{"id":1150057,"date":"2025-01-13T16:57:09","date_gmt":"2025-01-13T08:57:09","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1150057.html"},"modified":"2025-01-13T16:57:12","modified_gmt":"2025-01-13T08:57:12","slug":"python%e5%a6%82%e4%bd%95%e7%94%bb%e6%96%b9%e6%b3%a2%e4%bf%a1%e5%8f%b7","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1150057.html","title":{"rendered":"python\u5982\u4f55\u753b\u65b9\u6ce2\u4fe1\u53f7"},"content":{"rendered":"

\"python\u5982\u4f55\u753b\u65b9\u6ce2\u4fe1\u53f7\"<\/p>\n

\u8981\u5728Python\u4e2d\u753b\u51fa\u65b9\u6ce2\u4fe1\u53f7\uff0c\u53ef\u4ee5\u4f7f\u7528\u51e0\u4e2a\u5e38\u89c1\u7684\u5e93\uff0c\u6bd4\u5982NumPy\u548cMatplotlib\u3002\u9996\u5148\uff0c\u751f\u6210\u65b9\u6ce2\u4fe1\u53f7\u6570\u636e\u3001\u7136\u540e\u4f7f\u7528Matplotlib\u7ed8\u5236\u56fe\u5f62\u3001\u8c03\u6574\u56fe\u5f62\u7684\u5916\u89c2\u548c\u6837\u5f0f<\/strong>\u3002\u63a5\u4e0b\u6765\u6211\u4eec\u5c06\u8be6\u7ec6\u63cf\u8ff0\u8fd9\u4e9b\u6b65\u9aa4\u4e2d\u7684\u4e00\u90e8\u5206\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u751f\u6210\u65b9\u6ce2\u4fe1\u53f7\u6570\u636e<\/h3>\n<\/p>\n

\u5728\u751f\u6210\u65b9\u6ce2\u4fe1\u53f7\u6570\u636e\u65f6\uff0cNumPy\u5e93\u63d0\u4f9b\u4e86\u975e\u5e38\u6709\u7528\u7684\u5de5\u5177\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528NumPy\u7684signal.square<\/code>\u51fd\u6570\u6765\u751f\u6210\u65b9\u6ce2\u4fe1\u53f7\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u4f8b\u5b50\uff1a<\/p>\n<\/p>\n

import numpy as np<\/p>\n
from scipy import signal<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u751f\u6210\u65f6\u95f4\u5e8f\u5217<\/strong><\/h2>\n
t = np.linspace(0, 1, 500)<\/p>\n
\u751f\u6210\u65b9\u6ce2\u4fe1\u53f7<\/strong><\/h2>\n
square_wave = signal.square(2 * np.pi * 5 * t)<\/p>\n
\u7ed8\u5236\u65b9\u6ce2\u4fe1\u53f7<\/strong><\/h2>\n
plt.plot(t, square_wave)<\/p>\n
plt.title('Square Wave Signal')<\/p>\n
plt.xlabel('Time [s]')<\/p>\n
plt.ylabel('Amplitude')<\/p>\n
plt.grid(True)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u751f\u6210\u4e86\u4e00\u4e2a\u9891\u7387\u4e3a5 Hz\u7684\u65b9\u6ce2\u4fe1\u53f7\uff0c\u5e76\u5728\u65f6\u95f4\u533a\u95f40\u52301\u79d2\u5185\u8fdb\u884c\u4e86\u7ed8\u5236\u3002\u6211\u4eec\u4f7f\u7528Matplotlib\u5e93\u6765\u7ed8\u5236\u56fe\u5f62\uff0c\u5e76\u8bbe\u7f6e\u4e86\u56fe\u5f62\u7684\u6807\u9898\u3001X\u8f74\u548cY\u8f74\u6807\u7b7e\u4ee5\u53ca\u7f51\u683c\u7ebf\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u8c03\u6574\u56fe\u5f62\u7684\u5916\u89c2\u548c\u6837\u5f0f<\/h3>\n<\/p>\n
\u4e3a\u4e86\u4f7f\u56fe\u5f62\u66f4\u52a0\u7f8e\u89c2\u548c\u4e13\u4e1a\uff0c\u6211\u4eec\u53ef\u4ee5\u8fdb\u884c\u4e00\u4e9b\u8c03\u6574\uff0c\u4f8b\u5982\u8bbe\u7f6e\u7ebf\u6761\u989c\u8272\u3001\u6837\u5f0f\u3001\u56fe\u4f8b\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u7528\u7684\u8c03\u6574\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n
# \u8c03\u6574\u7ebf\u6761\u6837\u5f0f\u548c\u989c\u8272<\/p>\n
plt.plot(t, square_wave, color='red', linestyle='--', linewidth=2)<\/p>\n
\u6dfb\u52a0\u56fe\u4f8b<\/strong><\/h2>\n
plt.legend(['Square Wave'])<\/p>\n
\u8c03\u6574\u5750\u6807\u8f74\u8303\u56f4<\/strong><\/h2>\n
plt.xlim(0, 1)<\/p>\n
plt.ylim(-1.5, 1.5)<\/p>\n
\u8c03\u6574\u7f51\u683c\u6837\u5f0f<\/strong><\/h2>\n
plt.grid(which='both', linestyle='--', linewidth=0.5)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u5c06\u7ebf\u6761\u989c\u8272\u8bbe\u7f6e\u4e3a\u7ea2\u8272\uff0c\u7ebf\u6761\u6837\u5f0f\u8bbe\u7f6e\u4e3a\u865a\u7ebf\uff0c\u5e76\u4e14\u589e\u52a0\u4e86\u56fe\u4f8b\u3002\u6211\u4eec\u8fd8\u8c03\u6574\u4e86\u5750\u6807\u8f74\u7684\u8303\u56f4\u548c\u7f51\u683c\u6837\u5f0f\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528\u5176\u4ed6\u5e93\u548c\u65b9\u6cd5<\/h3>\n<\/p>\n
\u9664\u4e86\u4f7f\u7528NumPy\u548cMatplotlib\u5916\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u4f7f\u7528\u5176\u4ed6\u5e93\u548c\u65b9\u6cd5\u6765\u751f\u6210\u548c\u7ed8\u5236\u65b9\u6ce2\u4fe1\u53f7\u3002\u4f8b\u5982\uff0cSciPy\u5e93\u63d0\u4f9b\u4e86\u66f4\u591a\u7684\u4fe1\u53f7\u751f\u6210\u548c\u5904\u7406\u51fd\u6570\uff0cPandas\u5e93\u53ef\u4ee5\u7528\u4e8e\u5904\u7406\u548c\u53ef\u89c6\u5316\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528SciPy\u5e93\u751f\u6210\u548c\u7ed8\u5236\u65b9\u6ce2\u4fe1\u53f7\u7684\u4f8b\u5b50\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
from scipy import signal<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u751f\u6210\u65f6\u95f4\u5e8f\u5217<\/strong><\/h2>\n
t = np.linspace(0, 1, 500)<\/p>\n
\u751f\u6210\u65b9\u6ce2\u4fe1\u53f7<\/strong><\/h2>\n
square_wave = signal.square(2 * np.pi * 5 * t)<\/p>\n
\u7ed8\u5236\u65b9\u6ce2\u4fe1\u53f7<\/strong><\/h2>\n
plt.plot(t, square_wave)<\/p>\n
plt.title('Square Wave Signal')<\/p>\n
plt.xlabel('Time [s]')<\/p>\n
plt.ylabel('Amplitude')<\/p>\n
plt.grid(True)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528SciPy\u5e93\u7684signal.square<\/code>\u51fd\u6570\u751f\u6210\u65b9\u6ce2\u4fe1\u53f7\uff0c\u5e76\u4f7f\u7528Matplotlib\u5e93\u7ed8\u5236\u56fe\u5f62\u3002<\/p>\n<\/p>\n
\u56db\u3001\u7ed3\u5408\u4fe1\u53f7\u5904\u7406\u548c\u5206\u6790<\/h3>\n<\/p>\n
\u7ed8\u5236\u65b9\u6ce2\u4fe1\u53f7\u53ea\u662f\u4fe1\u53f7\u5904\u7406\u548c\u5206\u6790\u7684\u4e00\u90e8\u5206\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6211\u4eec\u53ef\u80fd\u9700\u8981\u5bf9\u4fe1\u53f7\u8fdb\u884c\u66f4\u591a\u7684\u5904\u7406\u548c\u5206\u6790\uff0c\u4f8b\u5982\u6ee4\u6ce2\u3001\u5085\u91cc\u53f6\u53d8\u6362\u3001\u9891\u8c31\u5206\u6790\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u4f8b\u5b50\uff0c\u6f14\u793a\u5982\u4f55\u5bf9\u65b9\u6ce2\u4fe1\u53f7\u8fdb\u884c\u5085\u91cc\u53f6\u53d8\u6362\u5e76\u7ed8\u5236\u9891\u8c31\u56fe\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
from scipy import signal, fftpack<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u751f\u6210\u65f6\u95f4\u5e8f\u5217<\/strong><\/h2>\n
t = np.linspace(0, 1, 500)<\/p>\n
\u751f\u6210\u65b9\u6ce2\u4fe1\u53f7<\/strong><\/h2>\n
square_wave = signal.square(2 * np.pi * 5 * t)<\/p>\n
\u8fdb\u884c\u5085\u91cc\u53f6\u53d8\u6362<\/strong><\/h2>\n
fft_result = fftpack.fft(square_wave)<\/p>\n
frequencies = fftpack.fftfreq(len(t), t[1] - t[0])<\/p>\n
\u7ed8\u5236\u65b9\u6ce2\u4fe1\u53f7<\/strong><\/h2>\n
plt.subplot(2, 1, 1)<\/p>\n
plt.plot(t, square_wave)<\/p>\n
plt.title('Square Wave Signal')<\/p>\n
plt.xlabel('Time [s]')<\/p>\n
plt.ylabel('Amplitude')<\/p>\n
plt.grid(True)<\/p>\n
\u7ed8\u5236\u9891\u8c31\u56fe<\/strong><\/h2>\n
plt.subplot(2, 1, 2)<\/p>\n
plt.plot(frequencies, np.abs(fft_result))<\/p>\n
plt.title('Frequency Spectrum')<\/p>\n
plt.xlabel('Frequency [Hz]')<\/p>\n
plt.ylabel('Amplitude')<\/p>\n
plt.grid(True)<\/p>\n
plt.tight_layout()<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u751f\u6210\u4e86\u65b9\u6ce2\u4fe1\u53f7\uff0c\u7136\u540e\u4f7f\u7528SciPy\u5e93\u7684fftpack.fft<\/code>\u51fd\u6570\u5bf9\u4fe1\u53f7\u8fdb\u884c\u5085\u91cc\u53f6\u53d8\u6362\uff0c\u5e76\u7ed8\u5236\u4e86\u9891\u8c31\u56fe\u3002\u6211\u4eec\u4f7f\u7528Matplotlib\u5e93\u7684subplot<\/code>\u51fd\u6570\u5c06\u65b9\u6ce2\u4fe1\u53f7\u548c\u9891\u8c31\u56fe\u7ed8\u5236\u5728\u540c\u4e00\u4e2a\u56fe\u4e2d\u3002<\/p>\n<\/p>\n
\u4e94\u3001\u5b9e\u9645\u5e94\u7528\u4e2d\u7684\u65b9\u6ce2\u4fe1\u53f7<\/h3>\n<\/p>\n
\u65b9\u6ce2\u4fe1\u53f7\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u6709\u5f88\u591a\u7528\u9014\uff0c\u4f8b\u5982\u5728\u901a\u4fe1\u7cfb\u7edf\u4e2d\u4f5c\u4e3a\u8f7d\u6ce2\u4fe1\u53f7\u3001\u5728\u63a7\u5236\u7cfb\u7edf\u4e2d\u4f5c\u4e3a\u6fc0\u52b1\u4fe1\u53f7\u3001\u5728\u97f3\u9891\u5904\u7406\u548c\u5408\u6210\u4e2d\u4f5c\u4e3a\u57fa\u7840\u6ce2\u5f62\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u5b9e\u9645\u5e94\u7528\u7684\u4f8b\u5b50\uff0c\u6f14\u793a\u5982\u4f55\u751f\u6210\u548c\u7ed8\u5236\u8c03\u5236\u540e\u7684\u65b9\u6ce2\u4fe1\u53f7\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
from scipy import signal<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u751f\u6210\u65f6\u95f4\u5e8f\u5217<\/strong><\/h2>\n
t = np.linspace(0, 1, 500)<\/p>\n
\u751f\u6210\u8f7d\u6ce2\u4fe1\u53f7<\/strong><\/h2>\n
carrier = np.sin(2 * np.pi * 10 * t)<\/p>\n
\u751f\u6210\u65b9\u6ce2\u8c03\u5236\u4fe1\u53f7<\/strong><\/h2>\n
modulation = signal.square(2 * np.pi * 2 * t)<\/p>\n
\u8c03\u5236\u8f7d\u6ce2\u4fe1\u53f7<\/strong><\/h2>\n
modulated_signal = carrier * modulation<\/p>\n
\u7ed8\u5236\u539f\u59cb\u8f7d\u6ce2\u4fe1\u53f7\u3001\u65b9\u6ce2\u8c03\u5236\u4fe1\u53f7\u548c\u8c03\u5236\u540e\u7684\u4fe1\u53f7<\/strong><\/h2>\n
plt.subplot(3, 1, 1)<\/p>\n
plt.plot(t, carrier)<\/p>\n
plt.title('Carrier Signal')<\/p>\n
plt.xlabel('Time [s]')<\/p>\n
plt.ylabel('Amplitude')<\/p>\n
plt.grid(True)<\/p>\n
plt.subplot(3, 1, 2)<\/p>\n
plt.plot(t, modulation)<\/p>\n
plt.title('Square Wave Modulation Signal')<\/p>\n
plt.xlabel('Time [s]')<\/p>\n
plt.ylabel('Amplitude')<\/p>\n
plt.grid(True)<\/p>\n
plt.subplot(3, 1, 3)<\/p>\n
plt.plot(t, modulated_signal)<\/p>\n
plt.title('Modulated Signal')<\/p>\n
plt.xlabel('Time [s]')<\/p>\n
plt.ylabel('Amplitude')<\/p>\n
plt.grid(True)<\/p>\n
plt.tight_layout()<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u751f\u6210\u4e86\u4e00\u4e2a\u9891\u7387\u4e3a10 Hz\u7684\u8f7d\u6ce2\u4fe1\u53f7\u548c\u4e00\u4e2a\u9891\u7387\u4e3a2 Hz\u7684\u65b9\u6ce2\u8c03\u5236\u4fe1\u53f7\uff0c\u7136\u540e\u5c06\u8f7d\u6ce2\u4fe1\u53f7\u548c\u8c03\u5236\u4fe1\u53f7\u76f8\u4e58\uff0c\u5f97\u5230\u8c03\u5236\u540e\u7684\u4fe1\u53f7\u3002\u6700\u540e\uff0c\u6211\u4eec\u4f7f\u7528Matplotlib\u5e93\u5c06\u539f\u59cb\u8f7d\u6ce2\u4fe1\u53f7\u3001\u65b9\u6ce2\u8c03\u5236\u4fe1\u53f7\u548c\u8c03\u5236\u540e\u7684\u4fe1\u53f7\u7ed8\u5236\u5728\u540c\u4e00\u4e2a\u56fe\u4e2d\u3002<\/p>\n<\/p>\n
\u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u5728\u8fd9\u7bc7\u6587\u7ae0\u4e2d\uff0c\u6211\u4eec\u8be6\u7ec6\u4ecb\u7ecd\u4e86\u5982\u4f55\u5728Python\u4e2d\u751f\u6210\u548c\u7ed8\u5236\u65b9\u6ce2\u4fe1\u53f7\u3002\u6211\u4eec\u9996\u5148\u4f7f\u7528NumPy\u548cMatplotlib\u5e93\u751f\u6210\u548c\u7ed8\u5236\u4e86\u65b9\u6ce2\u4fe1\u53f7\uff0c\u7136\u540e\u4ecb\u7ecd\u4e86\u5982\u4f55\u8c03\u6574\u56fe\u5f62\u7684\u5916\u89c2\u548c\u6837\u5f0f\u3002\u63a5\u7740\uff0c\u6211\u4eec\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528\u5176\u4ed6\u5e93\u548c\u65b9\u6cd5\u751f\u6210\u548c\u7ed8\u5236\u65b9\u6ce2\u4fe1\u53f7\uff0c\u4f8b\u5982SciPy\u5e93\u3002\u968f\u540e\uff0c\u6211\u4eec\u7ed3\u5408\u4fe1\u53f7\u5904\u7406\u548c\u5206\u6790\uff0c\u6f14\u793a\u4e86\u5982\u4f55\u5bf9\u65b9\u6ce2\u4fe1\u53f7\u8fdb\u884c\u5085\u91cc\u53f6\u53d8\u6362\u5e76\u7ed8\u5236\u9891\u8c31\u56fe\u3002\u6700\u540e\uff0c\u6211\u4eec\u901a\u8fc7\u4e00\u4e2a\u5b9e\u9645\u5e94\u7528\u7684\u4f8b\u5b50\uff0c\u5c55\u793a\u4e86\u65b9\u6ce2\u4fe1\u53f7\u5728\u901a\u4fe1\u7cfb\u7edf\u4e2d\u7684\u5e94\u7528\u3002<\/p>\n<\/p>\n
\u901a\u8fc7\u8fd9\u4e9b\u793a\u4f8b\u548c\u65b9\u6cd5\uff0c\u76f8\u4fe1\u4f60\u5df2\u7ecf\u638c\u63e1\u4e86\u5728Python\u4e2d\u751f\u6210\u548c\u7ed8\u5236\u65b9\u6ce2\u4fe1\u53f7\u7684\u57fa\u672c\u6280\u5de7\uff0c\u5e76\u80fd\u591f\u5c06\u8fd9\u4e9b\u6280\u5de7\u5e94\u7528\u5230\u5b9e\u9645\u7684\u4fe1\u53f7\u5904\u7406\u548c\u5206\u6790\u4e2d\u3002\u5e0c\u671b\u8fd9\u7bc7\u6587\u7ae0\u5bf9\u4f60\u6709\u6240\u5e2e\u52a9\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u4f7f\u7528Python\u7ed8\u5236\u65b9\u6ce2\u4fe1\u53f7\u7684\u57fa\u672c\u6b65\u9aa4\u662f\u4ec0\u4e48\uff1f<\/strong>
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