Continuous Wavelet Transform with Scipy.signal: what is parameter "widths" in cwt() function? How do time-frequency?
complex morlet was added Aug 10, 2007
ricker and cwt were added Sep 20, 2011


There's no indication that cwt is meant to be compatible with morlet.  As cwt docstring says: 


  Wavelet function, which should take 2 arguments. ... second is a width parameter, defining the size of the wavelet (e.g. standard deviation of a gaussian).


The morlet function takes 4 arguments, the second of which is not a width parameter, it's a frequency parameter, so I don't think it is meant to be used with cwt. Using ricker as a template, you are supposed to define your own functions to use with cwt. In addition, cwt cannot handle complex wavelets (as of v0.18).

I'd suggest you try a different implementation that has this done for you:


Pyscellania has a Wavelets module (now mirrored at github) which implements real/complex Morlet, MexicanHat, Paul order 2, Paul order 4, 1st Derivative Of Gaussian, 4th Derivative Of Gaussian, Unnormalised version of continuous Haar transform, Normalised Haar
aaren/wavelets supports Morlet, Paul, DOG, Ricker
Machine Learning PYthon (mlpy) has mlpy.wavelet.cwt that supports Morlet, Paul, and Derivative Of Gaussian wavelets
Dapid/fast-pycwt supports Morlet and Ricker
ObsPy (seismological observatories) has a cwt module and "for now only 'morlet' is implemented"
pyCWT has Morlet wavelet