{"id":1072696,"date":"2025-01-08T11:18:26","date_gmt":"2025-01-08T03:18:26","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1072696.html"},"modified":"2025-01-08T11:18:29","modified_gmt":"2025-01-08T03:18:29","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e5%af%b9nc%e6%96%87%e4%bb%b6%e8%bf%9b%e8%a1%8c%e7%bc%96%e8%be%91-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1072696.html","title":{"rendered":"\u5982\u4f55\u7528Python\u5bf9nc\u6587\u4ef6\u8fdb\u884c\u7f16\u8f91"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25102826\/96f45ada-91c9-4e7a-9121-58ed9b89e521.webp\" alt=\"\u5982\u4f55\u7528Python\u5bf9nc\u6587\u4ef6\u8fdb\u884c\u7f16\u8f91\" \/><\/p>\n<p><p> <strong>\u5982\u4f55\u7528Python\u5bf9nc\u6587\u4ef6\u8fdb\u884c\u7f16\u8f91<\/strong><\/p>\n<\/p>\n<p><p><strong>\u8981\u7528Python\u5bf9nc\u6587\u4ef6\u8fdb\u884c\u7f16\u8f91\uff0c\u53ef\u4ee5\u4f7f\u7528Python\u7684netCDF4\u5e93\u3001\u4f7f\u7528\u53d8\u91cf\u4e0e\u5c5e\u6027\u7f16\u8f91\u3001\u4f7f\u7528\u6570\u636e\u8bfb\u53d6\u4e0e\u5199\u5165\u529f\u80fd<\/strong>\u3002\u9996\u5148\u9700\u8981\u5b89\u88c5\u5e76\u5bfc\u5165netCDF4\u5e93\uff0c\u7136\u540e\u6253\u5f00nc\u6587\u4ef6\u8fdb\u884c\u7f16\u8f91\u3002\u5728\u7f16\u8f91\u8fc7\u7a0b\u4e2d\uff0c\u53ef\u4ee5\u4fee\u6539\u5df2\u6709\u7684\u53d8\u91cf\u548c\u5c5e\u6027\uff0c\u6216\u8005\u6dfb\u52a0\u65b0\u7684\u53d8\u91cf\u548c\u5c5e\u6027\u3002\u63a5\u4e0b\u6765\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u529f\u80fd\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u5b89\u88c5\u4e0e\u5bfc\u5165netCDF4\u5e93<\/h3>\n<\/p>\n<p><p>\u4e3a\u4e86\u5728Python\u4e2d\u5904\u7406.nc\u6587\u4ef6\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5netCDF4\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install netCDF4<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165\u8be5\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import netCDF4 as nc<\/p>\n<p>import numpy as np<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e8c\u3001\u6253\u5f00\u4e0e\u8bfb\u53d6.nc\u6587\u4ef6<\/h3>\n<\/p>\n<p><p>\u8981\u7f16\u8f91.nc\u6587\u4ef6\uff0c\u9996\u5148\u9700\u8981\u6253\u5f00\u5e76\u8bfb\u53d6\u6587\u4ef6\u5185\u5bb9\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u6253\u5f00.nc\u6587\u4ef6<\/p>\n<p>dataset = nc.Dataset(&#39;example.nc&#39;, &#39;r+&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u91cc\u7684&#39;r+&#39;\u8868\u793a\u6587\u4ef6\u4ee5\u8bfb\u5199\u6a21\u5f0f\u6253\u5f00\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u67e5\u770b\u6587\u4ef6\u5185\u5bb9<\/h3>\n<\/p>\n<p><p>\u5728\u7f16\u8f91.nc\u6587\u4ef6\u4e4b\u524d\uff0c\u53ef\u4ee5\u67e5\u770b\u6587\u4ef6\u5185\u5bb9\uff0c\u5305\u62ec\u5168\u5c40\u5c5e\u6027\u3001\u7ef4\u5ea6\u3001\u53d8\u91cf\u548c\u53d8\u91cf\u5c5e\u6027\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u67e5\u770b\u5168\u5c40\u5c5e\u6027<\/p>\n<p>print(dataset.ncattrs())<\/p>\n<h2><strong>\u67e5\u770b\u7ef4\u5ea6<\/strong><\/h2>\n<p>print(dataset.dimensions)<\/p>\n<h2><strong>\u67e5\u770b\u53d8\u91cf<\/strong><\/h2>\n<p>print(dataset.variables)<\/p>\n<h2><strong>\u67e5\u770b\u53d8\u91cf\u5c5e\u6027<\/strong><\/h2>\n<p>var = dataset.variables[&#39;variable_name&#39;]<\/p>\n<p>print(var.ncattrs())<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u56db\u3001\u7f16\u8f91\u53d8\u91cf\u4e0e\u5c5e\u6027<\/h3>\n<\/p>\n<p><h4>1\u3001\u4fee\u6539\u5df2\u6709\u53d8\u91cf<\/h4>\n<\/p>\n<p><p>\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u4fee\u6539\u5df2\u6709\u53d8\u91cf\u7684\u6570\u636e\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u83b7\u53d6\u53d8\u91cf<\/p>\n<p>var = dataset.variables[&#39;variable_name&#39;]<\/p>\n<h2><strong>\u4fee\u6539\u53d8\u91cf\u6570\u636e<\/strong><\/h2>\n<p>data = var[:]<\/p>\n<p>data[:] = np.array([1, 2, 3, 4, 5])<\/p>\n<p>var[:] = data<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u4fee\u6539\u53d8\u91cf\u5c5e\u6027<\/h4>\n<\/p>\n<p><p>\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u4fee\u6539\u53d8\u91cf\u7684\u5c5e\u6027\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u4fee\u6539\u53d8\u91cf\u5c5e\u6027<\/p>\n<p>var.setncattr(&#39;units&#39;, &#39;new_units&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3\u3001\u6dfb\u52a0\u65b0\u53d8\u91cf<\/h4>\n<\/p>\n<p><p>\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u6dfb\u52a0\u65b0\u53d8\u91cf\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5b9a\u4e49\u65b0\u53d8\u91cf<\/p>\n<p>new_var = dataset.createVariable(&#39;new_variable&#39;, np.float32, (&#39;dimension_name&#39;,))<\/p>\n<h2><strong>\u8bbe\u7f6e\u65b0\u53d8\u91cf\u5c5e\u6027<\/strong><\/h2>\n<p>new_var.units = &#39;new_units&#39;<\/p>\n<h2><strong>\u8bbe\u7f6e\u65b0\u53d8\u91cf\u6570\u636e<\/strong><\/h2>\n<p>new_var[:] = np.array([1.0, 2.0, 3.0, 4.0, 5.0])<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>4\u3001\u6dfb\u52a0\u65b0\u5c5e\u6027<\/h4>\n<\/p>\n<p><p>\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u6dfb\u52a0\u65b0\u5c5e\u6027\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u6dfb\u52a0\u65b0\u5c5e\u6027<\/p>\n<p>dataset.setncattr(&#39;new_attribute&#39;, &#39;new_value&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e94\u3001\u4fdd\u5b58\u5e76\u5173\u95ed\u6587\u4ef6<\/h3>\n<\/p>\n<p><p>\u5b8c\u6210\u7f16\u8f91\u540e\uff0c\u9700\u8981\u4fdd\u5b58\u5e76\u5173\u95ed\u6587\u4ef6\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u4fdd\u5b58\u5e76\u5173\u95ed\u6587\u4ef6<\/p>\n<p>dataset.close()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u516d\u3001\u793a\u4f8b\u4ee3\u7801<\/h3>\n<\/p>\n<p><p>\u4ee5\u4e0b\u662f\u4e00\u4e2a\u5b8c\u6574\u7684\u793a\u4f8b\u4ee3\u7801\uff0c\u6f14\u793a\u4e86\u5982\u4f55\u7528Python\u5bf9.nc\u6587\u4ef6\u8fdb\u884c\u7f16\u8f91\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import netCDF4 as nc<\/p>\n<p>import numpy as np<\/p>\n<h2><strong>\u6253\u5f00.nc\u6587\u4ef6<\/strong><\/h2>\n<p>dataset = nc.Dataset(&#39;example.nc&#39;, &#39;r+&#39;)<\/p>\n<h2><strong>\u67e5\u770b\u5168\u5c40\u5c5e\u6027<\/strong><\/h2>\n<p>print(dataset.ncattrs())<\/p>\n<h2><strong>\u67e5\u770b\u7ef4\u5ea6<\/strong><\/h2>\n<p>print(dataset.dimensions)<\/p>\n<h2><strong>\u67e5\u770b\u53d8\u91cf<\/strong><\/h2>\n<p>print(dataset.variables)<\/p>\n<h2><strong>\u67e5\u770b\u53d8\u91cf\u5c5e\u6027<\/strong><\/h2>\n<p>var = dataset.variables[&#39;variable_name&#39;]<\/p>\n<p>print(var.ncattrs())<\/p>\n<h2><strong>\u4fee\u6539\u5df2\u6709\u53d8\u91cf\u6570\u636e<\/strong><\/h2>\n<p>data = var[:]<\/p>\n<p>data[:] = np.array([1, 2, 3, 4, 5])<\/p>\n<p>var[:] = data<\/p>\n<h2><strong>\u4fee\u6539\u53d8\u91cf\u5c5e\u6027<\/strong><\/h2>\n<p>var.setncattr(&#39;units&#39;, &#39;new_units&#39;)<\/p>\n<h2><strong>\u5b9a\u4e49\u65b0\u53d8\u91cf<\/strong><\/h2>\n<p>new_var = dataset.createVariable(&#39;new_variable&#39;, np.float32, (&#39;dimension_name&#39;,))<\/p>\n<h2><strong>\u8bbe\u7f6e\u65b0\u53d8\u91cf\u5c5e\u6027<\/strong><\/h2>\n<p>new_var.units = &#39;new_units&#39;<\/p>\n<h2><strong>\u8bbe\u7f6e\u65b0\u53d8\u91cf\u6570\u636e<\/strong><\/h2>\n<p>new_var[:] = np.array([1.0, 2.0, 3.0, 4.0, 5.0])<\/p>\n<h2><strong>\u6dfb\u52a0\u65b0\u5c5e\u6027<\/strong><\/h2>\n<p>dataset.setncattr(&#39;new_attribute&#39;, &#39;new_value&#39;)<\/p>\n<h2><strong>\u4fdd\u5b58\u5e76\u5173\u95ed\u6587\u4ef6<\/strong><\/h2>\n<p>dataset.close()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e03\u3001\u5904\u7406\u590d\u6742.nc\u6587\u4ef6<\/h3>\n<\/p>\n<p><p>\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u66f4\u590d\u6742\u7684.nc\u6587\u4ef6\uff0c\u9700\u8981\u5904\u7406\u591a\u4e2a\u7ef4\u5ea6\u548c\u53d8\u91cf\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u5904\u7406\uff1a<\/p>\n<\/p>\n<p><h4>1\u3001\u5904\u7406\u591a\u7ef4\u5ea6\u53d8\u91cf<\/h4>\n<\/p>\n<p><pre><code class=\"language-python\"># \u83b7\u53d6\u591a\u7ef4\u5ea6\u53d8\u91cf<\/p>\n<p>var = dataset.variables[&#39;multi_dim_variable&#39;]<\/p>\n<h2><strong>\u4fee\u6539\u591a\u7ef4\u5ea6\u53d8\u91cf\u6570\u636e<\/strong><\/h2>\n<p>data = var[:, :]<\/p>\n<p>data[:, :] = np.random.rand(data.shape[0], data.shape[1])<\/p>\n<p>var[:, :] = data<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u5904\u7406\u65f6\u95f4\u7ef4\u5ea6<\/h4>\n<\/p>\n<p><pre><code class=\"language-python\"># \u83b7\u53d6\u65f6\u95f4\u53d8\u91cf<\/p>\n<p>time_var = dataset.variables[&#39;time&#39;]<\/p>\n<h2><strong>\u4fee\u6539\u65f6\u95f4\u53d8\u91cf\u6570\u636e<\/strong><\/h2>\n<p>time_var[:] = np.arange(0, len(time_var))<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u516b\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u53ef\u4ee5\u4f7f\u7528Python\u7684netCDF4\u5e93\u5bf9.nc\u6587\u4ef6\u8fdb\u884c\u7f16\u8f91\uff0c\u5305\u62ec\u4fee\u6539\u53d8\u91cf\u548c\u5c5e\u6027\u3001\u6dfb\u52a0\u65b0\u53d8\u91cf\u548c\u5c5e\u6027\u7b49\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u5bf9.nc\u6587\u4ef6\u8fdb\u884c\u66f4\u590d\u6742\u7684\u5904\u7406\u3002\u5e0c\u671b\u672c\u6587\u80fd\u591f\u5e2e\u52a9\u60a8\u66f4\u597d\u5730\u7406\u89e3\u548c\u4f7f\u7528Python\u5904\u7406.nc\u6587\u4ef6\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>Python\u53ef\u4ee5\u5982\u4f55\u5e2e\u52a9\u6211\u5904\u7406nc\u6587\u4ef6\uff1f<\/strong><br \/>Python\u63d0\u4f9b\u4e86\u591a\u4e2a\u5e93\u6765\u5904\u7406nc\u6587\u4ef6\uff08NetCDF\u683c\u5f0f\uff09\uff0c\u4f8b\u5982xarray\u548cnetCDF4\u3002\u8fd9\u4e9b\u5e93\u5141\u8bb8\u7528\u6237\u8bfb\u53d6\u3001\u7f16\u8f91\u548c\u4fdd\u5b58nc\u6587\u4ef6\u4e2d\u7684\u6570\u636e\u3002\u901a\u8fc7\u8fd9\u4e9b\u5de5\u5177\uff0c\u4f60\u53ef\u4ee5\u8f7b\u677e\u5730\u63d0\u53d6\u6570\u636e\u3001\u8fdb\u884c\u6570\u5b66\u8fd0\u7b97\u3001\u4fee\u6539\u6570\u636e\u96c6\u7684\u7ef4\u5ea6\u548c\u5c5e\u6027\u7b49\u3002<\/p>\n<p><strong>\u4f7f\u7528Python\u7f16\u8f91nc\u6587\u4ef6\u65f6\u9700\u8981\u6ce8\u610f\u54ea\u4e9b\u4e8b\u9879\uff1f<\/strong><br \/>\u5728\u7f16\u8f91nc\u6587\u4ef6\u65f6\uff0c\u786e\u4fdd\u4f60\u4e86\u89e3\u6587\u4ef6\u7684\u7ed3\u6784\u548c\u6570\u636e\u7c7b\u578b\u3002\u4e0d\u540c\u7684nc\u6587\u4ef6\u53ef\u80fd\u5177\u6709\u4e0d\u540c\u7684\u53d8\u91cf\u548c\u7ef4\u5ea6\uff0c\u4e86\u89e3\u8fd9\u4e9b\u4fe1\u606f\u53ef\u4ee5\u5e2e\u52a9\u4f60\u907f\u514d\u6570\u636e\u635f\u574f\u3002\u6b64\u5916\uff0c\u7f16\u8f91\u540e\u4e00\u5b9a\u8981\u4fdd\u5b58\u4e3a\u65b0\u7684\u6587\u4ef6\uff0c\u4ee5\u9632\u539f\u59cb\u6587\u4ef6\u4e22\u5931\u6216\u635f\u574f\u3002<\/p>\n<p><strong>\u6709\u4ec0\u4e48\u793a\u4f8b\u4ee3\u7801\u53ef\u4ee5\u53c2\u8003\u4ee5\u7f16\u8f91nc\u6587\u4ef6\uff1f<\/strong><br \/>\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff0c\u4f7f\u7528netCDF4\u5e93\u8bfb\u53d6nc\u6587\u4ef6\u5e76\u4fee\u6539\u5176\u4e2d\u7684\u53d8\u91cf\uff1a<\/p>\n<pre><code class=\"language-python\">from netCDF4 import Dataset\n\n# \u6253\u5f00nc\u6587\u4ef6\ndataset = Dataset(&#39;example.nc&#39;, &#39;r+&#39;)\n\n# \u8bfb\u53d6\u53d8\u91cf\ndata_var = dataset.variables[&#39;temperature&#39;][:]\n\n# \u4fee\u6539\u6570\u636e\ndata_var[0] += 1.0  # \u5c06\u7b2c\u4e00\u4e2a\u6570\u636e\u70b9\u589e\u52a01\n\n# \u5199\u56de\u4fee\u6539\ndataset.variables[&#39;temperature&#39;][:] = data_var\n\n# \u5173\u95ed\u6587\u4ef6\ndataset.close()\n<\/code><\/pre>\n<p>\u8fd9\u4e2a\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u6253\u5f00nc\u6587\u4ef6\u3001\u8bfb\u53d6\u53d8\u91cf\u3001\u8fdb\u884c\u4fee\u6539\u5e76\u4fdd\u5b58\u66f4\u6539\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5982\u4f55\u7528Python\u5bf9nc\u6587\u4ef6\u8fdb\u884c\u7f16\u8f91 \u8981\u7528Python\u5bf9nc\u6587\u4ef6\u8fdb\u884c\u7f16\u8f91\uff0c\u53ef\u4ee5\u4f7f\u7528Python\u7684netCDF4 [&hellip;]","protected":false},"author":3,"featured_media":1072699,"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\/1072696"}],"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=1072696"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1072696\/revisions"}],"predecessor-version":[{"id":1072702,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1072696\/revisions\/1072702"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1072699"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1072696"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1072696"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1072696"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}