{"id":969798,"date":"2024-12-27T05:20:14","date_gmt":"2024-12-26T21:20:14","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/969798.html"},"modified":"2024-12-27T05:20:16","modified_gmt":"2024-12-26T21:20:16","slug":"python%e5%a6%82%e4%bd%95%e6%b1%82%e8%bd%ac%e7%bd%ae","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/969798.html","title":{"rendered":"python\u5982\u4f55\u6c42\u8f6c\u7f6e"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/24183921\/6b6400a7-2810-4d60-966c-f94ded338c2e.webp\" alt=\"python\u5982\u4f55\u6c42\u8f6c\u7f6e\" \/><\/p>\n<p><p> \u5728Python\u4e2d\uff0c\u6c42\u77e9\u9635\u7684\u8f6c\u7f6e\u4e3b\u8981\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u65b9\u6cd5\uff1a<strong>\u4f7f\u7528NumPy\u5e93\u7684<code>transpose()<\/code>\u51fd\u6570\u3001\u4f7f\u7528NumPy\u5e93\u7684.T\u5c5e\u6027\u3001\u624b\u52a8\u5b9e\u73b0\u8f6c\u7f6e\u529f\u80fd<\/strong>\u3002\u5176\u4e2d\uff0c\u4f7f\u7528NumPy\u5e93\u662f\u6700\u5e38\u89c1\u548c\u9ad8\u6548\u7684\u65b9\u6cd5\u3002\u4e0b\u9762\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u51e0\u79cd\u65b9\u6cd5\uff0c\u5e76\u63d0\u4f9b\u76f8\u5e94\u7684\u4ee3\u7801\u793a\u4f8b\u3002<\/p>\n<\/p>\n<p><p>\u4e00\u3001NUMPY\u5e93\u7684<code>transpose()<\/code>\u51fd\u6570<\/p>\n<\/p>\n<p><p>NumPy\u662fPython\u4e2d\u4e00\u4e2a\u5f3a\u5927\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\uff0c\u63d0\u4f9b\u4e86\u8bb8\u591a\u7528\u4e8e\u6570\u7ec4\u548c\u77e9\u9635\u64cd\u4f5c\u7684\u51fd\u6570\u3002\u8981\u8ba1\u7b97\u77e9\u9635\u7684\u8f6c\u7f6e\uff0c\u6700\u76f4\u63a5\u7684\u65b9\u6cd5\u5c31\u662f\u4f7f\u7528NumPy\u7684<code>transpose()<\/code>\u51fd\u6570\u3002<\/p>\n<\/p>\n<ol>\n<li><strong>\u5b89\u88c5\u4e0e\u5bfc\u5165NumPy<\/strong><\/li>\n<\/ol>\n<p><p>\u5728\u4f7f\u7528NumPy\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u786e\u4fdd\u8be5\u5e93\u5df2\u5b89\u88c5\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5NumPy\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u5728\u4ee3\u7801\u4e2d\u5bfc\u5165NumPy\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li><strong>\u4f7f\u7528<code>transpose()<\/code>\u51fd\u6570<\/strong><\/li>\n<\/ol>\n<p><p><code>transpose()<\/code>\u51fd\u6570\u53ef\u4ee5\u7528\u4e8e\u5c06\u4e00\u4e2a\u77e9\u9635\u8fdb\u884c\u8f6c\u7f6e\u3002\u793a\u4f8b\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\uff08\u77e9\u9635\uff09<\/strong><\/h2>\n<p>matrix = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n<h2><strong>\u4f7f\u7528transpose()\u51fd\u6570\u8fdb\u884c\u8f6c\u7f6e<\/strong><\/h2>\n<p>transposed_matrix = np.transpose(matrix)<\/p>\n<p>print(&quot;\u539f\u77e9\u9635\uff1a&quot;)<\/p>\n<p>print(matrix)<\/p>\n<p>print(&quot;\u8f6c\u7f6e\u77e9\u9635\uff1a&quot;)<\/p>\n<p>print(transposed_matrix)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u521b\u5efa\u4e86\u4e00\u4e2a\u4e8c\u7ef4NumPy\u6570\u7ec4\uff0c\u7136\u540e\u901a\u8fc7\u8c03\u7528<code>np.transpose()<\/code>\u51fd\u6570\u6765\u83b7\u53d6\u5176\u8f6c\u7f6e\u77e9\u9635\u3002<\/p>\n<\/p>\n<p><p>\u4e8c\u3001NUMPY\u5e93\u7684.T\u5c5e\u6027<\/p>\n<\/p>\n<p><p>\u9664\u4e86\u4f7f\u7528<code>transpose()<\/code>\u51fd\u6570\uff0cNumPy\u8fd8\u63d0\u4f9b\u4e86\u4e00\u79cd\u66f4\u7b80\u6d01\u7684\u65b9\u6cd5\u6765\u83b7\u53d6\u77e9\u9635\u7684\u8f6c\u7f6e\uff0c\u5373\u4f7f\u7528.T\u5c5e\u6027\u3002<\/p>\n<\/p>\n<ol>\n<li><strong>\u4f7f\u7528.T\u5c5e\u6027<\/strong><\/li>\n<\/ol>\n<p><p>.T\u5c5e\u6027\u662fNumPy\u6570\u7ec4\u7684\u4e00\u4e2a\u5185\u7f6e\u5c5e\u6027\uff0c\u53ef\u4ee5\u76f4\u63a5\u7528\u6765\u83b7\u53d6\u77e9\u9635\u7684\u8f6c\u7f6e\u3002\u793a\u4f8b\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\uff08\u77e9\u9635\uff09<\/strong><\/h2>\n<p>matrix = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n<h2><strong>\u4f7f\u7528.T\u5c5e\u6027\u8fdb\u884c\u8f6c\u7f6e<\/strong><\/h2>\n<p>transposed_matrix = matrix.T<\/p>\n<p>print(&quot;\u539f\u77e9\u9635\uff1a&quot;)<\/p>\n<p>print(matrix)<\/p>\n<p>print(&quot;\u8f6c\u7f6e\u77e9\u9635\uff1a&quot;)<\/p>\n<p>print(transposed_matrix)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u79cd\u65b9\u6cd5\u76f8\u5bf9\u66f4\u7b80\u5355\u548c\u76f4\u89c2\uff0c\u5c24\u5176\u662f\u5728\u4ee3\u7801\u4e2d\u591a\u6b21\u9700\u8981\u8f6c\u7f6e\u64cd\u4f5c\u65f6\uff0c\u663e\u5f97\u5c24\u4e3a\u4fbf\u5229\u3002<\/p>\n<\/p>\n<p><p>\u4e09\u3001\u624b\u52a8\u5b9e\u73b0\u8f6c\u7f6e\u529f\u80fd<\/p>\n<\/p>\n<p><p>\u5982\u679c\u4e0d\u60f3\u4f9d\u8d56NumPy\u5e93\uff0c\u4e5f\u53ef\u4ee5\u624b\u52a8\u7f16\u5199\u4ee3\u7801\u6765\u5b9e\u73b0\u77e9\u9635\u7684\u8f6c\u7f6e\u3002\u624b\u52a8\u8f6c\u7f6e\u7684\u57fa\u672c\u539f\u7406\u662f\u5c06\u77e9\u9635\u7684\u884c\u548c\u5217\u8fdb\u884c\u4ea4\u6362\u3002<\/p>\n<\/p>\n<ol>\n<li><strong>\u4e8c\u7ef4\u5217\u8868\u5b9e\u73b0\u8f6c\u7f6e<\/strong><\/li>\n<\/ol>\n<p><p>\u4e0b\u9762\u662f\u4e00\u4e2a\u624b\u52a8\u5b9e\u73b0\u77e9\u9635\u8f6c\u7f6e\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u5217\u8868\uff08\u77e9\u9635\uff09<\/p>\n<p>matrix = [[1, 2, 3], [4, 5, 6]]<\/p>\n<h2><strong>\u624b\u52a8\u8f6c\u7f6e\u77e9\u9635<\/strong><\/h2>\n<p>transposed_matrix = [[row[i] for row in matrix] for i in range(len(matrix[0]))]<\/p>\n<p>print(&quot;\u539f\u77e9\u9635\uff1a&quot;)<\/p>\n<p>print(matrix)<\/p>\n<p>print(&quot;\u8f6c\u7f6e\u77e9\u9635\uff1a&quot;)<\/p>\n<p>print(transposed_matrix)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u6765\u5b9e\u73b0\u8f6c\u7f6e\uff1a\u5916\u5c42\u5faa\u73af\u904d\u5386\u5217\u7d22\u5f15\uff0c\u5185\u5c42\u5faa\u73af\u904d\u5386\u884c\uff0c\u5e76\u4ea4\u6362\u884c\u548c\u5217\u7684\u4f4d\u7f6e\u3002<\/p>\n<\/p>\n<p><p>\u56db\u3001NUMPY\u5e93\u7684<code>swapaxes()<\/code>\u51fd\u6570<\/p>\n<\/p>\n<p><p>NumPy\u5e93\u4e2d\u8fd8\u6709\u4e00\u4e2a\u51fd\u6570<code>swapaxes()<\/code>\uff0c\u5b83\u4e5f\u53ef\u4ee5\u7528\u4e8e\u77e9\u9635\u8f6c\u7f6e\uff0c\u7279\u522b\u9002\u7528\u4e8e\u66f4\u9ad8\u7ef4\u5ea6\u7684\u6570\u7ec4\u3002<\/p>\n<\/p>\n<ol>\n<li><strong>\u4f7f\u7528<code>swapaxes()<\/code>\u51fd\u6570<\/strong><\/li>\n<\/ol>\n<p><p><code>swapaxes()<\/code>\u51fd\u6570\u7528\u4e8e\u4ea4\u6362\u6570\u7ec4\u7684\u4e24\u4e2a\u8f74\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\uff08\u77e9\u9635\uff09<\/strong><\/h2>\n<p>matrix = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n<h2><strong>\u4f7f\u7528swapaxes()\u8fdb\u884c\u8f6c\u7f6e<\/strong><\/h2>\n<p>transposed_matrix = np.swapaxes(matrix, 0, 1)<\/p>\n<p>print(&quot;\u539f\u77e9\u9635\uff1a&quot;)<\/p>\n<p>print(matrix)<\/p>\n<p>print(&quot;\u8f6c\u7f6e\u77e9\u9635\uff1a&quot;)<\/p>\n<p>print(transposed_matrix)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528<code>swapaxes()<\/code>\u51fd\u6570\u4ea4\u6362\u4e86\u7b2c0\u8f74\u548c\u7b2c1\u8f74\uff0c\u5b9e\u73b0\u4e86\u77e9\u9635\u7684\u8f6c\u7f6e\u3002<\/p>\n<\/p>\n<p><p>\u4e94\u3001\u5e94\u7528\u573a\u666f\u4e0e\u6027\u80fd\u8003\u8651<\/p>\n<\/p>\n<p><p>\u5728\u5b9e\u9645\u7684\u79d1\u5b66\u8ba1\u7b97\u548c\u6570\u636e\u5904\u7406\u8fc7\u7a0b\u4e2d\uff0c\u77e9\u9635\u8f6c\u7f6e\u662f\u4e00\u4e2a\u5e38\u89c1\u7684\u64cd\u4f5c\u3002\u5728\u9009\u62e9\u8f6c\u7f6e\u65b9\u6cd5\u65f6\uff0c\u9700\u8981\u8003\u8651\u4ee5\u4e0b\u51e0\u70b9\uff1a<\/p>\n<\/p>\n<ol>\n<li><strong>\u6027\u80fd<\/strong><\/li>\n<\/ol>\n<p><p>\u5bf9\u4e8e\u5927\u89c4\u6a21\u77e9\u9635\u7684\u8f6c\u7f6e\u64cd\u4f5c\uff0c\u4f7f\u7528NumPy\u5e93\u7684<code>transpose()<\/code>\u51fd\u6570\u6216.T\u5c5e\u6027\u662f\u6700\u4f73\u9009\u62e9\uff0c\u56e0\u4e3aNumPy\u57fa\u4e8eC\u8bed\u8a00\u5b9e\u73b0\uff0c\u5177\u6709\u9ad8\u6548\u7684\u6027\u80fd\u3002<\/p>\n<\/p>\n<ol start=\"2\">\n<li><strong>\u53ef\u8bfb\u6027<\/strong><\/li>\n<\/ol>\n<p><p>\u5728\u4ee3\u7801\u53ef\u8bfb\u6027\u65b9\u9762\uff0c\u4f7f\u7528.T\u5c5e\u6027\u662f\u6700\u7b80\u6d01\u660e\u4e86\u7684\u65b9\u6cd5\uff0c\u5c24\u5176\u662f\u5728\u4ee3\u7801\u4e2d\u9700\u8981\u591a\u6b21\u8f6c\u7f6e\u64cd\u4f5c\u65f6\u3002<\/p>\n<\/p>\n<ol start=\"3\">\n<li><strong>\u517c\u5bb9\u6027<\/strong><\/li>\n<\/ol>\n<p><p>\u5982\u679c\u4f60\u7684\u9879\u76ee\u4e2d\u6ca1\u6709\u4f7f\u7528NumPy\u5e93\uff0c\u53ef\u4ee5\u9009\u62e9\u624b\u52a8\u5b9e\u73b0\u8f6c\u7f6e\uff0c\u4f46\u8fd9\u79cd\u65b9\u6cd5\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u65f6\u6027\u80fd\u8f83\u5dee\u3002<\/p>\n<\/p>\n<ol start=\"4\">\n<li><strong>\u9ad8\u7ef4\u6570\u7ec4<\/strong><\/li>\n<\/ol>\n<p><p>\u5bf9\u4e8e\u4e09\u7ef4\u6216\u66f4\u9ad8\u7ef4\u5ea6\u7684\u6570\u7ec4\uff0c<code>swapaxes()<\/code>\u51fd\u6570\u63d0\u4f9b\u4e86\u7075\u6d3b\u7684\u8f74\u4ea4\u6362\u529f\u80fd\uff0c\u53ef\u4ee5\u7528\u4e8e\u66f4\u590d\u6742\u7684\u8f6c\u7f6e\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><p>\u7efc\u4e0a\u6240\u8ff0\uff0cPython\u4e2d\u6c42\u8f6c\u7f6e\u7684\u65b9\u6cd5\u591a\u79cd\u591a\u6837\uff0c\u6839\u636e\u5177\u4f53\u7684\u5e94\u7528\u573a\u666f\u548c\u9700\u6c42\uff0c\u53ef\u4ee5\u9009\u62e9\u6700\u5408\u9002\u7684\u65b9\u6cd5\u8fdb\u884c\u64cd\u4f5c\u3002\u901a\u8fc7\u5bf9\u6bd4\u8fd9\u4e9b\u65b9\u6cd5\u7684\u4f18\u7f3a\u70b9\uff0c\u53ef\u4ee5\u5e2e\u52a9\u5f00\u53d1\u8005\u5728\u5b9e\u9645\u9879\u76ee\u4e2d\u505a\u51fa\u66f4\u597d\u7684\u51b3\u7b56\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u5b9e\u73b0\u77e9\u9635\u7684\u8f6c\u7f6e\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u6765\u8f7b\u677e\u5b9e\u73b0\u77e9\u9635\u7684\u8f6c\u7f6e\u3002\u9996\u5148\uff0c\u9700\u8981\u5b89\u88c5NumPy\u5e93\uff0c\u5b89\u88c5\u540e\u53ef\u4ee5\u4f7f\u7528<code>numpy.transpose()<\/code>\u51fd\u6570\u6765\u8f6c\u7f6e\u4e00\u4e2a\u6570\u7ec4\u3002\u4f8b\u5982\uff0c\u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\u5e76\u8c03\u7528\u8be5\u51fd\u6570\u5373\u53ef\u83b7\u5f97\u8f6c\u7f6e\u7ed3\u679c\u3002<\/p>\n<p><strong>NumPy\u5e93\u662f\u5426\u662f\u8fdb\u884c\u77e9\u9635\u8f6c\u7f6e\u7684\u552f\u4e00\u9009\u62e9\uff1f<\/strong><br \/>\u867d\u7136NumPy\u5e93\u662f\u8f6c\u7f6e\u77e9\u9635\u7684\u5e38\u7528\u5de5\u5177\uff0c\u4f46Python\u7684\u539f\u751f\u5217\u8868\u4e5f\u53ef\u4ee5\u5b9e\u73b0\u8f6c\u7f6e\u529f\u80fd\u3002\u901a\u8fc7\u5217\u8868\u63a8\u5bfc\u5f0f\uff0c\u53ef\u4ee5\u5c06\u539f\u59cb\u77e9\u9635\u7684\u884c\u4e0e\u5217\u4e92\u6362\u3002\u4f8b\u5982\uff0c\u5bf9\u4e8e\u4e00\u4e2a\u4e8c\u7ef4\u5217\u8868\uff0c\u53ef\u4ee5\u4f7f\u7528<code>[[row[i] for row in matrix] for i in range(len(matrix[0]))]<\/code>\u6765\u5b9e\u73b0\u8f6c\u7f6e\u3002<\/p>\n<p><strong>\u5728\u8f6c\u7f6e\u77e9\u9635\u65f6\uff0c\u5982\u4f55\u5904\u7406\u4e0d\u89c4\u5219\u7684\u4e8c\u7ef4\u5217\u8868\uff1f<\/strong><br \/>\u5bf9\u4e8e\u4e0d\u89c4\u5219\u7684\u4e8c\u7ef4\u5217\u8868\uff0c\u8f6c\u7f6e\u8fc7\u7a0b\u53ef\u80fd\u4f1a\u9047\u5230\u95ee\u9898\uff0c\u56e0\u4e3a\u4e0d\u540c\u884c\u7684\u957f\u5ea6\u4e0d\u540c\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u5efa\u8bae\u5148\u5c06\u5176\u6807\u51c6\u5316\u4e3a\u4e00\u4e2a\u89c4\u5219\u7684\u77e9\u9635\uff0c\u5373\u6240\u6709\u5b50\u5217\u8868\u7684\u957f\u5ea6\u76f8\u540c\uff0c\u7136\u540e\u518d\u4f7f\u7528\u4e0a\u8ff0\u65b9\u6cd5\u8fdb\u884c\u8f6c\u7f6e\u3002\u5426\u5219\uff0c\u8f6c\u7f6e\u64cd\u4f5c\u53ef\u80fd\u4f1a\u5f15\u53d1\u9519\u8bef\u6216\u5f97\u5230\u610f\u60f3\u4e0d\u5230\u7684\u7ed3\u679c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u6c42\u77e9\u9635\u7684\u8f6c\u7f6e\u4e3b\u8981\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u65b9\u6cd5\uff1a\u4f7f\u7528NumPy\u5e93\u7684transpose()\u51fd\u6570\u3001\u4f7f\u7528Nu [&hellip;]","protected":false},"author":3,"featured_media":969804,"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\/969798"}],"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=969798"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/969798\/revisions"}],"predecessor-version":[{"id":969807,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/969798\/revisions\/969807"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/969804"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=969798"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=969798"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=969798"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}