{"id":175401,"date":"2024-05-08T18:50:57","date_gmt":"2024-05-08T10:50:57","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/175401.html"},"modified":"2024-05-08T18:51:11","modified_gmt":"2024-05-08T10:51:11","slug":"python-numpy-%e6%95%b0%e7%bb%84%e5%a6%82%e4%bd%95%e5%af%b9%e6%af%8f%e4%b8%aa%e5%85%83%e7%b4%a0%e8%bf%9b%e8%a1%8c%e6%93%8d%e4%bd%9c","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/175401.html","title":{"rendered":"python numpy \u6570\u7ec4\u5982\u4f55\u5bf9\u6bcf\u4e2a\u5143\u7d20\u8fdb\u884c\u64cd\u4f5c"},"content":{"rendered":"<p style=\"text-align:center\"><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/27053219\/27b39ec9-41cb-4baf-b1be-cb9332ca9393.webp\" alt=\"python numpy \u6570\u7ec4\u5982\u4f55\u5bf9\u6bcf\u4e2a\u5143\u7d20\u8fdb\u884c\u64cd\u4f5c\" \/><\/p>\n<p><p><strong>Python NumPy \u6570\u7ec4\u53ef\u4ee5\u901a\u8fc7\u901a\u7528\u51fd\u6570\uff08ufuncs\uff09\u3001\u6570\u7ec4\u5e7f\u64ad\u3001\u7d22\u5f15\u548c\u5207\u7247\u64cd\u4f5c\u3001\u4ee5\u53ca\u5411\u91cf\u5316\u7684\u6570\u503c\u65b9\u6cd5\u5bf9\u6bcf\u4e00\u4e2a\u5143\u7d20\u8fdb\u884c\u64cd\u4f5c<\/strong>\u3002\u8fd9\u4e9b\u64cd\u4f5c\u5141\u8bb8\u6267\u884c\u9ad8\u6548\u7684\u5143\u7d20\u7ea7\u8ba1\u7b97\uff0c\u4e0e\u7eafPython\u5faa\u73af\u76f8\u6bd4\uff0c\u6267\u884c\u901f\u5ea6\u66f4\u5feb\u3001\u4ee3\u7801\u66f4\u7b80\u6d01\u3002\u7279\u522b\u662f\u901a\u8fc7<strong>\u901a\u7528\u51fd\u6570<\/strong>\u6267\u884c\u6570\u5b66\u8fd0\u7b97\u65f6\uff0c\u53ef\u4ee5\u76f4\u63a5\u5c06\u64cd\u4f5c\u5e94\u7528\u4e8e\u6574\u4e2a\u6570\u7ec4\uff0c\u65e0\u9700\u7f16\u5199\u663e\u5f0f\u5faa\u73af\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u901a\u7528\u51fd\u6570\uff08Universal Functions\uff09<\/h3>\n<\/p>\n<p><p>NumPy\u63d0\u4f9b\u4e86\u4e00\u7cfb\u5217\u7684\u5185\u7f6e\u51fd\u6570\uff0c\u79f0\u4e3a\u901a\u7528\u51fd\u6570\uff08ufuncs\uff09\uff0c\u7528\u4e8e\u6267\u884c\u5143\u7d20\u7ea7\u522b\u7684\u64cd\u4f5c\u3002\u8fd9\u4e9b\u51fd\u6570\u662f\u4f18\u5316\u8fc7\u7684\u3001\u7f16\u8bd1\u7ea7\u7684\u51fd\u6570\uff0c\u80fd\u591f\u63d0\u4f9b\u5728\u6574\u4e2a\u6570\u7ec4\u4e0a\u5e7f\u6cdb\u8fd0\u7b97\u7684\u80fd\u529b\u3002<\/p>\n<\/p>\n<p><h4>1. \u6570\u5b66\u8fd0\u7b97<\/h4>\n<\/p>\n<p><p>\u4f8b\u5982\uff0c\u5bf9\u6570\u7ec4\u4e2d\u7684\u6bcf\u4e2a\u5143\u7d20\u6267\u884c\u6570\u5b66\u8fd0\u7b97\uff0c\u5982\u52a0\u6cd5\u3001\u51cf\u6cd5\u3001\u4e58\u6cd5\u548c\u9664\u6cd5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u7b80\u5355\u7684\u6570\u7ec4<\/strong><\/h2>\n<p>arr = np.array([1, 2, 3, 4])<\/p>\n<h2><strong>\u52a0\u6cd5\uff1a\u5bf9\u6bcf\u4e2a\u5143\u7d20\u52a05<\/strong><\/h2>\n<p>arr_add = arr + 5<\/p>\n<h2><strong>\u51cf\u6cd5\uff1a\u5bf9\u6bcf\u4e2a\u5143\u7d20\u51cf2<\/strong><\/h2>\n<p>arr_sub = arr - 2<\/p>\n<h2><strong>\u4e58\u6cd5\uff1a\u5bf9\u6bcf\u4e2a\u5143\u7d20\u4e58\u4ee510<\/strong><\/h2>\n<p>arr_mul = arr * 10<\/p>\n<h2><strong>\u9664\u6cd5\uff1a\u5bf9\u6bcf\u4e2a\u5143\u7d20\u9664\u4ee53<\/strong><\/h2>\n<p>arr_div = arr \/ 3<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2. \u4e09\u89d2\u51fd\u6570<\/h4>\n<\/p>\n<p><p>\u4f60\u4e5f\u53ef\u4ee5\u5bf9\u6bcf\u4e2a\u5143\u7d20\u6267\u884c\u4e09\u89d2\u51fd\u6570\u64cd\u4f5c\uff0c\u5982\u6c42\u6b63\u5f26\u3001\u4f59\u5f26\u3001\u6b63\u5207\u7b49\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u6b63\u5f26\u51fd\u6570<\/p>\n<p>arr_sin = np.sin(arr)<\/p>\n<h2><strong>\u4f59\u5f26\u51fd\u6570<\/strong><\/h2>\n<p>arr_cos = np.cos(arr)<\/p>\n<h2><strong>\u6b63\u5207\u51fd\u6570<\/strong><\/h2>\n<p>arr_tan = np.tan(arr)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e8c\u3001\u6570\u7ec4\u5e7f\u64ad<\/h3>\n<\/p>\n<p><p>\u6570\u7ec4\u5e7f\u64ad\uff08Broadcasting\uff09\u662fNumPy\u7684\u4e00\u4e2a\u5f3a\u5927\u7279\u6027\uff0c\u8ba9\u4e0d\u540c\u5f62\u72b6\u7684\u6570\u7ec4\u4e4b\u95f4\u53ef\u4ee5\u6267\u884c\u7b97\u672f\u8fd0\u7b97\u3002<\/p>\n<\/p>\n<p><h4>1. \u5e7f\u64ad\u89c4\u5219<\/h4>\n<\/p>\n<p><p>\u53ea\u8981\u6570\u7ec4\u7684\u7ef4\u5ea6\u517c\u5bb9\uff0c\u5e7f\u64ad\u673a\u5236\u5141\u8bb8NumPy\u81ea\u52a8\u6269\u5c55\u8f83\u5c0f\u7684\u6570\u7ec4\uff0c\u4ee5\u9002\u5e94\u8f83\u5927\u6570\u7ec4\u7684\u5f62\u72b6\u3002<\/p>\n<\/p>\n<p><h4>2. \u5e94\u7528\u793a\u4f8b<\/h4>\n<\/p>\n<p><p>\u5047\u8bbe\u6211\u4eec\u60f3\u8981\u5c06\u4e00\u4e2a\u5e38\u6570\u503c\u52a0\u5230\u4e00\u4e2a\u77e9\u9635\u7684\u6bcf\u4e2a\u5143\u7d20\u4e2d\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u521b\u5efa\u4e00\u4e2a3x3\u7684\u77e9\u9635<\/p>\n<p>matrix = np.array([[1, 2, 3],<\/p>\n<p>                   [4, 5, 6],<\/p>\n<p>                   [7, 8, 9]])<\/p>\n<h2><strong>\u5c06\u503c2\u5e7f\u64ad\u5230\u77e9\u9635\u7684\u6bcf\u4e2a\u5143\u7d20<\/strong><\/h2>\n<p>result = matrix + 2<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e09\u3001\u7d22\u5f15\u548c\u5207\u7247\u64cd\u4f5c<\/h3>\n<\/p>\n<p><p>\u901a\u8fc7\u7d22\u5f15\u548c\u5207\u7247\uff0c\u53ef\u4ee5\u9009\u53d6\u6570\u7ec4\u4e2d\u60f3\u8981\u64cd\u4f5c\u7684\u5143\u7d20\u6216\u5b50\u6570\u7ec4\uff0c\u5e76\u5bf9\u5b83\u4eec\u8fdb\u884c\u4fee\u6539\u3002<\/p>\n<\/p>\n<p><h4>1. \u7d22\u5f15<\/h4>\n<\/p>\n<p><p>\u7d22\u5f15\u53ef\u4ee5\u7528\u6765\u9009\u62e9\u6570\u7ec4\u4e2d\u7684\u7279\u5b9a\u5143\u7d20\uff0c\u5e76\u5bf9\u5176\u6267\u884c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><h4>2. \u5207\u7247<\/h4>\n<\/p>\n<p><p>\u5207\u7247\u7528\u4e8e\u9009\u62e9\u6570\u7ec4\u7684\u4e00\u4e2a\u533a\u57df\uff0c\u5e76\u5bf9\u8be5\u533a\u57df\u5185\u7684\u6240\u6709\u5143\u7d20\u8fdb\u884c\u76f8\u540c\u7684\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u9009\u53d6\u6570\u7ec4\u7684\u7b2c\u4e8c\u884c<\/p>\n<p>second_row = matrix[1, :]<\/p>\n<h2><strong>\u9009\u53d6\u6570\u7ec4\u7684\u7b2c\u4e09\u5217<\/strong><\/h2>\n<p>third_column = matrix[:, 2]<\/p>\n<h2><strong>\u5bf9\u9009\u62e9\u7684\u533a\u57df\u8fdb\u884c\u64cd\u4f5c<\/strong><\/h2>\n<p>matrix[1, :] *= 2<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u56db\u3001\u5411\u91cf\u5316\u65b9\u6cd5<\/h3>\n<\/p>\n<p><p>\u5411\u91cf\u5316\u65b9\u6cd5\u901a\u8fc7\u5e94\u7528\u5185\u7f6e\u7684NumPy\u51fd\u6570\u6765\u907f\u514d\u663e\u5f0f\u5faa\u73af\uff0c\u8fdb\u884c\u6570\u7ec4\u64cd\u4f5c\uff0c\u5e76\u4e14\u901a\u5e38\u6267\u884c\u5f97\u66f4\u5feb\u3002<\/p>\n<\/p>\n<p><h4>1. \u5411\u91cf\u5316\u64cd\u4f5c\u793a\u4f8b<\/h4>\n<\/p>\n<p><p>\u82e5\u8981\u5728\u4e00\u4e2a\u6570\u7ec4\u4e2d\u627e\u5230\u6240\u6709\u6b63\u6570\u5143\u7d20\u7684\u5012\u6570\uff0c\u53ef\u4ee5\u4f7f\u7528\u5411\u91cf\u5316\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><h4>2. \u5e94\u7528\u5b9e\u4f8b<\/h4>\n<\/p>\n<p><pre><code class=\"language-python\"># \u521b\u5efa\u4e00\u4e2a\u6570\u7ec4<\/p>\n<p>arr_vect = np.array([-1, 2, -3, 4])<\/p>\n<h2><strong>\u4f7f\u7528\u6761\u4ef6\u8868\u8fbe\u5f0f\u548c\u5411\u91cf\u5316\u64cd\u4f5c<\/strong><\/h2>\n<p>inverse_positives = np.where(arr_vect &gt; 0, 1 \/ arr_vect, arr_vect)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e94\u3001\u77e9\u9635\u548c\u5411\u91cf\u8fd0\u7b97<\/h3>\n<\/p>\n<p><p>\u9664\u4e86\u5143\u7d20\u7ea7\u7684\u64cd\u4f5c\u4e4b\u5916\uff0cNumPy\u4e5f\u652f\u6301\u77e9\u9635\u4e58\u6cd5\u3001\u70b9\u79ef\u7b49\u7ebf\u6027\u4ee3\u6570\u8fd0\u7b97\uff0c\u8fd9\u4e9b\u8fd0\u7b97\u5728\u8bb8\u591a\u60c5\u51b5\u4e0b\u6d89\u53ca\u5230\u5143\u7d20\u7ea7\u7684\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<p><h4>1. \u77e9\u9635\u4e58\u6cd5<\/h4>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<code>np.dot<\/code>\u51fd\u6570\u6216\u8005<code>@<\/code>\u8fd0\u7b97\u7b26\u6765\u8fdb\u884c\u77e9\u9635\u4e58\u6cd5\u3002<\/p>\n<\/p>\n<p><h4>2. \u70b9\u79ef<\/h4>\n<\/p>\n<p><p>\u70b9\u79ef\u662f\u53e6\u4e00\u79cd\u5728\u6570\u7ec4\u6216\u77e9\u9635\u4e2d\u6d89\u53ca\u5143\u7d20\u7ea7\u522b\u8fd0\u7b97\u7684\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5b9a\u4e49\u4e24\u4e2a\u77e9\u9635<\/p>\n<p>matrix_a = np.array([[1, 2],<\/p>\n<p>                     [3, 4]])<\/p>\n<p>matrix_b = np.array([[5, 6],<\/p>\n<p>                     [7, 8]])<\/p>\n<h2><strong>\u77e9\u9635\u4e58\u6cd5<\/strong><\/h2>\n<p>matrix_product = np.dot(matrix_a, matrix_b)<\/p>\n<h2><strong>\u53e6\u4e00\u79cd\u77e9\u9635\u4e58\u6cd5<\/strong><\/h2>\n<p>matrix_product_alt = matrix_a @ matrix_b<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u7406\u89e3\u548c\u8fd0\u7528\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u53ef\u4ee5\u4f7f\u5f97\u5bf9NumPy\u6570\u7ec4\u4e2d\u7684\u6bcf\u4e2a\u5143\u7d20\u8fdb\u884c\u64cd\u4f5c\u7684\u8fc7\u7a0b\u66f4\u9ad8\u6548\u548c\u7b80\u6d01\u3002\u65e0\u8bba\u662f\u8fdb\u884c\u7b80\u5355\u7684\u6570\u5b66\u8fd0\u7b97\uff0c\u8fd8\u662f\u66f4\u590d\u6742\u7684\u6570\u636e\u53d8\u6362\uff0cNumPy\u90fd\u63d0\u4f9b\u4e86\u5f3a\u5927\u800c\u65b9\u4fbf\u7684\u5de5\u5177\u6765\u6267\u884c\u8fd9\u4e9b\u4efb\u52a1\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p><strong>\u5982\u4f55\u5728Python\u7684numpy\u6570\u7ec4\u4e2d\u5bf9\u6bcf\u4e2a\u5143\u7d20\u8fdb\u884c\u64cd\u4f5c\uff1f<\/strong><\/p>\n<ol>\n<li><strong>\u5982\u4f55\u5bf9numpy\u6570\u7ec4\u4e2d\u7684\u5143\u7d20\u8fdb\u884c\u52a0\u6cd5\u8fd0\u7b97\uff1f<\/strong><\/li>\n<\/ol>\n<p>\u8981\u5bf9numpy\u6570\u7ec4\u4e2d\u7684\u6bcf\u4e2a\u5143\u7d20\u8fdb\u884c\u52a0\u6cd5\u8fd0\u7b97\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528numpy\u7684\u77e2\u91cf\u5316\u64cd\u4f5c\u529f\u80fd\u3002\u4f8b\u5982\uff0c\u5982\u679c\u60a8\u6709\u4e24\u4e2anumpy\u6570\u7ec4a\u548cb\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7\u6267\u884c\u64cd\u4f5c<code>result = a + b<\/code>\u6765\u5c06\u5b83\u4eec\u7684\u5bf9\u5e94\u5143\u7d20\u76f8\u52a0\u5e76\u5c06\u7ed3\u679c\u5b58\u50a8\u5728\u7ed3\u679c\u6570\u7ec4result\u4e2d\u3002<\/p>\n<ol start=\"2\">\n<li><strong>\u5982\u4f55\u5bf9numpy\u6570\u7ec4\u4e2d\u7684\u5143\u7d20\u8fdb\u884c\u4e58\u6cd5\u8fd0\u7b97\uff1f<\/strong><\/li>\n<\/ol>\n<p>\u7c7b\u4f3c\u4e8e\u52a0\u6cd5\u8fd0\u7b97\uff0c\u8981\u5bf9numpy\u6570\u7ec4\u4e2d\u7684\u5143\u7d20\u6267\u884c\u4e58\u6cd5\u8fd0\u7b97\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528numpy\u7684\u77e2\u91cf\u5316\u64cd\u4f5c\u529f\u80fd\u3002\u4f8b\u5982\uff0c\u5982\u679c\u60a8\u6709\u4e24\u4e2anumpy\u6570\u7ec4a\u548cb\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7\u6267\u884c\u64cd\u4f5c<code>result = a * b<\/code>\u6765\u5c06\u5b83\u4eec\u7684\u5bf9\u5e94\u5143\u7d20\u76f8\u4e58\u5e76\u5c06\u7ed3\u679c\u5b58\u50a8\u5728\u7ed3\u679c\u6570\u7ec4result\u4e2d\u3002<\/p>\n<ol start=\"3\">\n<li><strong>\u5982\u4f55\u5bf9numpy\u6570\u7ec4\u4e2d\u7684\u5143\u7d20\u6267\u884c\u81ea\u5b9a\u4e49\u51fd\u6570\u64cd\u4f5c\uff1f<\/strong><\/li>\n<\/ol>\n<p>\u5982\u679c\u60a8\u60f3\u5bf9numpy\u6570\u7ec4\u4e2d\u7684\u6bcf\u4e2a\u5143\u7d20\u6267\u884c\u81ea\u5b9a\u4e49\u51fd\u6570\u64cd\u4f5c\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528numpy\u7684<code>np.vectorize<\/code>\u51fd\u6570\u3002\u8fd9\u4e2a\u51fd\u6570\u53ef\u4ee5\u5c06\u4e00\u4e2a\u5e38\u89c4\u7684Python\u51fd\u6570\u8f6c\u5316\u4e3a\u4e00\u4e2a\u80fd\u591f\u5728\u6574\u4e2anumpy\u6570\u7ec4\u4e0a\u8fdb\u884c\u64cd\u4f5c\u7684\u77e2\u91cf\u5316\u51fd\u6570\u3002\u4f8b\u5982\uff0c\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\u7247\u6bb5\uff0c\u6f14\u793a\u5982\u4f55\u5c06\u4e00\u4e2a\u81ea\u5b9a\u4e49\u51fd\u6570\u5e94\u7528\u4e8enumpy\u6570\u7ec4\uff1a<\/p>\n<pre><code>import numpy as np\n\n# \u5b9a\u4e49\u4e00\u4e2a\u81ea\u5b9a\u4e49\u51fd\u6570\ndef custom_function(x):\n    return x**2 + 1\n\n# \u5c06\u81ea\u5b9a\u4e49\u51fd\u6570\u8f6c\u5316\u4e3a\u77e2\u91cf\u5316\u51fd\u6570\nvectorized_function = np.vectorize(custom_function)\n\n# \u521b\u5efa\u4e00\u4e2anumpy\u6570\u7ec4\na = np.array([1, 2, 3, 4, 5])\n\n# \u5c06\u81ea\u5b9a\u4e49\u51fd\u6570\u5e94\u7528\u4e8enumpy\u6570\u7ec4\u7684\u6bcf\u4e2a\u5143\u7d20\nresult = vectorized_function(a)\n\nprint(result)\n<\/code><\/pre>\n<p>\u4e0a\u8ff0\u4ee3\u7801\u5c06\u5bf9numpy\u6570\u7ec4a\u4e2d\u7684\u6bcf\u4e2a\u5143\u7d20\u6267\u884c\u81ea\u5b9a\u4e49\u51fd\u6570custom_function\uff0c\u5e76\u5c06\u7ed3\u679c\u5b58\u50a8\u5728\u65b0\u7684numpy\u6570\u7ec4result\u4e2d\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python NumPy \u6570\u7ec4\u53ef\u4ee5\u901a\u8fc7\u901a\u7528\u51fd\u6570\uff08ufuncs\uff09\u3001\u6570\u7ec4\u5e7f\u64ad\u3001\u7d22\u5f15\u548c\u5207\u7247\u64cd\u4f5c\u3001\u4ee5\u53ca\u5411\u91cf\u5316\u7684\u6570\u503c\u65b9\u6cd5 [&hellip;]","protected":false},"author":3,"featured_media":175430,"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\/175401"}],"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=175401"}],"version-history":[{"count":0,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/175401\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/175430"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=175401"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=175401"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=175401"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}