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I want to compute wavelet coherence of two given timeseries in python. I tried working with pycwt but when calculating the cross-wavelet transform I find trouble due to shortness of data or too much of a trending (both things have already been taken care of so there is not much I can do). I compute the cross-wavelet manually and proceed to do the same with wavelet coherence, but I am in need of a smoothing function and it all gets messy and complicated. I don't think there is a simple way to do this, but maybe somebody have a clearer idea. I am following the paper "Partial wavelet coherence as a robust method for assesment of neurovascular coupling in neonates with hypoxic ischemic encephalopathy", by T. Hermans et al. I am also aware of a very useful R implementation of the wavelet coherence that computes it very easily, but I am asked to do the Python implementation exactly. Thank you everybody!

Tried pycwt package and more things on the way... I have been working on this for a while now.

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