Ale*_*onB 5 python matlab signal-processing matplotlib spectrogram
我在 MATLAB 中有一个程序,我想将它移植到 Python。问题是我在其中使用了内置spectrogram函数,虽然 matplotlibspecgram函数看起来相同,但当我同时运行这两个函数时,我得到了不同的结果。
这些是我一直在运行的代码。
MATLAB:
data = 1:999; %Dummy data. Just for testing.
Fs = 8000; % All the songs we'll be working on will be sampled at an 8KHz rate
tWindow = 64e-3; % The window must be long enough to get 64ms of the signal
NWindow = Fs*tWindow; % Number of elements the window must have
window = hamming(NWindow); % Window used in the spectrogram
NFFT = 512;
NOverlap = NWindow/2; % We want a 50% overlap
[S, F, T] = spectrogram(data, window, NOverlap, NFFT, Fs);
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Python:
import numpy as np
from matplotlib import mlab
data = range(1,1000) #Dummy data. Just for testing
Fs = 8000
tWindow = 64e-3
NWindow = Fs*tWindow
window = np.hamming(NWindow)
NFFT = 512
NOverlap = NWindow/2
[s, f, t] = mlab.specgram(data, NFFT = NFFT, Fs = Fs, window = window, noverlap = NOverlap)
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这是我在两次执行中得到的结果:
http://i.imgur.com/QSPvYsC.png
(两个程序中的 F 和 T 变量完全相同)
很明显,它们是不同的;事实上,Python 执行甚至不返回复数。可能是什么问题呢?有什么办法可以修复它还是我应该使用另一个频谱图功能?
非常感谢您的帮助。
在 中matplotlib,specgram默认返回功率谱密度 ( mode='PSD')。在 中MATLAB,spectrogram默认情况下返回短时傅里叶变换,除非nargout==4,在这种情况下它还会计算PSD。要使matplotlib行为与行为相匹配MATLAB,请设置mode='complex'