{"id":1080143,"date":"2025-01-08T12:27:21","date_gmt":"2025-01-08T04:27:21","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1080143.html"},"modified":"2025-01-08T12:27:24","modified_gmt":"2025-01-08T04:27:24","slug":"python%e5%a6%82%e4%bd%95%e7%94%bb3d%e5%af%86%e5%ba%a6%e5%9b%be-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1080143.html","title":{"rendered":"python\u5982\u4f55\u753b3d\u5bc6\u5ea6\u56fe"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/24182828\/9daa420e-a5c4-495f-bf26-ad0e933c0d7b.webp\" alt=\"python\u5982\u4f55\u753b3d\u5bc6\u5ea6\u56fe\" \/><\/p>\n<p><p> <strong>Python\u753b3D\u5bc6\u5ea6\u56fe\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528matplotlib\u3001seaborn\u548cmayavi\u3002<\/strong> \u5176\u4e2d\uff0c<strong>matplotlib<\/strong>\u662f\u6700\u5e38\u7528\u7684Python\u7ed8\u56fe\u5e93\uff0c\u9002\u5408\u7ed8\u5236\u5404\u79cd\u56fe\u5f62\uff0c\u5305\u62ec3D\u5bc6\u5ea6\u56fe\uff1b<strong>seaborn<\/strong>\u57fa\u4e8ematplotlib\uff0c\u63d0\u4f9b\u9ad8\u7ea7\u63a5\u53e3\u548c\u7f8e\u89c2\u7684\u9ed8\u8ba4\u6837\u5f0f\uff0c\u9002\u5408\u5feb\u901f\u7ed8\u56fe\uff1b<strong>mayavi<\/strong>\u5219\u4e13\u6ce8\u4e8e3D\u6570\u636e\u53ef\u89c6\u5316\uff0c\u9002\u5408\u5904\u7406\u590d\u6742\u76843D\u56fe\u5f62\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e09\u79cd\u5de5\u5177\u7ed8\u52363D\u5bc6\u5ea6\u56fe\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528Matplotlib\u7ed8\u52363D\u5bc6\u5ea6\u56fe<\/h3>\n<\/p>\n<p><p>Matplotlib\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00\uff0c\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u76843D\u7ed8\u56fe\u529f\u80fd\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Matplotlib\u7684<code>Axes3D<\/code>\u6a21\u5757\u6765\u7ed8\u52363D\u5bc6\u5ea6\u56fe\u3002<\/p>\n<\/p>\n<p><h4>\u5b89\u88c5\u548c\u5bfc\u5165\u5e93<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5Matplotlib\u5e93\u3002\u5982\u679c\u4f60\u8fd8\u6ca1\u6709\u5b89\u88c5\u5b83\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install matplotlib<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u7136\u540e\uff0c\u6211\u4eec\u9700\u8981\u5bfc\u5165\u5fc5\u8981\u7684\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p>import matplotlib.pyplot as plt<\/p>\n<p>from mpl_toolkits.mplot3d import Axes3D<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>\u521b\u5efa\u6570\u636e<\/h4>\n<\/p>\n<p><p>\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u9700\u8981\u521b\u5efa\u4e00\u4e9b\u6570\u636e\u6765\u7ed8\u52363D\u5bc6\u5ea6\u56fe\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u6765\u751f\u6210\u968f\u673a\u6570\u636e\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u968f\u673a\u6570\u636e<\/p>\n<p>x = np.random.normal(size=500)<\/p>\n<p>y = np.random.normal(size=500)<\/p>\n<p>z = np.random.normal(size=500)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>\u7ed8\u52363D\u5bc6\u5ea6\u56fe<\/h4>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Matplotlib\u7684<code>hist<\/code>\u51fd\u6570\u6765\u7ed8\u52363D\u5bc6\u5ea6\u56fe\u3002\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u521b\u5efa\u4e00\u4e2a3D\u56fe\u5f62\u5bf9\u8c61\uff0c\u7136\u540e\u4f7f\u7528<code>hist<\/code>\u51fd\u6570\u5c06\u6570\u636e\u6dfb\u52a0\u5230\u56fe\u5f62\u4e2d\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u521b\u5efa3D\u56fe\u5f62\u5bf9\u8c61<\/p>\n<p>fig = plt.figure()<\/p>\n<p>ax = fig.add_subplot(111, projection=&#39;3d&#39;)<\/p>\n<h2><strong>\u7ed8\u52363D\u5bc6\u5ea6\u56fe<\/strong><\/h2>\n<p>hist, xedges, yedges = np.histogram2d(x, y, bins=30, density=True)<\/p>\n<p>xpos, ypos = np.meshgrid(xedges[:-1] + 0.25, yedges[:-1] + 0.25, indexing=&quot;ij&quot;)<\/p>\n<p>xpos = xpos.ravel()<\/p>\n<p>ypos = ypos.ravel()<\/p>\n<p>zpos = 0<\/p>\n<h2><strong>\u4f7f\u7528bar3d\u51fd\u6570\u7ed8\u52363D\u67f1\u72b6\u56fe<\/strong><\/h2>\n<p>dx = dy = 0.5 * np.ones_like(zpos)<\/p>\n<p>dz = hist.ravel()<\/p>\n<p>ax.bar3d(xpos, ypos, zpos, dx, dy, dz, zsort=&#39;average&#39;)<\/p>\n<h2><strong>\u663e\u793a\u56fe\u5f62<\/strong><\/h2>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Matplotlib\u7ed8\u5236\u4e00\u4e2a\u7b80\u5355\u76843D\u5bc6\u5ea6\u56fe\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528Seaborn\u7ed8\u52363D\u5bc6\u5ea6\u56fe<\/h3>\n<\/p>\n<p><p>Seaborn\u662f\u4e00\u4e2a\u57fa\u4e8eMatplotlib\u7684\u9ad8\u7ea7\u7ed8\u56fe\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u7f8e\u89c2\u7684\u9ed8\u8ba4\u6837\u5f0f\u548c\u9ad8\u7ea7\u63a5\u53e3\uff0c\u53ef\u4ee5\u8ba9\u6211\u4eec\u66f4\u8f7b\u677e\u5730\u7ed8\u5236\u5404\u79cd\u56fe\u5f62\u3002\u867d\u7136Seaborn\u4e3b\u8981\u7528\u4e8e2D\u7ed8\u56fe\uff0c\u4f46\u6211\u4eec\u53ef\u4ee5\u7ed3\u5408Matplotlib\u76843D\u529f\u80fd\u6765\u7ed8\u52363D\u5bc6\u5ea6\u56fe\u3002<\/p>\n<\/p>\n<p><h4>\u5b89\u88c5\u548c\u5bfc\u5165\u5e93<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5Seaborn\u5e93\u3002\u5982\u679c\u4f60\u8fd8\u6ca1\u6709\u5b89\u88c5\u5b83\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install seaborn<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u7136\u540e\uff0c\u6211\u4eec\u9700\u8981\u5bfc\u5165\u5fc5\u8981\u7684\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p>import seaborn as sns<\/p>\n<p>import matplotlib.pyplot as plt<\/p>\n<p>from mpl_toolkits.mplot3d import Axes3D<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>\u521b\u5efa\u6570\u636e<\/h4>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4e0e\u4e4b\u524d\u76f8\u540c\u7684\u65b9\u6cd5\u751f\u6210\u968f\u673a\u6570\u636e\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u968f\u673a\u6570\u636e<\/p>\n<p>x = np.random.normal(size=500)<\/p>\n<p>y = np.random.normal(size=500)<\/p>\n<p>z = np.random.normal(size=500)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>\u7ed8\u52363D\u5bc6\u5ea6\u56fe<\/h4>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Seaborn\u7684<code>kdeplot<\/code>\u51fd\u6570\u6765\u7ed8\u52362D\u5bc6\u5ea6\u56fe\uff0c\u7136\u540e\u7ed3\u5408Matplotlib\u76843D\u529f\u80fd\u6765\u7ed8\u52363D\u5bc6\u5ea6\u56fe\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u521b\u5efa3D\u56fe\u5f62\u5bf9\u8c61<\/p>\n<p>fig = plt.figure()<\/p>\n<p>ax = fig.add_subplot(111, projection=&#39;3d&#39;)<\/p>\n<h2><strong>\u7ed8\u52362D\u5bc6\u5ea6\u56fe<\/strong><\/h2>\n<p>sns.kdeplot(x, y, cmap=&quot;Blues&quot;, shade=True, ax=ax)<\/p>\n<h2><strong>\u663e\u793a\u56fe\u5f62<\/strong><\/h2>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Seaborn\u548cMatplotlib\u7ed3\u5408\u7ed8\u5236\u4e00\u4e2a\u7b80\u5355\u76843D\u5bc6\u5ea6\u56fe\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u4f7f\u7528Mayavi\u7ed8\u52363D\u5bc6\u5ea6\u56fe<\/h3>\n<\/p>\n<p><p>Mayavi\u662f\u4e00\u4e2a\u4e13\u6ce8\u4e8e3D\u6570\u636e\u53ef\u89c6\u5316\u7684\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u76843D\u7ed8\u56fe\u529f\u80fd\uff0c\u9002\u5408\u5904\u7406\u590d\u6742\u76843D\u56fe\u5f62\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Mayavi\u7ed8\u5236\u9ad8\u8d28\u91cf\u76843D\u5bc6\u5ea6\u56fe\u3002<\/p>\n<\/p>\n<p><h4>\u5b89\u88c5\u548c\u5bfc\u5165\u5e93<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5Mayavi\u5e93\u3002\u5982\u679c\u4f60\u8fd8\u6ca1\u6709\u5b89\u88c5\u5b83\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install mayavi<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u7136\u540e\uff0c\u6211\u4eec\u9700\u8981\u5bfc\u5165\u5fc5\u8981\u7684\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p>from mayavi import mlab<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>\u521b\u5efa\u6570\u636e<\/h4>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4e0e\u4e4b\u524d\u76f8\u540c\u7684\u65b9\u6cd5\u751f\u6210\u968f\u673a\u6570\u636e\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u968f\u673a\u6570\u636e<\/p>\n<p>x = np.random.normal(size=500)<\/p>\n<p>y = np.random.normal(size=500)<\/p>\n<p>z = np.random.normal(size=500)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>\u7ed8\u52363D\u5bc6\u5ea6\u56fe<\/h4>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Mayavi\u7684<code>points3d<\/code>\u51fd\u6570\u6765\u7ed8\u52363D\u5bc6\u5ea6\u56fe\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u7ed8\u52363D\u5bc6\u5ea6\u56fe<\/p>\n<p>mlab.points3d(x, y, z, mode=&#39;point&#39;, colormap=&#39;blue&#39;)<\/p>\n<h2><strong>\u663e\u793a\u56fe\u5f62<\/strong><\/h2>\n<p>mlab.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Mayavi\u7ed8\u5236\u4e00\u4e2a\u7b80\u5355\u76843D\u5bc6\u5ea6\u56fe\u3002<\/p>\n<\/p>\n<p><h3>\u56db\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u5728\u672c\u6559\u7a0b\u4e2d\uff0c\u6211\u4eec\u4ecb\u7ecd\u4e86\u4e09\u79cd\u4f7f\u7528Python\u7ed8\u52363D\u5bc6\u5ea6\u56fe\u7684\u65b9\u6cd5\uff1aMatplotlib\u3001Seaborn\u548cMayavi\u3002Matplotlib\u662f\u6700\u5e38\u7528\u7684Python\u7ed8\u56fe\u5e93\uff0c\u9002\u5408\u7ed8\u5236\u5404\u79cd\u56fe\u5f62\uff0c\u5305\u62ec3D\u5bc6\u5ea6\u56fe\uff1bSeaborn\u57fa\u4e8eMatplotlib\uff0c\u63d0\u4f9b\u9ad8\u7ea7\u63a5\u53e3\u548c\u7f8e\u89c2\u7684\u9ed8\u8ba4\u6837\u5f0f\uff0c\u9002\u5408\u5feb\u901f\u7ed8\u56fe\uff1bMayavi\u4e13\u6ce8\u4e8e3D\u6570\u636e\u53ef\u89c6\u5316\uff0c\u9002\u5408\u5904\u7406\u590d\u6742\u76843D\u56fe\u5f62\u3002\u6839\u636e\u4f60\u7684\u9700\u6c42\u548c\u504f\u597d\uff0c\u4f60\u53ef\u4ee5\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177\u6765\u7ed8\u52363D\u5bc6\u5ea6\u56fe\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u4f7f\u7528Python\u7ed8\u52363D\u5bc6\u5ea6\u56fe\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u4e2a\u5e93\u6765\u7ed8\u52363D\u5bc6\u5ea6\u56fe\uff0c\u6700\u5e38\u7528\u7684\u5305\u62ecMatplotlib\u548cSeaborn\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u5b89\u88c5\u8fd9\u4e9b\u5e93\uff0c\u5e76\u5229\u7528\u5b83\u4eec\u63d0\u4f9b\u7684\u529f\u80fd\u6765\u7ed8\u52363D\u5bc6\u5ea6\u56fe\u3002\u4f8b\u5982\uff0c\u4f7f\u7528Matplotlib\u7684<code>Axes3D<\/code>\u6a21\u5757\u53ef\u4ee5\u5f88\u65b9\u4fbf\u5730\u521b\u5efa3D\u56fe\u5f62\uff0c\u5e76\u7ed3\u5408<code>histogram2d<\/code>\u51fd\u6570\u751f\u6210\u5bc6\u5ea6\u56fe\u3002<\/p>\n<p><strong>\u9700\u8981\u54ea\u4e9b\u5e93\u6765\u5b9e\u73b03D\u5bc6\u5ea6\u56fe\u7684\u7ed8\u5236\uff1f<\/strong><br \/>\u7ed8\u52363D\u5bc6\u5ea6\u56fe\u901a\u5e38\u9700\u8981\u5b89\u88c5Matplotlib\u548cNumPy\u3002\u5982\u679c\u9700\u8981\u66f4\u9ad8\u7ea7\u7684\u53ef\u89c6\u5316\u6548\u679c\uff0c\u8fd8\u53ef\u4ee5\u8003\u8651\u4f7f\u7528Plotly\u3001Mayavi\u6216\u5176\u4ed6\u56fe\u5f62\u5e93\u3002\u786e\u4fdd\u5728Python\u73af\u5883\u4e2d\u5b89\u88c5\u8fd9\u4e9b\u5e93\uff0c\u6bd4\u5982\u4f7f\u7528<code>pip install matplotlib numpy<\/code>\u547d\u4ee4\u3002<\/p>\n<p><strong>\u5982\u4f55\u81ea\u5b9a\u4e493D\u5bc6\u5ea6\u56fe\u7684\u6837\u5f0f\u548c\u989c\u8272\uff1f<\/strong><br \/>\u5728Matplotlib\u4e2d\uff0c\u4f60\u53ef\u4ee5\u901a\u8fc7\u8c03\u6574<code>cmap<\/code>\u53c2\u6570\u6765\u9009\u62e9\u4e0d\u540c\u7684\u989c\u8272\u6620\u5c04\uff0c\u4ee5\u589e\u5f3a\u56fe\u5f62\u7684\u89c6\u89c9\u6548\u679c\u3002\u6b64\u5916\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u900f\u660e\u5ea6\u3001\u8fb9\u754c\u989c\u8272\u548c\u56fe\u4f8b\u7b49\u5c5e\u6027\u6765\u81ea\u5b9a\u4e49\u56fe\u5f62\u7684\u5916\u89c2\u3002\u67e5\u9605Matplotlib\u7684\u5b98\u65b9\u6587\u6863\u53ef\u4ee5\u83b7\u5f97\u66f4\u591a\u5173\u4e8e\u6837\u5f0f\u8c03\u6574\u7684\u8be6\u7ec6\u4fe1\u606f\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u753b3D\u5bc6\u5ea6\u56fe\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528matplotlib\u3001seaborn\u548cmayavi\u3002 \u5176\u4e2d\uff0cmatplo 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