Faded line in spectrogram for a chirp I've generated this spectrogram using wavelet convolution.
The chirp is generated like so:
framerate = 10000
DURATION = 10
N = DURATION*framerate
k = np.arange(N)
chirp = sig.chirp(k, 0.01, N, .49)


Each row (linearly representing a frequency) is generated like so:
$$row_f = |IFFT(FFT(chirp) * FFT(wavelet_f))|$$
where $f$ represents the frequency.
When I use matplotlib's built in spectrogram tool, I get this image:

L = 100  # length of one segment
overlap = L/2  # overlap between segments
plt.figure(figsize = (10, 5))
plt.specgram(sounddata, NFFT=L, Fs=2, noverlap=overlap, sides='onesided')

In this plot, the line is seemingly cleaner - not blurring over time. Why is the line blurring? I thought wavelet convolution was supposed to have higher resolution than STFT.
If you think of the spectrograms as filter banks it might be easier to conceptualize. With a STFT, each bin in the bank has the same time/frequency resolution. With the Wavelet transform, the bins at lower frequencies have higher frequency resolution, which means they must also have lower time resolution.  There is an inherent trade off between time and frequency resolution such that one cannot be increased without decreasing the other.  This can be thought of intuitively as an impulse in the time domain has an infinitely wide frequency response, or infinitely high resolution in the time domain and zero resolution in the frequency domain.