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#some random data | |
my_data = np.random.random(2048) | |
#### Your Code | |
Fs = 10E6 # Sampling Rate | |
w_length= 256 # window length | |
nFFT=2 * w_length | |
n_overlap=np.fix(w_length/2) | |
p_to = 8 *w_length | |
Pxx, freqs, bins= mlab.specgram(my_data,NFFT=nFFT,Fs=Fs, | |
detrend=mlab.detrend_linear, | |
noverlap=n_overlap, | |
pad_to=p_to,scale_by_freq=True) | |
cp = np.copy(Pxx) #copying to show the trick with indexes | |
#find a maximum frequency index | |
maxfreq = 1E5 #replace by your maximum freq | |
if maxfreq: | |
lastfreq = freqs.searchsorted(maxfreq) | |
if lastfreq > len(freqs): | |
lastfreq = len(freqs)-1 | |
Pxx = np.flipud(Pxx) #flipping image in the y-axis | |
interp='nearest' | |
seismic = plt.get_cmap('seismic') | |
cmap=seismic | |
fig = plt.figure() | |
ax1=fig.add_subplot(211) | |
extent = 0,4,freqs[0],freqs[lastfreq] # new extent | |
#plot reduced range | |
img1=ax1.imshow(Pxx[-lastfreq:], interpolation=interp, aspect='auto', | |
extent=extent ,cmap=cmap) | |
fig.colorbar(img1) | |
#this two images are the same | |
ax2=fig.add_subplot(212) | |
img2=ax2.imshow(np.flipud(cp[:lastfreq]), interpolation=interp, aspect='auto', | |
extent=extent ,cmap=cmap) | |
ax1.set_autoscaley_on(False) | |
fig.colorbar(img2) | |
plt.show() |
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