{"id":1134492,"date":"2025-01-08T21:16:08","date_gmt":"2025-01-08T13:16:08","guid":{"rendered":""},"modified":"2025-01-08T21:16:10","modified_gmt":"2025-01-08T13:16:10","slug":"python%e5%a6%82%e4%bd%95%e5%b0%86%e6%95%b0%e6%8d%ae%e5%86%99%e5%85%a5mat%e6%96%87%e4%bb%b6%e6%a0%bc%e5%bc%8f","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1134492.html","title":{"rendered":"python\u5982\u4f55\u5c06\u6570\u636e\u5199\u5165mat\u6587\u4ef6\u683c\u5f0f"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25103421\/2f9295bd-2a22-43a1-b309-67fa7dc6fd18.webp\" alt=\"python\u5982\u4f55\u5c06\u6570\u636e\u5199\u5165mat\u6587\u4ef6\u683c\u5f0f\" \/><\/p>\n<p><p> <strong>\u8981\u5c06\u6570\u636e\u5199\u5165MAT\u6587\u4ef6\u683c\u5f0f\uff0c\u53ef\u4ee5\u4f7f\u7528Python\u7684SciPy\u5e93\u4e2d\u7684<code>scipy.io.savemat<\/code>\u51fd\u6570\u3001MATLAB\u5f15\u64ceAPI\u6216\u8005h5py\u5e93\u6765\u5b9e\u73b0\u3002\u4f7f\u7528SciPy\u5e93\u662f\u6700\u7b80\u5355\u548c\u5e38\u89c1\u7684\u65b9\u6cd5\u3002\u4e0b\u9762\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5\u3002<\/strong><\/p>\n<\/p>\n<p><p><strong>\u4f7f\u7528SciPy\u5e93\u5199\u5165MAT\u6587\u4ef6\u683c\u5f0f\u662f\u6700\u7b80\u5355\u548c\u5e38\u89c1\u7684\u65b9\u6cd5\u3002\u5177\u4f53\u6b65\u9aa4\u5982\u4e0b\uff1a<\/strong><\/p>\n<\/p>\n<ol>\n<li>\u5bfc\u5165\u5fc5\u8981\u7684\u5e93\uff1b<\/li>\n<li>\u521b\u5efa\u6216\u83b7\u53d6\u9700\u8981\u5b58\u50a8\u7684\u6570\u636e\uff1b<\/li>\n<li>\u4f7f\u7528<code>scipy.io.savemat<\/code>\u51fd\u6570\u5c06\u6570\u636e\u4fdd\u5b58\u4e3aMAT\u6587\u4ef6\u3002<\/li>\n<\/ol>\n<p><p>\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u63cf\u8ff0\u6bcf\u4e00\u4e2a\u6b65\u9aa4\uff0c\u5e76\u63d0\u4f9b\u5177\u4f53\u7684\u4ee3\u7801\u793a\u4f8b\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u5bfc\u5165\u5fc5\u8981\u7684\u5e93<\/h3>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5bfc\u5165SciPy\u5e93\u4e2d\u7684io\u6a21\u5757\u3002\u8fd9\u4e2a\u6a21\u5757\u63d0\u4f9b\u4e86\u5c06\u6570\u636e\u5199\u5165MAT\u6587\u4ef6\u7684\u529f\u80fd\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import scipy.io<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e8c\u3001\u521b\u5efa\u6216\u83b7\u53d6\u9700\u8981\u5b58\u50a8\u7684\u6570\u636e<\/h3>\n<\/p>\n<p><p>\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u5305\u542b\u4e00\u4e9b\u6570\u636e\u7684\u5b57\u5178\uff0c\u6570\u636e\u53ef\u4ee5\u662f\u4efb\u610f\u7684NumPy\u6570\u7ec4\u6216\u8005\u5176\u4ed6Python\u6570\u636e\u7c7b\u578b\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p>data = {<\/p>\n<p>    &#39;array_1&#39;: np.array([1, 2, 3, 4, 5]),<\/p>\n<p>    &#39;array_2&#39;: np.array([[1, 2], [3, 4], [5, 6]])<\/p>\n<p>}<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e09\u3001\u4f7f\u7528scipy.io.savemat\u51fd\u6570\u5c06\u6570\u636e\u4fdd\u5b58\u4e3aMAT\u6587\u4ef6<\/h3>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<code>scipy.io.savemat<\/code>\u51fd\u6570\u5c06\u6570\u636e\u5199\u5165MAT\u6587\u4ef6\u3002\u8fd9\u4e2a\u51fd\u6570\u9700\u8981\u4e24\u4e2a\u53c2\u6570\uff1a\u6587\u4ef6\u540d\u548c\u8981\u4fdd\u5b58\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">scipy.io.savemat(&#39;example.mat&#39;, data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u6bb5\u4ee3\u7801\u5c06\u6570\u636e\u5b57\u5178\u4fdd\u5b58\u5230\u4e00\u4e2a\u540d\u4e3a<code>example.mat<\/code>\u7684\u6587\u4ef6\u4e2d\u3002<\/p>\n<\/p>\n<p><h3>\u56db\u3001\u8be6\u7ec6\u4ecb\u7ecd\u548c\u6269\u5c55<\/h3>\n<\/p>\n<p><h4>1\u3001SciPy\u5e93\u7684\u4f7f\u7528<\/h4>\n<\/p>\n<p><p>SciPy\u5e93\u4e2d\u7684<code>scipy.io.savemat<\/code>\u51fd\u6570\u975e\u5e38\u7075\u6d3b\uff0c\u53ef\u4ee5\u5904\u7406\u5404\u79cd\u7c7b\u578b\u7684\u6570\u636e\uff0c\u5982\u6807\u91cf\u3001\u5411\u91cf\u3001\u77e9\u9635\u548c\u591a\u7ef4\u6570\u7ec4\u3002\u5b83\u8fd8\u652f\u6301\u5c06\u591a\u4e2a\u53d8\u91cf\u540c\u65f6\u4fdd\u5b58\u5230\u4e00\u4e2aMAT\u6587\u4ef6\u4e2d\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5bfc\u5165\u5e93<\/p>\n<p>import scipy.io<\/p>\n<p>import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u6570\u636e<\/strong><\/h2>\n<p>data = {<\/p>\n<p>    &#39;scalar&#39;: 42,<\/p>\n<p>    &#39;vector&#39;: np.array([1, 2, 3, 4, 5]),<\/p>\n<p>    &#39;matrix&#39;: np.array([[1, 2], [3, 4], [5, 6]]),<\/p>\n<p>    &#39;multidim_array&#39;: np.random.rand(3, 3, 3)<\/p>\n<p>}<\/p>\n<h2><strong>\u4fdd\u5b58\u6570\u636e\u5230MAT\u6587\u4ef6<\/strong><\/h2>\n<p>scipy.io.savemat(&#39;extended_example.mat&#39;, data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001MATLAB\u5f15\u64ceAPI\u7684\u4f7f\u7528<\/h4>\n<\/p>\n<p><p>\u5982\u679c\u4f60\u6709MATLAB\u5b89\u88c5\u5728\u4f60\u7684\u7cfb\u7edf\u4e0a\uff0c\u53ef\u4ee5\u4f7f\u7528MATLAB\u5f15\u64ceAPI\u6765\u4e0eMATLAB\u8fdb\u884c\u4ea4\u4e92\u3002\u9996\u5148\u9700\u8981\u5b89\u88c5MATLAB\u5f15\u64ceAPI\uff0c\u53ef\u4ee5\u901a\u8fc7MATLAB\u63d0\u4f9b\u7684<code>setup.py<\/code>\u811a\u672c\u8fdb\u884c\u5b89\u88c5\u3002\u7136\u540e\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5c06\u6570\u636e\u5199\u5165MAT\u6587\u4ef6\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import matlab.engine<\/p>\n<p>import numpy as np<\/p>\n<h2><strong>\u542f\u52a8MATLAB\u5f15\u64ce<\/strong><\/h2>\n<p>eng = matlab.engine.start_matlab()<\/p>\n<h2><strong>\u521b\u5efa\u6570\u636e<\/strong><\/h2>\n<p>array_1 = matlab.double(np.array([1, 2, 3, 4, 5]).tolist())<\/p>\n<p>array_2 = matlab.double(np.array([[1, 2], [3, 4], [5, 6]]).tolist())<\/p>\n<h2><strong>\u5c06\u6570\u636e\u4fdd\u5b58\u4e3aMAT\u6587\u4ef6<\/strong><\/h2>\n<p>eng.workspace[&#39;array_1&#39;] = array_1<\/p>\n<p>eng.workspace[&#39;array_2&#39;] = array_2<\/p>\n<p>eng.save(&#39;example_with_matlab.mat&#39;, &#39;array_1&#39;, &#39;array_2&#39;)<\/p>\n<h2><strong>\u5173\u95edMATLAB\u5f15\u64ce<\/strong><\/h2>\n<p>eng.quit()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e94\u3001\u4f7f\u7528h5py\u5e93\u4fdd\u5b58MAT\u6587\u4ef6<\/h3>\n<\/p>\n<p><p>MAT\u6587\u4ef6\u5b9e\u9645\u4e0a\u662f\u57fa\u4e8eHDF5\u683c\u5f0f\u7684\uff0c\u56e0\u6b64\u53ef\u4ee5\u4f7f\u7528h5py\u5e93\u6765\u521b\u5efa\u548c\u64cd\u4f5cMAT\u6587\u4ef6\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import h5py<\/p>\n<p>import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u6570\u636e<\/strong><\/h2>\n<p>data = {<\/p>\n<p>    &#39;array_1&#39;: np.array([1, 2, 3, 4, 5]),<\/p>\n<p>    &#39;array_2&#39;: np.array([[1, 2], [3, 4], [5, 6]])<\/p>\n<p>}<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2aHDF5\u6587\u4ef6<\/strong><\/h2>\n<p>with h5py.File(&#39;example_with_h5py.mat&#39;, &#39;w&#39;) as f:<\/p>\n<p>    for key, value in data.items():<\/p>\n<p>        f.create_dataset(key, data=value)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3\u3001\u5904\u7406\u590d\u6742\u6570\u636e\u7ed3\u6784<\/h4>\n<\/p>\n<p><p>MAT\u6587\u4ef6\u53ef\u4ee5\u4fdd\u5b58\u590d\u6742\u7684\u6570\u636e\u7ed3\u6784\uff0c\u5982\u5b57\u5178\u3001\u5217\u8868\u548c\u5143\u7ec4\u3002SciPy\u5e93\u63d0\u4f9b\u4e86\u5c06\u8fd9\u4e9b\u6570\u636e\u7ed3\u6784\u8f6c\u6362\u4e3aMAT\u6587\u4ef6\u6240\u9700\u683c\u5f0f\u7684\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import scipy.io<\/p>\n<p>import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u590d\u6742\u6570\u636e\u7ed3\u6784<\/strong><\/h2>\n<p>complex_data = {<\/p>\n<p>    &#39;scalar&#39;: 42,<\/p>\n<p>    &#39;vector&#39;: np.array([1, 2, 3, 4, 5]),<\/p>\n<p>    &#39;matrix&#39;: np.array([[1, 2], [3, 4], [5, 6]]),<\/p>\n<p>    &#39;nested_dict&#39;: {<\/p>\n<p>        &#39;nested_scalar&#39;: 3.14,<\/p>\n<p>        &#39;nested_vector&#39;: np.array([7, 8, 9])<\/p>\n<p>    }<\/p>\n<p>}<\/p>\n<h2><strong>\u4fdd\u5b58\u590d\u6742\u6570\u636e\u7ed3\u6784\u5230MAT\u6587\u4ef6<\/strong><\/h2>\n<p>scipy.io.savemat(&#39;complex_example.mat&#39;, complex_data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>4\u3001\u8bfb\u53d6MAT\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>SciPy\u5e93\u540c\u6837\u63d0\u4f9b\u4e86\u8bfb\u53d6MAT\u6587\u4ef6\u7684\u529f\u80fd\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<code>scipy.io.loadmat<\/code>\u51fd\u6570\u6765\u8bfb\u53d6MAT\u6587\u4ef6\u4e2d\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import scipy.io<\/p>\n<h2><strong>\u8bfb\u53d6MAT\u6587\u4ef6<\/strong><\/h2>\n<p>loaded_data = scipy.io.loadmat(&#39;example.mat&#39;)<\/p>\n<h2><strong>\u67e5\u770b\u6570\u636e<\/strong><\/h2>\n<p>print(loaded_data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>Python\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u5c06\u6570\u636e\u5199\u5165MAT\u6587\u4ef6\u683c\u5f0f\uff0c\u5305\u62ec\u4f7f\u7528SciPy\u5e93\u3001MATLAB\u5f15\u64ceAPI\u548ch5py\u5e93\u3002<strong>SciPy\u5e93\u7684<code>scipy.io.savemat<\/code>\u51fd\u6570\u662f\u6700\u7b80\u5355\u548c\u6700\u5e38\u89c1\u7684\u65b9\u6cd5<\/strong>\uff0c\u5b83\u53ef\u4ee5\u5904\u7406\u5404\u79cd\u7c7b\u578b\u7684\u6570\u636e\uff0c\u5e76\u4e14\u53ef\u4ee5\u5c06\u591a\u4e2a\u53d8\u91cf\u540c\u65f6\u4fdd\u5b58\u5230\u4e00\u4e2aMAT\u6587\u4ef6\u4e2d\u3002MATLAB\u5f15\u64ceAPI\u9002\u7528\u4e8e\u9700\u8981\u4e0eMATLAB\u8fdb\u884c\u66f4\u6df1\u5ea6\u96c6\u6210\u7684\u573a\u666f\uff0c\u800ch5py\u5e93\u5219\u63d0\u4f9b\u4e86\u5904\u7406HDF5\u683c\u5f0f\u6587\u4ef6\u7684\u7075\u6d3b\u6027\u3002<\/p>\n<\/p>\n<p><p>\u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u4f60\u5e94\u8be5\u80fd\u591f\u9009\u62e9\u9002\u5408\u4f60\u9700\u6c42\u7684\u65b9\u6cd5\uff0c\u5c06Python\u4e2d\u7684\u6570\u636e\u5199\u5165MAT\u6587\u4ef6\u683c\u5f0f\u3002\u65e0\u8bba\u662f\u7b80\u5355\u7684\u6570\u636e\u7ed3\u6784\u8fd8\u662f\u590d\u6742\u7684\u6570\u636e\u7ed3\u6784\uff0cPython\u90fd\u80fd\u8f7b\u677e\u5904\u7406\u5e76\u4fdd\u5b58\u4e3aMAT\u6587\u4ef6\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u4f7f\u7528Python\u5c06\u6570\u636e\u4fdd\u5b58\u4e3aMAT\u6587\u4ef6\u683c\u5f0f\uff1f<\/strong><br \/>\u4f7f\u7528Python\u4fdd\u5b58\u6570\u636e\u4e3aMAT\u6587\u4ef6\u683c\u5f0f\uff0c\u901a\u5e38\u4f1a\u4f7f\u7528<code>scipy.io<\/code>\u5e93\u4e2d\u7684<code>savemat<\/code>\u51fd\u6570\u3002\u4f60\u9700\u8981\u5c06\u6570\u636e\u7ec4\u7ec7\u6210\u5b57\u5178\u5f62\u5f0f\uff0c\u5176\u4e2d\u952e\u5bf9\u5e94MAT\u6587\u4ef6\u4e2d\u7684\u53d8\u91cf\u540d\uff0c\u503c\u4e3a\u4f60\u5e0c\u671b\u4fdd\u5b58\u7684\u6570\u636e\u6570\u7ec4\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n<pre><code class=\"language-python\">import numpy as np\nfrom scipy.io import savemat\n\ndata = {\n    &#39;array1&#39;: np.array([1, 2, 3]),\n    &#39;array2&#39;: np.array([[1, 2], [3, 4]])\n}\n\nsavemat(&#39;data.mat&#39;, data)\n<\/code><\/pre>\n<p><strong>MAT\u6587\u4ef6\u683c\u5f0f\u652f\u6301\u54ea\u4e9b\u6570\u636e\u7c7b\u578b\uff1f<\/strong><br \/>MAT\u6587\u4ef6\u683c\u5f0f\u652f\u6301\u591a\u79cd\u6570\u636e\u7c7b\u578b\uff0c\u5305\u62ec\u4f46\u4e0d\u9650\u4e8e\u6570\u503c\u6570\u7ec4\u3001\u5b57\u7b26\u4e32\u3001\u7ed3\u6784\u4f53\u3001\u5355\u5143\u683c\u6570\u7ec4\u7b49\u3002\u4f7f\u7528Python\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7NumPy\u6570\u7ec4\u3001Python\u5217\u8868\u7b49\u5f62\u5f0f\u521b\u5efa\u8fd9\u4e9b\u6570\u636e\u7c7b\u578b\uff0c<code>savemat<\/code>\u51fd\u6570\u4f1a\u81ea\u52a8\u5c06\u5176\u8f6c\u6362\u4e3aMATLAB\u53ef\u8bc6\u522b\u7684\u683c\u5f0f\u3002<\/p>\n<p><strong>\u5728Python\u4e2d\u8bfb\u53d6MAT\u6587\u4ef6\u9700\u8981\u54ea\u4e9b\u5e93\uff1f<\/strong><br \/>\u8981\u5728Python\u4e2d\u8bfb\u53d6MAT\u6587\u4ef6\uff0c\u901a\u5e38\u4f7f\u7528<code>scipy.io<\/code>\u5e93\u4e2d\u7684<code>loadmat<\/code>\u51fd\u6570\u3002\u8fd9\u4e2a\u51fd\u6570\u53ef\u4ee5\u8bfb\u53d6MAT\u6587\u4ef6\u5e76\u5c06\u5176\u5185\u5bb9\u52a0\u8f7d\u4e3aPython\u5b57\u5178\u5bf9\u8c61\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u8bfb\u53d6\u793a\u4f8b\uff1a<\/p>\n<pre><code class=\"language-python\">from scipy.io import loadmat\n\ndata = loadmat(&#39;data.mat&#39;)\nprint(data)\n<\/code><\/pre>\n<p>\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u8bbf\u95eeMAT\u6587\u4ef6\u4e2d\u7684\u53d8\u91cf\u548c\u6570\u636e\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u8981\u5c06\u6570\u636e\u5199\u5165MAT\u6587\u4ef6\u683c\u5f0f\uff0c\u53ef\u4ee5\u4f7f\u7528Python\u7684SciPy\u5e93\u4e2d\u7684scipy.io.savemat\u51fd\u6570\u3001MAT [&hellip;]","protected":false},"author":3,"featured_media":1134502,"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\/1134492"}],"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=1134492"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1134492\/revisions"}],"predecessor-version":[{"id":1134503,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1134492\/revisions\/1134503"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1134502"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1134492"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1134492"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1134492"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}