I'm working on a dataset of spectroscopies and i'm classifying them by transforming the 1D signal into a 2D one by the [`ssqueezepy` library](https://github.com/OverLordGoldDragon/ssqueezepy).

For instance, consider to have a 1D signal and the corresponding 2D image, generated by executing the function:

`Tx, _ = ssq_cwt(input_1D_signal, wavelet="gmw", nv = 64, scales=0.1)`

From the library above. The study I performed highlights the areas of the cwt image that are most important for classification. Do you know if there is a way to find the corresponding information in the original 1D signal?
I'm using the inverse mapping in the library, `issq_cwt(Tx)`, but I don't know how to find the corresponing highlighted informations.

Unfortunately I'm nearing a deadline, so I can't immerse myself much in the literature behind it, so I hope someone who already knows the synchrosquezing procedure can help me.

Edit: Looking inside the library code is explained that the inverse function above is [from the eq.15 of this paper](https://arxiv.org/pdf/1105.0010.pdf).

There is a way to relate the math procedure done on the image of the transformed signal directly on the heatmap image? I'm trying to brute-pass the grayscale heatmap to the issq\_cwt() function to obtain a result(which even seems acceptable), is that correct?