{"id":954857,"date":"2024-12-27T02:05:42","date_gmt":"2024-12-26T18:05:42","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/954857.html"},"modified":"2024-12-27T02:05:45","modified_gmt":"2024-12-26T18:05:45","slug":"python%e5%a6%82%e4%bd%95%e8%be%93%e5%87%ba%e6%95%b0%e5%ad%97%e6%96%b9%e9%98%b5","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/954857.html","title":{"rendered":"python\u5982\u4f55\u8f93\u51fa\u6570\u5b57\u65b9\u9635"},"content":{"rendered":"

\"python\u5982\u4f55\u8f93\u51fa\u6570\u5b57\u65b9\u9635\"<\/p>\n

\u5728Python\u4e2d\uff0c\u8f93\u51fa\u6570\u5b57\u65b9\u9635\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528\u5d4c\u5957\u5faa\u73af\u3001\u5217\u8868\u63a8\u5bfc\u5f0f\u3001NumPy\u5e93\u7b49<\/strong>\u3002\u5176\u4e2d\uff0c\u6700\u7b80\u5355\u7684\u65b9\u6cd5\u662f\u4f7f\u7528\u5d4c\u5957\u5faa\u73af\u6765\u751f\u6210\u548c\u6253\u5370\u65b9\u9635\u3002\u5d4c\u5957\u5faa\u73af\u7684\u4f18\u52bf\u5728\u4e8e\u5176\u76f4\u89c2\u6027\u548c\u7075\u6d3b\u6027\uff0c\u80fd\u591f\u8f7b\u677e\u5730\u63a7\u5236\u65b9\u9635\u7684\u5927\u5c0f\u548c\u5185\u5bb9<\/strong>\u3002\u901a\u8fc7\u53cc\u91cd\u5faa\u73af\uff0c\u53ef\u4ee5\u904d\u5386\u65b9\u9635\u7684\u6bcf\u4e00\u884c\u548c\u6bcf\u4e00\u5217\uff0c\u4ece\u800c\u8f93\u51fa\u6bcf\u4e2a\u5143\u7d20\u7684\u4f4d\u7f6e\u548c\u503c\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u51e0\u79cd\u5b9e\u73b0\u65b9\u6cd5\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528\u5d4c\u5957\u5faa\u73af\u8f93\u51fa\u6570\u5b57\u65b9\u9635<\/p>\n<\/p>\n

\u5d4c\u5957\u5faa\u73af\u662fPython\u4e2d\u6700\u57fa\u672c\u7684\u5faa\u73af\u63a7\u5236\u7ed3\u6784\u4e4b\u4e00\uff0c\u5b83\u80fd\u8ba9\u6211\u4eec\u4ee5\u4e00\u79cd\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\u6765\u751f\u6210\u548c\u8f93\u51fa\u6570\u5b57\u65b9\u9635\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u4f7f\u7528\u5d4c\u5957\u5faa\u73af\u6765\u8f93\u51fa\u6570\u5b57\u65b9\u9635\u7684\u4f8b\u5b50\uff1a<\/p>\n<\/p>\n

def print_square_matrix(n):<\/p>\n
    for i in range(n):<\/p>\n
        for j in range(n):<\/p>\n
            print(f'{i * n + j + 1:2}', end=' ')<\/p>\n
        print()<\/p>\n
print_square_matrix(5)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u5b9a\u4e49\u4e86\u4e00\u4e2a\u51fd\u6570print_square_matrix<\/code>\uff0c\u5b83\u63a5\u53d7\u4e00\u4e2a\u53c2\u6570n<\/code>\uff0c\u8868\u793a\u65b9\u9635\u7684\u5927\u5c0f\u3002\u6211\u4eec\u4f7f\u7528\u4e24\u4e2a\u5d4c\u5957\u7684for<\/code>\u5faa\u73af\u6765\u904d\u5386\u65b9\u9635\u7684\u6bcf\u4e00\u884c\u548c\u6bcf\u4e00\u5217\u3002\u5728\u6bcf\u6b21\u8fed\u4ee3\u4e2d\uff0c\u6211\u4eec\u8ba1\u7b97\u5f53\u524d\u5143\u7d20\u7684\u503c\u5e76\u6253\u5370\u51fa\u6765\u3002\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u6211\u4eec\u53ef\u4ee5\u8f93\u51fa\u4e00\u4e2a\u5927\u5c0f\u4e3an x n<\/code>\u7684\u6570\u5b57\u65b9\u9635\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u751f\u6210\u65b9\u9635<\/p>\n<\/p>\n
\u5217\u8868\u63a8\u5bfc\u5f0f\u662fPython\u4e2d\u4e00\u79cd\u7b80\u6d01\u800c\u5f3a\u5927\u7684\u8bed\u6cd5\u7ed3\u6784\uff0c\u5b83\u5141\u8bb8\u6211\u4eec\u4ee5\u4e00\u79cd\u7b80\u6d01\u7684\u65b9\u5f0f\u6765\u521b\u5efa\u5217\u8868\u3002\u5728\u751f\u6210\u6570\u5b57\u65b9\u9635\u65f6\uff0c\u5217\u8868\u63a8\u5bfc\u5f0f\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u7b80\u5316\u4ee3\u7801\u5e76\u63d0\u9ad8\u53ef\u8bfb\u6027\u3002<\/p>\n<\/p>\n
def generate_square_matrix(n):<\/p>\n
    return [[i * n + j + 1 for j in range(n)] for i in range(n)]<\/p>\n
matrix = generate_square_matrix(5)<\/p>\n
for row in matrix:<\/p>\n
    print(' '.join(f'{num:2}' for num in row))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u751f\u6210\u4e86\u4e00\u4e2a\u4e8c\u7ef4\u5217\u8868matrix<\/code>\uff0c\u5176\u4e2d\u6bcf\u4e2a\u5143\u7d20\u90fd\u662f\u65b9\u9635\u4e2d\u7684\u4e00\u4e2a\u6570\u5b57\u3002\u7136\u540e\uff0c\u6211\u4eec\u904d\u5386matrix<\/code>\u4e2d\u7684\u6bcf\u4e00\u884c\uff0c\u5e76\u4f7f\u7528join<\/code>\u65b9\u6cd5\u5c06\u6bcf\u884c\u7684\u5143\u7d20\u8fde\u63a5\u6210\u4e00\u4e2a\u5b57\u7b26\u4e32\u8fdb\u884c\u6253\u5370\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528NumPy\u5e93\u521b\u5efa\u548c\u8f93\u51fa\u65b9\u9635<\/p>\n<\/p>\n
NumPy\u662fPython\u4e2d\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u8bb8\u591a\u65b9\u4fbf\u7684\u51fd\u6570\u6765\u751f\u6210\u548c\u64cd\u4f5c\u77e9\u9635\u3002\u4f7f\u7528NumPy\uff0c\u6211\u4eec\u53ef\u4ee5\u66f4\u52a0\u9ad8\u6548\u5730\u751f\u6210\u548c\u8f93\u51fa\u6570\u5b57\u65b9\u9635\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
def numpy_square_matrix(n):<\/p>\n
    matrix = np.arange(1, n2 + 1).reshape(n, n)<\/p>\n
    return matrix<\/p>\n
matrix = numpy_square_matrix(5)<\/p>\n
for row in matrix:<\/p>\n
    print(' '.join(f'{num:2}' for num in row))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528NumPy\u7684arange<\/code>\u51fd\u6570\u751f\u6210\u4e00\u4e2a\u4ece1\u5230n2<\/code>\u7684\u6570\u7ec4\uff0c\u7136\u540e\u4f7f\u7528reshape<\/code>\u65b9\u6cd5\u5c06\u5176\u91cd\u5851\u4e3a\u4e00\u4e2an x n<\/code>\u7684\u77e9\u9635\u3002\u8fd9\u6837\uff0c\u6211\u4eec\u5c31\u5f97\u5230\u4e86\u4e00\u4e2a\u6570\u5b57\u65b9\u9635\uff0c\u5e76\u53ef\u4ee5\u901a\u8fc7\u904d\u5386\u77e9\u9635\u7684\u6bcf\u4e00\u884c\u6765\u8f93\u51fa\u7ed3\u679c\u3002<\/p>\n<\/p>\n
\u56db\u3001\u65b9\u9635\u7684\u5e38\u89c1\u5e94\u7528<\/p>\n<\/p>\n
\u6570\u5b57\u65b9\u9635\u5728\u8bb8\u591a\u5b9e\u9645\u5e94\u7528\u4e2d\u975e\u5e38\u6709\u7528\uff0c\u4ee5\u4e0b\u662f\u51e0\u4e2a\u5e38\u89c1\u7684\u5e94\u7528\u573a\u666f\uff1a<\/p>\n<\/p>\n
    \n
  1. \n
    \u77e9\u9635\u8fd0\u7b97<\/strong>\uff1a\u6570\u5b57\u65b9\u9635\u5e38\u7528\u4e8e\u6570\u5b66\u4e2d\u7684\u77e9\u9635\u8fd0\u7b97\uff0c\u5982\u52a0\u6cd5\u3001\u51cf\u6cd5\u3001\u4e58\u6cd5\u548c\u8f6c\u7f6e\u7b49\u3002\u901a\u8fc7\u5c06\u6570\u5b57\u65b9\u9635\u8868\u793a\u4e3a\u77e9\u9635\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u7ebf\u6027\u4ee3\u6570\u4e2d\u7684\u5404\u79cd\u65b9\u6cd5\u6765\u8fdb\u884c\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<\/li>\n
  2. \n
    \u56fe\u50cf\u5904\u7406<\/strong>\uff1a\u5728\u56fe\u50cf\u5904\u7406\u4e2d\uff0c\u56fe\u50cf\u901a\u5e38\u88ab\u8868\u793a\u4e3a\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\u6216\u77e9\u9635\uff0c\u5176\u4e2d\u6bcf\u4e2a\u5143\u7d20\u4ee3\u8868\u4e00\u4e2a\u50cf\u7d20\u7684\u989c\u8272\u503c\u3002\u901a\u8fc7\u64cd\u4f5c\u8fd9\u4e9b\u77e9\u9635\uff0c\u6211\u4eec\u53ef\u4ee5\u5b9e\u73b0\u56fe\u50cf\u7684\u65cb\u8f6c\u3001\u7f29\u653e\u3001\u5e73\u79fb\u7b49\u53d8\u6362\u3002<\/p>\n<\/p>\n<\/li>\n
  3. \n
    \u6570\u503c\u6a21\u62df<\/strong>\uff1a\u5728\u7269\u7406\u5b66\u548c\u5de5\u7a0b\u5b66\u4e2d\uff0c\u6570\u5b57\u65b9\u9635\u5e38\u7528\u4e8e\u6570\u503c\u6a21\u62df\uff0c\u5982\u6709\u9650\u5143\u5206\u6790\u548c\u6570\u503c\u79ef\u5206\u7b49\u3002\u901a\u8fc7\u5c06\u7269\u7406\u95ee\u9898\u79bb\u6563\u5316\u4e3a\u65b9\u9635\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u8ba1\u7b97\u673a\u8fdb\u884c\u9ad8\u6548\u7684\u6570\u503c\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n
    \u4e94\u3001\u603b\u7ed3<\/p>\n<\/p>\n
    \u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u6211\u4eec\u4e86\u89e3\u4e86\u5982\u4f55\u5728Python\u4e2d\u8f93\u51fa\u6570\u5b57\u65b9\u9635\u7684\u51e0\u79cd\u65b9\u6cd5\uff0c\u5305\u62ec\u4f7f\u7528\u5d4c\u5957\u5faa\u73af\u3001\u5217\u8868\u63a8\u5bfc\u5f0f\u548cNumPy\u5e93\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u52bf\u548c\u9002\u7528\u573a\u666f\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u6765\u751f\u6210\u548c\u64cd\u4f5c\u6570\u5b57\u65b9\u9635\u3002\u5e0c\u671b\u672c\u6587\u7684\u5185\u5bb9\u80fd\u591f\u5e2e\u52a9\u60a8\u66f4\u597d\u5730\u7406\u89e3\u548c\u5e94\u7528Python\u4e2d\u7684\u6570\u5b57\u65b9\u9635\u3002<\/p>\n<\/p>\n
    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
     \u5982\u4f55\u5728Python\u4e2d\u521b\u5efa\u4e00\u4e2a\u6570\u5b57\u65b9\u9635\uff1f<\/strong>
    \u5728Python\u4e2d\u521b\u5efa\u6570\u5b57\u65b9\u9635\uff0c\u53ef\u4ee5\u4f7f\u7528\u5d4c\u5957\u5faa\u73af\u6765\u751f\u6210\u4e00\u4e2a\u4e8c\u7ef4\u5217\u8868\u3002\u6bcf\u4e2a\u5217\u8868\u4e2d\u7684\u5143\u7d20\u53ef\u4ee5\u6839\u636e\u9700\u8981\u8fdb\u884c\u521d\u59cb\u5316\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u751f\u6210\u4e00\u4e2a3×3\u7684\u6570\u5b57\u65b9\u9635\uff1a  <\/p>\n
    n = 3\nmatrix = [[(i * n + j + 1) for j in range(n)] for i in range(n)]\nfor row in matrix:\n    print(row)\n<\/code><\/pre>\n
    \u8fd9\u5c06\u8f93\u51fa\u4e00\u4e2a\u5305\u542b1\u52309\u76843×3\u65b9\u9635\u3002<\/p>\n
    \u5982\u4f55\u683c\u5f0f\u5316\u8f93\u51fa\u6570\u5b57\u65b9\u9635\u7684\u6bcf\u4e00\u884c\uff1f<\/strong>
    \u4e3a\u4e86\u4f7f\u8f93\u51fa\u7684\u65b9\u9635\u770b\u8d77\u6765\u66f4\u6574\u9f50\uff0c\u53ef\u4ee5\u5728\u6253\u5370\u6bcf\u4e00\u884c\u65f6\u4f7f\u7528\u683c\u5f0f\u5316\u5b57\u7b26\u4e32\u3002\u8fd9\u6837\u53ef\u4ee5\u786e\u4fdd\u6bcf\u4e2a\u6570\u5b57\u90fd\u5360\u7528\u76f8\u540c\u7684\u7a7a\u95f4\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u6765\u683c\u5f0f\u5316\u8f93\u51fa\uff1a  <\/p>\n
    for row in matrix:\n    print(" ".join(f"{num:2}" for num in row))\n<\/code><\/pre>\n
    \u8fd9\u5c06\u8f93\u51fa\u6bcf\u4e2a\u6570\u5b57\u5360\u75282\u4e2a\u5b57\u7b26\u7684\u5bbd\u5ea6\uff0c\u4ece\u800c\u4f7f\u65b9\u9635\u6574\u9f50\u6392\u5217\u3002<\/p>\n
    \u662f\u5426\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u6765\u751f\u6210\u6570\u5b57\u65b9\u9635\uff1f<\/strong>
    NumPy\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u529f\u80fd\u6765\u5904\u7406\u6570\u7ec4\u548c\u77e9\u9635\u3002\u53ef\u4ee5\u4f7f\u7528NumPy\u7684arange<\/code>\u548creshape<\/code>\u51fd\u6570\u8f7b\u677e\u751f\u6210\u6570\u5b57\u65b9\u9635\u3002\u4f8b\u5982\uff1a  <\/p>\n
    import numpy as np\nn = 3\nmatrix = np.arange(1, n*n + 1).reshape(n, n)\nprint(matrix)\n<\/code><\/pre>\n
    \u8fd9\u6837\u5c06\u751f\u6210\u4e00\u4e2a3×3\u7684\u65b9\u9635\uff0c\u5e76\u76f4\u63a5\u4ee5\u77e9\u9635\u5f62\u5f0f\u8f93\u51fa\uff0c\u65b9\u4fbf\u540e\u7eed\u7684\u6570\u5b66\u8fd0\u7b97\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u8f93\u51fa\u6570\u5b57\u65b9\u9635\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528\u5d4c\u5957\u5faa\u73af\u3001\u5217\u8868\u63a8\u5bfc\u5f0f\u3001NumPy\u5e93\u7b49\u3002\u5176\u4e2d\uff0c\u6700\u7b80\u5355\u7684\u65b9\u6cd5\u662f\u4f7f\u7528\u5d4c\u5957 […]","protected":false},"author":3,"featured_media":954861,"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\/954857"}],"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=954857"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/954857\/revisions"}],"predecessor-version":[{"id":954863,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/954857\/revisions\/954863"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/954861"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=954857"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=954857"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=954857"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}