{"id":1083270,"date":"2025-01-08T12:56:30","date_gmt":"2025-01-08T04:56:30","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1083270.html"},"modified":"2025-01-08T12:56:32","modified_gmt":"2025-01-08T04:56:32","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e5%88%b6%e4%bd%9c%e4%ba%8c%e5%85%83%e7%9b%b8%e5%9b%be-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1083270.html","title":{"rendered":"\u5982\u4f55\u7528python\u5236\u4f5c\u4e8c\u5143\u76f8\u56fe"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u5236\u4f5c\u4e8c\u5143\u76f8\u56fe\"<\/p>\n

\u7528Python\u5236\u4f5c\u4e8c\u5143\u76f8\u56fe\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u65b9\u5f0f\u5b9e\u73b0\uff1a\u4f7f\u7528Matplotlib\u3001Pandas\u3001Seaborn\u3001SciPy\u3001NumPy\u7b49\u5e93\u3001\u901a\u8fc7\u7ed8\u5236\u76f8\u56fe\u3001\u5206\u6790\u6570\u636e\u3001\u751f\u6210\u56fe\u50cf\u3002<\/strong>\u9996\u5148\uff0c\u4f60\u9700\u8981\u5b89\u88c5\u5fc5\u8981\u7684\u5e93\uff0c\u5982Matplotlib\u3001NumPy\u7b49\u3002\u7136\u540e\uff0c\u4f7f\u7528Python\u7f16\u5199\u4ee3\u7801\uff0c\u5bfc\u5165\u6570\u636e\u3001\u5904\u7406\u6570\u636e\u5e76\u7ed8\u5236\u76f8\u56fe\u3002\u4ee5\u4e0b\u662f\u8be6\u7ec6\u7684\u6b65\u9aa4\u548c\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n

\u4e00\u3001\u5b89\u88c5\u5fc5\u8981\u7684Python\u5e93<\/h3>\n<\/p>\n

\u5728\u5f00\u59cb\u7f16\u5199\u4ee3\u7801\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5\u4e00\u4e9b\u5fc5\u8981\u7684Python\u5e93\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528pip\u6765\u5b89\u88c5\u8fd9\u4e9b\u5e93\u3002\u4ee5\u4e0b\u662f\u9700\u8981\u5b89\u88c5\u7684\u5e93\u53ca\u5176\u5b89\u88c5\u547d\u4ee4\uff1a<\/p>\n<\/p>\n

pip install matplotlib numpy pandas seaborn scipy<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u5bfc\u5165\u5fc5\u8981\u7684\u5e93<\/h3>\n<\/p>\n
\u5728\u7f16\u5199\u4ee3\u7801\u7684\u5f00\u5934\uff0c\u5bfc\u5165\u6240\u6709\u9700\u8981\u7684\u5e93\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import numpy as np<\/p>\n
import pandas as pd<\/p>\n
import seaborn as sns<\/p>\n
from scipy.interpolate import griddata<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u6570\u636e\u51c6\u5907<\/h3>\n<\/p>\n
\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u51c6\u5907\u4e00\u4e9b\u7528\u4e8e\u7ed8\u5236\u4e8c\u5143\u76f8\u56fe\u7684\u6570\u636e\u3002\u5047\u8bbe\u6211\u4eec\u6709\u4e24\u4e2a\u6210\u5206A\u548cB\u4ee5\u53ca\u5b83\u4eec\u5728\u4e0d\u540c\u6e29\u5ea6\u4e0b\u7684\u76f8\u5bb9\u6027\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u5c06\u8fd9\u4e9b\u6570\u636e\u5b58\u50a8\u5728\u4e00\u4e2aPandas DataFrame\u4e2d\uff1a<\/p>\n<\/p>\n
data = {<\/p>\n
    'A': [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9],<\/p>\n
    'B': [0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1],<\/p>\n
    'Temperature': [100, 150, 200, 250, 300, 350, 400, 450, 500]<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u751f\u6210\u4e8c\u5143\u76f8\u56fe<\/h3>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u4f7f\u7528Matplotlib\u548cSeaborn\u6765\u751f\u6210\u4e8c\u5143\u76f8\u56fe\u3002\u6211\u4eec\u5c06\u7ed8\u5236\u6210\u5206A\u548cB\u7684\u76f8\u5bb9\u6027\u968f\u6e29\u5ea6\u53d8\u5316\u7684\u56fe\u50cf\u3002<\/p>\n<\/p>\n
1\u3001\u7ed8\u5236\u57fa\u7840\u76f8\u56fe<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u6211\u4eec\u521b\u5efa\u4e00\u4e2a\u57fa\u7840\u7684\u76f8\u56fe\uff0c\u663e\u793a\u6210\u5206A\u548cB\u7684\u76f8\u5bf9\u542b\u91cf\u968f\u6e29\u5ea6\u53d8\u5316\u7684\u60c5\u51b5\uff1a<\/p>\n<\/p>\n
plt.figure(figsize=(10, 6))<\/p>\n
sns.scatterplot(x='A', y='B', hue='Temperature', palette='coolwarm', data=df)<\/p>\n
plt.title('Binary Phase Diagram')<\/p>\n
plt.xlabel('Component A')<\/p>\n
plt.ylabel('Component B')<\/p>\n
plt.colorbar(label='Temperature')<\/p>\n
plt.grid(True)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u6dfb\u52a0\u7b49\u6e29\u7ebf<\/h4>\n<\/p>\n
\u4e3a\u4e86\u66f4\u597d\u5730\u5c55\u793a\u76f8\u56fe\uff0c\u6211\u4eec\u53ef\u4ee5\u6dfb\u52a0\u7b49\u6e29\u7ebf\uff0c\u663e\u793a\u5728\u4e0d\u540c\u6e29\u5ea6\u4e0b\u6210\u5206A\u548cB\u7684\u76f8\u5bb9\u6027\u8303\u56f4\uff1a<\/p>\n<\/p>\n
# \u521b\u5efa\u7f51\u683c\u6570\u636e<\/p>\n
grid_x, grid_y = np.mgrid[0:1:100j, 0:1:100j]<\/p>\n
grid_z = griddata((df['A'], df['B']), df['Temperature'], (grid_x, grid_y), method='cubic')<\/p>\n
\u7ed8\u5236\u7b49\u6e29\u7ebf<\/strong><\/h2>\n
plt.figure(figsize=(10, 6))<\/p>\n
plt.contourf(grid_x, grid_y, grid_z, levels=14, cmap='coolwarm')<\/p>\n
plt.colorbar(label='Temperature')<\/p>\n
plt.scatter(df['A'], df['B'], c=df['Temperature'], cmap='coolwarm', edgecolor='k')<\/p>\n
plt.title('Binary Phase Diagram with Isotherms')<\/p>\n
plt.xlabel('Component A')<\/p>\n
plt.ylabel('Component B')<\/p>\n
plt.grid(True)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u5206\u6790\u548c\u89e3\u91ca\u76f8\u56fe<\/h3>\n<\/p>\n
\u5728\u751f\u6210\u4e86\u4e8c\u5143\u76f8\u56fe\u4e4b\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5bf9\u5176\u8fdb\u884c\u5206\u6790\u548c\u89e3\u91ca\u3002\u76f8\u56fe\u663e\u793a\u4e86\u6210\u5206A\u548cB\u5728\u4e0d\u540c\u6e29\u5ea6\u4e0b\u7684\u76f8\u5bb9\u6027\u8303\u56f4\u3002\u901a\u8fc7\u89c2\u5bdf\u76f8\u56fe\u4e2d\u7684\u7b49\u6e29\u7ebf\uff0c\u6211\u4eec\u53ef\u4ee5\u4e86\u89e3\u5728\u4e0d\u540c\u6e29\u5ea6\u4e0b\u6210\u5206A\u548cB\u7684\u76f8\u4e92\u4f5c\u7528\u3002\u4f8b\u5982\uff0c\u5f53\u6e29\u5ea6\u8f83\u4f4e\u65f6\uff0c\u6210\u5206A\u548cB\u7684\u76f8\u5bb9\u6027\u8f83\u5dee\uff0c\u800c\u968f\u7740\u6e29\u5ea6\u5347\u9ad8\uff0c\u76f8\u5bb9\u6027\u9010\u6e10\u589e\u52a0\u3002<\/p>\n<\/p>\n
\u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u672c\u6587\uff0c\u6211\u4eec\u4e86\u89e3\u4e86\u5982\u4f55\u4f7f\u7528Python\u548c\u4e00\u4e9b\u5e38\u7528\u7684\u5e93\uff08\u5982Matplotlib\u3001NumPy\u3001Pandas\u3001Seaborn\u548cSciPy\uff09\u6765\u5236\u4f5c\u4e8c\u5143\u76f8\u56fe\u3002\u9996\u5148\uff0c\u6211\u4eec\u51c6\u5907\u4e86\u6570\u636e\uff0c\u7136\u540e\u4f7f\u7528\u8fd9\u4e9b\u5e93\u751f\u6210\u76f8\u56fe\uff0c\u5e76\u6dfb\u52a0\u4e86\u7b49\u6e29\u7ebf\u4ee5\u66f4\u597d\u5730\u5c55\u793a\u6570\u636e\u3002\u6700\u540e\uff0c\u6211\u4eec\u5bf9\u76f8\u56fe\u8fdb\u884c\u4e86\u5206\u6790\u548c\u89e3\u91ca\uff0c\u4e86\u89e3\u4e86\u6210\u5206A\u548cB\u5728\u4e0d\u540c\u6e29\u5ea6\u4e0b\u7684\u76f8\u5bb9\u6027\u60c5\u51b5\u3002<\/p>\n<\/p>\n
\u4e03\u3001\u4ee3\u7801\u4f18\u5316\u548c\u6269\u5c55<\/h3>\n<\/p>\n
\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u4e8c\u5143\u76f8\u56fe\u53ef\u80fd\u5305\u542b\u66f4\u591a\u7684\u6210\u5206\u548c\u66f4\u590d\u6742\u7684\u6570\u636e\u3002\u4e3a\u4e86\u5904\u7406\u8fd9\u4e9b\u60c5\u51b5\uff0c\u6211\u4eec\u53ef\u4ee5\u5bf9\u4ee3\u7801\u8fdb\u884c\u4f18\u5316\u548c\u6269\u5c55\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u66f4\u591a\u7684\u6210\u5206\u3001\u66f4\u591a\u7684\u6e29\u5ea6\u6570\u636e\uff0c\u5e76\u4f7f\u7528\u66f4\u590d\u6742\u7684\u63d2\u503c\u65b9\u6cd5\u3002\u6b64\u5916\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u5c06\u4ee3\u7801\u5c01\u88c5\u6210\u51fd\u6570\uff0c\u4ee5\u4fbf\u66f4\u65b9\u4fbf\u5730\u91cd\u590d\u4f7f\u7528\u3002<\/p>\n<\/p>\n
1\u3001\u5c01\u88c5\u6210\u51fd\u6570<\/h4>\n<\/p>\n
\u6211\u4eec\u53ef\u4ee5\u5c06\u751f\u6210\u4e8c\u5143\u76f8\u56fe\u7684\u4ee3\u7801\u5c01\u88c5\u6210\u4e00\u4e2a\u51fd\u6570\uff0c\u4ee5\u4fbf\u66f4\u65b9\u4fbf\u5730\u91cd\u590d\u4f7f\u7528\uff1a<\/p>\n<\/p>\n
def plot_binary_phase_diagram(df):<\/p>\n
    # \u521b\u5efa\u7f51\u683c\u6570\u636e<\/p>\n
    grid_x, grid_y = np.mgrid[0:1:100j, 0:1:100j]<\/p>\n
    grid_z = griddata((df['A'], df['B']), df['Temperature'], (grid_x, grid_y), method='cubic')<\/p>\n
    # \u7ed8\u5236\u7b49\u6e29\u7ebf<\/p>\n
    plt.figure(figsize=(10, 6))<\/p>\n
    plt.contourf(grid_x, grid_y, grid_z, levels=14, cmap='coolwarm')<\/p>\n
    plt.colorbar(label='Temperature')<\/p>\n
    plt.scatter(df['A'], df['B'], c=df['Temperature'], cmap='coolwarm', edgecolor='k')<\/p>\n
    plt.title('Binary Phase Diagram with Isotherms')<\/p>\n
    plt.xlabel('Component A')<\/p>\n
    plt.ylabel('Component B')<\/p>\n
    plt.grid(True)<\/p>\n
    plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5904\u7406\u66f4\u591a\u6210\u5206\u548c\u66f4\u590d\u6742\u7684\u6570\u636e<\/h4>\n<\/p>\n
\u4e3a\u4e86\u5904\u7406\u66f4\u591a\u7684\u6210\u5206\u548c\u66f4\u590d\u6742\u7684\u6570\u636e\uff0c\u6211\u4eec\u53ef\u4ee5\u6269\u5c55\u6570\u636e\u51c6\u5907\u6b65\u9aa4\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u6dfb\u52a0\u66f4\u591a\u7684\u6210\u5206C\u3001D\u7b49\uff0c\u5e76\u4f7f\u7528\u66f4\u590d\u6742\u7684\u63d2\u503c\u65b9\u6cd5\u6765\u5904\u7406\u8fd9\u4e9b\u6570\u636e\uff1a<\/p>\n<\/p>\n
data = {<\/p>\n
    'A': [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9],<\/p>\n
    'B': [0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1],<\/p>\n
    'C': [0.5, 0.4, 0.3, 0.2, 0.1, 0.2, 0.3, 0.4, 0.5],<\/p>\n
    'D': [0.5, 0.6, 0.7, 0.8, 0.9, 0.8, 0.7, 0.6, 0.5],<\/p>\n
    'Temperature': [100, 150, 200, 250, 300, 350, 400, 450, 500]<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
def plot_ternary_phase_diagram(df):<\/p>\n
    # \u521b\u5efa\u7f51\u683c\u6570\u636e<\/p>\n
    grid_x, grid_y = np.mgrid[0:1:100j, 0:1:100j]<\/p>\n
    grid_z = griddata((df['A'], df['B']), df['Temperature'], (grid_x, grid_y), method='cubic')<\/p>\n
    # \u7ed8\u5236\u7b49\u6e29\u7ebf<\/p>\n
    plt.figure(figsize=(10, 6))<\/p>\n
    plt.contourf(grid_x, grid_y, grid_z, levels=14, cmap='coolwarm')<\/p>\n
    plt.colorbar(label='Temperature')<\/p>\n
    plt.scatter(df['A'], df['B'], c=df['Temperature'], cmap='coolwarm', edgecolor='k')<\/p>\n
    plt.title('Ternary Phase Diagram with Isotherms')<\/p>\n
    plt.xlabel('Component A')<\/p>\n
    plt.ylabel('Component B')<\/p>\n
    plt.grid(True)<\/p>\n
    plt.show()<\/p>\n
plot_ternary_phase_diagram(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u8fd9\u4e9b\u4f18\u5316\u548c\u6269\u5c55\uff0c\u6211\u4eec\u53ef\u4ee5\u66f4\u597d\u5730\u5904\u7406\u590d\u6742\u7684\u4e8c\u5143\u6216\u4e09\u5143\u76f8\u56fe\uff0c\u5e76\u751f\u6210\u66f4\u7cbe\u786e\u548c\u8be6\u7ec6\u7684\u56fe\u50cf\u3002\u8fd9\u4e9b\u65b9\u6cd5\u4e0d\u4ec5\u9002\u7528\u4e8e\u4e8c\u5143\u76f8\u56fe\uff0c\u8fd8\u53ef\u4ee5\u5e94\u7528\u4e8e\u66f4\u590d\u6742\u7684\u591a\u5143\u76f8\u56fe\uff0c\u4ece\u800c\u5e2e\u52a9\u6211\u4eec\u66f4\u597d\u5730\u7406\u89e3\u6210\u5206\u4e4b\u95f4\u7684\u76f8\u4e92\u4f5c\u7528\u548c\u76f8\u5bb9\u6027\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u9009\u62e9\u9002\u5408\u7684\u5e93\u6765\u5236\u4f5c\u4e8c\u5143\u76f8\u56fe\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u5e38\u7528\u7684\u5e93\u5305\u62ecMatplotlib\u548cSeaborn\u3002Matplotlib\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u7ed8\u56fe\u529f\u80fd\uff0c\u9002\u5408\u4e8e\u81ea\u5b9a\u4e49\u4e8c\u5143\u76f8\u56fe\u7684\u9700\u6c42\u3002Seaborn\u5219\u66f4\u9002\u5408\u7528\u4e8e\u7edf\u8ba1\u6570\u636e\u7684\u53ef\u89c6\u5316\uff0c\u80fd\u591f\u7b80\u5316\u56fe\u8868\u7684\u521b\u5efa\u8fc7\u7a0b\u3002\u9009\u62e9\u5e93\u65f6\uff0c\u5e94\u8003\u8651\u9879\u76ee\u7684\u5177\u4f53\u9700\u6c42\u548c\u4e2a\u4eba\u7684\u7f16\u7a0b\u4e60\u60ef\u3002<\/p>\n
\u5236\u4f5c\u4e8c\u5143\u76f8\u56fe\u7684\u57fa\u672c\u6b65\u9aa4\u662f\u4ec0\u4e48\uff1f<\/strong>
\u5236\u4f5c\u4e8c\u5143\u76f8\u56fe\u7684\u4e00\u822c\u6b65\u9aa4\u5305\u62ec\uff1a\u9996\u5148\uff0c\u51c6\u5907\u6570\u636e\u96c6\uff0c\u786e\u4fdd\u6570\u636e\u5305\u542b\u4e24\u4e2a\u53d8\u91cf\u7684\u6570\u503c\uff1b\u63a5\u7740\uff0c\u4f7f\u7528\u9002\u5408\u7684\u5e93\uff08\u5982Matplotlib\uff09\u6765\u7ed8\u5236\u6563\u70b9\u56fe\u6216\u70ed\u56fe\uff1b\u6700\u540e\uff0c\u8c03\u6574\u56fe\u8868\u7684\u6837\u5f0f\u548c\u6807\u7b7e\uff0c\u4ee5\u786e\u4fdd\u4fe1\u606f\u6e05\u6670\u53ef\u8bfb\u3002\u5173\u6ce8\u6570\u636e\u7684\u53ef\u89c6\u5316\u6548\u679c\uff0c\u80fd\u591f\u5e2e\u52a9\u66f4\u597d\u5730\u7406\u89e3\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002<\/p>\n
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