{"id":930124,"date":"2024-12-26T17:09:39","date_gmt":"2024-12-26T09:09:39","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/930124.html"},"modified":"2024-12-26T17:09:41","modified_gmt":"2024-12-26T09:09:41","slug":"python%e5%a6%82%e4%bd%95%e5%bc%95%e5%85%a5sqrt","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/930124.html","title":{"rendered":"Python\u5982\u4f55\u5f15\u5165sqrt"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25065026\/f9747279-9af2-4d72-925e-d5792fcd6ef1.webp\" alt=\"Python\u5982\u4f55\u5f15\u5165sqrt\" \/><\/p>\n<p><p> <strong>Python\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528<code>math<\/code>\u6a21\u5757\u4e2d\u7684<code>sqrt<\/code>\u51fd\u6570\u6765\u5f15\u5165\u5e73\u65b9\u6839\u51fd\u6570\u3001\u786e\u4fdd\u5728\u4ee3\u7801\u4e2d\u51c6\u786e\u65e0\u8bef\u5730\u6267\u884c\u6570\u5b66\u8ba1\u7b97\u3001\u53ef\u4ee5\u901a\u8fc7\u5bfc\u5165\u6574\u4e2a\u6a21\u5757\u6216\u4ec5\u5bfc\u5165\u7279\u5b9a\u51fd\u6570\u7684\u65b9\u5f0f\u8fdb\u884c\u3002<\/strong>\u5728Python\u4e2d\uff0c<code>math<\/code>\u6a21\u5757\u662f\u4e00\u4e2a\u6807\u51c6\u5e93\u6a21\u5757\uff0c\u5b83\u63d0\u4f9b\u4e86\u8bb8\u591a\u6709\u7528\u7684\u6570\u5b66\u51fd\u6570\u548c\u5e38\u6570\u3002<code>sqrt<\/code>\u51fd\u6570\u662f\u5176\u4e2d\u4e4b\u4e00\uff0c\u7528\u4e8e\u8ba1\u7b97\u4e00\u4e2a\u6570\u7684\u5e73\u65b9\u6839\u3002\u4f7f\u7528<code>sqrt<\/code>\u51fd\u6570\u53ef\u4ee5\u4f7f\u4ee3\u7801\u66f4\u6613\u8bfb\uff0c\u5e76\u51cf\u5c11\u7f16\u5199\u81ea\u5b9a\u4e49\u5e73\u65b9\u6839\u51fd\u6570\u7684\u9700\u6c42\u3002\u6b64\u5916\uff0c\u4f7f\u7528\u6807\u51c6\u5e93\u51fd\u6570\u901a\u5e38\u4f1a\u5e26\u6765\u6027\u80fd\u4e0a\u7684\u4f18\u52bf\uff0c\u56e0\u4e3a\u5b83\u4eec\u7ecf\u8fc7\u4f18\u5316\u5e76\u7528C\u8bed\u8a00\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<p><p>\u4e3a\u4e86\u5728Python\u4e2d\u4f7f\u7528<code>sqrt<\/code>\u51fd\u6570\uff0c\u4f60\u9996\u5148\u9700\u8981\u5bfc\u5165<code>math<\/code>\u6a21\u5757\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4e24\u79cd\u65b9\u5f0f\u6765\u5b9e\u73b0\uff1a\u7b2c\u4e00\u79cd\u662f\u76f4\u63a5\u5bfc\u5165\u6574\u4e2a<code>math<\/code>\u6a21\u5757\uff0c\u7136\u540e\u901a\u8fc7<code>math.sqrt()<\/code>\u6765\u8c03\u7528\u51fd\u6570\uff1b\u7b2c\u4e8c\u79cd\u662f\u4ec5\u5bfc\u5165<code>sqrt<\/code>\u51fd\u6570\uff0c\u8fd9\u6837\u53ef\u4ee5\u76f4\u63a5\u4f7f\u7528<code>sqrt()<\/code>\u8fdb\u884c\u8c03\u7528\u3002<\/p>\n<\/p>\n<p><p>\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528\u8fd9\u4e24\u79cd\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import math<\/p>\n<h2><strong>\u4f7f\u7528\u6574\u4e2a\u6a21\u5757<\/strong><\/h2>\n<p>result = math.sqrt(16)<\/p>\n<p>print(&quot;The square root of 16 is:&quot;, result)<\/p>\n<h2><strong>\u6216\u8005<\/strong><\/h2>\n<p>from math import sqrt<\/p>\n<h2><strong>\u76f4\u63a5\u4f7f\u7528\u51fd\u6570<\/strong><\/h2>\n<p>result = sqrt(16)<\/p>\n<p>print(&quot;The square root of 16 is:&quot;, result)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4e00\u3001MATH\u6a21\u5757\u7684\u5f15\u5165\u4e0e\u4f7f\u7528<\/p>\n<\/p>\n<p><p>\u5728Python\u7f16\u7a0b\u4e2d\uff0c<code>math<\/code>\u6a21\u5757\u662f\u4e00\u4e2a\u975e\u5e38\u91cd\u8981\u7684\u5de5\u5177\u3002\u5b83\u63d0\u4f9b\u4e86\u8bb8\u591a\u6570\u5b66\u51fd\u6570\u548c\u5e38\u6570\uff0c\u4f7f\u5f97\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u8fdb\u884c\u5404\u79cd\u6570\u5b66\u8ba1\u7b97\u3002\u5bf9\u4e8e\u5e73\u65b9\u6839\u8ba1\u7b97\uff0c<code>math<\/code>\u6a21\u5757\u4e2d\u7684<code>sqrt<\/code>\u51fd\u6570\u662f\u4e00\u4e2a\u9ad8\u6548\u4e14\u6613\u4e8e\u4f7f\u7528\u7684\u9009\u62e9\u3002\u4e86\u89e3\u5982\u4f55\u6b63\u786e\u5730\u5bfc\u5165\u548c\u4f7f\u7528<code>math<\/code>\u6a21\u5757\u4e0d\u4ec5\u80fd\u63d0\u5347\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\uff0c\u8fd8\u80fd\u63d0\u9ad8\u7a0b\u5e8f\u7684\u6267\u884c\u6548\u7387\u3002<\/p>\n<\/p>\n<ol>\n<li><code>MATH<\/code>\u6a21\u5757\u7684\u5bfc\u5165\u65b9\u6cd5<\/li>\n<\/ol>\n<p><p>\u5728\u4f7f\u7528<code>math<\/code>\u6a21\u5757\u4e2d\u7684\u51fd\u6570\u4e4b\u524d\uff0c\u5fc5\u987b\u5148\u5bfc\u5165\u8be5\u6a21\u5757\u3002Python\u63d0\u4f9b\u4e86\u591a\u79cd\u5bfc\u5165\u6a21\u5757\u7684\u65b9\u6cd5\uff0c\u6839\u636e\u9700\u6c42\u7684\u4e0d\u540c\uff0c\u53ef\u4ee5\u9009\u62e9\u6700\u5408\u9002\u7684\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<ul>\n<li>\n<p><strong>\u5bfc\u5165\u6574\u4e2a\u6a21\u5757<\/strong>\uff1a\u8fd9\u662f\u6700\u5e38\u89c1\u7684\u5bfc\u5165\u65b9\u5f0f\uff0c\u80fd\u591f\u8bbf\u95ee<code>math<\/code>\u6a21\u5757\u4e2d\u7684\u6240\u6709\u51fd\u6570\u548c\u5e38\u6570\u3002\u4f7f\u7528\u65f6\u9700\u8981\u5728\u51fd\u6570\u540d\u524d\u52a0\u4e0a\u6a21\u5757\u540d\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import math<\/p>\n<p>result = math.sqrt(25)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u5bfc\u5165\u7279\u5b9a\u51fd\u6570<\/strong>\uff1a\u5982\u679c\u53ea\u9700\u8981\u4f7f\u7528<code>math<\/code>\u6a21\u5757\u4e2d\u7684\u67d0\u4e00\u4e2a\u6216\u51e0\u4e2a\u51fd\u6570\uff0c\u53ef\u4ee5\u9009\u62e9\u53ea\u5bfc\u5165\u8fd9\u4e9b\u51fd\u6570\u3002\u8fd9\u79cd\u65b9\u5f0f\u4f7f\u4ee3\u7801\u66f4\u7b80\u6d01\uff0c\u5e76\u907f\u514d\u547d\u540d\u51b2\u7a81\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from math import sqrt<\/p>\n<p>result = sqrt(25)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u5bfc\u5165\u5e76\u91cd\u547d\u540d\u6a21\u5757<\/strong>\uff1a\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u4e3a\u4e86\u7b80\u5316\u8c03\u7528\u6216\u907f\u514d\u4e0e\u5176\u4ed6\u6a21\u5757\u51b2\u7a81\uff0c\u53ef\u4ee5\u5728\u5bfc\u5165\u65f6\u4e3a\u6a21\u5757\u6307\u5b9a\u4e00\u4e2a\u522b\u540d\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import math as m<\/p>\n<p>result = m.sqrt(25)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n<ol start=\"2\">\n<li><code>MATH<\/code>\u6a21\u5757\u4e2d\u7684\u5176\u4ed6\u5e38\u7528\u51fd\u6570<\/li>\n<\/ol>\n<p><p>\u9664\u4e86<code>sqrt<\/code>\u51fd\u6570\uff0c<code>math<\/code>\u6a21\u5757\u8fd8\u63d0\u4f9b\u4e86\u8bb8\u591a\u5176\u4ed6\u6709\u7528\u7684\u6570\u5b66\u51fd\u6570\u548c\u5e38\u6570\u3002\u4e86\u89e3\u8fd9\u4e9b\u51fd\u6570\u6709\u52a9\u4e8e\u6211\u4eec\u5728\u7f16\u7a0b\u65f6\u66f4\u9ad8\u6548\u5730\u89e3\u51b3\u95ee\u9898\u3002<\/p>\n<\/p>\n<ul>\n<li>\n<p><strong><code>pow(x, y)<\/code><\/strong>\uff1a\u8ba1\u7b97x\u7684y\u6b21\u5e42\uff0c\u76f8\u5f53\u4e8exy\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">result = math.pow(3, 2)  # \u7ed3\u679c\u4e3a9.0<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong><code>ceil(x)<\/code><\/strong>\uff1a\u8fd4\u56de\u5927\u4e8e\u6216\u7b49\u4e8ex\u7684\u6700\u5c0f\u6574\u6570\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">result = math.ceil(4.2)  # \u7ed3\u679c\u4e3a5<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong><code>floor(x)<\/code><\/strong>\uff1a\u8fd4\u56de\u5c0f\u4e8e\u6216\u7b49\u4e8ex\u7684\u6700\u5927\u6574\u6570\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">result = math.floor(4.8)  # \u7ed3\u679c\u4e3a4<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong><code>pi<\/code>\u548c<code>e<\/code><\/strong>\uff1a\u6570\u5b66\u5e38\u6570\u03c0\u548ce\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">print(math.pi)  # \u8f93\u51fa3.141592653589793<\/p>\n<p>print(math.e)   # \u8f93\u51fa2.718281828459045<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong><code>log(x[, base])<\/code><\/strong>\uff1a\u8ba1\u7b97\u4ee5base\u4e3a\u5e95\u7684x\u7684\u5bf9\u6570\uff0c\u9ed8\u8ba4\u5e95\u4e3ae\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">result = math.log(10, 10)  # \u7ed3\u679c\u4e3a1.0<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n<p><p>\u901a\u8fc7\u719f\u7ec3\u638c\u63e1<code>math<\/code>\u6a21\u5757\u7684\u4f7f\u7528\uff0c\u53ef\u4ee5\u5927\u5927\u63d0\u9ad8Python\u7f16\u7a0b\u4e2d\u6570\u5b66\u8fd0\u7b97\u7684\u6548\u7387\u548c\u51c6\u786e\u6027\u3002<\/p>\n<\/p>\n<p><p>\u4e8c\u3001\u5e73\u65b9\u6839\u51fd\u6570\u7684\u6df1\u5165\u7406\u89e3<\/p>\n<\/p>\n<p><p>\u5e73\u65b9\u6839\u662f\u6570\u5b66\u4e2d\u7684\u4e00\u4e2a\u91cd\u8981\u6982\u5ff5\uff0c\u5728\u8bb8\u591a\u79d1\u5b66\u8ba1\u7b97\u3001\u5de5\u7a0b\u5e94\u7528\u548c\u65e5\u5e38\u751f\u6d3b\u4e2d\u90fd\u6709\u5e7f\u6cdb\u7684\u5e94\u7528\u3002\u5728Python\u4e2d\uff0c\u8ba1\u7b97\u5e73\u65b9\u6839\u7684\u65b9\u6cd5\u975e\u5e38\u7b80\u5355\uff0c\u53ea\u9700\u8981\u4f7f\u7528<code>math<\/code>\u6a21\u5757\u4e2d\u7684<code>sqrt<\/code>\u51fd\u6570\u5373\u53ef\u3002\u4e3a\u4e86\u66f4\u597d\u5730\u7406\u89e3\u8fd9\u4e00\u51fd\u6570\u7684\u5de5\u4f5c\u539f\u7406\uff0c\u6211\u4eec\u9700\u8981\u6df1\u5165\u63a2\u8ba8\u5176\u5b9e\u73b0\u673a\u5236\u548c\u5e94\u7528\u573a\u666f\u3002<\/p>\n<\/p>\n<ol>\n<li><code>SQRT<\/code>\u51fd\u6570\u7684\u57fa\u672c\u539f\u7406<\/li>\n<\/ol>\n<p><p><code>sqrt<\/code>\u51fd\u6570\u7528\u4e8e\u8ba1\u7b97\u4e00\u4e2a\u6570\u7684\u5e73\u65b9\u6839\uff0c\u5373\u6c42\u89e3\u4e00\u4e2a\u6570\u7684\u4e8c\u6b21\u65b9\u4e3a\u7ed9\u5b9a\u503c\u7684\u539f\u6570\u3002\u5e73\u65b9\u6839\u901a\u5e38\u7528\u4e8e\u51e0\u4f55\u8ba1\u7b97\u3001\u7269\u7406\u516c\u5f0f\u3001\u7edf\u8ba1\u5206\u6790\u7b49\u591a\u4e2a\u9886\u57df\u3002<\/p>\n<\/p>\n<ul>\n<li>\n<p><strong>\u6570\u5b66\u5b9a\u4e49<\/strong>\uff1a\u5bf9\u4e8e\u975e\u8d1f\u5b9e\u6570x\uff0c\u5176\u5e73\u65b9\u6839\u662f\u6ee1\u8db3y\u00b2 = x\u7684\u975e\u8d1f\u6570y\u3002\u5e73\u65b9\u6839\u7684\u7b26\u53f7\u4e3a\u221a\uff0c\u4f8b\u5982\uff0c\u221a9 = 3\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u8ba1\u7b97\u590d\u6742\u6027<\/strong>\uff1a\u8ba1\u7b97\u5e73\u65b9\u6839\u5728\u6570\u5b66\u4e0a\u5c5e\u4e8e\u6c42\u89e3\u65b9\u7a0b\u7684\u95ee\u9898\u3002\u5bf9\u4e8e\u8ba1\u7b97\u673a\u800c\u8a00\uff0c\u5b9e\u73b0\u9ad8\u6548\u7684\u5e73\u65b9\u6839\u8ba1\u7b97\u901a\u5e38\u9700\u8981\u4f7f\u7528\u4f18\u5316\u7684\u7b97\u6cd5\uff0c\u5982\u725b\u987f\u6cd5\u6216\u4e8c\u8fdb\u5236\u641c\u7d22\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>Python\u5b9e\u73b0<\/strong>\uff1aPython\u7684<code>sqrt<\/code>\u51fd\u6570\u662f\u7528C\u8bed\u8a00\u5b9e\u73b0\u7684\uff0c\u7ecf\u8fc7\u9ad8\u5ea6\u4f18\u5316\uff0c\u80fd\u591f\u5feb\u901f\u5730\u8ba1\u7b97\u5e73\u65b9\u6839\u3002\u7531\u4e8ePython\u7684\u52a8\u6001\u7279\u6027\uff0c<code>sqrt<\/code>\u51fd\u6570\u53ef\u4ee5\u5904\u7406\u6574\u6570\u548c\u6d6e\u70b9\u6570\u3002<\/p>\n<\/p>\n<\/li>\n<\/ul>\n<ol start=\"2\">\n<li><code>SQRT<\/code>\u51fd\u6570\u7684\u5e38\u89c1\u5e94\u7528\u573a\u666f<\/li>\n<\/ol>\n<p><p>\u5e73\u65b9\u6839\u51fd\u6570\u5728\u8bb8\u591a\u5b9e\u9645\u95ee\u9898\u4e2d\u90fd\u6709\u5e94\u7528\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u5e94\u7528\u573a\u666f\u3002<\/p>\n<\/p>\n<ul>\n<li>\n<p><strong>\u51e0\u4f55\u8ba1\u7b97<\/strong>\uff1a\u5728\u51e0\u4f55\u56fe\u5f62\u4e2d\uff0c\u5e73\u65b9\u6839\u5e38\u7528\u4e8e\u8ba1\u7b97\u8ddd\u79bb\u3001\u9762\u79ef\u548c\u4f53\u79ef\u3002\u4f8b\u5982\uff0c\u8ba1\u7b97\u4e24\u70b9\u4e4b\u95f4\u7684\u6b27\u51e0\u91cc\u5f97\u8ddd\u79bb\u9700\u8981\u7528\u5230\u5e73\u65b9\u6839\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import math<\/p>\n<p>x1, y1 = 1, 2<\/p>\n<p>x2, y2 = 4, 6<\/p>\n<p>distance = math.sqrt((x2 - x1)&lt;strong&gt;2 + (y2 - y1)&lt;\/strong&gt;2)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u7269\u7406\u516c\u5f0f<\/strong>\uff1a\u5728\u7269\u7406\u5b66\u4e2d\uff0c\u8bb8\u591a\u516c\u5f0f\u6d89\u53ca\u5e73\u65b9\u6839\u3002\u4f8b\u5982\uff0c\u8ba1\u7b97\u81ea\u7531\u843d\u4f53\u8fd0\u52a8\u7684\u901f\u5ea6\u3001\u6ce2\u52a8\u65b9\u7a0b\u4e2d\u7684\u9891\u7387\u7b49\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">velocity = math.sqrt(2 * gravity * height)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u7edf\u8ba1\u5206\u6790<\/strong>\uff1a\u5728\u7edf\u8ba1\u5b66\u4e2d\uff0c\u6807\u51c6\u5dee\u548c\u65b9\u5dee\u7684\u8ba1\u7b97\u901a\u5e38\u9700\u8981\u7528\u5230\u5e73\u65b9\u6839\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p>data = [1, 2, 3, 4, 5]<\/p>\n<p>std_dev = np.std(data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u91d1\u878d\u8ba1\u7b97<\/strong>\uff1a\u5728\u91d1\u878d\u9886\u57df\uff0c\u5e73\u65b9\u6839\u5e38\u7528\u4e8e\u8ba1\u7b97\u6ce2\u52a8\u7387\u3001\u98ce\u9669\u8bc4\u4f30\u7b49\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">volatility = math.sqrt(np.var(stock_returns))<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n<p><p>\u901a\u8fc7\u638c\u63e1<code>sqrt<\/code>\u51fd\u6570\u7684\u539f\u7406\u548c\u5e94\u7528\uff0c\u53ef\u4ee5\u66f4\u597d\u5730\u89e3\u51b3\u5b9e\u9645\u95ee\u9898\uff0c\u63d0\u9ad8\u4ee3\u7801\u7684\u51c6\u786e\u6027\u548c\u6548\u7387\u3002<\/p>\n<\/p>\n<p><p>\u4e09\u3001\u5e73\u65b9\u6839\u8ba1\u7b97\u7684\u9ad8\u7ea7\u6280\u5de7<\/p>\n<\/p>\n<p><p>\u5728Python\u4e2d\u4f7f\u7528\u5e73\u65b9\u6839\u8ba1\u7b97\u4e0d\u4ec5\u9650\u4e8e\u57fa\u7840\u5e94\u7528\uff0c\u8fd8\u53ef\u4ee5\u901a\u8fc7\u4e00\u4e9b\u9ad8\u7ea7\u6280\u5de7\u548c\u65b9\u6cd5\u6765\u63d0\u5347\u8ba1\u7b97\u7684\u6548\u7387\u548c\u7cbe\u5ea6\u3002\u8fd9\u5bf9\u4e8e\u9700\u8981\u5904\u7406\u5927\u91cf\u6570\u636e\u6216\u8fdb\u884c\u590d\u6742\u8fd0\u7b97\u7684\u573a\u666f\u5c24\u4e3a\u91cd\u8981\u3002\u4e0b\u9762\u4ecb\u7ecd\u4e00\u4e9b\u63d0\u9ad8\u5e73\u65b9\u6839\u8ba1\u7b97\u6548\u7387\u7684\u9ad8\u7ea7\u6280\u5de7\u3002<\/p>\n<\/p>\n<ol>\n<li>\u5411\u91cf\u5316\u8ba1\u7b97<\/li>\n<\/ol>\n<p><p>\u5411\u91cf\u5316\u8ba1\u7b97\u662f\u4e00\u79cd\u901a\u8fc7\u5c06\u591a\u4e2a\u6570\u636e\u70b9\u7ec4\u5408\u6210\u5411\u91cf\u8fdb\u884c\u4e00\u6b21\u6027\u8ba1\u7b97\u7684\u65b9\u6cd5\u3002\u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u5927\u5927\u63d0\u9ad8\u8ba1\u7b97\u6548\u7387\uff0c\u5c24\u5176\u662f\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u65f6\u3002Python\u4e2d\u7684<code>numpy<\/code>\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u5411\u91cf\u5316\u529f\u80fd\uff0c\u4f7f\u5f97\u6211\u4eec\u53ef\u4ee5\u9ad8\u6548\u5730\u8fdb\u884c\u5e73\u65b9\u6839\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<ul>\n<li>\n<p><strong>\u4f7f\u7528<code>numpy.sqrt<\/code><\/strong>\uff1a<code>numpy<\/code>\u5e93\u4e2d\u7684<code>sqrt<\/code>\u51fd\u6570\u5141\u8bb8\u5bf9\u6570\u7ec4\u8fdb\u884c\u5143\u7d20\u7ea7\u522b\u7684\u5e73\u65b9\u6839\u8ba1\u7b97\u3002\u8fd9\u79cd\u65b9\u5f0f\u6bd4\u901a\u8fc7\u5faa\u73af\u9010\u4e2a\u8ba1\u7b97\u8981\u5feb\u5f97\u591a\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p>data = np.array([1, 4, 9, 16, 25])<\/p>\n<p>result = np.sqrt(data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n<ol start=\"2\">\n<li>\u81ea\u5b9a\u4e49\u5e73\u65b9\u6839\u7b97\u6cd5<\/li>\n<\/ol>\n<p><p>\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u6807\u51c6\u5e93\u7684<code>sqrt<\/code>\u51fd\u6570\u53ef\u80fd\u65e0\u6cd5\u6ee1\u8db3\u7279\u5b9a\u9700\u6c42\uff0c\u6216\u8005\u9700\u8981\u5728\u53d7\u9650\u73af\u5883\u4e0b\u5b9e\u73b0\u5e73\u65b9\u6839\u8ba1\u7b97\u3002\u8fd9\u65f6\u53ef\u4ee5\u8003\u8651\u5b9e\u73b0\u81ea\u5b9a\u4e49\u7684\u5e73\u65b9\u6839\u7b97\u6cd5\u3002<\/p>\n<\/p>\n<ul>\n<li>\n<p><strong>\u725b\u987f\u6cd5<\/strong>\uff1a\u725b\u987f\u6cd5\u662f\u4e00\u79cd\u5e38\u7528\u7684\u8fed\u4ee3\u7b97\u6cd5\uff0c\u7528\u4e8e\u903c\u8fd1\u5e73\u65b9\u6839\u3002\u8be5\u65b9\u6cd5\u901a\u8fc7\u4e0d\u65ad\u66f4\u65b0\u4f30\u8ba1\u503c\u6765\u63a5\u8fd1\u5b9e\u9645\u7684\u5e73\u65b9\u6839\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def newton_sqrt(number, tolerance=1e-10):<\/p>\n<p>    estimate = number \/ 2.0<\/p>\n<p>    while True:<\/p>\n<p>        better_estimate = (estimate + number \/ estimate) \/ 2.0<\/p>\n<p>        if abs(estimate - better_estimate) &lt; tolerance:<\/p>\n<p>            return better_estimate<\/p>\n<p>        estimate = better_estimate<\/p>\n<p>result = newton_sqrt(16)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u4e8c\u5206\u67e5\u627e\u6cd5<\/strong>\uff1a\u4e8c\u5206\u67e5\u627e\u6cd5\u662f\u4e00\u79cd\u57fa\u4e8e\u5206\u6cbb\u601d\u60f3\u7684\u7b97\u6cd5\uff0c\u901a\u8fc7\u4e0d\u65ad\u7f29\u5c0f\u641c\u7d22\u8303\u56f4\u6765\u903c\u8fd1\u5e73\u65b9\u6839\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def binary_search_sqrt(number, tolerance=1e-10):<\/p>\n<p>    low, high = 0, number<\/p>\n<p>    while high - low &gt; tolerance:<\/p>\n<p>        mid = (low + high) \/ 2.0<\/p>\n<p>        if mid * mid &lt; number:<\/p>\n<p>            low = mid<\/p>\n<p>        else:<\/p>\n<p>            high = mid<\/p>\n<p>    return (low + high) \/ 2.0<\/p>\n<p>result = binary_search_sqrt(16)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n<ol start=\"3\">\n<li>\u7cbe\u5ea6\u4e0e\u6027\u80fd\u7684\u6743\u8861<\/li>\n<\/ol>\n<p><p>\u5728\u8fdb\u884c\u5e73\u65b9\u6839\u8ba1\u7b97\u65f6\uff0c\u901a\u5e38\u9700\u8981\u5728\u8ba1\u7b97\u7cbe\u5ea6\u548c\u6027\u80fd\u4e4b\u95f4\u8fdb\u884c\u6743\u8861\u3002\u9ad8\u7cbe\u5ea6\u8ba1\u7b97\u901a\u5e38\u9700\u8981\u66f4\u591a\u7684\u8ba1\u7b97\u8d44\u6e90\uff0c\u800c\u9ad8\u6027\u80fd\u8ba1\u7b97\u53ef\u80fd\u4f1a\u727a\u7272\u4e00\u4e9b\u7cbe\u5ea6\u3002\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u7b97\u6cd5\u548c\u7cbe\u5ea6\u8bbe\u7f6e\uff0c\u80fd\u591f\u8fbe\u5230\u6700\u4f73\u6548\u679c\u3002<\/p>\n<\/p>\n<ul>\n<li>\n<p><strong>\u8c03\u6574\u7cbe\u5ea6<\/strong>\uff1a\u5728\u81ea\u5b9a\u4e49\u7b97\u6cd5\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u8c03\u6574\u5bb9\u5dee\u53c2\u6570\u6765\u63a7\u5236\u8ba1\u7b97\u7cbe\u5ea6\u3002\u8f83\u5c0f\u7684\u5bb9\u5dee\u901a\u5e38\u4f1a\u5e26\u6765\u66f4\u9ad8\u7684\u7cbe\u5ea6\uff0c\u4f46\u9700\u8981\u66f4\u591a\u7684\u8ba1\u7b97\u8fed\u4ee3\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u4f18\u5316\u6027\u80fd<\/strong>\uff1a\u5bf9\u4e8e\u5927\u89c4\u6a21\u8ba1\u7b97\u4efb\u52a1\uff0c\u53ef\u4ee5\u8003\u8651\u4f7f\u7528\u5e76\u884c\u8ba1\u7b97\u6280\u672f\uff0c\u5982\u591a\u7ebf\u7a0b\u6216\u591a\u8fdb\u7a0b\uff0c\u6765\u63d0\u9ad8\u8ba1\u7b97\u6548\u7387\u3002<\/p>\n<\/p>\n<\/li>\n<\/ul>\n<p><p>\u901a\u8fc7\u8fd9\u4e9b\u9ad8\u7ea7\u6280\u5de7\uff0c\u53ef\u4ee5\u5728\u4e0d\u540c\u573a\u666f\u4e0b\u7075\u6d3b\u5e94\u7528\u5e73\u65b9\u6839\u8ba1\u7b97\uff0c\u6ee1\u8db3\u4e0d\u540c\u7684\u6027\u80fd\u548c\u7cbe\u5ea6\u9700\u6c42\u3002<\/p>\n<\/p>\n<p><p>\u56db\u3001\u5e73\u65b9\u6839\u7684\u5e94\u7528\u5b9e\u4f8b<\/p>\n<\/p>\n<p><p>\u5e73\u65b9\u6839\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u6709\u7740\u5e7f\u6cdb\u7684\u7528\u9014\uff0c\u4ece\u79d1\u5b66\u8ba1\u7b97\u5230\u65e5\u5e38\u751f\u6d3b\uff0c\u5e73\u65b9\u6839\u7684\u8ba1\u7b97\u5e38\u5e38\u6210\u4e3a\u89e3\u51b3\u95ee\u9898\u7684\u5173\u952e\u6b65\u9aa4\u3002\u5728\u8fd9\u4e00\u90e8\u5206\uff0c\u6211\u4eec\u5c06\u901a\u8fc7\u51e0\u4e2a\u5177\u4f53\u7684\u5e94\u7528\u5b9e\u4f8b\u6765\u5c55\u793a\u5e73\u65b9\u6839\u8ba1\u7b97\u7684\u5b9e\u9645\u5e94\u7528\u3002<\/p>\n<\/p>\n<ol>\n<li>\u56fe\u50cf\u5904\u7406\u4e2d\u7684\u5e94\u7528<\/li>\n<\/ol>\n<p><p>\u5728\u56fe\u50cf\u5904\u7406\u9886\u57df\uff0c\u5e73\u65b9\u6839\u5e38\u7528\u4e8e\u8ba1\u7b97\u50cf\u7d20\u4e4b\u95f4\u7684\u8ddd\u79bb\u3001\u56fe\u50cf\u7684\u4eae\u5ea6\u7b49\u3002\u4f8b\u5982\uff0c\u5728\u56fe\u50cf\u9510\u5316\u3001\u8fb9\u7f18\u68c0\u6d4b\u7b49\u64cd\u4f5c\u4e2d\uff0c\u5e38\u5e38\u9700\u8981\u7528\u5230\u5e73\u65b9\u6839\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<ul>\n<li>\n<p><strong>\u56fe\u50cf\u9510\u5316<\/strong>\uff1a\u5728\u9510\u5316\u56fe\u50cf\u65f6\uff0c\u9700\u8981\u8ba1\u7b97\u50cf\u7d20\u68af\u5ea6\u7684\u5e45\u503c\uff0c\u8fd9\u901a\u5e38\u6d89\u53ca\u5e73\u65b9\u6839\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p>from scipy.ndimage import sobel<\/p>\n<p>def sharpen_image(image):<\/p>\n<p>    dx = sobel(image, axis=0)<\/p>\n<p>    dy = sobel(image, axis=1)<\/p>\n<p>    gradient_magnitude = np.sqrt(dx&lt;strong&gt;2 + dy&lt;\/strong&gt;2)<\/p>\n<p>    return gradient_magnitude<\/p>\n<h2><strong>\u793a\u4f8b\u56fe\u50cf\u5904\u7406<\/strong><\/h2>\n<p>image = np.random.rand(256, 256)<\/p>\n<p>sharpened_image = sharpen_image(image)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n<ol start=\"2\">\n<li>\u6570\u636e\u79d1\u5b66\u4e2d\u7684\u5e94\u7528<\/li>\n<\/ol>\n<p><p>\u5728\u6570\u636e\u79d1\u5b66\u4e2d\uff0c\u5e73\u65b9\u6839\u5e38\u7528\u4e8e\u6807\u51c6\u5dee\u3001\u5747\u65b9\u8bef\u5dee\u7b49\u7edf\u8ba1\u91cf\u7684\u8ba1\u7b97\u3002\u8fd9\u4e9b\u7edf\u8ba1\u91cf\u80fd\u591f\u5e2e\u52a9\u6211\u4eec\u4e86\u89e3\u6570\u636e\u7684\u5206\u5e03\u548c\u8bef\u5dee\u3002<\/p>\n<\/p>\n<ul>\n<li>\n<p><strong>\u6807\u51c6\u5dee\u8ba1\u7b97<\/strong>\uff1a\u6807\u51c6\u5dee\u662f\u8861\u91cf\u6570\u636e\u5206\u6563\u7a0b\u5ea6\u7684\u6307\u6807\uff0c\u5e73\u65b9\u6839\u5728\u8ba1\u7b97\u6807\u51c6\u5dee\u65f6\u626e\u6f14\u7740\u91cd\u8981\u89d2\u8272\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p>data = [10, 12, 23, 23, 16, 23, 21, 16]<\/p>\n<p>mean = np.mean(data)<\/p>\n<p>variance = np.mean((data - mean)2)<\/p>\n<p>std_deviation = np.sqrt(variance)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u5747\u65b9\u8bef\u5dee<\/strong>\uff1a\u5747\u65b9\u8bef\u5dee\u7528\u4e8e\u8861\u91cf\u9884\u6d4b\u503c\u4e0e\u771f\u5b9e\u503c\u4e4b\u95f4\u7684\u5dee\u5f02\uff0c\u662f<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u6a21\u578b\u8bc4\u4f30\u7684\u91cd\u8981\u6307\u6807\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def mean_squared_error(y_true, y_pred):<\/p>\n<p>    return np.mean((y_true - y_pred)  2)<\/p>\n<p>def root_mean_squared_error(y_true, y_pred):<\/p>\n<p>    return np.sqrt(mean_squared_error(y_true, y_pred))<\/p>\n<h2><strong>\u793a\u4f8b\u6570\u636e<\/strong><\/h2>\n<p>y_true = [3, -0.5, 2, 7]<\/p>\n<p>y_pred = [2.5, 0.0, 2, 8]<\/p>\n<p>rmse = root_mean_squared_error(y_true, y_pred)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n<ol start=\"3\">\n<li>\u5de5\u7a0b\u8ba1\u7b97\u4e2d\u7684\u5e94\u7528<\/li>\n<\/ol>\n<p><p>\u5728\u5de5\u7a0b\u9886\u57df\uff0c\u5e73\u65b9\u6839\u5e38\u7528\u4e8e\u8ba1\u7b97\u7ed3\u6784\u7684\u5e94\u529b\u3001\u632f\u52a8\u9891\u7387\u7b49\u3002\u5728\u8fd9\u4e9b\u8ba1\u7b97\u4e2d\uff0c\u51c6\u786e\u7684\u5e73\u65b9\u6839\u8ba1\u7b97\u662f\u786e\u4fdd\u5de5\u7a0b\u8bbe\u8ba1\u5b89\u5168\u7684\u91cd\u8981\u56e0\u7d20\u3002<\/p>\n<\/p>\n<ul>\n<li>\n<p><strong>\u7ed3\u6784\u5e94\u529b\u8ba1\u7b97<\/strong>\uff1a\u5728\u5de5\u7a0b\u8bbe\u8ba1\u4e2d\uff0c\u7ed3\u6784\u5e94\u529b\u7684\u8ba1\u7b97\u6d89\u53ca\u5e73\u65b9\u6839\u7684\u5e94\u7528\uff0c\u4ee5\u786e\u4fdd\u7ed3\u6784\u7684\u7a33\u5b9a\u6027\u548c\u5b89\u5168\u6027\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def calculate_stress(force, area):<\/p>\n<p>    return force \/ area<\/p>\n<p>def calculate_von_mises_stress(sigma_x, sigma_y, tau_xy):<\/p>\n<p>    return np.sqrt(sigma_x&lt;strong&gt;2 + sigma_y&lt;\/strong&gt;2 - sigma_x * sigma_y + 3 * tau_xy2)<\/p>\n<h2><strong>\u793a\u4f8b\u5de5\u7a0b\u8ba1\u7b97<\/strong><\/h2>\n<p>sigma_x = 100<\/p>\n<p>sigma_y = 80<\/p>\n<p>tau_xy = 30<\/p>\n<p>von_mises_stress = calculate_von_mises_stress(sigma_x, sigma_y, tau_xy)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n<p><p>\u901a\u8fc7\u8fd9\u4e9b\u5b9e\u4f8b\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u5e73\u65b9\u6839\u8ba1\u7b97\u5728\u4e0d\u540c\u9886\u57df\u7684\u5e7f\u6cdb\u5e94\u7528\u3002\u638c\u63e1\u5e73\u65b9\u6839\u7684\u8ba1\u7b97\u6280\u5de7\u548c\u5e94\u7528\u573a\u666f\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u66f4\u597d\u5730\u89e3\u51b3\u5b9e\u9645\u95ee\u9898\uff0c\u63d0\u9ad8\u5de5\u4f5c\u6548\u7387\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u5bfc\u5165sqrt\u51fd\u6570\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u5bfc\u5165math\u6a21\u5757\u6765\u4f7f\u7528sqrt\u51fd\u6570\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5b9e\u73b0\uff1a  <\/p>\n<pre><code class=\"language-python\">import math\nresult = math.sqrt(16)\nprint(result)  # \u8f93\u51fa: 4.0\n<\/code><\/pre>\n<p>\u8fd9\u6837\u5c31\u80fd\u4f7f\u7528math\u6a21\u5757\u4e2d\u7684sqrt\u51fd\u6570\u6765\u8ba1\u7b97\u5e73\u65b9\u6839\u3002<\/p>\n<p><strong>\u4f7f\u7528sqrt\u51fd\u6570\u65f6\u9700\u8981\u6ce8\u610f\u54ea\u4e9b\u4e8b\u9879\uff1f<\/strong><br \/>\u4f7f\u7528sqrt\u51fd\u6570\u65f6\uff0c\u9700\u8981\u786e\u4fdd\u8f93\u5165\u503c\u4e3a\u975e\u8d1f\u6570\u3002\u5982\u679c\u8f93\u5165\u8d1f\u6570\uff0c\u7a0b\u5e8f\u5c06\u629b\u51faValueError\u5f02\u5e38\u3002\u4e3a\u4e86\u907f\u514d\u8fd9\u79cd\u60c5\u51b5\uff0c\u53ef\u4ee5\u5728\u8c03\u7528sqrt\u4e4b\u524d\u68c0\u67e5\u8f93\u5165\u662f\u5426\u5927\u4e8e\u6216\u7b49\u4e8e\u96f6\u3002\u4f8b\u5982\uff1a  <\/p>\n<pre><code class=\"language-python\">import math\n\nnum = -4\nif num &gt;= 0:\n    print(math.sqrt(num))\nelse:\n    print(&quot;\u8f93\u5165\u503c\u5fc5\u987b\u4e3a\u975e\u8d1f\u6570&quot;)\n<\/code><\/pre>\n<p><strong>\u662f\u5426\u6709\u5176\u4ed6\u65b9\u6cd5\u53ef\u4ee5\u8ba1\u7b97\u5e73\u65b9\u6839\uff1f<\/strong><br \/>\u9664\u4e86\u4f7f\u7528math\u6a21\u5757\u7684sqrt\u51fd\u6570\uff0cPython\u8fd8\u63d0\u4f9b\u4e86\u5176\u4ed6\u65b9\u5f0f\u6765\u8ba1\u7b97\u5e73\u65b9\u6839\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528\u5e42\u8fd0\u7b97\u7b26\uff08**\uff09\u6765\u5b9e\u73b0\uff1a  <\/p>\n<pre><code class=\"language-python\">result = 16 ** 0.5\nprint(result)  # \u8f93\u51fa: 4.0\n<\/code><\/pre>\n<p>\u6b64\u5916\uff0c\u4f7f\u7528NumPy\u5e93\u7684sqrt\u51fd\u6570\u4e5f\u662f\u4e00\u79cd\u5e38\u89c1\u9009\u62e9\uff0c\u7279\u522b\u662f\u5728\u5904\u7406\u6570\u7ec4\u65f6\u3002\u786e\u4fdd\u6839\u636e\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528math\u6a21\u5757\u4e2d\u7684sqrt\u51fd\u6570\u6765\u5f15\u5165\u5e73\u65b9\u6839\u51fd\u6570\u3001\u786e\u4fdd\u5728\u4ee3\u7801\u4e2d\u51c6\u786e\u65e0\u8bef\u5730\u6267\u884c\u6570\u5b66\u8ba1\u7b97\u3001\u53ef\u4ee5 [&hellip;]","protected":false},"author":3,"featured_media":930127,"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\/930124"}],"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=930124"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/930124\/revisions"}],"predecessor-version":[{"id":930128,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/930124\/revisions\/930128"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/930127"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=930124"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=930124"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=930124"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}