{"id":1047986,"date":"2024-12-31T13:47:09","date_gmt":"2024-12-31T05:47:09","guid":{"rendered":""},"modified":"2024-12-31T13:47:13","modified_gmt":"2024-12-31T05:47:13","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e5%81%9a%e8%a1%8c%e5%88%97%e5%bc%8f%e8%ae%a1%e7%ae%97","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1047986.html","title":{"rendered":"\u5982\u4f55\u7528python\u505a\u884c\u5217\u5f0f\u8ba1\u7b97"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-docs.pingcode.com\/wp-content\/uploads\/2024\/12\/fbed7d03-1549-4668-af0f-db1f2f4052a4.webp?x-oss-process=image\/auto-orient,1\/format,webp\" alt=\"\u5982\u4f55\u7528python\u505a\u884c\u5217\u5f0f\u8ba1\u7b97\" \/><\/p>\n<p><p> <strong>\u5982\u4f55\u7528python\u505a\u884c\u5217\u5f0f\u8ba1\u7b97<\/strong><\/p>\n<\/p>\n<p><p>\u5728Python\u4e2d\u8ba1\u7b97\u884c\u5217\u5f0f\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\uff0c<strong>\u4f7f\u7528NumPy\u5e93\u3001\u4f7f\u7528SymPy\u5e93\u3001\u624b\u52a8\u5b9e\u73b0\u884c\u5217\u5f0f\u8ba1\u7b97<\/strong>\u3002NumPy\u5e93\u548cSymPy\u5e93\u63d0\u4f9b\u4e86\u7b80\u5355\u6613\u7528\u7684\u51fd\u6570\u6765\u8ba1\u7b97\u884c\u5217\u5f0f\uff0c\u975e\u5e38\u9002\u5408\u521d\u5b66\u8005\u548c\u9700\u8981\u5feb\u901f\u5b9e\u73b0\u7684\u573a\u666f\u3002\u624b\u52a8\u5b9e\u73b0\u884c\u5217\u5f0f\u8ba1\u7b97\u5219\u53ef\u4ee5\u5e2e\u52a9\u7406\u89e3\u884c\u5217\u5f0f\u7684\u8ba1\u7b97\u8fc7\u7a0b\uff0c\u9002\u5408\u6df1\u5165\u5b66\u4e60\u548c\u7406\u89e3\u77e9\u9635\u4ee3\u6570\u7684\u539f\u7406\u3002<strong>\u4ee5\u4e0b\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528NumPy\u548cSymPy\u5e93\u8fdb\u884c\u884c\u5217\u5f0f\u8ba1\u7b97\uff0c\u5e76\u63d0\u4f9b\u624b\u52a8\u8ba1\u7b97\u884c\u5217\u5f0f\u7684\u793a\u4f8b<\/strong>\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528NumPy\u5e93<\/h3>\n<\/p>\n<p><p>NumPy\u662fPython\u4e2d\u8fdb\u884c\u79d1\u5b66\u8ba1\u7b97\u7684\u57fa\u7840\u5e93\uff0c\u63d0\u4f9b\u4e86\u8bb8\u591a\u7ebf\u6027\u4ee3\u6570\u8fd0\u7b97\u7684\u51fd\u6570\uff0c\u5305\u62ec\u8ba1\u7b97\u884c\u5217\u5f0f\u3002\u4f7f\u7528NumPy\u5e93\u8ba1\u7b97\u884c\u5217\u5f0f\u975e\u5e38\u7b80\u5355\uff0c\u53ea\u9700\u8981\u51e0\u884c\u4ee3\u7801\u5373\u53ef\u5b8c\u6210\u3002<\/p>\n<\/p>\n<p><h4>1\u3001\u5b89\u88c5NumPy\u5e93<\/h4>\n<\/p>\n<p><p>\u9996\u5148\u9700\u8981\u5b89\u88c5NumPy\u5e93\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<p><h4>2\u3001\u8ba1\u7b97\u884c\u5217\u5f0f<\/h4>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u7684<code>numpy.linalg.det<\/code>\u51fd\u6570\u8ba1\u7b97\u884c\u5217\u5f0f\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\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>matrix = np.array([[1, 2], [3, 4]])<\/p>\n<h2><strong>\u8ba1\u7b97\u884c\u5217\u5f0f<\/strong><\/h2>\n<p>det = np.linalg.det(matrix)<\/p>\n<p>print(f&quot;\u884c\u5217\u5f0f\u7684\u503c\u4e3a: {det}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u5b9a\u4e49\u4e86\u4e00\u4e2a2&#215;2\u7684\u77e9\u9635\uff0c\u5e76\u4f7f\u7528<code>numpy.linalg.det<\/code>\u51fd\u6570\u8ba1\u7b97\u5176\u884c\u5217\u5f0f\u3002\u8f93\u51fa\u7ed3\u679c\u4e3a<code>-2.0<\/code>\uff0c\u8fd9\u6b63\u662f\u8fd9\u4e2a\u77e9\u9635\u7684\u884c\u5217\u5f0f\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528SymPy\u5e93<\/h3>\n<\/p>\n<p><p>SymPy\u662fPython\u4e2d\u7684\u4e00\u4e2a\u7b26\u53f7\u8ba1\u7b97\u5e93\uff0c\u53ef\u4ee5\u8fdb\u884c\u7b26\u53f7\u6570\u5b66\u8fd0\u7b97\uff0c\u5305\u62ec\u8ba1\u7b97\u884c\u5217\u5f0f\u3002SymPy\u5e93\u63d0\u4f9b\u4e86\u66f4\u52a0\u7075\u6d3b\u548c\u7cbe\u786e\u7684\u8ba1\u7b97\u65b9\u5f0f\uff0c\u9002\u5408\u9700\u8981\u7b26\u53f7\u8fd0\u7b97\u7684\u573a\u666f\u3002<\/p>\n<\/p>\n<p><h4>1\u3001\u5b89\u88c5SymPy\u5e93<\/h4>\n<\/p>\n<p><p>\u540c\u6837\u5730\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5SymPy\u5e93\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<p><h4>2\u3001\u8ba1\u7b97\u884c\u5217\u5f0f<\/h4>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528SymPy\u5e93\u7684<code>det<\/code>\u51fd\u6570\u8ba1\u7b97\u884c\u5217\u5f0f\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import sympy as sp<\/p>\n<h2><strong>\u5b9a\u4e49\u4e00\u4e2a\u77e9\u9635<\/strong><\/h2>\n<p>matrix = sp.Matrix([[1, 2], [3, 4]])<\/p>\n<h2><strong>\u8ba1\u7b97\u884c\u5217\u5f0f<\/strong><\/h2>\n<p>det = matrix.det()<\/p>\n<p>print(f&quot;\u884c\u5217\u5f0f\u7684\u503c\u4e3a: {det}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u5b9a\u4e49\u4e86\u4e00\u4e2a2&#215;2\u7684\u77e9\u9635\uff0c\u5e76\u4f7f\u7528SymPy\u5e93\u7684<code>det<\/code>\u51fd\u6570\u8ba1\u7b97\u5176\u884c\u5217\u5f0f\u3002\u8f93\u51fa\u7ed3\u679c\u4e3a<code>-2<\/code>\uff0c\u8fd9\u6b63\u662f\u8fd9\u4e2a\u77e9\u9635\u7684\u884c\u5217\u5f0f\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u624b\u52a8\u5b9e\u73b0\u884c\u5217\u5f0f\u8ba1\u7b97<\/h3>\n<\/p>\n<p><p>\u867d\u7136\u4f7f\u7528\u5e93\u51fd\u6570\u8ba1\u7b97\u884c\u5217\u5f0f\u975e\u5e38\u65b9\u4fbf\uff0c\u4f46\u624b\u52a8\u5b9e\u73b0\u884c\u5217\u5f0f\u8ba1\u7b97\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u66f4\u597d\u5730\u7406\u89e3\u884c\u5217\u5f0f\u7684\u8ba1\u7b97\u8fc7\u7a0b\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u624b\u52a8\u5b9e\u73b0\u884c\u5217\u5f0f\u8ba1\u7b97\u7684\u793a\u4f8b\u3002<\/p>\n<\/p>\n<p><h4>1\u3001\u8ba1\u7b972&#215;2\u77e9\u9635\u7684\u884c\u5217\u5f0f<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8e2&#215;2\u7684\u77e9\u9635\uff0c\u884c\u5217\u5f0f\u7684\u8ba1\u7b97\u516c\u5f0f\u4e3a\uff1a<\/p>\n<\/p>\n<p><p>[ \\text{det}(A) = a_{11}a_{22} &#8211; a_{12}a_{21} ]<\/p>\n<\/p>\n<p><p>\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def det_2x2(matrix):<\/p>\n<p>    return matrix[0][0] * matrix[1][1] - matrix[0][1] * matrix[1][0]<\/p>\n<h2><strong>\u5b9a\u4e49\u4e00\u4e2a2x2\u7684\u77e9\u9635<\/strong><\/h2>\n<p>matrix = [[1, 2], [3, 4]]<\/p>\n<h2><strong>\u8ba1\u7b97\u884c\u5217\u5f0f<\/strong><\/h2>\n<p>det = det_2x2(matrix)<\/p>\n<p>print(f&quot;\u884c\u5217\u5f0f\u7684\u503c\u4e3a: {det}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u5b9a\u4e49\u4e86\u4e00\u4e2a\u51fd\u6570<code>det_2x2<\/code>\uff0c\u7528\u4e8e\u8ba1\u7b972&#215;2\u77e9\u9635\u7684\u884c\u5217\u5f0f\u3002\u7136\u540e\u6211\u4eec\u5b9a\u4e49\u4e86\u4e00\u4e2a2&#215;2\u7684\u77e9\u9635\uff0c\u5e76\u4f7f\u7528<code>det_2x2<\/code>\u51fd\u6570\u8ba1\u7b97\u5176\u884c\u5217\u5f0f\u3002\u8f93\u51fa\u7ed3\u679c\u4e3a<code>-2<\/code>\uff0c\u8fd9\u6b63\u662f\u8fd9\u4e2a\u77e9\u9635\u7684\u884c\u5217\u5f0f\u3002<\/p>\n<\/p>\n<p><h4>2\u3001\u8ba1\u7b97NxN\u77e9\u9635\u7684\u884c\u5217\u5f0f<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8eNxN\u7684\u77e9\u9635\uff0c\u53ef\u4ee5\u4f7f\u7528\u9012\u5f52\u7684\u65b9\u6cd5\u8ba1\u7b97\u884c\u5217\u5f0f\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def det(matrix):<\/p>\n<p>    # \u77e9\u9635\u7684\u9636\u6570<\/p>\n<p>    n = len(matrix)<\/p>\n<p>    # \u5982\u679c\u662f2x2\u77e9\u9635\uff0c\u76f4\u63a5\u8ba1\u7b97<\/p>\n<p>    if n == 2:<\/p>\n<p>        return matrix[0][0] * matrix[1][1] - matrix[0][1] * matrix[1][0]<\/p>\n<p>    determinant = 0<\/p>\n<p>    for c in range(n):<\/p>\n<p>        # \u8ba1\u7b97\u4f59\u5b50\u5f0f<\/p>\n<p>        sub_matrix = [row[:c] + row[c + 1:] for row in matrix[1:]]<\/p>\n<p>        # \u9012\u5f52\u8ba1\u7b97\u884c\u5217\u5f0f<\/p>\n<p>        determinant += ((-1)  c) * matrix[0][c] * det(sub_matrix)<\/p>\n<p>    return determinant<\/p>\n<h2><strong>\u5b9a\u4e49\u4e00\u4e2a3x3\u7684\u77e9\u9635<\/strong><\/h2>\n<p>matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]<\/p>\n<h2><strong>\u8ba1\u7b97\u884c\u5217\u5f0f<\/strong><\/h2>\n<p>determinant = det(matrix)<\/p>\n<p>print(f&quot;\u884c\u5217\u5f0f\u7684\u503c\u4e3a: {determinant}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u5b9a\u4e49\u4e86\u4e00\u4e2a\u9012\u5f52\u51fd\u6570<code>det<\/code>\uff0c\u7528\u4e8e\u8ba1\u7b97NxN\u77e9\u9635\u7684\u884c\u5217\u5f0f\u3002\u7136\u540e\u6211\u4eec\u5b9a\u4e49\u4e86\u4e00\u4e2a3&#215;3\u7684\u77e9\u9635\uff0c\u5e76\u4f7f\u7528<code>det<\/code>\u51fd\u6570\u8ba1\u7b97\u5176\u884c\u5217\u5f0f\u3002\u8f93\u51fa\u7ed3\u679c\u4e3a<code>0<\/code>\uff0c\u8fd9\u6b63\u662f\u8fd9\u4e2a\u77e9\u9635\u7684\u884c\u5217\u5f0f\u3002<\/p>\n<\/p>\n<p><h3>\u56db\u3001\u884c\u5217\u5f0f\u7684\u6027\u8d28<\/h3>\n<\/p>\n<p><p>\u5728\u8ba1\u7b97\u884c\u5217\u5f0f\u7684\u8fc7\u7a0b\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u5229\u7528\u4e00\u4e9b\u884c\u5217\u5f0f\u7684\u6027\u8d28\u6765\u7b80\u5316\u8ba1\u7b97\u3002\u4ee5\u4e0b\u662f\u51e0\u4e2a\u5e38\u7528\u7684\u884c\u5217\u5f0f\u6027\u8d28\uff1a<\/p>\n<\/p>\n<p><h4>1\u3001\u4ea4\u6362\u4e24\u884c\uff08\u5217\uff09\u884c\u5217\u5f0f\u53d8\u53f7<\/h4>\n<\/p>\n<p><p>\u5982\u679c\u4ea4\u6362\u77e9\u9635\u7684\u4e24\u884c\uff08\u5217\uff09\uff0c\u884c\u5217\u5f0f\u7684\u503c\u4f1a\u53d8\u53f7\u3002\u8fd9\u4e2a\u6027\u8d28\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u901a\u8fc7\u53d8\u6362\u77e9\u9635\u7b80\u5316\u884c\u5217\u5f0f\u7684\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<p><h4>2\u3001\u77e9\u9635\u4e2d\u6709\u4e24\u884c\uff08\u5217\uff09\u76f8\u540c\uff0c\u884c\u5217\u5f0f\u4e3a\u96f6<\/h4>\n<\/p>\n<p><p>\u5982\u679c\u77e9\u9635\u4e2d\u6709\u4e24\u884c\uff08\u5217\uff09\u76f8\u540c\uff0c\u90a3\u4e48\u8fd9\u4e2a\u77e9\u9635\u7684\u884c\u5217\u5f0f\u4e3a\u96f6\u3002\u8fd9\u4e2a\u6027\u8d28\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u5feb\u901f\u5224\u65ad\u67d0\u4e9b\u77e9\u9635\u7684\u884c\u5217\u5f0f\u3002<\/p>\n<\/p>\n<p><h4>3\u3001\u77e9\u9635\u4e58\u4ee5\u4e00\u4e2a\u6570\uff0c\u884c\u5217\u5f0f\u4e58\u4ee5\u8fd9\u4e2a\u6570\u7684\u5e42<\/h4>\n<\/p>\n<p><p>\u5982\u679c\u4e00\u4e2a\u77e9\u9635\u7684\u67d0\u4e00\u884c\uff08\u5217\uff09\u4e58\u4ee5\u4e00\u4e2a\u6570\uff0c\u90a3\u4e48\u884c\u5217\u5f0f\u7684\u503c\u4e5f\u4f1a\u4e58\u4ee5\u8fd9\u4e2a\u6570\u3002\u8fd9\u4e2a\u6027\u8d28\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u901a\u8fc7\u7f29\u653e\u77e9\u9635\u7b80\u5316\u884c\u5217\u5f0f\u7684\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<p><h4>4\u3001\u77e9\u9635\u884c\u5217\u5f0f\u7684\u4e58\u79ef\u7b49\u4e8e\u5404\u884c\u5217\u5f0f\u7684\u4e58\u79ef<\/h4>\n<\/p>\n<p><p>\u5982\u679c\u4e24\u4e2a\u77e9\u9635\u76f8\u4e58\uff0c\u90a3\u4e48\u5b83\u4eec\u7684\u884c\u5217\u5f0f\u7684\u4e58\u79ef\u7b49\u4e8e\u5404\u81ea\u884c\u5217\u5f0f\u7684\u4e58\u79ef\u3002\u8fd9\u4e2a\u6027\u8d28\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u901a\u8fc7\u5206\u89e3\u77e9\u9635\u7b80\u5316\u884c\u5217\u5f0f\u7684\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<p><h3>\u4e94\u3001\u884c\u5217\u5f0f\u7684\u5e94\u7528<\/h3>\n<\/p>\n<p><p>\u884c\u5217\u5f0f\u5728\u7ebf\u6027\u4ee3\u6570\u4e2d\u6709\u7740\u5e7f\u6cdb\u7684\u5e94\u7528\uff0c\u4ee5\u4e0b\u662f\u51e0\u4e2a\u5e38\u89c1\u7684\u5e94\u7528\u573a\u666f\uff1a<\/p>\n<\/p>\n<p><h4>1\u3001\u5224\u65ad\u77e9\u9635\u662f\u5426\u53ef\u9006<\/h4>\n<\/p>\n<p><p>\u884c\u5217\u5f0f\u53ef\u4ee5\u7528\u4e8e\u5224\u65ad\u77e9\u9635\u662f\u5426\u53ef\u9006\u3002\u5982\u679c\u77e9\u9635\u7684\u884c\u5217\u5f0f\u4e0d\u4e3a\u96f6\uff0c\u90a3\u4e48\u8fd9\u4e2a\u77e9\u9635\u662f\u53ef\u9006\u7684\uff1b\u5426\u5219\uff0c\u8fd9\u4e2a\u77e9\u9635\u662f\u4e0d\u53ef\u9006\u7684\u3002<\/p>\n<\/p>\n<p><h4>2\u3001\u6c42\u89e3\u7ebf\u6027\u65b9\u7a0b\u7ec4<\/h4>\n<\/p>\n<p><p>\u884c\u5217\u5f0f\u53ef\u4ee5\u7528\u4e8e\u6c42\u89e3\u7ebf\u6027\u65b9\u7a0b\u7ec4\u3002\u901a\u8fc7\u8ba1\u7b97\u7cfb\u6570\u77e9\u9635\u7684\u884c\u5217\u5f0f\u548c\u589e\u5e7f\u77e9\u9635\u7684\u884c\u5217\u5f0f\uff0c\u53ef\u4ee5\u786e\u5b9a\u7ebf\u6027\u65b9\u7a0b\u7ec4\u7684\u89e3\u7684\u60c5\u51b5\u3002<\/p>\n<\/p>\n<p><h4>3\u3001\u8ba1\u7b97\u77e9\u9635\u7684\u7279\u5f81\u503c<\/h4>\n<\/p>\n<p><p>\u884c\u5217\u5f0f\u53ef\u4ee5\u7528\u4e8e\u8ba1\u7b97\u77e9\u9635\u7684\u7279\u5f81\u503c\u3002\u901a\u8fc7\u8ba1\u7b97\u7279\u5f81\u591a\u9879\u5f0f\u7684\u6839\uff0c\u53ef\u4ee5\u5f97\u5230\u77e9\u9635\u7684\u7279\u5f81\u503c\u3002<\/p>\n<\/p>\n<p><h3>\u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u672c\u6587\u4ecb\u7ecd\u4e86\u5982\u4f55\u4f7f\u7528Python\u8ba1\u7b97\u884c\u5217\u5f0f\uff0c\u5305\u62ec\u4f7f\u7528NumPy\u5e93\u3001\u4f7f\u7528SymPy\u5e93\u548c\u624b\u52a8\u5b9e\u73b0\u884c\u5217\u5f0f\u8ba1\u7b97\u3002\u4f7f\u7528\u5e93\u51fd\u6570\u8ba1\u7b97\u884c\u5217\u5f0f\u975e\u5e38\u65b9\u4fbf\uff0c\u9002\u5408\u9700\u8981\u5feb\u901f\u5b9e\u73b0\u7684\u573a\u666f\uff1b\u624b\u52a8\u5b9e\u73b0\u884c\u5217\u5f0f\u8ba1\u7b97\u5219\u53ef\u4ee5\u5e2e\u52a9\u7406\u89e3\u884c\u5217\u5f0f\u7684\u8ba1\u7b97\u8fc7\u7a0b\u3002\u901a\u8fc7\u5b66\u4e60\u884c\u5217\u5f0f\u7684\u8ba1\u7b97\u65b9\u6cd5\u548c\u6027\u8d28\uff0c\u6211\u4eec\u53ef\u4ee5\u66f4\u597d\u5730\u7406\u89e3\u548c\u5e94\u7528\u884c\u5217\u5f0f\u5728\u5b9e\u9645\u95ee\u9898\u4e2d\u7684\u4f5c\u7528\u3002\u5e0c\u671b\u672c\u6587\u80fd\u591f\u5e2e\u52a9\u8bfb\u8005\u638c\u63e1\u884c\u5217\u5f0f\u7684\u8ba1\u7b97\u65b9\u6cd5\uff0c\u5e76\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u7075\u6d3b\u8fd0\u7528\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u4f7f\u7528Python\u8ba1\u7b97\u77e9\u9635\u7684\u884c\u5217\u5f0f\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u6765\u8ba1\u7b97\u77e9\u9635\u7684\u884c\u5217\u5f0f\u3002NumPy\u63d0\u4f9b\u4e86\u4e00\u4e2a\u540d\u4e3a<code>numpy.linalg.det()<\/code>\u7684\u51fd\u6570\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u5b8c\u6210\u8fd9\u4e00\u4efb\u52a1\u3002\u9996\u5148\uff0c\u4f60\u9700\u8981\u5bfc\u5165NumPy\u5e93\uff0c\u5e76\u521b\u5efa\u4e00\u4e2a\u77e9\u9635\uff0c\u7136\u540e\u8c03\u7528\u8be5\u51fd\u6570\u5373\u53ef\u5f97\u5230\u884c\u5217\u5f0f\u7684\u503c\u3002\u4f8b\u5982\uff1a<\/p>\n<pre><code class=\"language-python\">import numpy as np\n\n# \u521b\u5efa\u4e00\u4e2a2x2\u77e9\u9635\nmatrix = np.array([[1, 2], [3, 4]])\ndet = np.linalg.det(matrix)\nprint(det)  # \u8f93\u51fa\uff1a-2.0\n<\/code><\/pre>\n<p><strong>\u5728Python\u4e2d\u8ba1\u7b97\u5927\u77e9\u9635\u884c\u5217\u5f0f\u7684\u6548\u7387\u5982\u4f55\uff1f<\/strong><br \/>\u4f7f\u7528NumPy\u8fdb\u884c\u884c\u5217\u5f0f\u8ba1\u7b97\u7684\u6548\u7387\u76f8\u5bf9\u8f83\u9ad8\uff0c\u7279\u522b\u662f\u5bf9\u4e8e\u8f83\u5c0f\u7684\u77e9\u9635\u3002NumPy\u5e95\u5c42\u4f7f\u7528\u4e86\u9ad8\u6548\u7684C\u8bed\u8a00\u4ee3\u7801\u6765\u5904\u7406\u6570\u7ec4\u8fd0\u7b97\uff0c\u56e0\u6b64\u5728\u5904\u7406\u5927\u578b\u77e9\u9635\u65f6\u4e5f\u80fd\u4fdd\u6301\u8f83\u597d\u7684\u6027\u80fd\u3002\u7136\u800c\uff0c\u5bf9\u4e8e\u975e\u5e38\u5927\u7684\u77e9\u9635\uff0c\u8ba1\u7b97\u884c\u5217\u5f0f\u7684\u65f6\u95f4\u590d\u6742\u5ea6\u53ef\u80fd\u4f1a\u663e\u8457\u589e\u52a0\uff0c\u5efa\u8bae\u5728\u5904\u7406\u6781\u5927\u89c4\u6a21\u77e9\u9635\u65f6\u8003\u8651\u5176\u4ed6\u65b9\u6cd5\uff0c\u5982LU\u5206\u89e3\u3002<\/p>\n<p><strong>\u662f\u5426\u53ef\u4ee5\u5728Python\u4e2d\u4f7f\u7528\u5176\u4ed6\u5e93\u8fdb\u884c\u884c\u5217\u5f0f\u8ba1\u7b97\uff1f<\/strong><br \/>\u9664\u4e86NumPy\uff0cPython\u4e2d\u8fd8\u6709\u5176\u4ed6\u4e00\u4e9b\u5e93\u53ef\u4ee5\u7528\u4e8e\u8ba1\u7b97\u884c\u5217\u5f0f\u3002\u4f8b\u5982\uff0cSymPy\u662f\u4e00\u4e2a\u7528\u4e8e\u7b26\u53f7\u6570\u5b66\u7684\u5e93\uff0c\u53ef\u4ee5\u5904\u7406\u7b26\u53f7\u8868\u8fbe\u5f0f\u5e76\u8ba1\u7b97\u884c\u5217\u5f0f\u3002\u4f7f\u7528SymPy\uff0c\u4f60\u53ef\u4ee5\u8f7b\u677e\u5904\u7406\u7b26\u53f7\u77e9\u9635\u5e76\u83b7\u5f97\u7cbe\u786e\u7684\u7ed3\u679c\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n<pre><code class=\"language-python\">import sympy as sp\n\n# \u521b\u5efa\u4e00\u4e2a\u7b26\u53f7\u77e9\u9635\nx, y, z = sp.symbols(&#39;x y z&#39;)\nmatrix = sp.Matrix([[x, y], [z, 1]])\ndet = matrix.det()\nprint(det)  # \u8f93\u51fa\uff1ax - yz\n<\/code><\/pre>\n<p>\u4f7f\u7528\u8fd9\u4e9b\u5de5\u5177\uff0c\u7528\u6237\u53ef\u4ee5\u6839\u636e\u81ea\u5df1\u7684\u9700\u6c42\u9009\u62e9\u6700\u5408\u9002\u7684\u5e93\u6765\u8ba1\u7b97\u884c\u5217\u5f0f\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5982\u4f55\u7528python\u505a\u884c\u5217\u5f0f\u8ba1\u7b97 \u5728Python\u4e2d\u8ba1\u7b97\u884c\u5217\u5f0f\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\uff0c\u4f7f\u7528NumPy\u5e93\u3001\u4f7f\u7528SymPy\u5e93 [&hellip;]","protected":false},"author":3,"featured_media":1047998,"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\/1047986"}],"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=1047986"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1047986\/revisions"}],"predecessor-version":[{"id":1048005,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1047986\/revisions\/1048005"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1047998"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1047986"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1047986"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1047986"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}