LT4QZ2HjvJk++W4/5IK9WkfDfgmJWiy+X5RBeHw+q7OWfRxAQmp0QxKTmS3ORIMuPCPtFPPlBdvSFf2+qkvr2b+rZuTna6aO7soc3ppr3bTY/b27colFJgdViwmk2E28yE2yxEOyxE2i1EOSzEhFuJsluJDrMSafd9P8xmJsxmxm4xYZHuEHEWAwngRuDU59qo3q/7aK2fAJ4AKCws9Mto0OSUKCwmxd7jLVw5xIGzU94pqWNudhyx4WdvwQ3G1y6ezGsfnODnaw4OaV6w1ppvv7yXkppWnr5rnt9mMSRHO/jz3fP5644qfvKPYq587D0uzk/mMwvGsWhC4ie6X443d/FuaT2v7DzOtoombBYT189K594LJpCbPPxujFOiHVYumZrCJb2fQJwuDxWNHZTVdVDX5qSxvYcejxePVxNuMxNht5AcZSc12kF2YgRp0Y5hd0OdLsxmJicxYti/3IUYroEE8DrgLuAVYCbwl0AWBOCwmpmcEsW+4y3DOs6J5i6Kq1v59hV5fqoM0mPD+MKSCfxm3WE+d954ZmXFDmr/pzdV8NoHJ/jWZVOGNSh4JkopPlWYxaVTU3l2SwVPbTrC28V12C0mchIiSIi0fewjPsCExAi+ddkUPj0vKyiDZg6rmbzUaPJSB9Y6F2I06zeAtdalSqlapdSdQJPWOigLI0zPiGHNgRq01kP++LbuYB0AF+X7N+juWzaRF7ZX8sPX97P6vsUDHrx5t7Sen/yjmMumpXD/sol+remjYsKtfPWiSXxx6QS2HWliw8F6jjV10tDeTaTdwvgJCczIjGHhhATyUqPk47EQBhnQyI/W+tFAF3K6gswYXiyqpOpkF1nxQ+trXVtcx7j4cL/frBBpt/Cdq/L4+ou7WbGhjAeW5/a7T2ltGw88v5NJyZH88pZZQQk9u8XMkklJLJk0/P5vIYT/hdyNGKdMz4gBGHI3hNPlYVNZAxfmJQck7K6flcG1M9N55K1Sdh07ec5tjzV28rmnt+OwmXnqrnlE2kPuBkQhhAFCNoDzUj8ciBuKLWWNOF1eluf5t/vhFKUUP76hgNRoB/c9t+Osq6UdrmvjU7/fTEePm6fvmkd6bFhA6hFCjDwhG8AOq5lJKVHsG+Ij4teW1BFmNbNgfLyfK/tQtMPKU3fNQ2v41IrNvFNci7d3HpXb4+XpTUe44beb8XjhxXsXUdDbqhdCCAjBxXg+anpGNG8X1w16IE5rzdqSOs7LTRzU3WVDMSU1ipfvX8wdT23j7meLyIwLIzMujMN1HTS0d7NkUiI/vWH6kPuxhRCjV4gHcAyrinwL4AzmpodDde0cb+4a0OCYP2TGhfP3ryzhzQM1vLLrOK1dLpZOTuLSaSlcOjVFZhkIIc4opAN4Tu8trtsrmgYVwGtLfNPPlucFb/Q/zGbmulkZXDcrI2jnFEKMbCHbBwy+RXmiHRbeL2sa1H5ri+vIT4smLUYGvIQQoSukA9hsUswfn8DWI439b9yrvq2b7Ueb/LL4jhBCBFJIBzDAwgnxVDR2Ut0ysIXQ3zpQi9ZweUFqgCsTQojhGQEB7Hss0dbygXVD/Gt/DTkJ4eSl+m9BGSGECISQD+D8tGiiHJYBdUO0dLnYfLiBywpSZeaBECLkhXwAm02K+TnxvD+AFvA7xbW4vZorCoa3hKUQQgRDyAcw+LohjjR0UNnUec7t/r6nmrQYBzPkjjMhxAgwIgL41IDaq7uOn3Wb481drDtYxw2zM/y+gLcQQgTCiAjgrPhw5o+P55Vdx8/6CPaVW4+hgc8s8M9jkYQQItBGRAAD3DQng/KGDj6obP7Ez3rcXl7YXslFeclDfk6bEEIE24gJ4Cump2G3mHh55ye7Idbsr6GhvZvbFmYbUJkQQgzNiAngUw93fH3PCU529PR9v7PHzf+9VUp2QjhL5ckPQogRZMQEMMB9SyfS0e3m66s+6Ft390dvHOBIYwf/feN0GXwTQowoIb0a2ukKMmL43jXT+O6r+/j3l/YQZjWzclsl9y2dyOKJiUaXJ4QQgzKiAhjgswvGsaeymdU7qrCZTVycn8xDl0w2uiwhhBg0dbZpXUNRWFioi4qK/Ha8c2nq6CE2zCrdDkIIwyildmitC4e6/4hrAZ8SH2EzugQhhBiWETUIJ4QQo4lfuyCUUvXA0QFsmgg0+O3Eo59cr8GTazZ4cs0Gb4rWeshr3/q1C0JrPaCJuEqpouH0m4w1cr0GT67Z4Mk1Gzyl1LAGvaQLQgghDCIBLIQQBjEqgJ8w6LwjlVyvwZNrNnhyzQZvWNfMr4NwQgghBk66IIQQwiASwEIIYRAJYCGEMIjfb0VWSj0INAMxWuvHBrrNQPYbjZRSDuAzQD2wAPie1tp7hu3kmp1GKTUe+KbW+oGz/FyuWS+l1HLABtwKfENr/YnHjMv1+pBSKhW4FjgBZAOPB+LfpV9bwEqpSUCa1vpZIE4plTeQbQay3yh2OeDRWr8OVAOzTt9ArtlZLQAizvQDuWYfUkolAZO11muAL50lfOV6fdxtwAta6zfw3d076/QN/HHN/N0FsRzY1vt6N7B0gNsMZL/Raj2wsfd1GlBxhm3kmp1GKXUZ8M9zbCLX7EOXAzlKqa8Av1BKnemXllyvj9sM/FwpFQNMAErPsM2wr5m/AzgRaO193Q7ED3Cbgew3Kmmtm7XWZUqpXODwmVonyDX7mN6Phx1a65ZzbCbX7EPpwDGt9a+Bl4CbzrCNXK+PKwJqgVcAh9a6/QzbDPua+TuAG4FTC1NE9X49kG0Gst+o1Rsos7XWz5xlE7lmHzcTsCillgGpSqmCM2wj1+xDXcCpp9lW4fukdTq5Xh93H/AYcBGQp5SafYZthn3N/B3A64B5va9nAhuUUqc/qvj0bdaf5XtjQu8g3JVa69VKKatSaqZcs3PTWq/RWq/XWq8HaoCDcs3OaTswt/d1KlAu16tfMUCj9t2p9gowLhDXzK8BrLUuBWqVUncCTUAs8OtzbaO1Lj3T9/xZV4i7B7hMKfUcsBa5ZgOifG4GpgFzkGt2VlrrLQC91ysfOIZcr/48C9yllLoayMP3i97v10xuRRZCCIPIjRhCCGEQCWAhhDCIBLAQQhhEAlgIIQwiASyEEAaRABZCCIP8f5koze2a9SbxAAAAAElFTkSuQmCC\n", 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\n", 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" ] @@ -1787,11 +1755,54 @@ "axs[0].plot(x1, y1)\n", "axs[1].plot(x1, y1)\n", "ticks = np.arange(0., 8.1, 2.)\n", - "# list comprehension to get all tick labels...\n", "tickla = [f'{tick:1.2f}' for tick in ticks]\n", "axs[1].xaxis.set_ticks(ticks)\n", "axs[1].xaxis.set_ticklabels(tickla)\n", - "#axs[1].set_xlim(axs[0].get_xlim())\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#一般绘图时会自动创建刻度,而如果通过上面的例子使用set_ticks创建刻度可能会导致tick的范围与所绘制图形的范围不一致的问题。\n", + "#所以在下面的案例中,axs[1]中set_xtick的设置要与数据范围所对应,然后再通过set_xticklabels设置刻度所对应的标签\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "fig, axs = plt.subplots(2, 1, figsize=(6, 4), tight_layout=True)\n", + "x1 = np.linspace(0.0, 6.0, 100)\n", + "y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)\n", + "axs[0].plot(x1, y1)\n", + "axs[0].set_xticks([0,1,2,3,4,5,6])\n", + "\n", + "axs[1].plot(x1, y1)\n", + "axs[1].set_xticks([0,1,2,3,4,5,6])#要将x轴的刻度放在数据范围中的哪些位置\n", + "axs[1].set_xticklabels(['zero','one', 'two', 'three', 'four', 'five','six'],#设置刻度对应的标签\n", + " rotation=30, fontsize='small')#rotation选项设定x刻度标签倾斜30度。\n", + "axs[1].xaxis.set_ticks_position('bottom')#set_ticks_position()方法是用来设置刻度所在的位置,常用的参数有bottom、top、both、none\n", + "print(axs[1].xaxis.get_ticklines())\n", "plt.show()" ] }, @@ -1817,6 +1828,13 @@ "set_major_formatter和set_minor_formatter这两个formatter格式命令可以接收字符串格式(matplotlib.ticker.StrMethodFormatter)或函数参数(matplotlib.ticker.FuncFormatter)来设置刻度值的格式 。" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Tick Formatters" + ] + }, { "cell_type": "code", "execution_count": 17, @@ -1890,13 +1908,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "至于刻度的位置,matplotlib给出了常用的几种locator的类型。如果要绘制更复杂的图,可以先设置locator的类型,然后通过set_major_locator(locator)绘制即可\n", - "- locator=plt.MaxNLocator(nbins=7) \n", - "- locator=plt.FixedLocator(locs=[0,0.5,1.5,2.5,3.5,4.5,5.5,6])#直接指定刻度所在的位置 \n", - "- locator=plt.AutoLocator()#自动分配刻度值的位置 \n", - "- locator=plt.IndexLocator(offset=0.5, base=1)#面元间距是1,从0.5开始 \n", - "- locator=plt.MultipleLocator(1.5)#将刻度的标签设置为1.5的倍数 \n", - "- locator=plt.LinearLocator(numticks=5)#线性划分5等分,4个刻度 " + "### Tick Locators " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "在普通的绘图中,我们可以直接通过上图的set_ticks进行设置刻度的位置,缺点是需要自己指定或者接受matplotlib默认给定的刻度。当需要更改刻度的位置时,matplotlib给了常用的几种locator的类型。如果要绘制更复杂的图,可以先设置locator的类型,然后通过axs.xaxis.set_major_locator(locator)绘制即可 \n", + "locator=plt.MaxNLocator(nbins=7) \n", + "locator=plt.FixedLocator(locs=[0,0.5,1.5,2.5,3.5,4.5,5.5,6])#直接指定刻度所在的位置 \n", + "locator=plt.AutoLocator()#自动分配刻度值的位置 \n", + "locator=plt.IndexLocator(offset=0.5, base=1)#面元间距是1,从0.5开始 \n", + "locator=plt.MultipleLocator(1.5)#将刻度的标签设置为1.5的倍数 \n", + "locator=plt.LinearLocator(numticks=5)#线性划分5等分,4个刻度 " ] }, { @@ -1986,68 +2012,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "**一些相关案例**" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" - ] - }, - { - "data": { - "image/png": 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BS4HeyeecZURkFbAKYNSoUQGGMnDT81N5ZG05nW7voI0Ie2VnFWnxTuaPHZxremKddu65qJhvv7iTt/bVsGLiwKdUOpf61i5uefwDXA47T942nxHJoT3jH52RwPNfvYD7X9/PQ+8c5J2yWn74malcOiU0fXydbi9/2nqc36w/xN4TLSTFOrhxwWhumD86aEPgbTZh/Igkxo9I4sYFo/H5DLurmll/oI73Dtbz/OZj/Pb9I4D/TtEzrVra2MxExmQlUJAW36++LGMMJ9vdHG1op8J6lNe2cbC2lYO1rbR0ek6VTXQ5GJOZwLS8FK6YnsOo9HhGpsSRneRiRHIsqXHOfiULYwydbh8n27s52d5NQ1s3tS1d1LZ0UXPqZyd7TjSzdn/Xx2LoS6zTRpzTjt1mw24DuwgGTh2cPV5Dp8eL29u/+6X1JNkEl91Ktg5GJjuJjTktedhtOE5LGiL+mqLBf4D3+rCSgI9uj48ur48ut48ujz/JNbR10+n20un2WT+9dHr8ZUPNbhMcNrH2QXDYbThtgt0uOGz+fbJb+3T6/p3+n/X0828ZqEATVCZQbi23ApMCKWOMWQ2sBigpKQnbXfZm5Kfisb74s0elhXx7nW4vb+yp4fJpOUGZ2qi/rispYPXacv7rr2UsG5/d7zPOQHS6vax6YjM1zV08d8cFg9Yv5LTb+IdLJ3DZ1JHc9/x27nhiM5dPy+Gbl01gdEZggzJ6O9HUydObKnhqwxHq27qZODKJ/7x2GlfNyCMuJrQnODabnKpl3bG0iG6Pj+3HGvmwopGtR/0//7K96lR5u01Is2obKXFOElwOfD1n2D5o7nRT39bNybbuT9SERiS7KMpK5DMz8yjKSmBcdhLjshMZkewKSg1cRKymvjhyU899kXqn20tDWzd1rV00trtp6vA/Wjo9dFgH945u76mz/56zfYdVg3HYhTin3f+IsRPrtJMU6x+ckhDjICnWSXKc/2eiyxHypvez8fkM3V5/La3bc3ptx4fvtNqM12eQ01LG6cmkJwE5rITjsAlOx0e1uXDuX38FmqDqgZ6LapKs54GUiQgzCvxNKtuPNg5Kgnp3fx2tXZ6Qjt7ri9Nu4xuXjOfeZ7fy/JZjXFcSvKmVTmeM4VsvbGfzkZP87w2zmTnIg08Apual8Ke7LuSX7xzkwTcP8OquE3x2Vh53rRgXUKLy+gxr99fy9MYK3txbg9dnuGhiNrcuGsMFRRlhG7wQ4/joOrEeje3dHKprO/Woa+2m+bSDec+Zsc0G+WnxzCxIJT0hhsxEFwXp8YxKjyc/LY6ECOsHinXayU3tXzIb6mw2IdZmH/bX+AX6CXwLuBl4EZgBPCMio40xR85S5unAwwytkcn+Nu7tg3Q9zcs7q0iOdbCwKPgX557LldNzeeL9I/zo5T1cNDGbjCAOWOhx/xv7+ePW49x36YSwDVYAf0K+a0Ux15UU8NA7B3l6YwW//7CSiyZmc/GkESybmHXWPrG2Lg/vHqjjzT01vLmvhtqWLjITY7h98Viun1cQtBpZsKXGxzBrVAyzBuFkS6lQCihBGWPKRKRaRG4CGoBU4NvAVWcqY4yJjCtF+yAizMhPYdsgDJRwe328vruaSyaPDMt1Ljab8KPPTuPyB9bxby/t4SefnxnU9f/hw0p+9vp+rp2dz53LioK67kBlJ8fyvSun8LWlRaxeW85ftlfx2u5qwH+hdk5KLKnWSLJOj5cj9e0cbWjnmDUAICnWwdLxWXx6ag6XTB6h1ycpNUgCrsMbY+7v9dJV/SgTsabnp/LG3hpaOt0kxYZu5NcHhxpo7vTwqSmhH6RwJuNHJHHHkiJ+/tYBrp2TH7RpljYdauCbz29nwdh0/v2z0yLump3s5Fi+c8Vkvn35JPZUtfDm3mo2HmrgeFMne6qaOdnuJsZhY3RGPFPyUrh8eg6LxmVRUpg2qH2FSim/yGpkDqPp+SkYAzsqm0La9Pba7mpcDhuLiwe/ee90d60Yx1+2H+fbL+7g1a8vGXBb96G6Nu54opT8tDgevnFORNcyRITJuclMzk3mrnAHo5Q6o8g9igyy6fmpAGw7Grp+KGMMa3ZXs2hcZr/nnwuVWKedf7tmGofr27l/gHferWnu5JbHPkBEePQrc0mNjwlSlEqp4UwTlCU9IYaC9LiQXrC7p6qFysYOLgnCbd2D4cJxmVxXks9Dbx/kBeviz/NV1dTB51dvoLq5k0e+PCdiBw4opYYebeI7zfT8VLZWNIZs/a/vqUYELpoUGQkK4AefmUplYwfffGE7aQnO87qA99jJdr74yEZOtnXzxK3zmDNabySolAoerUGdZkZ+CpWNHdS1doVk/Wt2VzOzIDVkU9IEwuWw88svlTA5J5k7n9pC6eGGfr2vvLaVz/9yA43t3Txx23xNTkqpoNMEdZqefqhQNPNVNflvtRApzXunS3Q5eOwrc8lNieOWxz7gpe1V+PqYXw38V/Pf//p+Pn3/Otq7PTx9+4KwXIirlIp+mqBOMy0vBZuEZqDE69Z1N5+KwAQF/nss/fbWeYxIjuVvn97CygfW8coOf6Jq6XRzqK6NV3ZUcenP1vLT18u4ZPIIXrl3yccmNlVKqWDSPqjTJLgcjMtODEkNas2eGsZkJlCUFZxJREMhPy2eV7++hD9vO84Db+zna09twWmXj02uOTYrgSdvnc+iMA+TV0pFP01QvUzPT+WtvTUYY4J2oWlLp5v3D9Zx88LCiLt4tTe7TfjMrDyunJHLX7YfZ9fxZjISYqxbH8Qyd0waLsfwnh9MKTU4NEH1Mrcwjec3H6OsupUJI5PO/YZ+eKesFrfXcMnkwZ0cdiDsNuHqmXlcPTMv3KEopYYp7YPqZVFxFgDr9tcGbZ0v76giM9HFnNE6eadSSvWXJqhe8lLjGJuVwLsH6oKyvrYuD2/urWHltJFD4v4rSikVKTRB9WHxuEw2lNfT5fEOeF1v7q2h0+3j8jDedkIppYYiTVB9WFScRafbx+YjJwe8rpe2V5Gd5PrYDeWUUkqdmyaoPiwYm47DJry7f2DNfK1dHt7aV8PKaTnavKeUUudJE1QfkmKdzBqVyroBJqg39lTT5fFx+XRt3lNKqfOlCeoMFo3LYufxJk62dQe8jpe2VzEi2cUcvfW2UkqdN01QZ7CoOBNjYP3BwGpRLZ1u3i6rZeW0HGzavKeUUudNE9QZzMhPISnWwbqywBLUG3tq6Pb4uEKb95RSKiCaoM7AYbexsCiDdw/UYUzfM3ufzV+2V5GbEsusAm3eU0qpQGiCOotFxVlUNnZwqK7tvN5X1dTB2/tquGJGrjbvKaVUgDRBncUSa8but/ed37RHj60/jAG+tGB0CKJSSqnhIaAEJSL3ishNInLPOcqtF5EnrcfYwEIMn9EZCUzNS+bJjUfOeAO/3lo63Ty9sYKV03IoSI8PcYRKKRW9zjtBiUgxkGOMeRxIE5GJZyn+kDHmRutRHnCUYbRqSRHltW28vqe6X+Wf3XSUli4Pty8eE+LIlFIqugVSg1oObLKWtwFLz1J2gYjcLSIPisiQbE5cOXUk+WlxrF577vzq9vr4zfpDLBibfur28UoppQJzzqQhIheLyG09DyALaLZ+3QqcbZK5XxhjHgS2AEv6WPcqESkVkdLa2uDd3iKYHHYbty4aQ+mRk+ecm++l7VVUNXWyasmQa81USqmIc84EZYx53Rjzq54HUAf03MkvCajv630iEgv0HNGPAZ+4W58xZrUxpsQYU5KVlRXQDgyG60oKSIlzsnrtwTOWMcbwy7XlFGcnsmx89iBGp5RS0SmQZre3gLnW8gzgbRFxikjvIWuXAddZywVAWWAhhl+Cy8GXFozmtd3VlNe29llmze5q9lQ1c/visTq0XCmlguC8E5QxpgyoFpGbgAbr+WzgwV5FXwM6ROQqINkYs2XA0YbRTQsLcdptPLLu0Cd+t/5AHfc8+yETRiRx9azcMESnlFLRxxHIm4wx9/d6vhG4qtdr7cAjgYcWWbKSXFw7O5/nPqhABL5+UTHZybGsLavl9t+WMiYzgSdvm4/LYQ93qEopFRUCSlDD1T+tnIjLYePJDUd4cUsl18zO4/nNxyjKSuSp2+aTnhAT7hCVUipqDMmh3+GSFOvkX66awuvfWMqKSdk8vbGC8SMSeeZ2TU5KKRVsEshEqKFQUlJiSktLwx3GeSmvbWVkSizxMVoRVUqpQInIZmNMSe/X9cg6AGOzEsMdglJKRS1t4lNKKRWRNEEppZSKSBHTByUitcCRIKwqE/9sF9FO9zO66H5GF93P8zPaGPOJ6YQiJkEFi4iU9tXZFm10P6OL7md00f0MDm3iU0opFZE0QSmllIpI0ZigVoc7gEGi+xlddD+ji+5nEERdH5RSSqnoEI01KKWUUlFAE5RSSqmIpAlKKaVURIqqBCUi94rITSJyT7hjCRURWSgiz4c7jlATkVgRuUVErhSRH4pIVH1We4hIjIjcKiKfFZGvhzueUBORMSLyi3DHEUoisl5EnrQeY8MdT6iIyHIRuVREHhWR9FBsI2q+9CJSDOQYYx4H0kRkYrhjCgVjzHtA3/edjy6XAV5jzJ+BKmBmeMMJmUlAujHm90BBqL7oEWQ+kBDuIELsIWPMjdajPNzBhIKIZAHjjTF/Bb5mjGkIxXaiaTbz5cAma3kbsBTYG75w1AC9DWRYyznA4bBFEkLGmG0issN66gRawhlPKInIpcAr+E8+otkCEUkDxgP3GmN84Q4oBC4DCkXkbmCCiHzLGNMW7I1ETQ0K/5xQzdZyKxDtZ6JRzRjTaIw5KCLjgAOhOkOLFCJyH7DXGOMOdyyhICIjgTZjTFO4YxkEvzDGPAhsAZaEO5gQyQUqrP18Abg2FBuJpgRVDyRZy0nWczWEWQe1WcaYx8IdSygZY3zGmP8CvCLy6XDHEyIzAIeILANGisjU8IYTGiISC5y0nh4DRoYxnFDqACqt5WP4WzmCLpoS1FvAXGt5Bv4mIjVEWV/0lcaY34mIU0RmhDumUBCRBSJyo/X0BFAUznhCxRjzV2PM28aYt4ETxpid4Y4pRC4DrrOWC4CyMMYSSh8Ac6zlkcC+UGwkahKUMaYMqBaRm4AG63nUEZElwGIRuVpEJNzxhNBtwKUi8iTwJuANczyhcgjIFZGrgNnAY+ENJ3TE73PAFGtQUzR6Deiw/p/Jxpgt4Q4oFIwx7wNY/89JwJ9DsR2d6kgppVREipoalFJKqeiiCUoppVRE0gSllFIqImmCUkopFZE0QSmllIpImqCUUkpFJE1QSimlIpImKKWUUhFJE5RSSqmIpAlKKaVURIqY+0FlZmaawsLCcIehlFJqkG3evLnOGJPV+/WISVCFhYWUlpaGOwyllFKDTESO9PW6NvEppZSKSAElKBFZKCLPn6PMvSJyk4jcE1hoSimlhrOAEpQx5j38t1Xvk3WvlxxjzONAmohMDDC+fqtq6uDeZz+krLol1JtSSik1CELVxLcc2GQtbwOW9lVIRFaJSKmIlNbW1g5og7EOO6/tqmb12vIBrUcppVRkCFWCygSareVWIL2vQsaY1caYEmNMSVbWJwZwnJe0hBiuK8nnj1srOdHUOaB1KaWUCr9QJah6IMlaTrKeh9xti8fi9RkeXX9oMDanlFIqhAacoETEKSKje738FjDXWp4BvD3Q7fRHQXo8K6fl8PTGClo63YOxSaWUUiES6Ci+JcBiEbkamA08ePrvjTFlQLWI3AQ0WM8HxR1Limjp8vDMporB2qRSSqkQCOhCXWPMWqDotJeu6qPM/YEGNRDT8lNYWJTBb949zM0LxxDj0Eu9lFJqKIrKo/eqJWM50dzJn7YdD3coSimlAhSVCWrp+CwmjkziN+/qYAmllBqqojJBiQjXzMpjd1UzNS065FwppYaiqExQAAvGZgCwsbwhzJEopZQKRNQmqCm5ySS6HGw8NCiXYCmllAqyqE1QDruNksI0NmgNSimlhqSoTVDgb+Y7UNNKbUtXuENRSil1nqI6Qc0f458CcNMhrUUppdRQE9UJampeCgkxdjaUaz+UUkoNNVGdoJx2GyWF6ZqglFJqCIrqBAUwf2w6+2taqWvVfiillBpKoj5B9VwPpf1QSik1tER9gpqWl0K89kMppdSQE/UJymm3MWd0ms4ooZRSQ0zUJyjwN/Ptq26hXvuhlFJqyBg2CQq0H0oppYaSYZGgpuWlEGO3sfVYY7hDUUop1U/DIkHFOGxMGJnErsrmcIeilFKqn4ZFggKYmpfMzuNNGGPCHYpSSql+GDYJakpuCo3tbo6d7Ah3KEoppfph2CSoqXkpAOw63hTmSJRSSvXHsElQE0cmYbcJO7UfSimlhgRHoG8UkXuBRiDFGPPAGcqsBw5ZT79rjCkPdHsDFeu0U5ydyE6tQSml1JAQUA1KRIqBHGPM40CaiEw8Q9GHjDE3Wo+wJaceU/NS2FmpAyWUUmooCLSJbzmwyVreBiw9Q7kFInK3iDwoImFvTpyam0xdazfVzTqjhFJKRbpAk0Ym0NOZ0wqkn6HcL4wxDwJbgCW9fykiq0SkVERKa2trAwyl/3oGSuys1GY+pZSKdIEmqHogyVpOsp5/jIjEAietp8eAkb3LGGNWG2NKjDElWVlZAYbSf5NzkxFB+6GUUmoICDRBvQXMtZZnAO+IyOheZS4DrrOWC4CyALcVNPExDoqyEnUkn1JKDQEBJShjTBlQLSI3AQ1AKvBgr2KvAR0ichWQbIzZMpBAg2VqbrJeC6WUUkNAwMPMjTH393rpql6/bwceCXT9oTI1L4U/bD1OXWsXmYmucIejlFLqDMI+sm6wTcnVgRJKKTUUDL8ElZcMwK7jQ68favORk2wor8fn0+u4lFLRL+AmvqEqOdZJYUb8kKpBHalv44cv7WHN7moA8tPiuHZ2Pp+bk09BenyYo1NKqdAYdgkKYEpeCtuONoY7jHPq8nj56Zr9/ObdQzjswjcvm0BeahzPbz7GA2/u5+dvHeDn18/i09Nywh2qUkoF3fBMULnJvLS9iqYONylxznCHc0Y/WVPGL98p59rZ+XzzsgmMSI4F4OqZeRxv7OCup7fw9ee2kpMax8yC1PAGq5RSQTbs+qAAJuf4+6H2VEVuP9TOyiZ+te4Qny8p4H+um3EqOfXITY1j9ZdLyEpycdvjpVQ26n2ulFLRZXgmqFx/gtodoQMlPF4f//j77aTFx/BPKyedsVxmootHb55Ll8fLrY99QEunexCjVEqp0BqWCSo7KZbMRBe7I7QG9ej6w+ysbOb7V00hJf7sTZDFI5J46IY57K9p5ZvPbx+kCJVSKvSGZYICfy0qEmtQFfXt/M+afVw8KZuV0z4xfWGfFhVn8o1LxvPKzhOsLQv9pLtKKTUYhm+CyknmQE0r3R5fuEP5mO//eRcOm40ffGYqItLv9922eAyFGfF8/8+7cHsja5+UUioQwzdB5SbT7fVxsLY13KGcUl7byht7a1i1ZCw5KXHn9V6Xw853Lp/Mwdo2Hn/vcGgCVEqpQTR8E1RO5A2UeGpjBQ6b8IV5BQG9/6JJ2Swdn8X9r++nrlVvyqiUGtqGbYIak5lArNMWMQMlOt1ent98jEunjiQ7Kfbcb+iDiPDPV0ymw+3lv/+6L8gRKqXU4Bq2CcpuEyaMjJyBEn/edpymDjc3zu99W63zMy47kZsXFvJc6dEhNZ2TUkr1NmwTFPib+XZXNWNM+CdffXJjBeOyE1kwNn3A67rn4mKSY538dE3Y7xGplFIBG94JKjeZpg43x5s6wxrHzsomth1t5Ib5o85r5N6ZJMc6WbVkLG/srWHrEJhzUCml+jIs5+LrcfpAibzU8xs1F0xPbjhCnNPOZ2fnB22dNy0s5FfryvnJmjJ+e8u8oK03FIwxbKlo5NlNFbxfXk+n20uX20eX10dRViIXTcxm+cRsZhakYrcNPIErpYaGYZ2gJo5MQsSfoC6ZPCIsMTR3uvnj1uNcNSM3qBPXJrocfHVpEf/+yl5KDzdQUjjwpsNg8/kMz35wlMffO8y+6hbiY+wsn5BNSrwTl8OG025j69FGHnrnID9/6wDZSS7uvqiYL8wtwGkf1pV/pYaFYZ2gElwOxmQksLsqfIMJ/rztOB1uLzcsGBX0dX/5gkIeWXeI/3mtjGdWLQj6+geivrWLv//dNt7eV8u0vBR+dM00rpqZS6Lrkx/JxvZu3imr5ckNR/jnP+zk0XcP8c3LJnDplJFBaRJVSkWmYX8aOik3OaxDzV/ZcYIxmQlMy0sJ+rrjYux8bVkR75fX897BuqCvP1Aby+tZ+cA63jtYzw8+M5U/3XUhX5w/qs/kBJAaH8PVM/P4vzsu4JEvl2CzCV99cgs3/nojx3UWd6Wi1rBPUJNzkjna0EFzGGYCb2jr5v3yej49NXQ1gRvmj2JEsoufvFYWGaMVNxzh+kc2EB/j4MU7F/KlBaP7ve8iwiWTR/DqvYv5wdVT+LCikUt/tpYXPzwWEfumlAquYd3EBx8NlNhb1cK8MYPbT7Nm9wm8PsPKEN4RN9Zp5+4VxXznDzt5e18tyydmh2xb5/LMpgq+84edrJiYzQPXzzpjjelcHHYbX7qgkCXjs/j7/9vG3z23jTW7q/nRNdNIjY8JctTBcaKpk61HG9l1vIma5i4a2rs52dZNt9dHfIydRJeDpFgnBWlxFGUnUpSVyLjsRGKd9nCHrlTYaIKy7g2163jToCeol3ecYFR6PFOsGELlupICVq8t58d/3cfS8VnYwjAS7nelR/mnF3ewbEIWD904G5dj4Afe0RkJPHfHBaxeW85P1uzjw4pGfvr5mSwYmxGEiAem0+1l3f46XtlRxXsH6znR7L+UwW4TMhJiSE+IIS0+hsRYB21dHiobO2nuaOGPWzvwWZVBh02YkpdCyeg05hamMW9MBukJkZmAlQqFgBOUiNwLNAIpxpgHAi0TbtlJLrKSXOw4NrgDJRrbu1l/oI5bF48JeUd/jMPGNy4Zz9ef28pLO6q4ckZuSLfX2x8+rOSbL2xn0bhMHr5xTlCSUw+7TfjasiIWjcvknmc/5IuPbOCu5eO456JiHIM80s8Yw8ZDDTz3wVHW7K6mtctDSpyTpeOzmDUqlRkFqUzOST5rrajL4+VwXTsHalrZebyJzYdP8sSGI/z63UOI+Gv8i8ZlsnBcJnML04iPCd85Znu3hyP17RxtaKe6uZPq5i5qWjo52e6mrctDa5eH9m4vPp/B4P/72G1CfIyDOKeduBg7KXFO0uKdpMbHkJEYQ1ai//vY8wjn/vXFGEO310eXx0e3x//T6zX4jMFrDMaACNhEsIn/8xljt+Gw23DaBZfDjtMuOrinnwL674tIMZBjjLlfRL4nIhONMXvPt0wkEBFm5Kew7VjjoG53ze5qPD7Dyqmha9473ZUzcnno7YP8ZE0Zl00dOWjDtNftr+Xvf7eN+WPSWf2lkpA1WU3LT+Evdy/ie3/axQNvHuCdslp+/LkZTBiZFJLtna6l083vt1Ty5IYj7K9pJTnWweXTclg5PYeFRRnn9bd2OexMGJnEhJFJXD7d/9no8njZWdnEewfqefdAHb9Zf4hfri3HaRdmFqRyQVEmJaPTmFGQGtRLFcB/KcDxpg4O1rZxoKaVAzWtHKxp5VB9G7UtH5+Q2CaQleTy1wxdDtITYshPs2MT/wFZAK/P0OH20tHtpbG9m8P1bZxs66a509Pn9hNdDrKTXGQmuchKdJGZGENGoou0eCfJcU5S4pwkxTpPJbw4px27TfwPKwm4fT48XoPbSiwd3V463F7au/1JtLXT/7O500Nzh5uWTg8tnW7/7077fUe3l7Zuz6kabqBEwOWw4XL444112oh12nE57cQ6rGWHDZfTTozdRozDn9wcNhtOh+Cwyam/ae/GEJ/x/8+8xuDzGTw+g8frs376/wbd3o/+Hm6fwe3x4fH5cHsNHutv5bXW4fX5k6/P50/OPgP+0w2/lDgnr/3d0oH9Qc4i0NOT5cAma3kbsBTonXzOWUZEVgGrAEaNCv4w6/6anp/KG3traO50kxwb3C/4mbyy8wR5qXFMzw/+6L2+2G3CP1w6gdt/W8oLm4/xhXmh/3vvr27hzie3UJydyK9umktcTGj7UxJcDv77b2awbEIW3/3jLq54cB13LS/ma8uKiHEEPyFX1Lfz6HuH+F3pMVq7PEzPT+HHn5vOldNzg7qvLoedOaPTmTM6nbsvKqa928MHh0/y/sF63j9Yx8/f3H/qoFmUlcD0/FTGZiYwJiuBwowERiTHkhLn7PNv4PUZGtu7aWjrprali6Mn26loaKeioYPy2lbKa9vocHtPlU+NdzIuK5Fl47MozExgVHo8o9LjyUmJJSPRFfCF1B6vj5Ptbmpbuqht7aK2xV8bq2n2L9e2dLGnqpm61q4zJrOBEvEnxORYJ0mxDpJiHWQkxDAqPZ5El4P4GAfxMf5E6HL4E0dP7chu89eaehjDqYO820oI3R5/cuhye+n0+Oh0e62HtWy91tje/bEaWldPAvH4E4qvJ2mcIVH21NxsIjjtNuw2wWkX62dPzP5lp/2j5Bfr/Ki8oyfJW+vpqRH21A57hLqGG+jaM4Fya7kVmBRIGWPMamA1QElJSdiGYU3PT8EY2HmsiYXjMkO+veZON+v213LTBYWDWtW/eFI2s0alcv8b+/nMrLyQdsDXt3Zxy+Mf4HLa+fXNcwMeEBGIK6bncsHYDP71L7v56etlvLyjim9eNoEVE7MH/Pf2+QzrD9bxxPtHWLOnGrsIV87I5eaFhcwoSA3ODpxDfIyDpeOzWDo+C/B/nrYfbWLr0ZNsPdrIhvJ6Xvywso/32UlwOU6dYXt9hrauT9YIHDYhNzWOMZkJzB+TwbjsRIqyEhiXnUh6QkxIPrMOu+1Us965dHm8NHW4ae5w+392euhye62amQ+vz2ed+YOBUwdgh02ItWpZ8TF2Yp12kmMdJMY6SHA5SIxxhKV/diB8PkPvf0c0NR8GetSoB3raTpKs54GUiQjT81MB2DZICeqNPdW4vYaV0wenea+HiHDfpRP44iMbWb22nHsuKg7JdjrdXlY9sZma5i6eu+OCsEwjlZHo4v4vzOLK6bn86192c+vjpUzLS+HrFxcHlKhqmjt5YUslz2yqoKKhnbR4J3cuK+LLFxQyIjmw26MES3Ksk0XFmSwq/uiz297t4XBdO4fq2qhv66Kp3X8wb+v2YJOPzox7agnpVvNZQZq/NjTY/Xfnw+Wwk51kD/i2NNFkqCXU8xVognoLuBl4EZgBPCMio40xR85S5unAwwyt9IQYCtLj2D5I/VAv7zhBTkosM63EOJgWFmVy+fQcfv7WAa6YnsPYrMSgrt8Yw7de2M7mIyf53xtmM3OQahVncvHkESydkMWLH1by8zcPcOvjpYzOiGfFxGwumjiCeWPS+2z66uj2Ulbdwlv7anhzbw3brUE088ak8/efGs+lU0ZG9BDw+BgHk3OTT41SVWooCihBGWPKRKRaRG4CGoBU4NvAVWcqY4yJ6Hs/TM9PZWtFY8i3097tYW1ZLdfPGxW2s5/vXTmZtWW1fPvFnTx9+/ygNgn89PX9/HHrce67dEJIr+86H067jetKCrhmVh5/3Hqcl7Yf56mNFTy6/jAuh43MRBep8U7S4mPocHupaGg/NQBABGYVpHLfpf6plcZlBzehK6XOLOCOAWPM/b1euqofZSLWzPxUXtpeRV1rF5mJ524HD9Tasjq6PD4+FabJaQGyk2L5x09P5Nsv7uT5zcf4m5LAbjHf2wubj/HAG/u5riSfO5cVBWWdweS02/jcnHw+Nyef9m4P7x2oZ9PhBupau2hsd3OyvRuXw8aKCdmMyohndEY8F4zNICOEnwel1JlF1kUGYdQzmm77sUZWTAxd8nh9TzXJsQ7mDvJFwb1dP3cUL26p5N9e3sOKidkDPghvKK/nH3+/nYVFGfzwM9MivqM2PsbBxZNHcHEYTxSUUmcXuT2hg2xqXgo2gW1HQ3fBrtdneHNvDcsnZof9dhE2m/Cjz06jrcvD9/60a0Bz2e2sbOKOJzYzKj2eh26YE5Ih3Uqp4UePJJYEl4Nx2YkhHSix+chJGtq6w3bvqd7Gj0ji6xeP5y/bq/ivv+4LaB1bjzbyxUc2kOhy8NhX5pESPzjXkSmlop828Z1men4qb+2twRgTkiaqNbtP4LTLqetXIsGdy4qobOzgf98+SHpCDLctHtvv924+0sBNv/mA9IQYnr59Pvlp8SGMVCk13GgN6jQz8lOob+umMgT3GDLGsGZ3NRcUZZI0SLNV9IeI8IOrp/LpqSP54Ut7ePHDY/1635t7q/nSrzeRneTiuTsWaHJSSgWdJqjTnLpgNwT9UAdrWzlc384lk8J3u4szsduEn31hJguLMviH323nf17bR1N73/fHOt7Ywdee3Mwtj5VSkBbPs6sWkJMy+BfiKqWinzbxnWZiThJOu7D9WOOpiTqD5bXd1QARO2rM5bCz+sslfOuF7Tz45gEeW3+Yrywaw5XTc2jscFPX0sWeEy08srYcg+G+Sydw2+IxQZ2ZXCmlTqcJ6jQuh51JOckhmdl8ze5qpuWlRHRtI9Hl4BdfnM1dy5u5//X9PPCG/3G6T00ewXevnKxNekqpkNME1cuM/FR+v+UYHq8vaPOR1bT476b6dxePD8r6Qm1STjIPf2kOe080s/t4M5mJLjITXWQnu0J6EbNSSp1OE1Qv88ak88SGI2yvbGL2qLSgrPONPTUYAxdPiszmvTOZODKZiSN1LjelVHjoIIleLhyXiQisK6sL2jpf2l5FYUY8k3JCf/M8pZSKFpqgeklPiGFqbgrvHqgNyvrqW7t472Adl0/Pifjpf5RSKpJogurDouJMPqxopKWz76HW5+PVXSfwGbh8Wm4QIlNKqeFDE1QfFhdn4vEZNpQ3DHhdL22vYmxmgjbvKaXUedIE1Yc5o9OIc9p5d//AmvlqW7rYUF6vzXtKKRUATVB9cDnszBuTzroDAxso0dO8d8V0bd5TSqnzpQnqDBYXZ1Je2zagefle2n6ccdmJjB+hd2FVSqnzpQnqDBYX+2ccD7SZr6alk42HGrh8mjbvKaVUIDRBncH4EYlkJ7lYtz+wZr5Xd57AGII+p59SSg0XmqDOQERYVJzJ+gN1+Hznf7fZv2yvYvyIRMaP0NF7SikVCE1QZ7G4OJOT7W52HW8+r/ftO9HCpkMNXD0zL0SRKaVU9NMEdRYXjssE4I291ef1vkfWlRPntHPD/FGhCEsppYaFgBKUiNwrIjeJyD3nKLdeRJ60Hv2/l3iEyE6KZcn4LJ7cUEGn29uv95xo6uSPWyv5/NwCUuNjQhyhUkpFr/NOUCJSDOQYYx4H0kRk4lmKP2SMudF6lAccZRjdsWQsda1d/OHDyn6Vf+y9w3h9hlsuHBPiyJRSKroFUoNaDmyylrcBS89SdoGI3C0iD4rIJ7YlIqtEpFRESmtrgzM5a7AtLMpgSm4yq9eVn3OwRGuXh6c2HuHTU3MYlaE39FNKqYE4Z4ISkYtF5LaeB5AF9IwaaAXSz/L2XxhjHgS2AEt6/9IYs9oYU2KMKcnKygog/NATEVYtGUt5bRuv7zl7X9Szmypo6fRw+5Ih15qplFIR55wJyhjzujHmVz0PoA7oGTudBNT39T4RiQVOWk+PASODEG9YXD4th7zUOFavPXMrpdvr49H1h5k3Jp2ZBamDF5xSSkWpQJr43gLmWsszgLdFxCkio3uVuwy4zlouAMoCCzH8HHYbty0eQ+mRk2w+crLPMo+/d5jKxg5WLdbak1JKBcN5JyhjTBlQLSI3AQ3W89nAg72KvgZ0iMhVQLIxZsuAow2j60oKSIlz8tDbBzHm431RT7x/mB++tIcVE7NZMTE7TBEqpVR0kd4H23ApKSkxpaWl4Q7jrH72ehk/e30/s0el8v9WTmJuYTqPrj/E9/+8m4snZfOLG2bjctjDHaZSSg0pIrLZGFPS+3VHOIIZqu5eUczI5Fh+sqaMv3n4fWaNSuXDikY+NXkEP//ibGIcet2zUkoFix5Rz4PdJnxh3ijevm8Z//Cp8eyvbuXy6Tn84gZNTkopFWxagwpAfIyDu1YUc8fSIhw20dtpKKVUCGiCGgCnXWtNSikVKnqEVUopFZE0QSmllIpIETPMXERqgSNBWFUm/tkuop3uZ3TR/Ywuup/nZ7Qx5hPz3UVMggoWESntazx9tNH9jC66n9FF9zM4tIlPKaVURNIEpZRSKiJFY4JaHe4ABonuZ3TR/Ywuup9BEHV9UEoppaJDNNaglFJKRQFNUEoppSKSJiillFIRSROUUkqpiKQJaogTkXkiMjLccajQEZGo+p5Kr+n/RSQmXLGoyBZVH/zeRCRbROaFO45QEJF4EVkIjAWWhTmckBOREhHJDnccg0lEbCJSAiwUkYxwxxMsxho6LCJ5InIFUBzmkEJOREaKyEUiMiLcsQTT6ScbIrJSRIL6v4zKBCV+C4BRwCgRuSRavuAikikiFwDdwHJgC/CqiMSFN7LQEJEsEVkOuIBlIjIzzCENpqlADv59zw1zLEFjJd4vATcCh4wxu8IdUyiJSBYwCf+8dWNEJCnMIQ2IiCSIyD+JiMMYY0RkuojcDEwgOPOpnhJ194MSkU8DZcBIoN4Y87yIXAt4wxvZwIiIA7gFOIH/wNUBbAMWAh8AMcCHYQswCERETju7Hg2MAKqBmcaYn4rIDCC9d9loYjXXTgYO4f/fvmyMqRCRFBGxGWN84Y1wYETkamAvsBMQouwkuddneBHQBMQDxcaY1SLiBIbs59b6DLaJyE/xnzh5gAr8J8zfBRaJSIUx5kAwthc1Hw4RmSMifwe0A4eBTcA8ESnEf/B2hi+6gbEOzDOA6fi/3L8GrgZex/8ljzPGDPXk5LTOxpJEZDbwbfz7WwGUWwc2ARLho2aioaxX84jLquVPArKBWPz7ukhErgGmMIS/ryIyxWqSrgc+a31ey/A3X04Mb3QDY/3vvn1ajWKe9XmtxH8Q3wFMEZG5wGexTrKGImOMT0QS8NfsfyYiY40xjcaYvfhnlXAA94lIbDC2N2Q/8D1EJFVEpgGtwGj8TQZeY8xxYB1QALxkjKkNZ5yBspq0UoAG/E2Wl+LfVxdQAjxmjCkNW4DBc6fVX3gd/v08BqTir028YpVpMsb8OTzhBU9PYrIOZiIi84ElwFxgnDHmWWPMHuAXwLvAcWPMe8YYT/ii7h8RyRCR+6waMNYJx2T8Z9rXGmPeBZpFZAn+zzT4k9aQY+3rt4Ak4Mf4T4TBf/uJqfgTUZwxph34X/wH73eNMTXhiDcYrJOJG/G34DwNXGa97sTfF/6mMeYOY0xnULY3VE9ErS/5LPztuoXAU8Ac/GeafzDGVIUvuuARkS8DfzbGnBSRLwDj8Z+RvWyM6QpvdMFj9UkUAv8J+IB/wn/g2oq/6bJjqNeaRGSaMWbHac8LgeuBWmPMr6yzzv8EngSK8H/Zh8zBzOoHLQEqjTHlInIx0Ib/e/oKMAbIx/9/nQP8uzHGHa54B6KPfS0GvoV/nw6KSAr+fbzIGPPtcMYaLNY+fgH4P6DBGFMrIj8BNhtjnhKR2GAlph5DsgZlffCX4T9D8QC/x9/8sxWYhr/WFC3eBa61mgeOAz8zxrwYTcnJ8hT+s7Iiq6awCX9T7WZjTPtQTU49tSURSQY+Z43kirM+w7X4m7maRSTB+nL/HH9z9LqhlJwsXcCFQKa1v4n4m6T/hL/29Cb+E6wTxph/HarJydKzrxnWIIhD+GsUlwIYY5qs/f0jfHJo/RBVjv8YlA3caLV4vAJsBgh2coIhVoMSkURgMf4P/gRgF/5OyCPWa/sBXyj+UOEkIpn4a4plQ72T/GyspqAVQAvwF2PMkGz66c3qm/CISA7w7/gP2NPwH7x2AddaRV8Y4gdtRORG/N/Nf8ff/HMM//fzQuBVoHsoNFX2h7WvE4Hv9nwvReRBYD3wf9H4XbX6n5bhH6x1NNQnUUOqBmWMacV/xvk+/lrTAWAB/j/YMetMO6qSE4Axps4YszcaP/CnM8bsBp4FnoiW5GT5W6vP5QSwAX8T5s+Az+Cv+Tvwjzgd0snJ8jT+vqVM/PsK/tGIb1jfz6hITpan8fc3nX7tz6vA1ij+rqbj//x+OBg1/CFVg+phNXddCbwFVBhjDoY5JKXOSERuACYbY75tNfX8C/6mvDvxD+R5O5oOaNbAnnuAh4wxH4Q5nJCyRtjeCzwMfDBUm6Ij1VBNUDPxN+m9F01fbBWdxD9V0TfwjybdIyLfAJrxj8CMphrFKSJyGbDGGDOkrz/sj+G0r4NtqCaoqLxIU0Uvq39tOf5LBNZYl0Eopc5iSCYopYYia7RXvdb6leofTVBKKaUi0pAaxaeUUmr40ASllFIqImmCUkopFZE0QSmllIpImqCUUkpFJE1QSimlItL/B0ocuJ9o+qN0AAAAAElFTkSuQmCC\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#一般绘图时会自动创建刻度,而如果通过set_ticks创建刻度可能会导致tick的范围与所绘制图形的范围不一致的问题。\n", - "#所以在下面的案例中,axs[1]中set_xtick的设置要与数据范围所对应,然后再通过set_xticklabels设置刻度所对应的标签\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "fig, axs = plt.subplots(2, 1, figsize=(6, 4), tight_layout=True)\n", - "x1 = np.linspace(0.0, 6.0, 100)\n", - "y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)\n", - "axs[0].plot(x1, y1)\n", - "axs[0].set_xticks([0,1,2,3,4,5,6])\n", - "\n", - "axs[1].plot(x1, y1)\n", - "axs[1].set_xticks([0,1,2,3,4,5,6])#要将x轴的刻度放在数据范围中的哪些位置\n", - "axs[1].set_xticklabels(['zero','one', 'two', 'three', 'four', 'five','six'],#设置刻度对应的标签\n", - " rotation=30, fontsize='small')#rotation选项设定x刻度标签倾斜30度。\n", - "axs[1].xaxis.set_ticks_position('bottom')#set_ticks_position()方法是用来设置刻度所在的位置,常用的参数有bottom、top、both、none\n", - "print(axs[1].xaxis.get_ticklines())\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "在普通的绘图中,我们可以直接通过上图的set_ticks进行设置刻度的位置,缺点是需要自己指定或者接受matplotlib默认给定的刻度。当需要更改刻度的位置时,matplotlib给了常用的几种locator的类型。如果要绘制更复杂的图,可以先设置locator的类型,然后通过axs.xaxis.set_major_locator(locator)绘制即可 \n", - "locator=plt.MaxNLocator(nbins=7) \n", - "locator=plt.FixedLocator(locs=[0,0.5,1.5,2.5,3.5,4.5,5.5,6])#直接指定刻度所在的位置 \n", - "locator=plt.AutoLocator()#自动分配刻度值的位置 \n", - "locator=plt.IndexLocator(offset=0.5, base=1)#面元间距是1,从0.5开始 \n", - "locator=plt.MultipleLocator(1.5)#将刻度的标签设置为1.5的倍数 \n", - "locator=plt.LinearLocator(numticks=5)#线性划分5等分,4个刻度 \n", - "\n", - "axs.xaxis.set_major_locator(locator)" + "**其他案例**" ] }, { @@ -2315,17 +2280,17 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 参考资料\n", - "[1.Python学习笔记(4)——Matplotlib中的annotate(注解)的用法](https://blog.csdn.net/leaf_zizi/article/details/82886755)" + "## 作业\n", + "1.尝试在一张图中运用所讲过的功能,对title、text、xlable、ylabel、数学表达式、tick and ticklabel、legend进行详细的设计. \n", + "2.阅读你可能用到文献或者相关书籍,思考自己如何才能通过学过的例子将自己认为比较好看的图给复现出来." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## 作业\n", - "1.尝试在一张中运用所讲过的功能,对title、text、xlable、ylabel、数学表达式、tick and ticklabel、legend进行详细的设计. \n", - "2.阅读你可能用到文献或者相关书籍,思考自己如何才能通过学过的例子将自己认为比较好看的图给复现出来." + "## 参考资料\n", + "[1.Python学习笔记(4)——Matplotlib中的annotate(注解)的用法](https://blog.csdn.net/leaf_zizi/article/details/82886755)" ] } ], @@ -2363,7 +2328,7 @@ "height": "calc(100% - 180px)", "left": "10px", "top": "150px", - "width": "239.641px" + "width": "239.634px" }, "toc_section_display": true, "toc_window_display": true