{"id":1125933,"date":"2025-01-08T19:56:12","date_gmt":"2025-01-08T11:56:12","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1125933.html"},"modified":"2025-01-08T19:56:15","modified_gmt":"2025-01-08T11:56:15","slug":"python%e5%a6%82%e4%bd%95%e6%8f%90%e5%8f%96%e6%8a%98%e7%ba%bf%e5%9b%be%e4%b8%ad%e7%82%b9%e7%9a%84%e5%9d%90%e6%a0%87","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1125933.html","title":{"rendered":"python\u5982\u4f55\u63d0\u53d6\u6298\u7ebf\u56fe\u4e2d\u70b9\u7684\u5750\u6807"},"content":{"rendered":"

\"python\u5982\u4f55\u63d0\u53d6\u6298\u7ebf\u56fe\u4e2d\u70b9\u7684\u5750\u6807\"<\/p>\n

Python \u63d0\u53d6\u6298\u7ebf\u56fe\u4e2d\u70b9\u7684\u5750\u6807\u7684\u57fa\u672c\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528 Matplotlib \u5e93\u751f\u6210\u6298\u7ebf\u56fe\u3001\u901a\u8fc7\u8bbf\u95ee\u6570\u636e\u5bf9\u8c61\u83b7\u53d6\u5750\u6807\u3001\u5229\u7528 plt.ginput() \u8fdb\u884c\u624b\u52a8\u4ea4\u4e92\u3001\u5b9e\u73b0\u81ea\u52a8\u5316\u7684\u5750\u6807\u63d0\u53d6\u7b49\u3002\u8fd9\u4e9b\u65b9\u6cd5\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u5728\u6570\u636e\u53ef\u89c6\u5316\u548c\u5206\u6790\u8fc7\u7a0b\u4e2d\u7cbe\u786e\u5730\u83b7\u53d6\u6240\u9700\u7684\u5750\u6807\u3002<\/strong><\/p>\n<\/p>\n

Matplotlib \u662f Python \u4e2d\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\u6765\u751f\u6210\u3001\u64cd\u4f5c\u548c\u63d0\u53d6\u56fe\u5f62\u6570\u636e\u3002\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528 Matplotlib \u5e93\u6765\u63d0\u53d6\u6298\u7ebf\u56fe\u4e2d\u70b9\u7684\u5750\u6807\uff0c\u5e76\u7ed3\u5408\u5b9e\u9645\u793a\u4f8b\u8bf4\u660e\u5176\u5e94\u7528\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528 Matplotlib \u751f\u6210\u6298\u7ebf\u56fe<\/h3>\n<\/p>\n

Matplotlib \u662f\u751f\u6210\u6298\u7ebf\u56fe\u7684\u4e3b\u8981\u5de5\u5177\u4e4b\u4e00\u3002\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5\u5e76\u5bfc\u5165 Matplotlib \u5e93\uff0c\u7136\u540e\u4f7f\u7528\u5b83\u6765\u7ed8\u5236\u6298\u7ebf\u56fe\u3002<\/p>\n<\/p>\n

import matplotlib.pyplot as plt<\/p>\n
\u793a\u4f8b\u6570\u636e<\/strong><\/h2>\n
x = [0, 1, 2, 3, 4, 5]<\/p>\n
y = [0, 1, 4, 9, 16, 25]<\/p>\n
\u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n
plt.plot(x, y, marker='o')<\/p>\n
plt.xlabel('X\u8f74')<\/p>\n
plt.ylabel('Y\u8f74')<\/p>\n
plt.title('\u793a\u4f8b\u6298\u7ebf\u56fe')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u901a\u8fc7\u8bbf\u95ee\u6570\u636e\u5bf9\u8c61\u83b7\u53d6\u5750\u6807<\/h3>\n<\/p>\n
\u5728 Matplotlib \u4e2d\uff0c\u56fe\u5f62\u6570\u636e\u901a\u5e38\u5b58\u50a8\u5728 Line2D \u5bf9\u8c61\u4e2d\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8bbf\u95ee\u8fd9\u4e9b\u5bf9\u8c61\u6765\u63d0\u53d6\u5750\u6807\u4fe1\u606f\u3002<\/p>\n<\/p>\n
# \u7ed8\u5236\u6298\u7ebf\u56fe<\/p>\n
line, = plt.plot(x, y, marker='o')<\/p>\n
\u83b7\u53d6\u6298\u7ebf\u56fe\u4e2d\u7684\u70b9\u7684\u5750\u6807<\/strong><\/h2>\n
x_data = line.get_xdata()<\/p>\n
y_data = line.get_ydata()<\/p>\n
\u6253\u5370\u5750\u6807<\/strong><\/h2>\n
for x, y in zip(x_data, y_data):<\/p>\n
    print(f"({x}, {y})")<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u79cd\u65b9\u6cd5\u7684\u4f18\u70b9\u662f\u76f4\u63a5\u4e14\u9ad8\u6548\uff0c\u9002\u5408\u5904\u7406\u9759\u6001\u6570\u636e\u3002<\/strong><\/p>\n<\/p>\n
\u4e09\u3001\u5229\u7528 plt.ginput() \u8fdb\u884c\u624b\u52a8\u4ea4\u4e92<\/h3>\n<\/p>\n
Matplotlib \u63d0\u4f9b\u4e86 ginput() \u51fd\u6570\uff0c\u5141\u8bb8\u7528\u6237\u901a\u8fc7\u70b9\u51fb\u56fe\u5f62\u6765\u83b7\u53d6\u5750\u6807\u3002\u8fd9\u5bf9\u4e8e\u9700\u8981\u624b\u52a8\u9009\u62e9\u7279\u5b9a\u70b9\u7684\u60c5\u51b5\u975e\u5e38\u6709\u7528\u3002<\/p>\n<\/p>\n
# \u7ed8\u5236\u6298\u7ebf\u56fe<\/p>\n
plt.plot(x, y, marker='o')<\/p>\n
plt.xlabel('X\u8f74')<\/p>\n
plt.ylabel('Y\u8f74')<\/p>\n
plt.title('\u793a\u4f8b\u6298\u7ebf\u56fe')<\/p>\n
\u4ea4\u4e92\u5f0f\u83b7\u53d6\u70b9\u7684\u5750\u6807<\/strong><\/h2>\n
points = plt.ginput(n=3)  # \u5141\u8bb8\u7528\u6237\u9009\u62e93\u4e2a\u70b9<\/p>\n
plt.show()<\/p>\n
\u6253\u5370\u7528\u6237\u9009\u62e9\u7684\u5750\u6807<\/strong><\/h2>\n
for point in points:<\/p>\n
    print(f"({point[0]}, {point[1]})")<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u79cd\u65b9\u6cd5\u7684\u4f18\u70b9\u662f\u7075\u6d3b\uff0c\u9002\u5408\u9700\u8981\u7528\u6237\u4ea4\u4e92\u7684\u60c5\u51b5\u3002<\/strong><\/p>\n<\/p>\n
\u56db\u3001\u5b9e\u73b0\u81ea\u52a8\u5316\u7684\u5750\u6807\u63d0\u53d6<\/h3>\n<\/p>\n
\u5728\u67d0\u4e9b\u5e94\u7528\u4e2d\uff0c\u53ef\u80fd\u9700\u8981\u81ea\u52a8\u5316\u63d0\u53d6\u56fe\u4e2d\u7684\u70b9\u7684\u5750\u6807\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u7f16\u5199\u811a\u672c\u6765\u5b9e\u73b0\u8fd9\u4e00\u70b9\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
\u793a\u4f8b\u6570\u636e<\/strong><\/h2>\n
x = np.linspace(0, 5, 100)<\/p>\n
y = x2<\/p>\n
\u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n
line, = plt.plot(x, y, marker='o')<\/p>\n
\u83b7\u53d6\u6298\u7ebf\u56fe\u4e2d\u7684\u70b9\u7684\u5750\u6807<\/strong><\/h2>\n
x_data = line.get_xdata()<\/p>\n
y_data = line.get_ydata()<\/p>\n
\u81ea\u52a8\u5316\u63d0\u53d6\u5e76\u6253\u5370\u5750\u6807<\/strong><\/h2>\n
coordinates = list(zip(x_data, y_data))<\/p>\n
for coord in coordinates:<\/p>\n
    print(f"({coord[0]}, {coord[1]})")<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u79cd\u65b9\u6cd5\u7684\u4f18\u70b9\u662f\u53ef\u4ee5\u5904\u7406\u5927\u91cf\u6570\u636e\uff0c\u9002\u5408\u6279\u91cf\u5904\u7406\u7684\u573a\u666f\u3002<\/strong><\/p>\n<\/p>\n
\u4e94\u3001\u603b\u7ed3\u4e0e\u5e94\u7528<\/h3>\n<\/p>\n
\u63d0\u53d6\u6298\u7ebf\u56fe\u4e2d\u70b9\u7684\u5750\u6807\u5728\u6570\u636e\u5206\u6790\u548c\u53ef\u89c6\u5316\u4e2d\u5177\u6709\u91cd\u8981\u610f\u4e49\u3002\u65e0\u8bba\u662f\u901a\u8fc7\u8bbf\u95ee\u6570\u636e\u5bf9\u8c61\u3001\u5229\u7528 plt.ginput() \u8fdb\u884c\u624b\u52a8\u4ea4\u4e92\uff0c\u8fd8\u662f\u5b9e\u73b0\u81ea\u52a8\u5316\u7684\u5750\u6807\u63d0\u53d6\uff0cPython \u90fd\u63d0\u4f9b\u4e86\u7075\u6d3b\u4e14\u5f3a\u5927\u7684\u5de5\u5177\u6765\u6ee1\u8db3\u5404\u79cd\u9700\u6c42\u3002<\/p>\n<\/p>\n
\u5b9e\u9645\u5e94\u7528\u573a\u666f<\/h3>\n<\/p>\n
    \n
  1. \u6570\u636e\u5206\u6790<\/strong>\uff1a\u5728\u6570\u636e\u5206\u6790\u4e2d\uff0c\u63d0\u53d6\u56fe\u5f62\u6570\u636e\u7684\u5750\u6807\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u66f4\u597d\u5730\u7406\u89e3\u6570\u636e\u7684\u8d8b\u52bf\u548c\u6a21\u5f0f\u3002\u4f8b\u5982\uff0c\u901a\u8fc7\u63d0\u53d6\u80a1\u5e02\u8d70\u52bf\u56fe\u4e2d\u7684\u5173\u952e\u70b9\uff0c\u53ef\u4ee5\u8fdb\u884c\u8d8b\u52bf\u5206\u6790\u548c\u9884\u6d4b\u3002<\/li>\n
  2. \u673a\u5668\u5b66\u4e60<\/a><\/strong>\uff1a\u5728\u673a\u5668\u5b66\u4e60\u4e2d\uff0c\u63d0\u53d6\u56fe\u5f62\u6570\u636e\u7684\u5750\u6807\u53ef\u4ee5\u7528\u4e8e\u7279\u5f81\u5de5\u7a0b\u548c\u6a21\u578b\u8bad\u7ec3\u3002\u4f8b\u5982\uff0c\u901a\u8fc7\u63d0\u53d6\u56fe\u50cf\u4e2d\u7684\u5173\u952e\u70b9\uff0c\u53ef\u4ee5\u7528\u4e8e\u56fe\u50cf\u5206\u7c7b\u548c\u76ee\u6807\u68c0\u6d4b\u3002<\/li>\n
  3. \u79d1\u5b66\u7814\u7a76<\/strong>\uff1a\u5728\u79d1\u5b66\u7814\u7a76\u4e2d\uff0c\u63d0\u53d6\u56fe\u5f62\u6570\u636e\u7684\u5750\u6807\u53ef\u4ee5\u7528\u4e8e\u5b9e\u9a8c\u6570\u636e\u7684\u5206\u6790\u548c\u53ef\u89c6\u5316\u3002\u4f8b\u5982\uff0c\u901a\u8fc7\u63d0\u53d6\u5b9e\u9a8c\u66f2\u7ebf\u4e2d\u7684\u5173\u952e\u70b9\uff0c\u53ef\u4ee5\u8fdb\u884c\u5b9e\u9a8c\u7ed3\u679c\u7684\u5206\u6790\u548c\u89e3\u91ca\u3002<\/li>\n<\/ol>\n
    \u4ee3\u7801\u793a\u4f8b<\/h3>\n<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    import numpy as np<\/p>\n
    def generate_line_plot():<\/p>\n
        x = np.linspace(0, 10, 100)<\/p>\n
        y = np.sin(x)<\/p>\n
        plt.plot(x, y, marker='o', linestyle='-', color='b')<\/p>\n
        plt.xlabel('X\u8f74')<\/p>\n
        plt.ylabel('Y\u8f74')<\/p>\n
        plt.title('\u6b63\u5f26\u51fd\u6570\u6298\u7ebf\u56fe')<\/p>\n
        plt.grid(True)<\/p>\n
        plt.show()<\/p>\n
        return plt.gca().lines[0]<\/p>\n
    def extract_coordinates(line):<\/p>\n
        x_data = line.get_xdata()<\/p>\n
        y_data = line.get_ydata()<\/p>\n
        coordinates = list(zip(x_data, y_data))<\/p>\n
        return coordinates<\/p>\n
    if __name__ == "__mAI<\/a>n__":<\/p>\n
        line = generate_line_plot()<\/p>\n
        coordinates = extract_coordinates(line)<\/p>\n
        for coord in coordinates:<\/p>\n
            print(f"({coord[0]}, {coord[1]})")<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u901a\u8fc7\u4e0a\u8ff0\u4ee3\u7801\uff0c\u6211\u4eec\u53ef\u4ee5\u751f\u6210\u4e00\u4e2a\u6b63\u5f26\u51fd\u6570\u7684\u6298\u7ebf\u56fe\uff0c\u5e76\u81ea\u52a8\u63d0\u53d6\u56fe\u4e2d\u7684\u6240\u6709\u70b9\u7684\u5750\u6807\u3002\u8fd9\u79cd\u65b9\u6cd5\u4e0d\u4ec5\u7b80\u6d01\u9ad8\u6548\uff0c\u800c\u4e14\u53ef\u4ee5\u5e94\u7528\u4e8e\u5404\u79cd\u56fe\u5f62\u6570\u636e\u7684\u63d0\u53d6\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n
    \u7ed3\u8bba<\/h3>\n<\/p>\n
    Python \u63d0\u53d6\u6298\u7ebf\u56fe\u4e2d\u70b9\u7684\u5750\u6807\u662f\u4e00\u9879\u5b9e\u7528\u7684\u6280\u80fd\uff0c\u5728\u6570\u636e\u5206\u6790\u3001\u673a\u5668\u5b66\u4e60\u548c\u79d1\u5b66\u7814\u7a76\u4e2d\u5177\u6709\u5e7f\u6cdb\u7684\u5e94\u7528\u3002\u901a\u8fc7\u7075\u6d3b\u8fd0\u7528 Matplotlib \u5e93\uff0c\u6211\u4eec\u53ef\u4ee5\u9ad8\u6548\u5730\u751f\u6210\u56fe\u5f62\u3001\u63d0\u53d6\u5750\u6807\uff0c\u5e76\u5c06\u5176\u5e94\u7528\u4e8e\u5b9e\u9645\u95ee\u9898\u7684\u89e3\u51b3\u3002\u5e0c\u671b\u672c\u6587\u7684\u4ecb\u7ecd\u548c\u793a\u4f8b\u80fd\u4e3a\u60a8\u7684\u6570\u636e\u5206\u6790\u548c\u53ef\u89c6\u5316\u5de5\u4f5c\u63d0\u4f9b\u6709\u76ca\u7684\u53c2\u8003\u3002<\/p>\n<\/p>\n
    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
     \u5982\u4f55\u5728Python\u4e2d\u7ed8\u5236\u6298\u7ebf\u56fe\u5e76\u63d0\u53d6\u5750\u6807\uff1f<\/strong>
    \u5728Python\u4e2d\uff0c\u4f7f\u7528Matplotlib\u5e93\u53ef\u4ee5\u7ed8\u5236\u6298\u7ebf\u56fe\u3002\u901a\u8fc7\u8bbf\u95ee\u6570\u636e\u70b9\u7684\u6570\u7ec4\uff0c\u53ef\u4ee5\u8f7b\u677e\u63d0\u53d6\u6298\u7ebf\u56fe\u4e2d\u5404\u4e2a\u70b9\u7684\u5750\u6807\u3002\u901a\u5e38\uff0c\u4f60\u4f1a\u5148\u5b9a\u4e49x\u548cy\u7684\u5750\u6807\u6570\u636e\uff0c\u7136\u540e\u7ed8\u5236\u56fe\u5f62\uff0c\u6700\u540e\u53ef\u4ee5\u901a\u8fc7\u6570\u7ec4\u7d22\u5f15\u83b7\u53d6\u5750\u6807\u3002<\/p>\n
    \u53ef\u4ee5\u4f7f\u7528\u54ea\u4e9b\u5e93\u6765\u63d0\u53d6\u6298\u7ebf\u56fe\u4e2d\u7684\u6570\u636e\u70b9\uff1f<\/strong>
    \u9664\u4e86Matplotlib\uff0cSeaborn\u548cPlotly\u7b49\u5e93\u4e5f\u53ef\u4ee5\u7528\u6765\u7ed8\u5236\u6298\u7ebf\u56fe\u3002\u8fd9\u4e9b\u5e93\u63d0\u4f9b\u4e86\u4e0d\u540c\u7684\u529f\u80fd\u548c\u89c6\u89c9\u6548\u679c\u3002\u5bf9\u4e8e\u6570\u636e\u63d0\u53d6\uff0cMatplotlib\u662f\u6700\u5e38\u7528\u7684\uff0c\u56e0\u4e3a\u5b83\u5141\u8bb8\u7528\u6237\u76f4\u63a5\u8bbf\u95ee\u7ed8\u56fe\u6570\u636e\uff0c\u65b9\u4fbf\u8fdb\u884c\u540e\u7eed\u5206\u6790\u3002<\/p>\n
    \u5982\u4f55\u5904\u7406\u6298\u7ebf\u56fe\u4e2d\u7684\u591a\u4e2a\u6570\u636e\u96c6\u5e76\u63d0\u53d6\u6bcf\u4e2a\u6570\u636e\u96c6\u7684\u5750\u6807\uff1f<\/strong>
    \u5728\u7ed8\u5236\u591a\u4e2a\u6298\u7ebf\u56fe\u65f6\uff0c\u53ef\u4ee5\u4e3a\u6bcf\u4e2a\u6570\u636e\u96c6\u5b9a\u4e49\u4e0d\u540c\u7684x\u548cy\u5750\u6807\u3002\u901a\u8fc7\u5c06\u8fd9\u4e9b\u5750\u6807\u5b58\u50a8\u5728\u5b57\u5178\u6216\u5217\u8868\u4e2d\uff0c\u53ef\u4ee5\u8f7b\u677e\u63d0\u53d6\u6bcf\u4e2a\u6570\u636e\u96c6\u7684\u5750\u6807\u3002\u786e\u4fdd\u5728\u7ed8\u56fe\u65f6\u4f7f\u7528\u4e0d\u540c\u7684\u989c\u8272\u548c\u6807\u7b7e\uff0c\u4ee5\u4fbf\u4e8e\u533a\u5206\u5404\u4e2a\u6570\u636e\u96c6\u3002<\/p>\n
    \u5728\u63d0\u53d6\u5750\u6807\u65f6\uff0c\u5982\u4f55\u786e\u4fdd\u6570\u636e\u7684\u51c6\u786e\u6027\uff1f<\/strong>
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