{"id":992169,"date":"2024-12-27T08:35:02","date_gmt":"2024-12-27T00:35:02","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/992169.html"},"modified":"2024-12-27T08:35:04","modified_gmt":"2024-12-27T00:35:04","slug":"python%e5%a6%82%e4%bd%95%e7%94%9f%e6%88%90%e9%9a%8f%e6%9c%ba%e7%ba%bf%e6%ae%b5","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/992169.html","title":{"rendered":"python\u5982\u4f55\u751f\u6210\u968f\u673a\u7ebf\u6bb5"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25070122\/da388845-0b50-4654-83cb-4b473b0a4558.webp\" alt=\"python\u5982\u4f55\u751f\u6210\u968f\u673a\u7ebf\u6bb5\" \/><\/p>\n<p><p> <strong>Python\u751f\u6210\u968f\u673a\u7ebf\u6bb5\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528\u968f\u673a\u6570\u751f\u6210\u5668\u751f\u6210\u5750\u6807\u3001\u5229\u7528numpy\u5e93\u751f\u6210\u968f\u673a\u6570\u7ec4\u3001\u5229\u7528matplotlib\u53ef\u89c6\u5316\u7ebf\u6bb5\u3002\u63a5\u4e0b\u6765\uff0c\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u968f\u673a\u6570\u751f\u6210\u5668\u751f\u6210\u7ebf\u6bb5\u7684\u8d77\u70b9\u548c\u7ec8\u70b9\u5750\u6807\u3002<\/strong><\/p>\n<\/p>\n<p><p>\u751f\u6210\u968f\u673a\u7ebf\u6bb5\u6700\u7b80\u5355\u7684\u65b9\u6cd5\u662f\u5229\u7528Python\u7684\u5185\u7f6e\u5e93<code>random<\/code>\u3002\u9996\u5148\uff0c\u8bbe\u5b9a\u7ebf\u6bb5\u7684\u8d77\u70b9\u548c\u7ec8\u70b9\u5750\u6807\u7684\u8303\u56f4\uff0c\u7136\u540e\u4f7f\u7528<code>random.uniform<\/code>\u51fd\u6570\u751f\u6210\u8fd9\u4e9b\u5750\u6807\u3002\u5177\u4f53\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<ol>\n<li>\n<p><strong>\u5b9a\u4e49\u8303\u56f4<\/strong>\uff1a\u9996\u5148\u9700\u8981\u5b9a\u4e49\u7ebf\u6bb5\u7684\u8d77\u70b9\u548c\u7ec8\u70b9\u5750\u6807\u7684\u8303\u56f4\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u5c06x\u548cy\u5750\u6807\u7684\u8303\u56f4\u8bbe\u5b9a\u4e3a0\u5230100\u4e4b\u95f4\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u751f\u6210\u5750\u6807<\/strong>\uff1a\u4f7f\u7528<code>random.uniform<\/code>\u51fd\u6570\u751f\u6210\u7ebf\u6bb5\u8d77\u70b9\u548c\u7ec8\u70b9\u7684x\u548cy\u5750\u6807\u3002<code>random.uniform(a, b)<\/code>\u51fd\u6570\u4f1a\u751f\u6210\u4e00\u4e2a\u5728a\u548cb\u4e4b\u95f4\u7684\u6d6e\u70b9\u6570\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u6784\u5efa\u7ebf\u6bb5<\/strong>\uff1a\u5c06\u751f\u6210\u7684\u5750\u6807\u7ec4\u5408\u6210\u7ebf\u6bb5\u3002\u53ef\u4ee5\u4f7f\u7528\u4e00\u4e2a\u5143\u7ec4\u6216\u5217\u8868\u6765\u8868\u793a\u7ebf\u6bb5\uff0c\u4f8b\u5982\uff1a<code>((x1, y1), (x2, y2))<\/code>\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u53ef\u89c6\u5316\u7ebf\u6bb5<\/strong>\uff1a\u53ef\u4ee5\u4f7f\u7528<code>matplotlib<\/code>\u5e93\u6765\u7ed8\u5236\u751f\u6210\u7684\u7ebf\u6bb5\uff0c\u4ee5\u4fbf\u76f4\u89c2\u5730\u67e5\u770b\u7ed3\u679c\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n<p><p>\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u5b9e\u73b0\u4e0a\u8ff0\u6b65\u9aa4\u3002<\/p>\n<\/p>\n<p><h2>\u4e00\u3001\u4f7f\u7528RANDOM\u5e93\u751f\u6210\u968f\u673a\u7ebf\u6bb5<\/h2>\n<\/p>\n<p><h3>1. \u5b9a\u4e49\u5750\u6807\u8303\u56f4<\/h3>\n<\/p>\n<p><p>\u5728\u751f\u6210\u968f\u673a\u7ebf\u6bb5\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u5b9a\u4e49\u5750\u6807\u7684\u8303\u56f4\u3002\u5047\u8bbe\u6211\u4eec\u8981\u751f\u6210\u7684\u7ebf\u6bb5\u5728\u4e00\u4e2a\u4e8c\u7ef4\u5e73\u9762\u4e0a\uff0cx\u548cy\u7684\u5750\u6807\u8303\u56f4\u90fd\u8bbe\u5b9a\u4e3a0\u5230100\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import random<\/p>\n<h2><strong>\u5b9a\u4e49\u5750\u6807\u8303\u56f4<\/strong><\/h2>\n<p>x_min, x_max = 0, 100<\/p>\n<p>y_min, y_max = 0, 100<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2. \u751f\u6210\u968f\u673a\u5750\u6807<\/h3>\n<\/p>\n<p><p>\u4f7f\u7528<code>random.uniform<\/code>\u51fd\u6570\u751f\u6210\u7ebf\u6bb5\u7684\u8d77\u70b9\u548c\u7ec8\u70b9\u5750\u6807\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u968f\u673a\u8d77\u70b9\u5750\u6807<\/p>\n<p>x1 = random.uniform(x_min, x_max)<\/p>\n<p>y1 = random.uniform(y_min, y_max)<\/p>\n<h2><strong>\u751f\u6210\u968f\u673a\u7ec8\u70b9\u5750\u6807<\/strong><\/h2>\n<p>x2 = random.uniform(x_min, x_max)<\/p>\n<p>y2 = random.uniform(y_min, y_max)<\/p>\n<h2><strong>\u6784\u5efa\u7ebf\u6bb5<\/strong><\/h2>\n<p>line_segment = ((x1, y1), (x2, y2))<\/p>\n<p>print(f&quot;\u968f\u673a\u751f\u6210\u7684\u7ebf\u6bb5\u5750\u6807\u4e3a: {line_segment}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>3. \u53ef\u89c6\u5316\u7ebf\u6bb5<\/h3>\n<\/p>\n<p><p>\u4f7f\u7528<code>matplotlib<\/code>\u5e93\u6765\u7ed8\u5236\u751f\u6210\u7684\u7ebf\u6bb5\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import matplotlib.pyplot as plt<\/p>\n<h2><strong>\u63d0\u53d6\u5750\u6807<\/strong><\/h2>\n<p>x_values, y_values = zip(*line_segment)<\/p>\n<h2><strong>\u7ed8\u5236\u7ebf\u6bb5<\/strong><\/h2>\n<p>plt.plot(x_values, y_values, marker=&#39;o&#39;)<\/p>\n<p>plt.xlim(x_min, x_max)<\/p>\n<p>plt.ylim(y_min, y_max)<\/p>\n<p>plt.title(&quot;\u968f\u673a\u751f\u6210\u7684\u7ebf\u6bb5&quot;)<\/p>\n<p>plt.xlabel(&quot;X\u5750\u6807&quot;)<\/p>\n<p>plt.ylabel(&quot;Y\u5750\u6807&quot;)<\/p>\n<p>plt.grid(True)<\/p>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h2>\u4e8c\u3001\u4f7f\u7528NUMPY\u5e93\u751f\u6210\u968f\u673a\u7ebf\u6bb5<\/h2>\n<\/p>\n<p><p><code>numpy<\/code>\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u503c\u8ba1\u7b97\u529f\u80fd\uff0c\u53ef\u4ee5\u7528\u6765\u751f\u6210\u5927\u91cf\u968f\u673a\u6570\u636e\u3002\u4f7f\u7528<code>numpy<\/code>\u751f\u6210\u968f\u673a\u7ebf\u6bb5\u7684\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><h3>1. \u5bfc\u5165NUMPY\u5e93<\/h3>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86<code>numpy<\/code>\u5e93\uff0c\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528<code>pip install numpy<\/code>\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2. \u751f\u6210\u968f\u673a\u5750\u6807<\/h3>\n<\/p>\n<p><p>\u4f7f\u7528<code>numpy<\/code>\u7684<code>random.uniform<\/code>\u51fd\u6570\u751f\u6210\u968f\u673a\u5750\u6807\uff0c\u4e0e<code>random<\/code>\u5e93\u7c7b\u4f3c\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u968f\u673a\u5750\u6807<\/p>\n<p>x_coords = np.random.uniform(x_min, x_max, 2)<\/p>\n<p>y_coords = np.random.uniform(y_min, y_max, 2)<\/p>\n<h2><strong>\u6784\u5efa\u7ebf\u6bb5<\/strong><\/h2>\n<p>line_segment_np = list(zip(x_coords, y_coords))<\/p>\n<p>print(f&quot;\u4f7f\u7528numpy\u751f\u6210\u7684\u7ebf\u6bb5\u5750\u6807\u4e3a: {line_segment_np}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>3. \u53ef\u89c6\u5316\u7ebf\u6bb5<\/h3>\n<\/p>\n<p><p>\u540c\u6837\u4f7f\u7528<code>matplotlib<\/code>\u5e93\u6765\u7ed8\u5236<code>numpy<\/code>\u751f\u6210\u7684\u7ebf\u6bb5\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u63d0\u53d6\u5750\u6807<\/p>\n<p>x_values_np, y_values_np = zip(*line_segment_np)<\/p>\n<h2><strong>\u7ed8\u5236\u7ebf\u6bb5<\/strong><\/h2>\n<p>plt.plot(x_values_np, y_values_np, marker=&#39;o&#39;, color=&#39;r&#39;)<\/p>\n<p>plt.xlim(x_min, x_max)<\/p>\n<p>plt.ylim(y_min, y_max)<\/p>\n<p>plt.title(&quot;\u4f7f\u7528numpy\u751f\u6210\u7684\u968f\u673a\u7ebf\u6bb5&quot;)<\/p>\n<p>plt.xlabel(&quot;X\u5750\u6807&quot;)<\/p>\n<p>plt.ylabel(&quot;Y\u5750\u6807&quot;)<\/p>\n<p>plt.grid(True)<\/p>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h2>\u4e09\u3001\u751f\u6210\u591a\u6761\u968f\u673a\u7ebf\u6bb5<\/h2>\n<\/p>\n<p><p>\u5728\u5b9e\u8df5\u4e2d\uff0c\u6211\u4eec\u53ef\u80fd\u9700\u8981\u751f\u6210\u591a\u6761\u968f\u673a\u7ebf\u6bb5\u3002\u53ef\u4ee5\u901a\u8fc7\u5faa\u73af\u6765\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<p><h3>1. \u751f\u6210\u591a\u6761\u7ebf\u6bb5<\/h3>\n<\/p>\n<p><p>\u8bbe\u5b9a\u9700\u8981\u751f\u6210\u7684\u7ebf\u6bb5\u6570\u91cf\uff0c\u5229\u7528\u5faa\u73af\u751f\u6210\u591a\u6761\u7ebf\u6bb5\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">num_segments = 10  # \u9700\u8981\u751f\u6210\u7684\u7ebf\u6bb5\u6570\u91cf<\/p>\n<p>line_segments = []<\/p>\n<p>for _ in range(num_segments):<\/p>\n<p>    x1, y1 = random.uniform(x_min, x_max), random.uniform(y_min, y_max)<\/p>\n<p>    x2, y2 = random.uniform(x_min, x_max), random.uniform(y_min, y_max)<\/p>\n<p>    line_segments.append(((x1, y1), (x2, y2)))<\/p>\n<p>print(f&quot;\u751f\u6210\u7684\u591a\u6761\u7ebf\u6bb5\u5750\u6807\u4e3a: {line_segments}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2. \u53ef\u89c6\u5316\u591a\u6761\u7ebf\u6bb5<\/h3>\n<\/p>\n<p><p>\u4f7f\u7528<code>matplotlib<\/code>\u7ed8\u5236\u591a\u6761\u7ebf\u6bb5\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u7ed8\u5236\u591a\u6761\u7ebf\u6bb5<\/p>\n<p>plt.figure(figsize=(8, 8))<\/p>\n<p>for segment in line_segments:<\/p>\n<p>    x_values, y_values = zip(*segment)<\/p>\n<p>    plt.plot(x_values, y_values, marker=&#39;o&#39;)<\/p>\n<p>plt.xlim(x_min, x_max)<\/p>\n<p>plt.ylim(y_min, y_max)<\/p>\n<p>plt.title(&quot;\u591a\u6761\u968f\u673a\u751f\u6210\u7684\u7ebf\u6bb5&quot;)<\/p>\n<p>plt.xlabel(&quot;X\u5750\u6807&quot;)<\/p>\n<p>plt.ylabel(&quot;Y\u5750\u6807&quot;)<\/p>\n<p>plt.grid(True)<\/p>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h2>\u56db\u3001\u5e94\u7528\u573a\u666f\u4e0e\u4f18\u5316<\/h2>\n<\/p>\n<p><h3>1. \u5e94\u7528\u573a\u666f<\/h3>\n<\/p>\n<p><p>\u751f\u6210\u968f\u673a\u7ebf\u6bb5\u53ef\u4ee5\u5e94\u7528\u5728\u8ba1\u7b97\u673a\u89c6\u89c9\u3001\u56fe\u5f62\u5b66\u3001\u6e38\u620f\u5f00\u53d1\u7b49\u9886\u57df\u3002\u4f8b\u5982\uff0c\u5728\u6a21\u62df\u81ea\u7136\u73b0\u8c61\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528\u968f\u673a\u7ebf\u6bb5\u751f\u6210\u6811\u679d\u3001\u6cb3\u6d41\u7b49\uff1b\u5728\u6e38\u620f\u5f00\u53d1\u4e2d\uff0c\u53ef\u4ee5\u7528\u4e8e\u751f\u6210\u968f\u673a\u7684\u969c\u788d\u7269\u8def\u5f84\u3002<\/p>\n<\/p>\n<p><h3>2. \u4f18\u5316\u5efa\u8bae<\/h3>\n<\/p>\n<ul>\n<li><strong>\u63d0\u9ad8\u6548\u7387<\/strong>\uff1a\u5728\u751f\u6210\u5927\u91cf\u7ebf\u6bb5\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528<code>numpy<\/code>\u7684\u5411\u91cf\u5316\u64cd\u4f5c\uff0c\u63d0\u9ad8\u751f\u6210\u901f\u5ea6\u3002<\/li>\n<li><strong>\u907f\u514d\u91cd\u590d<\/strong>\uff1a\u5728\u67d0\u4e9b\u5e94\u7528\u573a\u666f\u4e2d\uff0c\u53ef\u80fd\u9700\u8981\u907f\u514d\u751f\u6210\u91cd\u590d\u7684\u7ebf\u6bb5\u3002\u53ef\u4ee5\u901a\u8fc7\u68c0\u67e5\u751f\u6210\u7684\u7ebf\u6bb5\u662f\u5426\u5df2\u7ecf\u5b58\u5728\u6765\u5b9e\u73b0\u3002<\/li>\n<li><strong>\u589e\u52a0\u7ea6\u675f<\/strong>\uff1a\u6709\u65f6\u9700\u8981\u751f\u6210\u5177\u6709\u7279\u5b9a\u7ea6\u675f\u7684\u7ebf\u6bb5\uff0c\u4f8b\u5982\u957f\u5ea6\u8303\u56f4\u3001\u7279\u5b9a\u65b9\u5411\u7b49\u3002\u53ef\u4ee5\u5728\u751f\u6210\u5750\u6807\u540e\u8ba1\u7b97\u7ebf\u6bb5\u957f\u5ea6\u6216\u65b9\u5411\uff0c\u5e76\u6839\u636e\u9700\u8981\u8fdb\u884c\u8c03\u6574\u3002<\/li>\n<\/ul>\n<p><p>\u4ee5\u4e0a\u662f\u5173\u4e8e\u5982\u4f55\u4f7f\u7528Python\u751f\u6210\u968f\u673a\u7ebf\u6bb5\u7684\u8be6\u7ec6\u4ecb\u7ecd\uff0c\u5305\u62ec\u4f7f\u7528<code>random<\/code>\u5e93\u548c<code>numpy<\/code>\u5e93\u7684\u65b9\u6cd5\uff0c\u4ee5\u53ca\u53ef\u89c6\u5316\u548c\u4f18\u5316\u7684\u5efa\u8bae\u3002\u901a\u8fc7\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u53ef\u4ee5\u7075\u6d3b\u5730\u751f\u6210\u548c\u5e94\u7528\u968f\u673a\u7ebf\u6bb5\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u751f\u6210\u968f\u673a\u7ebf\u6bb5\u7684\u5750\u6807\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528<code>random<\/code>\u6a21\u5757\u751f\u6210\u968f\u673a\u6570\u6765\u521b\u5efa\u7ebf\u6bb5\u7684\u5750\u6807\u3002\u9996\u5148\uff0c\u4f60\u9700\u8981\u5b9a\u4e49\u7ebf\u6bb5\u7684\u8d77\u70b9\u548c\u7ec8\u70b9\u7684\u5750\u6807\u3002\u4f8b\u5982\uff0c\u4f7f\u7528<code>random.uniform()<\/code>\u51fd\u6570\u53ef\u4ee5\u751f\u6210\u5728\u6307\u5b9a\u8303\u56f4\u5185\u7684\u968f\u673a\u6d6e\u70b9\u6570\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff1a  <\/p>\n<pre><code class=\"language-python\">import random\n\ndef generate_random_line_segment():\n    x1, y1 = random.uniform(0, 100), random.uniform(0, 100)\n    x2, y2 = random.uniform(0, 100), random.uniform(0, 100)\n    return (x1, y1), (x2, y2)\n\nline_segment = generate_random_line_segment()\nprint(&quot;\u968f\u673a\u7ebf\u6bb5\u7684\u5750\u6807:&quot;, line_segment)\n<\/code><\/pre>\n<p>\u8fd9\u4e2a\u4ee3\u7801\u7247\u6bb5\u5c06\u751f\u6210\u4e00\u4e2a\u968f\u673a\u7ebf\u6bb5\u7684\u8d77\u70b9\u548c\u7ec8\u70b9\u5750\u6807\u3002<\/p>\n<p><strong>\u5982\u4f55\u63a7\u5236\u751f\u6210\u7684\u968f\u673a\u7ebf\u6bb5\u7684\u957f\u5ea6\uff1f<\/strong><br \/>\u5982\u679c\u60f3\u8981\u63a7\u5236\u968f\u673a\u7ebf\u6bb5\u7684\u957f\u5ea6\uff0c\u53ef\u4ee5\u5728\u751f\u6210\u8d77\u70b9\u540e\uff0c\u8ba1\u7b97\u7ec8\u70b9\u7684\u5750\u6807\u3002\u9996\u5148\u9009\u62e9\u4e00\u4e2a\u968f\u673a\u89d2\u5ea6\uff0c\u7136\u540e\u6839\u636e\u6240\u9700\u7684\u957f\u5ea6\u8ba1\u7b97\u7ec8\u70b9\u7684\u5750\u6807\u3002\u4ee5\u4e0b\u662f\u5b9e\u73b0\u7684\u601d\u8def\uff1a  <\/p>\n<pre><code class=\"language-python\">import random\nimport math\n\ndef generate_random_line_segment_with_length(length):\n    angle = random.uniform(0, 2 * math.pi)  # \u968f\u673a\u9009\u62e9\u4e00\u4e2a\u89d2\u5ea6\n    x1, y1 = random.uniform(0, 100), random.uniform(0, 100)  # \u968f\u673a\u8d77\u70b9\n    x2 = x1 + length * math.cos(angle)\n    y2 = y1 + length * math.sin(angle)\n    return (x1, y1), (x2, y2)\n\nline_segment = generate_random_line_segment_with_length(50)\nprint(&quot;\u968f\u673a\u7ebf\u6bb5\u7684\u5750\u6807:&quot;, line_segment)\n<\/code><\/pre>\n<p>\u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u786e\u4fdd\u751f\u6210\u7684\u968f\u673a\u7ebf\u6bb5\u5177\u6709\u4f60\u6240\u8bbe\u5b9a\u7684\u957f\u5ea6\u3002<\/p>\n<p><strong>\u5982\u4f55\u5728Python\u4e2d\u53ef\u89c6\u5316\u751f\u6210\u7684\u968f\u673a\u7ebf\u6bb5\uff1f<\/strong><br \/>\u53ef\u89c6\u5316\u968f\u673a\u7ebf\u6bb5\u53ef\u4ee5\u4f7f\u7528<code>matplotlib<\/code>\u5e93\u3002\u901a\u8fc7\u7ed8\u5236\u7ebf\u6bb5\u7684\u8d77\u70b9\u548c\u7ec8\u70b9\uff0c\u53ef\u4ee5\u76f4\u89c2\u5730\u770b\u5230\u751f\u6210\u7684\u968f\u673a\u7ebf\u6bb5\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a  <\/p>\n<pre><code class=\"language-python\">import matplotlib.pyplot as plt\n\ndef plot_line_segment(line_segment):\n    (x1, y1), (x2, y2) = line_segment\n    plt.plot([x1, x2], [y1, y2], marker=&#39;o&#39;)\n    plt.xlim(0, 100)\n    plt.ylim(0, 100)\n    plt.title(&quot;\u968f\u673a\u7ebf\u6bb5\u53ef\u89c6\u5316&quot;)\n    plt.grid()\n    plt.show()\n\nline_segment = generate_random_line_segment()\nplot_line_segment(line_segment)\n<\/code><\/pre>\n<p>\u8fd0\u884c\u8fd9\u4e2a\u4ee3\u7801\u540e\uff0c\u53ef\u4ee5\u770b\u5230\u751f\u6210\u7684\u968f\u673a\u7ebf\u6bb5\u5728\u56fe\u5f62\u754c\u9762\u4e2d\u53ef\u89c6\u5316\u5c55\u793a\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u751f\u6210\u968f\u673a\u7ebf\u6bb5\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528\u968f\u673a\u6570\u751f\u6210\u5668\u751f\u6210\u5750\u6807\u3001\u5229\u7528numpy\u5e93\u751f\u6210\u968f\u673a\u6570\u7ec4\u3001\u5229\u7528matplot [&hellip;]","protected":false},"author":3,"featured_media":992173,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/992169"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=992169"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/992169\/revisions"}],"predecessor-version":[{"id":992176,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/992169\/revisions\/992176"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/992173"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=992169"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=992169"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=992169"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}