{"id":1076585,"date":"2025-01-08T11:54:45","date_gmt":"2025-01-08T03:54:45","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1076585.html"},"modified":"2025-01-08T11:54:47","modified_gmt":"2025-01-08T03:54:47","slug":"python%e4%b8%ad%e5%a6%82%e4%bd%95%e6%89%93%e7%9f%a9%e9%98%b5%e7%9a%84%e7%a7%a9-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1076585.html","title":{"rendered":"python\u4e2d\u5982\u4f55\u6253\u77e9\u9635\u7684\u79e9"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/24181057\/6a176412-416e-4e4a-8b03-4d3eb33ce568.webp\" alt=\"python\u4e2d\u5982\u4f55\u6253\u77e9\u9635\u7684\u79e9\" \/><\/p>\n<p><p> <strong>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u65b9\u5f0f\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\uff1a\u4f7f\u7528NumPy\u5e93\u3001SciPy\u5e93\u3001SymPy\u5e93\u3002\u63a8\u8350\u4f7f\u7528NumPy\u5e93\uff0c\u56e0\u4e3a\u5b83\u662f\u5904\u7406\u6570\u503c\u8fd0\u7b97\u7684\u6807\u51c6\u5e93\uff0c\u529f\u80fd\u5f3a\u5927\u4e14\u6027\u80fd\u4f18\u8d8a\u3002<\/strong><\/p>\n<\/p>\n<p><p>NumPy\u5e93\u63d0\u4f9b\u4e86\u4e00\u4e2a\u975e\u5e38\u65b9\u4fbf\u7684\u65b9\u6cd5\u6765\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\uff0c\u5373<code>numpy.linalg.matrix_rank<\/code>\u3002\u8fd9\u4e00\u65b9\u6cd5\u4e0d\u4ec5\u7b80\u6d01\uff0c\u800c\u4e14\u8ba1\u7b97\u6548\u7387\u9ad8\uff0c\u9002\u7528\u4e8e\u5927\u591a\u6570\u5e94\u7528\u573a\u666f\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528NumPy\u5e93\u6765\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\uff0c\u5e76\u5bf9\u5176\u4ed6\u65b9\u6cd5\u8fdb\u884c\u7b80\u5355\u4ecb\u7ecd\u3002<\/p>\n<\/p>\n<p><p>\u4e00\u3001NUMPY\u5e93\u8ba1\u7b97\u77e9\u9635\u7684\u79e9<\/p>\n<\/p>\n<p><p>NumPy\u662fPython\u4e2d\u6700\u4e3a\u5e7f\u6cdb\u4f7f\u7528\u7684\u6570\u503c\u8ba1\u7b97\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7ebf\u6027\u4ee3\u6570\u8fd0\u7b97\u529f\u80fd\u3002\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\u53ef\u4ee5\u901a\u8fc7<code>numpy.linalg.matrix_rank<\/code>\u51fd\u6570\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5NumPy\u5e93<\/li>\n<\/ol>\n<p><p>\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86NumPy\u5e93\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u4f7f\u7528<code>numpy.linalg.matrix_rank<\/code>\u8ba1\u7b97\u77e9\u9635\u7684\u79e9<\/li>\n<\/ol>\n<p><p>\u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528NumPy\u5e93\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u5b9a\u4e49\u4e00\u4e2a\u77e9\u9635<\/strong><\/h2>\n<p>A = np.array([[1, 2, 3],<\/p>\n<p>              [4, 5, 6],<\/p>\n<p>              [7, 8, 9]])<\/p>\n<h2><strong>\u8ba1\u7b97\u77e9\u9635\u7684\u79e9<\/strong><\/h2>\n<p>rank = np.linalg.matrix_rank(A)<\/p>\n<p>print(f&quot;\u77e9\u9635\u7684\u79e9\u662f: {rank}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u5bfc\u5165\u4e86NumPy\u5e93\uff0c\u7136\u540e\u5b9a\u4e49\u4e86\u4e00\u4e2a3&#215;3\u7684\u77e9\u9635<code>A<\/code>\u3002\u4f7f\u7528<code>numpy.linalg.matrix_rank<\/code>\u51fd\u6570\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\uff0c\u5e76\u8f93\u51fa\u7ed3\u679c\u3002<\/p>\n<\/p>\n<p><p><strong>\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong><\/p>\n<\/p>\n<p><p>NumPy\u5e93\u4e2d\u7684<code>numpy.linalg.matrix_rank<\/code>\u51fd\u6570\u662f\u4e13\u95e8\u7528\u6765\u8ba1\u7b97\u77e9\u9635\u79e9\u7684\u51fd\u6570\u3002\u5b83\u5185\u90e8\u5b9e\u73b0\u4e86\u9ad8\u6548\u7684\u7ebf\u6027\u4ee3\u6570\u8fd0\u7b97\uff0c\u80fd\u591f\u5feb\u901f\u8ba1\u7b97\u51fa\u77e9\u9635\u7684\u79e9\u3002\u8fd9\u4e2a\u51fd\u6570\u7684\u53c2\u6570\u662f\u4e00\u4e2a\u4efb\u610f\u5f62\u72b6\u7684\u6570\u7ec4\uff08\u77e9\u9635\uff09\uff0c\u8fd4\u56de\u503c\u662f\u4e00\u4e2a\u6574\u6570\uff0c\u8868\u793a\u77e9\u9635\u7684\u79e9\u3002<\/p>\n<\/p>\n<p><p>\u8ba1\u7b97\u77e9\u9635\u79e9\u7684\u57fa\u672c\u539f\u7406\u662f\u5c06\u77e9\u9635\u8fdb\u884c\u5947\u5f02\u503c\u5206\u89e3\uff08SVD\uff09\uff0c\u7136\u540e\u8ba1\u7b97\u5947\u5f02\u503c\u7684\u4e2a\u6570\u3002\u5947\u5f02\u503c\u5206\u89e3\u662f\u4e00\u79cd\u5c06\u77e9\u9635\u5206\u89e3\u4e3a\u4e09\u4e2a\u7279\u5b9a\u77e9\u9635\u7684\u56e0\u5b50\u5206\u89e3\u65b9\u6cd5\uff0c\u901a\u8fc7\u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u65b9\u4fbf\u5730\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\u3002<\/p>\n<\/p>\n<p><p>\u4e8c\u3001SCIPY\u5e93\u8ba1\u7b97\u77e9\u9635\u7684\u79e9<\/p>\n<\/p>\n<p><p>SciPy\u662f\u53e6\u4e00\u4e2a\u5f3a\u5927\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\uff0c\u63d0\u4f9b\u4e86\u66f4\u591a\u9ad8\u7ea7\u7684\u6570\u5b66\u3001\u79d1\u5b66\u548c\u5de5\u7a0b\u8ba1\u7b97\u529f\u80fd\u3002SciPy\u5e93\u540c\u6837\u53ef\u4ee5\u7528\u6765\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\uff0c\u4e0b\u9762\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5SciPy\u5e93<\/li>\n<\/ol>\n<p><p>\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86SciPy\u5e93\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install scipy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u4f7f\u7528<code>scipy.linalg.matrix_rank<\/code>\u8ba1\u7b97\u77e9\u9635\u7684\u79e9<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p>from scipy.linalg import matrix_rank<\/p>\n<h2><strong>\u5b9a\u4e49\u4e00\u4e2a\u77e9\u9635<\/strong><\/h2>\n<p>A = np.array([[1, 2, 3],<\/p>\n<p>              [4, 5, 6],<\/p>\n<p>              [7, 8, 9]])<\/p>\n<h2><strong>\u8ba1\u7b97\u77e9\u9635\u7684\u79e9<\/strong><\/h2>\n<p>rank = matrix_rank(A)<\/p>\n<p>print(f&quot;\u77e9\u9635\u7684\u79e9\u662f: {rank}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u5bfc\u5165\u4e86NumPy\u548cSciPy\u5e93\uff0c\u7136\u540e\u4f7f\u7528<code>scipy.linalg.matrix_rank<\/code>\u51fd\u6570\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\uff0c\u5e76\u8f93\u51fa\u7ed3\u679c\u3002<\/p>\n<\/p>\n<p><p>\u4e09\u3001SYMPY\u5e93\u8ba1\u7b97\u77e9\u9635\u7684\u79e9<\/p>\n<\/p>\n<p><p>SymPy\u662f\u4e00\u4e2a\u7528\u4e8e\u7b26\u53f7\u8ba1\u7b97\u7684Python\u5e93\uff0c\u9002\u5408\u5904\u7406\u7cbe\u5ea6\u8981\u6c42\u8f83\u9ad8\u7684\u6570\u5b66\u8ba1\u7b97\u3002SymPy\u5e93\u540c\u6837\u53ef\u4ee5\u7528\u6765\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\uff0c\u4e0b\u9762\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5SymPy\u5e93<\/li>\n<\/ol>\n<p><p>\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86SymPy\u5e93\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install sympy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u4f7f\u7528<code>sympy.Matrix.rank<\/code>\u8ba1\u7b97\u77e9\u9635\u7684\u79e9<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\">from sympy import Matrix<\/p>\n<h2><strong>\u5b9a\u4e49\u4e00\u4e2a\u77e9\u9635<\/strong><\/h2>\n<p>A = Matrix([[1, 2, 3],<\/p>\n<p>            [4, 5, 6],<\/p>\n<p>            [7, 8, 9]])<\/p>\n<h2><strong>\u8ba1\u7b97\u77e9\u9635\u7684\u79e9<\/strong><\/h2>\n<p>rank = A.rank()<\/p>\n<p>print(f&quot;\u77e9\u9635\u7684\u79e9\u662f: {rank}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u5bfc\u5165\u4e86SymPy\u5e93\uff0c\u7136\u540e\u4f7f\u7528<code>sympy.Matrix.rank<\/code>\u65b9\u6cd5\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\uff0c\u5e76\u8f93\u51fa\u7ed3\u679c\u3002<\/p>\n<\/p>\n<p><p><strong>\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong><\/p>\n<\/p>\n<p><p>SymPy\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7b26\u53f7\u8ba1\u7b97\u529f\u80fd\uff0c\u9002\u7528\u4e8e\u9700\u8981\u9ad8\u7cbe\u5ea6\u8ba1\u7b97\u7684\u573a\u666f\u3002<code>sympy.Matrix.rank<\/code>\u65b9\u6cd5\u53ef\u4ee5\u8ba1\u7b97\u4efb\u610f\u7b26\u53f7\u77e9\u9635\u7684\u79e9\uff0c\u9002\u7528\u4e8e\u5904\u7406\u7b26\u53f7\u77e9\u9635\u548c\u6570\u503c\u77e9\u9635\u3002\u8fd9\u79cd\u65b9\u6cd5\u7684\u4f18\u52bf\u5728\u4e8e\u53ef\u4ee5\u5904\u7406\u7cbe\u5ea6\u8981\u6c42\u8f83\u9ad8\u7684\u8ba1\u7b97\uff0c\u4f46\u6027\u80fd\u4e0a\u53ef\u80fd\u4e0d\u5982NumPy\u548cSciPy\u3002<\/p>\n<\/p>\n<p><p>\u56db\u3001\u77e9\u9635\u79e9\u7684\u5e94\u7528<\/p>\n<\/p>\n<ol>\n<li>\u77e9\u9635\u79e9\u5728\u7ebf\u6027\u4ee3\u6570\u4e2d\u7684\u5e94\u7528<\/li>\n<\/ol>\n<p><p>\u77e9\u9635\u7684\u79e9\u5728\u7ebf\u6027\u4ee3\u6570\u4e2d\u5177\u6709\u91cd\u8981\u7684\u610f\u4e49\u3002\u77e9\u9635\u7684\u79e9\u662f\u5176\u884c\uff08\u6216\u5217\uff09\u5411\u91cf\u7ec4\u7684\u7ebf\u6027\u65e0\u5173\u5411\u91cf\u7684\u6700\u5927\u4e2a\u6570\u3002\u79e9\u53ef\u4ee5\u7528\u4e8e\u5224\u65ad\u77e9\u9635\u662f\u5426\u53ef\u9006\uff0c\u77e9\u9635\u65b9\u7a0b\u662f\u5426\u6709\u89e3\u7b49\u3002\u4f8b\u5982\uff0c\u4e00\u4e2a\u65b9\u9635A\u662f\u53ef\u9006\u7684\u5f53\u4e14\u4ec5\u5f53\u5176\u79e9\u7b49\u4e8e\u5176\u9636\u6570\u3002<\/p>\n<\/p>\n<ol start=\"2\">\n<li>\u77e9\u9635\u79e9\u5728\u6570\u636e\u79d1\u5b66\u4e2d\u7684\u5e94\u7528<\/li>\n<\/ol>\n<p><p>\u5728\u6570\u636e\u79d1\u5b66\u4e2d\uff0c\u77e9\u9635\u79e9\u540c\u6837\u6709\u5e7f\u6cdb\u7684\u5e94\u7528\u3002\u6bd4\u5982\uff0c\u4e3b\u6210\u5206\u5206\u6790\uff08PCA\uff09\u662f\u4e00\u79cd\u5e38\u7528\u7684\u6570\u636e\u964d\u7ef4\u65b9\u6cd5\uff0c\u5b83\u901a\u8fc7\u8ba1\u7b97\u534f\u65b9\u5dee\u77e9\u9635\u7684\u79e9\u6765\u786e\u5b9a\u6570\u636e\u7684\u4e3b\u6210\u5206\u3002\u77e9\u9635\u79e9\u8fd8\u53ef\u4ee5\u7528\u4e8e\u6570\u636e\u538b\u7f29\u3001\u7279\u5f81\u63d0\u53d6\u7b49\u65b9\u9762\u3002<\/p>\n<\/p>\n<ol start=\"3\">\n<li>\u77e9\u9635\u79e9\u5728<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u4e2d\u7684\u5e94\u7528<\/li>\n<\/ol>\n<p><p>\u5728\u673a\u5668\u5b66\u4e60\u4e2d\uff0c\u77e9\u9635\u79e9\u4e5f\u6709\u91cd\u8981\u7684\u5e94\u7528\u3002\u4f8b\u5982\uff0c\u5728\u63a8\u8350\u7cfb\u7edf\u4e2d\uff0c\u77e9\u9635\u5206\u89e3\u662f\u4e00\u79cd\u5e38\u7528\u7684\u65b9\u6cd5\uff0c\u5b83\u901a\u8fc7\u5206\u89e3\u7528\u6237-\u7269\u54c1\u8bc4\u5206\u77e9\u9635\u6765\u9884\u6d4b\u7528\u6237\u672a\u8bc4\u5206\u7684\u7269\u54c1\u3002\u77e9\u9635\u5206\u89e3\u7684\u4e00\u4e2a\u91cd\u8981\u6b65\u9aa4\u662f\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\uff0c\u4ee5\u786e\u5b9a\u5206\u89e3\u7684\u7ef4\u5ea6\u3002<\/p>\n<\/p>\n<p><p>\u4e94\u3001\u6bd4\u8f83\u4e0d\u540c\u65b9\u6cd5\u7684\u4f18\u7f3a\u70b9<\/p>\n<\/p>\n<ol>\n<li>NumPy\u5e93<\/li>\n<\/ol>\n<p><p>\u4f18\u70b9\uff1a\u8ba1\u7b97\u6548\u7387\u9ad8\uff0c\u9002\u7528\u4e8e\u5927\u591a\u6570\u5e94\u7528\u573a\u666f\uff1b\u4f7f\u7528\u65b9\u4fbf\uff0c\u51fd\u6570\u63a5\u53e3\u7b80\u5355\u3002<\/p>\n<p>\u7f3a\u70b9\uff1a\u4e3b\u8981\u9002\u7528\u4e8e\u6570\u503c\u77e9\u9635\uff0c\u5bf9\u4e8e\u7b26\u53f7\u77e9\u9635\u652f\u6301\u8f83\u5dee\u3002<\/p>\n<\/p>\n<ol start=\"2\">\n<li>SciPy\u5e93<\/li>\n<\/ol>\n<p><p>\u4f18\u70b9\uff1a\u63d0\u4f9b\u4e86\u66f4\u591a\u9ad8\u7ea7\u7684\u6570\u5b66\u3001\u79d1\u5b66\u548c\u5de5\u7a0b\u8ba1\u7b97\u529f\u80fd\uff1b\u4e0eNumPy\u5e93\u517c\u5bb9\u6027\u597d\u3002<\/p>\n<p>\u7f3a\u70b9\uff1a\u8ba1\u7b97\u6548\u7387\u4e0eNumPy\u5e93\u76f8\u5f53\uff0c\u4e3b\u8981\u9002\u7528\u4e8e\u6570\u503c\u77e9\u9635\u3002<\/p>\n<\/p>\n<ol start=\"3\">\n<li>SymPy\u5e93<\/li>\n<\/ol>\n<p><p>\u4f18\u70b9\uff1a\u9002\u7528\u4e8e\u7b26\u53f7\u8ba1\u7b97\uff0c\u80fd\u591f\u5904\u7406\u9ad8\u7cbe\u5ea6\u8ba1\u7b97\uff1b\u51fd\u6570\u63a5\u53e3\u4e30\u5bcc\uff0c\u9002\u7528\u4e8e\u6570\u5b66\u7814\u7a76\u3002<\/p>\n<p>\u7f3a\u70b9\uff1a\u8ba1\u7b97\u6548\u7387\u8f83\u4f4e\uff0c\u4e3b\u8981\u9002\u7528\u4e8e\u7b26\u53f7\u77e9\u9635\u3002<\/p>\n<\/p>\n<p><p>\u516d\u3001\u603b\u7ed3<\/p>\n<\/p>\n<p><p>\u5728Python\u4e2d\uff0c\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\u6709\u591a\u79cd\u65b9\u6cd5\uff0c\u5176\u4e2dNumPy\u5e93\u662f\u6700\u4e3a\u5e38\u7528\u548c\u63a8\u8350\u7684\u65b9\u6cd5\u3002NumPy\u5e93\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u8ba1\u7b97\u51fd\u6570<code>numpy.linalg.matrix_rank<\/code>\uff0c\u9002\u7528\u4e8e\u5927\u591a\u6570\u6570\u503c\u8ba1\u7b97\u573a\u666f\u3002SciPy\u5e93\u63d0\u4f9b\u4e86\u66f4\u591a\u9ad8\u7ea7\u7684\u6570\u5b66\u8ba1\u7b97\u529f\u80fd\uff0c\u540c\u6837\u9002\u7528\u4e8e\u6570\u503c\u77e9\u9635\u7684\u79e9\u8ba1\u7b97\u3002SymPy\u5e93\u9002\u7528\u4e8e\u7b26\u53f7\u8ba1\u7b97\u548c\u9ad8\u7cbe\u5ea6\u8ba1\u7b97\uff0c\u9002\u5408\u5904\u7406\u7b26\u53f7\u77e9\u9635\u3002<\/p>\n<\/p>\n<p><p>\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u53d6\u51b3\u4e8e\u5177\u4f53\u7684\u9700\u6c42\u3002\u5982\u679c\u9700\u8981\u5904\u7406\u6570\u503c\u77e9\u9635\uff0c\u63a8\u8350\u4f7f\u7528NumPy\u5e93\uff1b\u5982\u679c\u9700\u8981\u5904\u7406\u7b26\u53f7\u77e9\u9635\u6216\u9ad8\u7cbe\u5ea6\u8ba1\u7b97\uff0c\u63a8\u8350\u4f7f\u7528SymPy\u5e93\u3002\u901a\u8fc7\u5408\u7406\u9009\u62e9\u8ba1\u7b97\u65b9\u6cd5\uff0c\u53ef\u4ee5\u63d0\u9ad8\u8ba1\u7b97\u6548\u7387\uff0c\u6ee1\u8db3\u4e0d\u540c\u573a\u666f\u7684\u9700\u6c42\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5728Python\u4e2d\uff0c\u5982\u4f55\u8ba1\u7b97\u4e00\u4e2a\u77e9\u9635\u7684\u79e9\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\u901a\u5e38\u4f7f\u7528NumPy\u5e93\u3002\u901a\u8fc7<code>numpy.linalg.matrix_rank()<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u8f7b\u677e\u83b7\u5f97\u77e9\u9635\u7684\u79e9\u3002\u9996\u5148\uff0c\u9700\u8981\u5bfc\u5165NumPy\u5e93\u5e76\u521b\u5efa\u4e00\u4e2a\u77e9\u9635\uff0c\u7136\u540e\u8c03\u7528\u8be5\u51fd\u6570\u3002\u4f8b\u5982\uff1a<\/p>\n<pre><code class=\"language-python\">import numpy as np\n\nmatrix = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\nrank = np.linalg.matrix_rank(matrix)\nprint(rank)\n<\/code><\/pre>\n<p>\u6b64\u4ee3\u7801\u4f1a\u8f93\u51fa\u77e9\u9635\u7684\u79e9\u3002<\/p>\n<p><strong>\u4f7f\u7528\u5176\u4ed6\u5e93\u8ba1\u7b97\u77e9\u9635\u79e9\u6709\u4ec0\u4e48\u4e0d\u540c\uff1f<\/strong><br \/>\u9664\u4e86NumPy\uff0cSciPy\u5e93\u4e5f\u53ef\u4ee5\u7528\u4e8e\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\u3002SciPy\u63d0\u4f9b\u4e86\u66f4\u591a\u7ebf\u6027\u4ee3\u6570\u529f\u80fd\uff0c\u6bd4\u5982<code>scipy.linalg.matrix_rank()<\/code>\u3002\u5b83\u7684\u4f7f\u7528\u65b9\u5f0f\u4e0eNumPy\u7c7b\u4f3c\uff0c\u4f46\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\u53ef\u80fd\u63d0\u4f9b\u66f4\u9ad8\u7684\u7cbe\u5ea6\u6216\u66f4\u590d\u6742\u7684\u8ba1\u7b97\u9009\u9879\u3002<\/p>\n<p><strong>\u5728\u8ba1\u7b97\u77e9\u9635\u79e9\u65f6\uff0c\u662f\u5426\u9700\u8981\u8003\u8651\u77e9\u9635\u7684\u7c7b\u578b\uff1f<\/strong><br \/>\u786e\u5b9e\uff0c\u77e9\u9635\u7684\u7c7b\u578b\uff08\u5982\u7a20\u5bc6\u77e9\u9635\u6216\u7a00\u758f\u77e9\u9635\uff09\u53ef\u80fd\u5f71\u54cd\u8ba1\u7b97\u7684\u6548\u7387\u548c\u7ed3\u679c\u3002\u5bf9\u4e8e\u5927\u89c4\u6a21\u7a00\u758f\u77e9\u9635\uff0c\u4f7f\u7528SciPy\u7684\u7a00\u758f\u77e9\u9635\u6a21\u5757\uff0c\u53ef\u4ee5\u63d0\u9ad8\u8ba1\u7b97\u6548\u7387\u3002\u786e\u4fdd\u6839\u636e\u77e9\u9635\u7684\u7279\u6027\u9009\u62e9\u5408\u9002\u7684\u5e93\u548c\u65b9\u6cd5\uff0c\u4ee5\u83b7\u5f97\u6700\u4f73\u6027\u80fd\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u65b9\u5f0f\u8ba1\u7b97\u77e9\u9635\u7684\u79e9\uff1a\u4f7f\u7528NumPy\u5e93\u3001SciPy\u5e93\u3001SymPy\u5e93\u3002\u63a8\u8350\u4f7f\u7528Nu [&hellip;]","protected":false},"author":3,"featured_media":1076599,"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\/1076585"}],"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=1076585"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1076585\/revisions"}],"predecessor-version":[{"id":1076603,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1076585\/revisions\/1076603"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1076599"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1076585"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1076585"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1076585"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}