Continuous Wavelet Transform time vector in python
Similar question here Which time-frequency coefficients does the Wavelet transform compute?

The picture you've shown is used for DWT such as pywt.wavedec, not CWT.

CWT is a continuous function; it exists at all points in the time-scale plane.

pywt.cwt produces a 2D array with constant numbers of columns and rows, so it's a regular sampling of the CWT, at whatever scales you specify, for every sample of the input:

shape(y)
Out[5]: (512,)

shape(freqs)
Out[6]: (128,)

shape(coef)
Out[7]: (128, 512)


I think the DWT's coefficients contain just enough information to reproduce the original exactly with an inverse DWT, while the CWT output has a lot of redundant information and is maybe missing some information.