{"id":1049731,"date":"2024-12-31T14:01:51","date_gmt":"2024-12-31T06:01:51","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1049731.html"},"modified":"2024-12-31T14:01:54","modified_gmt":"2024-12-31T06:01:54","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e7%94%bb%e4%b8%80%e4%b8%aa%e5%8d%8a%e5%9c%86","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1049731.html","title":{"rendered":"\u5982\u4f55\u7528Python\u753b\u4e00\u4e2a\u534a\u5706"},"content":{"rendered":"

\"\u5982\u4f55\u7528Python\u753b\u4e00\u4e2a\u534a\u5706\"<\/p>\n

\u5982\u4f55\u7528Python\u753b\u4e00\u4e2a\u534a\u5706<\/strong><\/p>\n<\/p>\n

\u8981\u7528Python\u753b\u4e00\u4e2a\u534a\u5706\uff0c\u53ef\u4ee5\u4f7f\u7528Matplotlib\u5e93\u3001Numpy\u5e93\u3001\u4ee3\u7801\u7b80\u5355\u4e14\u6613\u4e8e\u7406\u89e3\u3002<\/strong> Matplotlib\u5e93\u662fPython\u4e2d\u7528\u4e8e\u7ed8\u52362D\u56fe\u5f62\u7684\u975e\u5e38\u6d41\u884c\u7684\u5e93\uff0c\u800cNumpy\u5e93\u5219\u662fPython\u4e2d\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\u3002\u4f7f\u7528Matplotlib\u548cNumpy\u53ef\u4ee5\u8f7b\u677e\u521b\u5efa\u548c\u7ed8\u5236\u5404\u79cd\u56fe\u5f62\uff0c\u5305\u62ec\u534a\u5706\u3002\u5728\u672c\u6587\u4e2d\uff0c\u6211\u4eec\u5c06\u91cd\u70b9\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u5e93\u6765\u7ed8\u5236\u4e00\u4e2a\u534a\u5706\uff0c\u5e76\u8be6\u7ec6\u89e3\u91ca\u6bcf\u4e00\u6b65\u9aa4\u7684\u5b9e\u73b0\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5b89\u88c5\u6240\u9700\u5e93<\/h3>\n<\/p>\n

\u5728\u5f00\u59cb\u4e4b\u524d\uff0c\u60a8\u9700\u8981\u786e\u4fdd\u5df2\u5b89\u88c5\u4e86Matplotlib\u548cNumpy\u5e93\u3002\u5982\u679c\u8fd8\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install matplotlib numpy<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u5bfc\u5165\u6240\u9700\u5e93<\/h3>\n<\/p>\n
\u5728\u7ed8\u5236\u534a\u5706\u4e4b\u524d\uff0c\u6211\u4eec\u9996\u5148\u9700\u8981\u5bfc\u5165\u5fc5\u8981\u7684\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u8fdb\u884c\u5bfc\u5165\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import numpy as np<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u5b9a\u4e49\u534a\u5706\u7684\u53c2\u6570<\/h3>\n<\/p>\n
\u7ed8\u5236\u534a\u5706\u7684\u4e00\u4e2a\u5173\u952e\u6b65\u9aa4\u662f\u5b9a\u4e49\u5176\u53c2\u6570\uff0c\u5305\u62ec\u534a\u5f84\u3001\u4e2d\u5fc3\u70b9\u7b49\u3002\u4ee5\u4e0b\u662f\u5b9a\u4e49\u534a\u5706\u53c2\u6570\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
radius = 1  # \u534a\u5f84<\/p>\n
center = (0, 0)  # \u534a\u5706\u7684\u4e2d\u5fc3\u70b9<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u751f\u6210\u534a\u5706\u7684\u5750\u6807\u70b9<\/h3>\n<\/p>\n
\u4f7f\u7528Numpy\u5e93\u751f\u6210\u534a\u5706\u7684\u5750\u6807\u70b9\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u751f\u6210\u4e00\u7ec4\u89d2\u5ea6\u503c\uff0c\u5e76\u4f7f\u7528\u8fd9\u4e9b\u89d2\u5ea6\u8ba1\u7b97\u5bf9\u5e94\u7684\u5750\u6807\u70b9\u6765\u5b9e\u73b0\u8fd9\u4e00\u70b9\uff1a<\/p>\n<\/p>\n
theta = np.linspace(0, np.pi, 100)  # \u751f\u6210\u4ece0\u5230\u03c0\u7684100\u4e2a\u89d2\u5ea6\u503c<\/p>\n
x = center[0] + radius * np.cos(theta)  # \u8ba1\u7b97x\u5750\u6807<\/p>\n
y = center[1] + radius * np.sin(theta)  # \u8ba1\u7b97y\u5750\u6807<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u7ed8\u5236\u534a\u5706<\/h3>\n<\/p>\n
\u4f7f\u7528Matplotlib\u5e93\u7ed8\u5236\u751f\u6210\u7684\u534a\u5706\u5750\u6807\u70b9\uff0c\u5e76\u8bbe\u7f6e\u56fe\u5f62\u7684\u5c5e\u6027\uff1a<\/p>\n<\/p>\n
plt.figure()<\/p>\n
plt.plot(x, y, label='\u534a\u5706')<\/p>\n
plt.title('Python\u7ed8\u5236\u534a\u5706\u793a\u4f8b')<\/p>\n
plt.xlabel('X\u8f74')<\/p>\n
plt.ylabel('Y\u8f74')<\/p>\n
plt.axhline(0, color='black', linewidth=0.5)  # \u6dfb\u52a0x\u8f74<\/p>\n
plt.axvline(0, color='black', linewidth=0.5)  # \u6dfb\u52a0y\u8f74<\/p>\n
plt.grid()<\/p>\n
plt.legend()<\/p>\n
plt.axis('equal')  # \u4fdd\u6301x\u8f74\u548cy\u8f74\u6bd4\u4f8b\u76f8\u540c<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u4ee3\u7801\u5b8c\u6574\u793a\u4f8b<\/h3>\n<\/p>\n
\u4e3a\u4e86\u65b9\u4fbf\u5927\u5bb6\u66f4\u597d\u5730\u7406\u89e3\uff0c\u4ee5\u4e0b\u662f\u4e00\u4e2a\u5b8c\u6574\u7684\u4ee3\u7801\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import numpy as np<\/p>\n
\u5b9a\u4e49\u534a\u5706\u53c2\u6570<\/strong><\/h2>\n
radius = 1<\/p>\n
center = (0, 0)<\/p>\n
\u751f\u6210\u534a\u5706\u7684\u5750\u6807\u70b9<\/strong><\/h2>\n
theta = np.linspace(0, np.pi, 100)<\/p>\n
x = center[0] + radius * np.cos(theta)<\/p>\n
y = center[1] + radius * np.sin(theta)<\/p>\n
\u7ed8\u5236\u534a\u5706<\/strong><\/h2>\n
plt.figure()<\/p>\n
plt.plot(x, y, label='\u534a\u5706')<\/p>\n
plt.title('Python\u7ed8\u5236\u534a\u5706\u793a\u4f8b')<\/p>\n
plt.xlabel('X\u8f74')<\/p>\n
plt.ylabel('Y\u8f74')<\/p>\n
plt.axhline(0, color='black', linewidth=0.5)<\/p>\n
plt.axvline(0, color='black', linewidth=0.5)<\/p>\n
plt.grid()<\/p>\n
plt.legend()<\/p>\n
plt.axis('equal')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e03\u3001\u6269\u5c55\u5e94\u7528<\/h3>\n<\/p>\n
    \n
  1. \u8c03\u6574\u534a\u5706\u7684\u5927\u5c0f\u548c\u4f4d\u7f6e<\/strong>\uff1a\u901a\u8fc7\u66f4\u6539\u534a\u5f84\u548c\u4e2d\u5fc3\u70b9\u7684\u5750\u6807\uff0c\u53ef\u4ee5\u7ed8\u5236\u4e0d\u540c\u5927\u5c0f\u548c\u4f4d\u7f6e\u7684\u534a\u5706\u3002\u4f8b\u5982\uff0c\u8c03\u6574\u534a\u5f84\u4e3a2\uff0c\u4e2d\u5fc3\u70b9\u4e3a(1, 1)\uff1a<\/li>\n<\/ol>\n
    radius = 2<\/p>\n
    center = (1, 1)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
      \n
    1. \u7ed8\u5236\u591a\u4e2a\u534a\u5706<\/strong>\uff1a\u53ef\u4ee5\u901a\u8fc7\u591a\u6b21\u8c03\u7528\u7ed8\u5236\u51fd\u6570\u6765\u7ed8\u5236\u591a\u4e2a\u534a\u5706\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff0c\u7ed8\u5236\u4e24\u4e2a\u4e0d\u540c\u4f4d\u7f6e\u548c\u5927\u5c0f\u7684\u534a\u5706\uff1a<\/li>\n<\/ol>\n
      # \u7b2c\u4e00\u4e2a\u534a\u5706\u53c2\u6570<\/p>\n
      radius1 = 1<\/p>\n
      center1 = (0, 0)<\/p>\n
      theta1 = np.linspace(0, np.pi, 100)<\/p>\n
      x1 = center1[0] + radius1 * np.cos(theta1)<\/p>\n
      y1 = center1[1] + radius1 * np.sin(theta1)<\/p>\n
      \u7b2c\u4e8c\u4e2a\u534a\u5706\u53c2\u6570<\/strong><\/h2>\n
      radius2 = 2<\/p>\n
      center2 = (2, 2)<\/p>\n
      theta2 = np.linspace(0, np.pi, 100)<\/p>\n
      x2 = center2[0] + radius2 * np.cos(theta2)<\/p>\n
      y2 = center2[1] + radius2 * np.sin(theta2)<\/p>\n
      \u7ed8\u5236\u591a\u4e2a\u534a\u5706<\/strong><\/h2>\n
      plt.figure()<\/p>\n
      plt.plot(x1, y1, label='\u534a\u57061')<\/p>\n
      plt.plot(x2, y2, label='\u534a\u57062')<\/p>\n
      plt.title('Python\u7ed8\u5236\u591a\u4e2a\u534a\u5706\u793a\u4f8b')<\/p>\n
      plt.xlabel('X\u8f74')<\/p>\n
      plt.ylabel('Y\u8f74')<\/p>\n
      plt.axhline(0, color='black', linewidth=0.5)<\/p>\n
      plt.axvline(0, color='black', linewidth=0.5)<\/p>\n
      plt.grid()<\/p>\n
      plt.legend()<\/p>\n
      plt.axis('equal')<\/p>\n
      plt.show()<\/p>\n
      <\/code><\/pre>\n<\/p>\n
        \n
      1. \u81ea\u5b9a\u4e49\u534a\u5706\u7684\u6837\u5f0f<\/strong>\uff1a\u53ef\u4ee5\u901a\u8fc7Matplotlib\u7684\u6837\u5f0f\u9009\u9879\u81ea\u5b9a\u4e49\u534a\u5706\u7684\u989c\u8272\u3001\u7ebf\u578b\u7b49\u3002\u4f8b\u5982\uff0c\u8bbe\u7f6e\u534a\u5706\u7684\u989c\u8272\u4e3a\u7ea2\u8272\uff0c\u7ebf\u578b\u4e3a\u865a\u7ebf\uff1a<\/li>\n<\/ol>\n
        plt.plot(x, y, 'r--', label='\u7ea2\u8272\u865a\u7ebf\u534a\u5706')<\/p>\n
        <\/code><\/pre>\n<\/p>\n
          \n
        1. \u4fdd\u5b58\u56fe\u50cf<\/strong>\uff1a\u5982\u679c\u9700\u8981\u5c06\u7ed8\u5236\u7684\u534a\u5706\u4fdd\u5b58\u4e3a\u56fe\u50cf\u6587\u4ef6\uff0c\u53ef\u4ee5\u4f7f\u7528Matplotlib\u7684savefig<\/code>\u51fd\u6570\uff1a<\/li>\n<\/ol>\n
          plt.savefig('semi_circle.png')<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u516b\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
          \u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u6211\u4eec\u4e86\u89e3\u4e86\u5982\u4f55\u4f7f\u7528Python\u4e2d\u7684Matplotlib\u548cNumpy\u5e93\u6765\u7ed8\u5236\u4e00\u4e2a\u534a\u5706\u3002\u6211\u4eec\u9996\u5148\u5b89\u88c5\u5e76\u5bfc\u5165\u4e86\u5fc5\u8981\u7684\u5e93\uff0c\u7136\u540e\u5b9a\u4e49\u4e86\u534a\u5706\u7684\u53c2\u6570\uff0c\u5e76\u751f\u6210\u4e86\u534a\u5706\u7684\u5750\u6807\u70b9\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u4f7f\u7528Matplotlib\u7ed8\u5236\u4e86\u534a\u5706\uff0c\u5e76\u5c55\u793a\u4e86\u5982\u4f55\u8c03\u6574\u534a\u5706\u7684\u5927\u5c0f\u548c\u4f4d\u7f6e\u3001\u7ed8\u5236\u591a\u4e2a\u534a\u5706\u3001\u81ea\u5b9a\u4e49\u534a\u5706\u7684\u6837\u5f0f\u548c\u4fdd\u5b58\u56fe\u50cf\u3002<\/p>\n<\/p>\n
          \u5e0c\u671b\u672c\u6587\u80fd\u591f\u5e2e\u52a9\u60a8\u66f4\u597d\u5730\u7406\u89e3\u5982\u4f55\u7528Python\u7ed8\u5236\u534a\u5706\uff0c\u5e76\u6fc0\u53d1\u60a8\u63a2\u7d22\u548c\u5e94\u7528Python\u8fdb\u884c\u66f4\u591a\u56fe\u5f62\u7ed8\u5236\u7684\u5174\u8da3\u3002\u5982\u679c\u60a8\u6709\u4efb\u4f55\u95ee\u9898\u6216\u5efa\u8bae\uff0c\u6b22\u8fce\u5728\u8bc4\u8bba\u533a\u7559\u8a00\u3002<\/p>\n<\/p>\n
          \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
           \u4f7f\u7528Python\u753b\u534a\u5706\u9700\u8981\u54ea\u4e9b\u57fa\u672c\u7684\u5e93\uff1f<\/strong>
          \u5728Python\u4e2d\uff0c\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u6709Matplotlib\u548cPygame\u3002\u5bf9\u4e8e\u7ed8\u5236\u534a\u5706\uff0cMatplotlib\u662f\u4e00\u4e2a\u975e\u5e38\u9002\u5408\u7684\u9009\u62e9\uff0c\u56e0\u4e3a\u5b83\u63d0\u4f9b\u4e86\u7b80\u5355\u6613\u7528\u7684\u63a5\u53e3\u6765\u521b\u5efa\u5404\u79cd\u56fe\u5f62\u3002\u53ea\u9700\u5b89\u88c5Matplotlib\u5e93\uff0c\u4fbf\u53ef\u4ee5\u901a\u8fc7\u7b80\u5355\u7684\u4ee3\u7801\u5b9e\u73b0\u534a\u5706\u7684\u7ed8\u5236\u3002<\/p>\n
          \u5982\u4f55\u5728Matplotlib\u4e2d\u7ed8\u5236\u4e00\u4e2a\u534a\u5706\uff1f<\/strong>
          \u8981\u5728Matplotlib\u4e2d\u7ed8\u5236\u534a\u5706\uff0c\u53ef\u4ee5\u4f7f\u7528patches<\/code>\u6a21\u5757\u4e2d\u7684Arc<\/code>\u5bf9\u8c61\u3002\u901a\u8fc7\u5b9a\u4e49\u534a\u5706\u7684\u4e2d\u5fc3\u70b9\u3001\u534a\u5f84\u548c\u89d2\u5ea6\u8303\u56f4\uff0c\u53ef\u4ee5\u8f7b\u677e\u7ed8\u5236\u51fa\u6240\u9700\u7684\u534a\u5706\u3002\u6b64\u5916\uff0c\u4f7f\u7528plt.show()<\/code>\u53ef\u4ee5\u5c06\u7ed8\u5236\u7684\u56fe\u5f62\u663e\u793a\u51fa\u6765\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n
          import matplotlib.pyplot as plt\nimport numpy as np\n\n# \u521b\u5efa\u4e00\u4e2a\u534a\u5706\ntheta = np.linspace(0, np.pi, 100)\nx = np.cos(theta)\ny = np.sin(theta)\n\nplt.plot(x, y, color='blue')  # \u7ed8\u5236\u534a\u5706\nplt.xlim(-1.5, 1.5)\nplt.ylim(-1.5, 1.5)\nplt.gca().set_aspect('equal')  # \u4fdd\u6301\u7eb5\u6a2a\u6bd4\nplt.title("Half Circle")\nplt.show()\n<\/code><\/pre>\n
          \u5728\u7ed8\u5236\u534a\u5706\u65f6\u5982\u4f55\u81ea\u5b9a\u4e49\u989c\u8272\u548c\u6837\u5f0f\uff1f<\/strong>
          Matplotlib\u5141\u8bb8\u7528\u6237\u81ea\u5b9a\u4e49\u56fe\u5f62\u7684\u989c\u8272\u548c\u6837\u5f0f\u3002\u53ef\u4ee5\u5728plot()<\/code>\u51fd\u6570\u4e2d\u901a\u8fc7color<\/code>\u53c2\u6570\u8bbe\u7f6e\u989c\u8272\uff0c\u5e76\u53ef\u4ee5\u4f7f\u7528linestyle<\/code>\u53c2\u6570\u6765\u6307\u5b9a\u7ebf\u6761\u7684\u6837\u5f0f\uff08\u5982\u5b9e\u7ebf\u3001\u865a\u7ebf\u7b49\uff09\u3002\u4f8b\u5982\uff0c\u901a\u8fc7\u5c06color<\/code>\u8bbe\u7f6e\u4e3a'red'\u548clinestyle<\/code>\u8bbe\u7f6e\u4e3a'–'\uff0c\u53ef\u4ee5\u7ed8\u5236\u4e00\u4e2a\u7ea2\u8272\u7684\u865a\u7ebf\u534a\u5706\u3002\u4ee3\u7801\u793a\u4f8b\u5982\u4e0b\uff1a<\/p>\n
          plt.plot(x, y, color='red', linestyle='--')  # \u81ea\u5b9a\u4e49\u989c\u8272\u548c\u6837\u5f0f\n<\/code><\/pre>\n
          \u5728Python\u4e2d\u7ed8\u5236\u534a\u5706\u7684\u5e94\u7528\u573a\u666f\u6709\u54ea\u4e9b\uff1f<\/strong>
          \u7ed8\u5236\u534a\u5706\u7684\u5e94\u7528\u573a\u666f\u975e\u5e38\u5e7f\u6cdb\uff0c\u4f8b\u5982\u5728\u6570\u636e\u53ef\u89c6\u5316\u4e2d\uff0c\u534a\u5706\u53ef\u4ee5\u7528\u4e8e\u5c55\u793a\u67d0\u4e9b\u7279\u5b9a\u7684\u7edf\u8ba1\u6570\u636e\uff1b\u5728\u6e38\u620f\u5f00\u53d1\u4e2d\uff0c\u53ef\u4ee5\u7528\u4e8e\u521b\u5efa\u5404\u79cd\u5f62\u72b6\u7684\u7269\u4f53\uff1b\u5728\u6559\u80b2\u9886\u57df\uff0c\u6559\u5e08\u53ef\u4ee5\u5229\u7528\u534a\u5706\u5e2e\u52a9\u5b66\u751f\u66f4\u597d\u5730\u7406\u89e3\u51e0\u4f55\u6982\u5ff5\u548c\u76f8\u5173\u7684\u6570\u5b66\u77e5\u8bc6\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5982\u4f55\u7528Python\u753b\u4e00\u4e2a\u534a\u5706 \u8981\u7528Python\u753b\u4e00\u4e2a\u534a\u5706\uff0c\u53ef\u4ee5\u4f7f\u7528Matplotlib\u5e93\u3001Numpy\u5e93\u3001\u4ee3\u7801\u7b80 […]","protected":false},"author":3,"featured_media":1049740,"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\/1049731"}],"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=1049731"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1049731\/revisions"}],"predecessor-version":[{"id":1049742,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1049731\/revisions\/1049742"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1049740"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1049731"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1049731"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1049731"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}