{"id":53714,"date":"2025-08-12T16:19:59","date_gmt":"2025-08-12T08:19:59","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/53714.html"},"modified":"2025-08-12T16:19:59","modified_gmt":"2025-08-12T08:19:59","slug":"%e5%b0%8f%e6%9d%b0python%e9%ab%98%e7%ba%a7%ef%bc%88four-day%ef%bc%89-matplotlib%e5%ba%93","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/53714.html","title":{"rendered":"\u5c0f\u6770python\u9ad8\u7ea7\uff08four day\uff09\u2014\u2014matplotlib\u5e93"},"content":{"rendered":"

1.\u7ed8\u5236\u5b50\u56fe\u7684\u65b9\u5f0f<\/h2>\n
  • pyplot\u4e2d\u51fd\u6570subplot<\/span><\/li>\n
  • Figure\u7c7b\u4e2d\u7684\u51fd\u6570add_subplot<\/span><\/li>\n
  • pyplot\u4e2d\u51fd\u6570subplots<\/span><\/li>\n

    fig<\/span>,<\/span> ax <\/span>=<\/span> plt<\/span>.<\/span>subplots<\/span>(<\/span>nrows<\/span>=<\/span>1<\/span>,<\/span> ncols<\/span>=<\/span>1<\/span>,<\/span> *<\/span>,<\/span> sharex<\/span>=<\/span>False<\/span>,<\/span> sharey<\/span>=<\/span>False<\/span>,
    \n<\/span> squeeze<\/span>=<\/span>True<\/span>,<\/span> subplot_kw<\/span>=<\/span>None<\/span>,<\/span> gridspec_kw<\/span>=<\/span>None<\/span>,<\/span> **<\/span>fig_kw<\/span>)<\/span>
    \n\u529f\u80fd：\u7ed8\u5236\u591a\u4e2a\u5b50\u56fe，\u53ef\u4ee5\u4e00\u6b21\u751f\u6210\u591a\u4e2a<\/span>
    \n\u53c2\u6570：nrows\u548cncols：\u6574\u6570，\u8868\u793a\u5b50\u56fe\u7684\u884c\u6570\u548c\u5217\u6570\u3002<\/span>
    \n sharex\u548csharey：\u5e03\u5c14\u503c\u6216\u5b57\u7b26\u4e32，\u8868\u793a\u662f\u5426\u5171\u4eabx\u8f74\u6216y\u8f74\u7684\u5c5e\u6027\u3002 \u53ef\u9009\u503c\u6709<\/span>True<\/span>\u3001<\/span>False<\/span>\u3001<\/span>'row'<\/span>\u548c<\/span>'col'<\/span>\u3002<\/span>
    \n squeeze：\u5e03\u5c14\u503c，\u9ed8\u8ba4\u4e3a<\/span>True<\/span>\u3002\u5f53\u5b50\u56fe\u53ea\u6709\u4e00\u4e2a\u65f6，\u8fd4\u56de\u4e00\u4e2aAxes\u5bf9\u8c61
    \n\u800c\u4e0d\u662f\u4e00\u4e2a\u6570\u7ec4\u3002<\/span>False<\/span>\u65f6\u8fd4\u56de\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4<\/span>
    \n width_ratios：\u5217\u5bbd\u6bd4\u4f8b\u7684\u5e8f\u5217，\u7528\u4e8e\u8c03\u6574\u5404\u5217\u7684\u5bbd\u5ea6\u6bd4<\/span>
    \n height_ratios：\u884c\u9ad8\u6bd4\u4f8b\u7684\u5e8f\u5217，\u7528\u4e8e\u8c03\u6574\u5404\u884c\u7684\u9ad8\u5ea6\u6bd4<\/span>
    \n subplot_kw：\u5b57\u5178\u7c7b\u578b，\u53ef\u9009\u53c2\u6570\u3002\u628a\u5b57\u5178\u7684\u5173\u952e\u5b57\u4f20\u9012\u7ed9add_subplot<\/span>()
    \n<\/span>\u6765\u521b\u5efa\u6bcf\u4e2a\u5b50\u56fe\u3002<\/span>
    \n gridspec_kw：\u5b57\u5178\u7c7b\u578b，\u53ef\u9009\u53c2\u6570\u3002\u628a\u5b57\u5178\u7684\u5173\u952e\u5b57\u4f20\u9012\u7ed9GridSpec\u6784\u9020\u51fd\u6570
    \n\u521b\u5efa\u5b50\u56fe\u653e\u5728\u7f51\u683c\u91cc（grid）\u3002<\/span>
    \n **<\/span>fig_kw：\u628a\u6240\u6709\u8be6\u7ec6\u7684\u5173\u952e\u5b57\u53c2\u6570\u4f20\u7ed9figure<\/span>()<\/span>\u51fd\u6570\u3002<\/span>
    \n\u8fd4\u56de\u503c：fig：\u8fd9\u662f\u6574\u4e2a\u56fe\u5f62\u7684\u5bf9\u8c61，\u53ef\u4ee5\u5bf9\u5176\u8fdb\u884c\u5168\u5c40\u8bbe\u7f6e，\u5982\u6807\u9898\u3001\u5927\u5c0f\u7b49\u3002<\/span>
    \n axes：\u8fd9\u662f\u4e00\u4e2a\u6570\u7ec4，\u5305\u542b\u6240\u6709\u7684\u5b50\u56fe\u3002\u6570\u7ec4\u7684\u5f62\u72b6\u7531nrows\u548cncols\u51b3\u5b9a\u3002
    \n\u4f8b\u5982，\u5982\u679c nrows<\/span>=<\/span>2<\/span> \u548c ncols<\/span>=<\/span>3<\/span>，\u5219 axes \u5c06\u662f\u4e00\u4e2a 2×3 \u7684\u6570\u7ec4，\u6bcf\u4e2a\u5143\u7d20\u90fd\u662f\u4e00\u4e2a
    \n\u5b50\u56fe\u5bf9\u8c61\u3002<\/span>
    \n<\/span><\/p>\n

    # \u7ed8\u5236\u5b50\u56fe，\u8fd4\u56de\u503c\u5305\u542bFigure\u5bf9\u8c61\u548cAxes\u5bf9\u8c61，Axes\u5bf9\u8c61\u662f\u4e00\u4e2a\u6570\u7ec4，\u53ef\u4ee5\u901a\u8fc7\u4e0b\u6807\u8fdb\u884c\u8bbf\u95ee\u5b50\u56fe
    \nfig, ax = plt.subplots(2, 2)<\/p>\n

    ax[0, 0].plot([2,3], [4,5])
    \nax[0, 1].plot([1,1], [2,1])<\/p>\n

    fig.suptitle('sub')<\/p>\n

    plt.show()<\/p>\n

    \n

    2.pyplot\u4e2d\u5e38\u7528\u51fd\u6570<\/h2>\n

    <\/h5>\n
    gcf<\/span><\/h5>\n

    \u529f\u80fd：\u83b7\u53d6<\/span>\u5f53\u524d<\/span>\u7a97\u53e3<\/span>\u7684<\/span>Figure<\/span>\u5bf9\u8c61<\/span>，<\/span>\u5982\u679c\u6ca1\u6709\u6d3b\u52a8\u7684\u56fe\u5f62，\u8fd9\u4e2a\u51fd\u6570\u5c06\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u56fe\u5f62，\u5e76\u5c06\u5176\u4f5c\u4e3a\u5f53\u524d\u6d3b\u52a8\u7684\u56fe\u5f62\u3002\u901a\u8fc7\u6b64\u51fd\u6570\u83b7\u53d6\u4e86\u5f53\u524d\u56fe\u5f62\u7684Figure\u5bf9\u8c61\u540e，\u53ef\u4ee5\u8c03\u7528Figure\u7c7b\u4e2d\u7684\u76f8\u5173\u64cd\u4f5c<\/span><\/p>\n

    gca<\/span><\/h5>\n

    \u529f\u80fd：\u83b7\u53d6<\/span>\u83b7\u53d6\u5f53\u524d\u56fe\u5f62\u4e2d\u7684<\/span>Axes<\/span>\u5bf9\u8c61<\/span><\/p>\n

    x = np.arange(0, 2*np.pi, 0.1)
    \ny = np.sin(x)
    \nplt.plot(x, y, label='sin')
    \n# \u83b7\u53d6Figure\u5bf9\u8c61
    \nfig = plt.gcf()
    \nfig.suptitle('sin')
    \n# \u83b7\u53d6Axes\u5bf9\u8c61
    \nax = plt.gca()
    \nax.set_xlabel('x')<\/p>\n

    plt.show()<\/p>\n

    savefig<\/span><\/h5>\n

    matplotlib.pyplot \u6a21\u5757\u4e2d\u7684 savefig<\/span> \u51fd\u6570\u7528\u4e8e\u5c06\u5f53\u524d\u56fe\u5f62\u4fdd\u5b58\u5230\u6587\u4ef6\u4e2d\u3002<\/span><\/p>\n

    plt.<\/span>savefig<\/span>(<\/span>*args<\/span>,<\/span> **kwargs<\/span>)<\/span><\/p>\n

    \u53c2\u6570：<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0fname：\u5b57\u7b26\u4e32\u6216\u7c7b\u4f3c\u6587\u4ef6\u7684\u5bf9\u8c61，\u6307\u5b9a\u4fdd\u5b58\u6587\u4ef6\u7684\u8def\u5f84\u6216\u6587\u4ef6\u540d\u3002\u53ef\u4ee5\u662f\u76f8\u5bf9\u8def\u5f84\u6216\u7edd\u5bf9\u8def\u5f84\u3002\u5982\u679c\u6587\u4ef6\u6269\u5c55\u540d\u7f3a\u5931，\u5c06\u4f7f\u7528\u9ed8\u8ba4\u683c\u5f0f（\u901a\u5e38\u662f PNG）\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0dpi：\u53ef\u9009，\u6307\u5b9a\u4fdd\u5b58\u56fe\u50cf\u7684dpi<\/span>（\u6bcf\u82f1\u5bf8\u70b9\u6570）\u3002\u9ed8\u8ba4\u503c\u662ffigure.dpi\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0format：\u53ef\u9009，\u6307\u5b9a\u6587\u4ef6\u683c\u5f0f（\u5982 <\/span>'png'<\/span>,<\/span> 'pdf'<\/span>,<\/span> 'svg'<\/span>,<\/span> 'ps'<\/span>,<\/span> 'eps'<\/span>,<\/span> …）\u3002\u5982\u679c\u7701\u7565，\u5c06\u4f7f\u7528\u6587\u4ef6\u6269\u5c55\u540d\u63a8\u65ad\u683c\u5f0f\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0bbox_inches：\u53ef\u9009，\u6307\u5b9a\u88c1\u526a\u6846，\u53ef\u4ee5\u662f <\/span>'tight'<\/span>\u3001<\/span>'standard'<\/span> \u6216\u4e00\u4e2a Bbox \u5bf9\u8c61\u3002\u9ed8\u8ba4\u4e3a <\/span>'standard'<\/span>\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0<\/span>tight<\/span>:<\/span>\u4fdd\u5b58\u7684\u56fe\u5f62\u6587\u4ef6\u4e2d\u4e0d\u4f1a\u6709\u4e0d\u5fc5\u8981\u7684\u7a7a\u767d\u8fb9\u7f18，\u4f7f\u5f97\u56fe\u5f62\u66f4\u52a0\u7d27\u51d1\u548c\u6574\u6d01<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0pad_inches：\u53ef\u9009，\u6307\u5b9a\u8fb9\u6846\u586b\u5145\u91cf（\u4ee5\u82f1\u5bf8\u4e3a\u5355\u4f4d）\u3002\u9ed8\u8ba4\u4e3a 0.1\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0facecolor：\u53ef\u9009，\u6307\u5b9a\u56fe\u50cf\u7684\u80cc\u666f\u989c\u8272\u3002\u9ed8\u8ba4\u4e3a <\/span>'w'<\/span>（\u767d\u8272）\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0edgecolor：\u53ef\u9009，\u6307\u5b9a\u56fe\u50cf\u8fb9\u6846\u7684\u989c\u8272\u3002\u9ed8\u8ba4\u4e3a <\/span>'w'<\/span>（\u767d\u8272）\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0orientation：\u53ef\u9009，\u6307\u5b9a\u9875\u9762\u65b9\u5411（<\/span>'portrait'<\/span> \u6216 <\/span>'landscape'<\/span>），\u4ec5\u5bf9\u4fdd\u5b58\u4e3a PDF \u6587\u4ef6\u65f6\u6709\u6548\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0papertype：\u53ef\u9009，\u6307\u5b9a\u7eb8\u5f20\u7c7b\u578b（\u5982 <\/span>'a4'<\/span>,<\/span> 'letter'<\/span>），\u4ec5\u5bf9\u4fdd\u5b58\u4e3a PDF \u6587\u4ef6\u65f6\u6709\u6548\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0format_kwargs：\u53ef\u9009，\u5176\u4ed6\u4e0e\u683c\u5f0f\u76f8\u5173\u7684\u5173\u952e\u5b57\u53c2\u6570\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0metadata：\u53ef\u9009，\u6307\u5b9a\u8981\u5199\u5165\u6587\u4ef6\u7684\u5143\u6570\u636e\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0pil_kwargs \u548c pdf_kwargs：\u53ef\u9009，\u7279\u5b9a\u4e8e PIL \u6216 PDF \u683c\u5f0f\u7684\u53c2\u6570\u3002<\/span><\/p>\n

    x = np.arange(0, 2*np.pi, 0.1)
    \ny = np.sin(x)
    \nplt.plot(x, y, label='sin')<\/p>\n

    y = np.cos(x)
    \nplt.plot(x, y, label='cos')
    \n# \u9690\u85cf\u5750\u6807\u8f74
    \nplt.axis('off')
    \n# \u4fdd\u5b58\u56fe\u7247
    \nplt.savefig('.\/sin.png')<\/p>\n

    imsave<\/span><\/h5>\n

    \u7528\u4e8e\u5c06\u56fe\u50cf\u6570\u636e\u4fdd\u5b58\u5230\u78c1\u76d8\u4e0a\u7684\u51fd\u6570<\/span><\/p>\n

    matplotlib.pyplot.<\/span>imsave<\/span>(<\/span>fname<\/span>,<\/span> arr<\/span>,<\/span> **kwargs<\/span>)<\/span><\/p>\n

    \u53c2\u6570：fname：\u4fdd\u5b58\u56fe\u50cf\u7684\u6587\u4ef6\u540d，\u53ef\u4ee5\u662f\u76f8\u5bf9\u8def\u5f84\u6216\u7edd\u5bf9\u8def\u5f84\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0arr：\u8868\u793a\u56fe\u50cf\u7684NumPy\u6570\u7ec4\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0kwargs：\u53ef\u9009\u53c2\u6570，\u7528\u4e8e\u6307\u5b9a\u4fdd\u5b58\u7684\u56fe\u50cf\u683c\u5f0f\u4ee5\u53ca\u56fe\u50cf\u8d28\u91cf\u7b49\u53c2\u6570\u3002<\/span><\/p>\n

    imsave\u548csavefig\u533a\u522b<\/span><\/span>：<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0savefig\u53ef\u4ee5<\/span>\u5c06<\/span>\u7ed8\u5236<\/span>\u7684<\/span>\u56fe\u50cf<\/span><\/span>\u4fdd\u5b58<\/span><\/span>\u6210<\/span><\/span>\u6587\u4ef6<\/span><\/span>，<\/span>\u5305\u542b<\/span>\u5750\u6807<\/span><\/span>\u3001<\/span>\u6807\u9898<\/span>\u3001<\/span>\u56fe\u4f8b<\/span>\u7b49<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0imsave\u662f<\/span>\u5c06\u4e8c\u7ef4\u6216\u4e09\u7ef4\u6570\u636e<\/span><\/span>\u4fdd\u5b58<\/span><\/span>\u6210<\/span><\/span>\u56fe\u50cf\u6587\u4ef6<\/span><\/span>，<\/span>\u4e0d\u542b<\/span><\/span>\u5750\u6807<\/span><\/span>\u7b49<\/span>，<\/span>\u5b83<\/span>\u6ca1\u6cd5<\/span>\u76f4\u63a5<\/span>\u4fdd\u5b58plot\u7b49\u7ed8\u5236<\/span>\u7684<\/span>\u56fe\u50cf<\/span><\/p>\n

    arr = np.array([[1,2,3,1], [2,3,1,2]])
    \n# \u7ed8\u5236\u4e8c\u7ef4\u6216\u4e09\u7ef4\u6570\u636e\u56fe\u50cf,\u901a\u8fc7cmap\u8fdb\u884c\u989c\u8272\u6620\u5c04
    \nplt.imshow(arr, cmap='gray')
    \nplt.imsave('.\/test.png', arr)
    \nplt.show()<\/p>\n

    imshow<\/span><\/h5>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0imshow() \u51fd\u6570\u662f Matplotlib.pyplot \u5e93\u4e2d\u7684\u4e00\u4e2a\u51fd\u6570，\u5b83\u5e38\u7528\u4e8e\u7ed8\u5236\u4e8c\u7ef4\u7684\u7070\u5ea6\u56fe\u50cf\u6216\u5f69\u8272\u56fe\u50cf，\u4e5f\u53ef\u4ee5\u7528\u4e8e\u7ed8\u5236\u77e9\u9635\u3001\u70ed\u529b\u56fe\u3001\u5730\u56fe\u7b49\u3002<\/span><\/p>\n

    imshow<\/span>(<\/span>X<\/span>,<\/span> cmap<\/span>=<\/span>None<\/span>,<\/span> norm<\/span>=<\/span>None<\/span>,<\/span> aspect<\/span>=<\/span>None<\/span>,<\/span> interpolation<\/span>=<\/span>None<\/span>,<\/span> alpha<\/span>=<\/span>None<\/span>,<\/span> vmin<\/span>=<\/span>None<\/span>,<\/span> vmax<\/span>=<\/span>None<\/span>,<\/span> origin<\/span>=<\/span>None<\/span>,<\/span> extent<\/span>=<\/span>None<\/span>,<\/span> shape<\/span>=<\/span>None<\/span>,<\/span> filternorm<\/span>=<\/span>1<\/span>,<\/span> filterrad<\/span>=<\/span>4.0<\/span>,<\/span> imlim<\/span>=<\/span>None<\/span>,<\/span> resample<\/span>=<\/span>None<\/span>,<\/span> url<\/span>=<\/span>None<\/span>,<\/span> *<\/span>,<\/span> data<\/span>=<\/span>None<\/span>,<\/span> **<\/span>kwargs<\/span>)<\/span><\/p>\n

    \u53c2\u6570：X：\u56fe\u50cf\u6570\u636e\u3002\u8fd9\u901a\u5e38\u662f\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4（\u7070\u5ea6\u56fe\u50cf）\u6216\u4e00\u4e2a\u4e09\u7ef4\u6570\u7ec4（\u5f69\u8272\u56fe\u50cf，\u5176\u4e2d\u7b2c\u4e09\u7ef4\u662f\u989c\u8272\u901a\u9053）\u3002\u5bf9\u4e8e\u4e8c\u7ef4\u6570\u7ec4，\u53ef\u4ee5\u4f7f\u7528 cmap \u53c2\u6570\u6765\u6307\u5b9a\u989c\u8272\u6620\u5c04<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0cmap：\u989c\u8272\u6620\u5c04\u3002\u7528\u4e8e\u63a7\u5236\u56fe\u50cf\u4e2d\u4e0d\u540c\u6570\u503c\u6240\u5bf9\u5e94\u7684\u989c\u8272\u3002\u9ed8\u8ba4\u989c\u8272\u662f<\/span>'viridis'<\/span>，\u4e5f\u53ef\u4ee5\u8bbe\u7f6e\u5176\u4ed6\u989c\u8272，\u5982`gray`\u3001`hot`\u3001`jet`\u3001<\/span>'binary'<\/span>\u7b49 <\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0norm：\u7528\u4e8e\u5c06\u6570\u636e\u503c\u6807\u51c6\u5316\u5230 [<\/span>0<\/span>,<\/span> 1<\/span>] \u533a\u95f4\u3002\u4ee5\u4fbf\u4e0e\u989c\u8272\u6620\u5c04\u4e00\u8d77\u4f7f\u7528\u3002\u5982\u679c\u4e3a None，\u5219\u6570\u636e\u5c06\u76f4\u63a5\u7528\u4e8e\u989c\u8272\u6620\u5c04\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0aspect：\u63a7\u5236\u56fe\u50cf\u5bbd\u9ad8\u6bd4<\/span>,<\/span>'auto'<\/span>（\u9ed8\u8ba4，\u6839\u636e\u6570\u636e\u5f62\u72b6\u81ea\u52a8\u8c03\u6574）\u3001<\/span>'equal'<\/span>（\u4f7f\u50cf\u7d20\u4e3a\u6b63\u65b9\u5f62）\u6216\u6570\u5b57（\u6307\u5b9a\u5bbd\u9ad8\u6bd4）<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0interpolation：\u63d2\u503c\u65b9\u6cd5\u3002\u7528\u4e8e\u63a7\u5236\u56fe\u50cf\u7684\u5e73\u6ed1\u7a0b\u5ea6\u548c\u7ec6\u8282\u7a0b\u5ea6\u3002\u53ef\u4ee5\u9009\u62e9`nearest`\u3001`bilinear`\u3001`bicubic`\u7b49\u63d2\u503c\u65b9\u6cd5\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0alpha：\u56fe\u50cf\u900f\u660e\u5ea6\u3002\u53d6\u503c\u8303\u56f4\u4e3a<\/span>0<\/span>~<\/span>1<\/span>\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0origin：\u5750\u6807\u8f74\u539f\u70b9\u7684\u4f4d\u7f6e\u3002\u53ef\u4ee5\u8bbe\u7f6e\u4e3a`upper`\u6216`lower`\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0extent：\u63a7\u5236\u663e\u793a\u7684\u6570\u636e\u8303\u56f4\u3002\u53ef\u4ee5\u8bbe\u7f6e\u4e3a`[xmin<\/span>,<\/span> xmax<\/span>,<\/span> ymin<\/span>,<\/span> ymax]`\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0vmin\u3001vmax：\u63a7\u5236\u989c\u8272\u6620\u5c04\u7684\u503c\u57df\u8303\u56f4\u3002<\/span><\/p>\n

    \u00a0 \u00a0 \u00a0 \u00a0filternorm \u548c filterrad：\u7528\u4e8e\u56fe\u50cf\u6ee4\u6ce2\u7684\u5bf9\u8c61\u3002\u53ef\u4ee5\u8bbe\u7f6e\u4e3a`None`\u3001`antigrain`\u3001`freetype`\u7b49\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0imlim： \u7528\u4e8e\u6307\u5b9a\u56fe\u50cf\u663e\u793a\u8303\u56f4\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0resample：\u7528\u4e8e\u6307\u5b9a\u56fe\u50cf\u91cd\u91c7\u6837\u65b9\u5f0f\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0url：\u7528\u4e8e\u6307\u5b9a\u56fe\u50cf\u94fe\u63a5\u3002<\/span><\/p>\n

    \n

    plt.colorbar<\/span>()<\/span><\/p>\n

    \u529f\u80fd：\u663e\u793a\u989c\u8272\u67f1<\/span><\/p>\n

    imread<\/span><\/h5>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0imread() \u65b9\u6cd5\u662f Matplotlib \u5e93\u4e2d\u7684\u4e00\u4e2a\u51fd\u6570，\u7528\u4e8e\u4ece\u56fe\u50cf\u6587\u4ef6\u4e2d\u8bfb\u53d6\u56fe\u50cf\u6570\u636e\u3002<\/span><\/p>\n

    imread() \u65b9\u6cd5\u8fd4\u56de\u4e00\u4e2a numpy.ndarray \u5bf9\u8c61，\u5176\u5f62\u72b6\u662f (nrows, ncols, nchannels)，\u8868\u793a\u8bfb\u53d6\u7684\u56fe\u50cf\u7684\u884c\u6570\u3001\u5217\u6570\u548c\u901a\u9053\u6570：<\/span><\/p>\n

  • \u5982\u679c\u56fe\u50cf\u662f\u7070\u5ea6\u56fe\u50cf，\u5219 nchannels \u4e3a 1\u3002<\/span><\/li>\n
  • \u5982\u679c\u662f\u5f69\u8272\u56fe\u50cf，\u5219 nchannels \u4e3a 3 \u6216 4，\u5206\u522b\u8868\u793a\u7ea2\u3001\u7eff\u3001\u84dd\u4e09\u4e2a\u989c\u8272\u901a\u9053\u548c\u4e00\u4e2a alpha \u901a\u9053；\u4e3a3\u65f6\u8868\u793a\u7ea2\u7eff\u84dd，\u4e3a4\u65f6\u8868\u793a\u7ea2\u7eff\u84dd\u3001\u900f\u660e\u5ea6\u3002<\/span><\/li>\n

    matplotlib<\/span>.pyplot.<\/span>imread<\/span>(<\/span>fname<\/span>,<\/span> format<\/span>=<\/span>None<\/span>)<\/span><\/p>\n

    \u53c2\u6570：fname：\u6307\u5b9a\u4e86\u8981\u8bfb\u53d6\u7684\u56fe\u50cf\u6587\u4ef6\u7684\u6587\u4ef6\u540d\u6216\u6587\u4ef6\u8def\u5f84，\u53ef\u4ee5\u662f\u76f8\u5bf9\u8def\u5f84\u6216\u7edd\u5bf9\u8def\u5f84\u3002<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0format<\/span>：\u53c2\u6570\u6307\u5b9a\u4e86\u56fe\u50cf\u6587\u4ef6\u7684\u683c\u5f0f，\u5982\u679c\u4e0d\u6307\u5b9a，\u5219\u9ed8\u8ba4\u6839\u636e\u6587\u4ef6\u540e\u7f00\u540d\u6765\u81ea\u52a8\u8bc6\u522b\u683c\u5f0f\u3002<\/span><\/p>\n

    \u8fd4\u56de\u503c：numpy.ndarray \u5bf9\u8c61<\/span><\/p>\n

    arr = plt.imread('map.png')
    \nplt.imshow(arr)
    \nplt.show()<\/p>\n

    close<\/span><\/h5>\n

    plt.close(fig=None)<\/span><\/p>\n

    \u529f\u80fd：\u8be5\u51fd\u6570\u7528\u4e8e\u5173\u95ed\u4e00\u4e2a\u6216\u591a\u4e2a\u6253\u5f00\u7684\u56fe\u5f62\u7a97\u53e3，\u91ca\u653e\u8d44\u6e90<\/span><\/p>\n

    \u53c2\u6570：fig：\u6307\u5b9a\u8981\u5173\u95ed\u7684\u56fe\u5f62，\u53ef\u4ee5\u662fFigure\u5bf9\u8c61，\u4e5f\u53ef\u4ee5\u662f\u56fe\u5f62\u5bf9\u5e94\u7684\u6574\u6570<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0all：\u5173\u95ed\u6240\u6709\u56fe\u5f62，\u5982\u679c\u53c2\u6570\u7701\u7565，\u5173\u95ed\u5f53\u524d\u56fe\u50cf<\/span><\/p>\n

    <\/h3>\n

    Line2D\u00a0 \u7c7b\u51fd\u6570<\/h5>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0plt.plot\u51fd\u6570\u7684\u8fd4\u56de\u503c\u8868\u793a\u5305\u542b\u4e00\u4e2a\u6216\u591a\u4e2a Line2D \u5bf9\u8c61<\/span>（\u6709\u591a\u6761\u7ebf\u65f6\u4f1a\u8fd4\u56de\u591a\u4e2aLine2D\u5bf9\u8c61）<\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0Line2D \u662f Matplotlib \u4e2d\u7528\u4e8e\u8868\u793a\u4e8c\u7ef4\u7ebf\u6761\u7684\u7c7b\u3002\u901a\u8fc7\u8fd4\u56de Line2D \u5bf9\u8c61，\u4f60\u53ef\u4ee5\u8bbf\u95ee\u548c\u4fee\u6539\u7ebf\u6761\u7684\u5404\u79cd\u5c5e\u6027，\u4f8b\u5982\u989c\u8272\u3001\u7ebf\u578b\u3001\u6807\u7b7e\u7b49\u3002\u8fd9\u4f7f\u5f97 plt.plot() \u4e0d\u4ec5\u4ec5\u662f\u7ed8\u5236\u56fe\u5f62，\u8fd8\u53ef\u4ee5\u8ba9\u4f60\u5bf9\u7ed8\u5236\u7684\u7ebf\u6761\u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u5b9a\u5236\u3002<\/span><\/p>\n

    get_label<\/span><\/h6>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u8be5\u65b9\u6cd5\u7528\u4e8e\u83b7\u53d6\u56fe\u50cf<\/span>\u7684<\/span>\u6807\u7b7e<\/span>（\u53c2\u6570\u4e2d\u6307\u5b9a\u7684label\u503c）<\/span>\u3002\u8fd9\u4e2a\u65b9\u6cd5\u901a\u5e38\u7528\u4e8e\u83b7\u53d6\u5df2\u7ecf\u8bbe\u7f6e\u597d\u7684\u6807\u7b7e，\u4ee5\u4fbf\u4e8e\u540e\u7eed\u7684\u68c0\u67e5\u6216\u4fee\u6539.<\/span><\/p>\n

    set_data<\/span><\/h6>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u8be5\u51fd\u6570\u529f\u80fd\u4e3a\u7528\u4e8e\u52a8\u6001\u66f4\u65b0\u7ebf\u6761\u7684 x \u548c y \u6570\u636e\u3002\u4e3b\u8981\u5728\u9700\u8981\u5b9e\u65f6\u66f4\u65b0\u56fe\u5f62（\u4f8b\u5982\u52a8\u753b）\u7684\u573a\u666f\u4e2d\u3002<\/span><\/p>\n

    Line2D.set_<\/span>data<\/span>(<\/span>xdata<\/span>,<\/span> ydata<\/span>)<\/span><\/span><\/p>\n

    \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u8c03\u7528\u8be5\u65b9\u6cd5\u540e，\u56fe\u5f62\u4f1a\u6839\u636e\u65b0\u7684\u6570\u636e\u91cd\u65b0\u7ed8\u5236\u3002\u5b83\u4e0d\u4f1a\u81ea\u52a8\u5237\u65b0\u56fe\u5f62，\u4f46\u53ef\u4ee5\u4e0e plt.draw() \u6216 plt.pause() \u7b49\u65b9\u6cd5\u7ed3\u5408\u4f7f\u7528，\u4ee5\u5b9e\u73b0\u52a8\u6001\u66f4\u65b0\u7684\u6548\u679c\u3002<\/span><\/p>\n

    pause<\/span><\/h5>\n

    \u7528\u4e8e\u5728\u7ed8\u56fe\u65f6\u6682\u505c\u7a0b\u5e8f\u6267\u884c，\u5e76\u5728\u6307\u5b9a\u7684\u65f6\u95f4\u95f4\u9694\u540e\u7ee7\u7eed\u6267\u884c\u3002\u5b83\u5e38\u7528\u4e8e\u52a8\u6001\u66f4\u65b0\u56fe\u5f62\u6216\u521b\u5efa\u7b80\u5355\u7684\u52a8\u753b\u6548\u679c\u3002<\/span><\/p>\n

    \u51fd\u6570\u7684\u4f5c\u7528：<\/span><\/p>\n

      \n
    • \u6682\u505c\u7a0b\u5e8f<\/span>：plt.pause(interval) \u4f1a\u6682\u505c\u7a0b\u5e8f\u7684\u6267\u884c，\u6682\u505c\u7684\u65f6\u95f4\u7531\u53c2\u6570 interval（\u5355\u4f4d\u4e3a\u79d2）\u51b3\u5b9a\u3002<\/span><\/li>\n
    • \u5237\u65b0\u56fe\u5f62\u7a97\u53e3<\/span>：\u5728\u6682\u505c\u671f\u95f4，plt.pause() \u4f1a\u5f3a\u5236\u5237\u65b0\u56fe\u5f62\u7a97\u53e3，\u663e\u793a\u6700\u65b0\u7684\u56fe\u5f62\u5185\u5bb9\u3002\u8fd9\u4f7f\u5f97\u5b83\u7279\u522b\u9002\u5408\u7528\u4e8e\u52a8\u6001\u66f4\u65b0\u56fe\u5f62\u7684\u573a\u666f\u3002<\/span><\/li>\n<\/ul>\n

      \u51fd\u6570\u539f\u578b：<\/span><\/p>\n

      pyplot.pause<\/span>(<\/span>interval<\/span>)<\/span>
      \n\u53c2\u6570：interval：\u65f6\u95f4，\u79d2<\/span>
      \n<\/span><\/p>\n

      x = np.arange(0, 2*np.pi, 0.1)
      \ny = np.sin(x)
      \nld, = plt.plot(x, y, label='sin')<\/p>\n

      # \u83b7\u53d6\u56fe\u50cf\u4e2dlabel\u6570\u636e
      \n# ret = ld.get_label()
      \n# print(ret)<\/p>\n

      y = np.cos(x)
      \n# \u6839\u636e\u6307\u5b9a\u7684\u65f6\u95f4\u6682\u505c\u7a0b\u5e8f
      \nplt.pause(5)
      \n# \u4fee\u6539\u539f\u56fe\u50cf\u7684\u6570\u636e
      \nld.set_data(x, y)<\/p>\n

      plt.show()<\/p>\n

      \n

      3.\u7ed8\u5236\u5b50\u56fe\u7f51\u683c<\/h2>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u4f7f\u7528\u6a21\u5757gridspec\u4e2d\u7684\u51fd\u6570GridSpec\u7ed8\u5236<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u5728 Matplotlib \u4e2d，GridSpec \u5bf9\u8c61\u63d0\u4f9b\u4e86\u4e00\u79cd\u7075\u6d3b\u7684\u65b9\u5f0f\u6765\u521b\u5efa\u5b50\u56fe\u7f51\u683c（subplots grid），\u5141\u8bb8\u5b50\u56fe\u8de8\u8d8a\u591a\u4e2a\u884c\u548c\u5217，\u4ee5\u53ca\u5177\u6709\u4e0d\u5747\u5300\u7684\u884c\u9ad8\u548c\u5217\u5bbd\u3002<\/span><\/p>\n

      from<\/span> matplotlib<\/span>.<\/span>gridspec <\/span>import<\/span> GridSpec<\/span><\/p>\n

      \n

      GridSpec<\/span>(<\/span>nrows<\/span>,<\/span> ncols<\/span>,<\/span> figure<\/span>=<\/span>None<\/span>,<\/span> left<\/span>=<\/span>None<\/span>,<\/span> right<\/span>=<\/span>None<\/span>,<\/span> bottom<\/span>=<\/span>None<\/span>,<\/span> top<\/span>=<\/span>None<\/span>,<\/span> wspace<\/span>=<\/span>None<\/span>,<\/span> hspace<\/span>=<\/span>None<\/span>,<\/span> width_ratios<\/span>=<\/span>None<\/span>,<\/span> height_ratios<\/span>=<\/span>None<\/span>,<\/span> w_pad<\/span>=<\/span>None<\/span>,<\/span> h_pad<\/span>=<\/span>None<\/span>)<\/span><\/p>\n

      \n

      \u53c2\u6570：nrows: <\/span>int<\/span>\u5b50\u56fe\u7f51\u683c\u7684\u884c\u6570\u3002<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0ncols: <\/span>int<\/span>\u5b50\u56fe\u7f51\u683c\u7684\u5217\u6570\u3002<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0figure: matplotlib<\/span>.<\/span>figure<\/span>.<\/span>Figure<\/span>,<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0optional<\/span>,<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0default<\/span>: None<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u6307\u5b9a\u7684\u56fe\u5f62\u5bf9\u8c61\u3002\u5982\u679c\u672a\u63d0\u4f9b，\u5219\u9ed8\u8ba4\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u56fe\u5f62\u5bf9\u8c61\u3002<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0left<\/span>: <\/span>float<\/span>,<\/span> optional<\/span>,<\/span> default<\/span>: None\u5b50\u56fe\u7f51\u683c\u5de6\u4fa7\u7684\u76f8\u5bf9\u4f4d\u7f6e（<\/span>0<\/span> \u5230 <\/span>1<\/span> \u7684\u6bd4\u4f8b）\u3002\u5982\u679c\u672a\u6307\u5b9a，\u5219\u4f7f\u7528\u9ed8\u8ba4\u7684\u5de6\u8fb9\u754c\u3002<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0right<\/span>: <\/span>float<\/span>,<\/span> optional<\/span>,<\/span> default<\/span>: None\u5b50\u56fe\u7f51\u683c\u53f3\u4fa7\u7684\u76f8\u5bf9\u4f4d\u7f6e（<\/span>0<\/span> \u5230 <\/span>1<\/span> \u7684\u6bd4\u4f8b）\u3002\u5982\u679c\u672a\u6307\u5b9a，\u5219\u4f7f\u7528\u9ed8\u8ba4\u7684\u53f3\u8fb9\u754c\u3002<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0bottom: <\/span>float<\/span>,<\/span> optional<\/span>,<\/span> default<\/span>: None\u5b50\u56fe\u7f51\u683c\u5e95\u90e8\u7684\u76f8\u5bf9\u4f4d\u7f6e（<\/span>0<\/span> \u5230 <\/span>1<\/span> \u7684\u6bd4\u4f8b）\u3002\u5982\u679c\u672a\u6307\u5b9a，\u5219\u4f7f\u7528\u9ed8\u8ba4\u7684\u5e95\u8fb9\u754c\u3002<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0top<\/span>: <\/span>float<\/span>,<\/span> optional<\/span>,<\/span> default<\/span>: None\u5b50\u56fe\u7f51\u683c\u9876\u90e8\u7684\u76f8\u5bf9\u4f4d\u7f6e（<\/span>0<\/span> \u5230 <\/span>1<\/span> \u7684\u6bd4\u4f8b）\u3002\u5982\u679c\u672a\u6307\u5b9a，\u5219\u4f7f\u7528\u9ed8\u8ba4\u7684\u9876\u8fb9\u754c\u3002<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0wspace: <\/span>float<\/span> or<\/span> None<\/span>,<\/span> optional<\/span>,<\/span> default<\/span>: None\u5b50\u56fe\u4e4b\u95f4\u7684\u6c34\u5e73\u95f4\u8ddd（\u4ee5\u82f1\u5bf8\u4e3a\u5355\u4f4d）\u6216\u4f5c\u4e3a\u5b50\u56fe\u5bbd\u5ea6\u7684\u6bd4\u4f8b\u3002\u5982\u679c\u672a\u6307\u5b9a，\u5219\u4f7f\u7528\u9ed8\u8ba4\u7684\u95f4\u8ddd\u3002<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0hspace: <\/span>float<\/span> or<\/span> None<\/span>,<\/span> optional<\/span>,<\/span> default<\/span>: None\u5b50\u56fe\u4e4b\u95f4\u7684\u5782\u76f4\u95f4\u8ddd（\u4ee5\u82f1\u5bf8\u4e3a\u5355\u4f4d）\u6216\u4f5c\u4e3a\u5b50\u56fe\u9ad8\u5ea6\u7684\u6bd4\u4f8b\u3002\u5982\u679c\u672a\u6307\u5b9a，\u5219\u4f7f\u7528\u9ed8\u8ba4\u7684\u95f4\u8ddd\u3002<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0width_ratios: list <\/span>of<\/span> floats<\/span>,<\/span> optional<\/span>,<\/span> default<\/span>: None<\/span><\/p>\n

      \u6307\u5b9a\u6bcf\u4e00\u5217\u7684\u5bbd\u5ea6\u6bd4\u4f8b\u3002\u5982\u679c\u6307\u5b9a，\u5219 ncols \u5fc5\u987b\u4e0e\u5217\u8868\u957f\u5ea6\u5339\u914d\u3002<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0height_ratios: list <\/span>of<\/span> floats<\/span>,<\/span> optional<\/span>,<\/span> default<\/span>: None<\/span><\/p>\n

      \u6307\u5b9a\u6bcf\u4e00\u884c\u7684\u9ad8\u5ea6\u6bd4\u4f8b\u3002\u5982\u679c\u6307\u5b9a，\u5219 nrows \u5fc5\u987b\u4e0e\u5217\u8868\u957f\u5ea6\u5339\u914d\u3002<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0w_pad: <\/span>float<\/span>,<\/span> optional<\/span>,<\/span> default<\/span>: None\u5b50\u56fe\u4e4b\u95f4\u7684\u6c34\u5e73\u586b\u5145（\u4ee5\u82f1\u5bf8\u4e3a\u5355\u4f4d）\u3002\u5982\u679c\u672a\u6307\u5b9a，\u5219\u4f7f\u7528\u9ed8\u8ba4\u7684\u586b\u5145\u3002<\/span><\/p>\n

      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0h_pad: <\/span>float<\/span>,<\/span> optional<\/span>,<\/span> default<\/span>: None\u5b50\u56fe\u4e4b\u95f4\u7684\u5782\u76f4\u586b\u5145（\u4ee5\u82f1\u5bf8\u4e3a\u5355\u4f4d）\u3002\u5982\u679c\u672a\u6307\u5b9a，\u5219\u4f7f\u7528\u9ed8\u8ba4\u7684\u586b\u5145\u3002<\/span><\/p>\n

      import matplotlib.pyplot as plt
      \nimport numpy as np
      \nfrom matplotlib.gridspec import GridSpec
      \n# import matplotlib.gridspec as gs
      \nfig = plt.figure()<\/p>\n

      # \u6dfb\u52a0\u5b50\u56fe\u7f51\u683c
      \ngs = GridSpec(2, 3)
      \n# \u5728\u7b2c\u4e00\u884c\u6dfb\u52a0\u4e09\u4e2a\u5b50\u56fe
      \nfig.add_subplot(gs[0, 0])
      \nfig.add_subplot(gs[0, 1])
      \nfig.add_subplot(gs[0, 2])
      \n# \u5728\u7b2c\u4e8c\u884c\u6dfb\u52a0\u4e00\u4e2a\u5b50\u56fe
      \nfig.add_subplot(gs[1, :])<\/p>\n

      plt.show()<\/p>\n<\/p>\n<\/p><\/p>\n","protected":false},"excerpt":{"rendered":"

      \u6587\u7ae0\u6d4f\u89c8\u9605\u8bfb248\u6b21\uff0c\u70b9\u8d5e6\u6b21\uff0c\u6536\u85cf3\u6b21\u3002\u62b1\u6028\u8eab\u5904\u9ed1\u6697\uff0c\u4e0d\u5982\u63d0\u706f\u524d\u884c\u3002<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[2468,81,190],"topic":[],"class_list":["post-53714","post","type-post","status-publish","format-standard","hentry","category-server","tag-matplotlib","tag-python","tag-190"],"yoast_head":"\n\u5c0f\u6770python\u9ad8\u7ea7\uff08four day\uff09\u2014\u2014matplotlib\u5e93 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wsisp.com\/helps\/53714.html\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u5c0f\u6770python\u9ad8\u7ea7\uff08four day\uff09\u2014\u2014matplotlib\u5e93 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"og:description\" content=\"\u6587\u7ae0\u6d4f\u89c8\u9605\u8bfb248\u6b21\uff0c\u70b9\u8d5e6\u6b21\uff0c\u6536\u85cf3\u6b21\u3002\u62b1\u6028\u8eab\u5904\u9ed1\u6697\uff0c\u4e0d\u5982\u63d0\u706f\u524d\u884c\u3002\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.wsisp.com\/helps\/53714.html\" \/>\n<meta property=\"og:site_name\" content=\"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"article:published_time\" content=\"2025-08-12T08:19:59+00:00\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u4f5c\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u9884\u8ba1\u9605\u8bfb\u65f6\u95f4\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 \u5206\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/53714.html\",\"url\":\"https:\/\/www.wsisp.com\/helps\/53714.html\",\"name\":\"\u5c0f\u6770python\u9ad8\u7ea7\uff08four day\uff09\u2014\u2014matplotlib\u5e93 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\",\"isPartOf\":{\"@id\":\"https:\/\/www.wsisp.com\/helps\/#website\"},\"datePublished\":\"2025-08-12T08:19:59+00:00\",\"dateModified\":\"2025-08-12T08:19:59+00:00\",\"author\":{\"@id\":\"https:\/\/www.wsisp.com\/helps\/#\/schema\/person\/358e386c577a3ab51c4493330a20ad41\"},\"breadcrumb\":{\"@id\":\"https:\/\/www.wsisp.com\/helps\/53714.html#breadcrumb\"},\"inLanguage\":\"zh-Hans\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.wsisp.com\/helps\/53714.html\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/53714.html#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"\u9996\u9875\",\"item\":\"https:\/\/www.wsisp.com\/helps\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"\u5c0f\u6770python\u9ad8\u7ea7\uff08four day\uff09\u2014\u2014matplotlib\u5e93\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/#website\",\"url\":\"https:\/\/www.wsisp.com\/helps\/\",\"name\":\"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\",\"description\":\"\u9999\u6e2f\u670d\u52a1\u5668_\u9999\u6e2f\u4e91\u670d\u52a1\u5668\u8d44\u8baf_\u670d\u52a1\u5668\u5e2e\u52a9\u6587\u6863_\u670d\u52a1\u5668\u6559\u7a0b\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.wsisp.com\/helps\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"zh-Hans\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/#\/schema\/person\/358e386c577a3ab51c4493330a20ad41\",\"name\":\"admin\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"zh-Hans\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/gravatar.wp-china-yes.net\/avatar\/?s=96&d=mystery\",\"contentUrl\":\"https:\/\/gravatar.wp-china-yes.net\/avatar\/?s=96&d=mystery\",\"caption\":\"admin\"},\"sameAs\":[\"http:\/\/wp.wsisp.com\"],\"url\":\"https:\/\/www.wsisp.com\/helps\/author\/admin\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"\u5c0f\u6770python\u9ad8\u7ea7\uff08four day\uff09\u2014\u2014matplotlib\u5e93 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.wsisp.com\/helps\/53714.html","og_locale":"zh_CN","og_type":"article","og_title":"\u5c0f\u6770python\u9ad8\u7ea7\uff08four day\uff09\u2014\u2014matplotlib\u5e93 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3","og_description":"\u6587\u7ae0\u6d4f\u89c8\u9605\u8bfb248\u6b21\uff0c\u70b9\u8d5e6\u6b21\uff0c\u6536\u85cf3\u6b21\u3002\u62b1\u6028\u8eab\u5904\u9ed1\u6697\uff0c\u4e0d\u5982\u63d0\u706f\u524d\u884c\u3002","og_url":"https:\/\/www.wsisp.com\/helps\/53714.html","og_site_name":"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3","article_published_time":"2025-08-12T08:19:59+00:00","author":"admin","twitter_card":"summary_large_image","twitter_misc":{"\u4f5c\u8005":"admin","\u9884\u8ba1\u9605\u8bfb\u65f6\u95f4":"5 \u5206"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/www.wsisp.com\/helps\/53714.html","url":"https:\/\/www.wsisp.com\/helps\/53714.html","name":"\u5c0f\u6770python\u9ad8\u7ea7\uff08four day\uff09\u2014\u2014matplotlib\u5e93 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3","isPartOf":{"@id":"https:\/\/www.wsisp.com\/helps\/#website"},"datePublished":"2025-08-12T08:19:59+00:00","dateModified":"2025-08-12T08:19:59+00:00","author":{"@id":"https:\/\/www.wsisp.com\/helps\/#\/schema\/person\/358e386c577a3ab51c4493330a20ad41"},"breadcrumb":{"@id":"https:\/\/www.wsisp.com\/helps\/53714.html#breadcrumb"},"inLanguage":"zh-Hans","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.wsisp.com\/helps\/53714.html"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/www.wsisp.com\/helps\/53714.html#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"\u9996\u9875","item":"https:\/\/www.wsisp.com\/helps"},{"@type":"ListItem","position":2,"name":"\u5c0f\u6770python\u9ad8\u7ea7\uff08four day\uff09\u2014\u2014matplotlib\u5e93"}]},{"@type":"WebSite","@id":"https:\/\/www.wsisp.com\/helps\/#website","url":"https:\/\/www.wsisp.com\/helps\/","name":"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3","description":"\u9999\u6e2f\u670d\u52a1\u5668_\u9999\u6e2f\u4e91\u670d\u52a1\u5668\u8d44\u8baf_\u670d\u52a1\u5668\u5e2e\u52a9\u6587\u6863_\u670d\u52a1\u5668\u6559\u7a0b","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.wsisp.com\/helps\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"zh-Hans"},{"@type":"Person","@id":"https:\/\/www.wsisp.com\/helps\/#\/schema\/person\/358e386c577a3ab51c4493330a20ad41","name":"admin","image":{"@type":"ImageObject","inLanguage":"zh-Hans","@id":"https:\/\/www.wsisp.com\/helps\/#\/schema\/person\/image\/","url":"https:\/\/gravatar.wp-china-yes.net\/avatar\/?s=96&d=mystery","contentUrl":"https:\/\/gravatar.wp-china-yes.net\/avatar\/?s=96&d=mystery","caption":"admin"},"sameAs":["http:\/\/wp.wsisp.com"],"url":"https:\/\/www.wsisp.com\/helps\/author\/admin"}]}},"_links":{"self":[{"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/posts\/53714","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/comments?post=53714"}],"version-history":[{"count":0,"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/posts\/53714\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/media?parent=53714"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/categories?post=53714"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/tags?post=53714"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/topic?post=53714"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}