ProxPython is now using the built-in random generator numpy.random.poisson. According to the comments in PossionRan the argument is the mean (often called lambda). I also checked Numerical Recipes p. 294. Therefore calling

numpy.random.poisson(x)

should yield the same as calling

PoissonRan(x).

This resolves the overflow issue with PoissonRan, but I still get the following warnings:

../proxtoolbox/ProxOperators/proxoperators.py:265: RuntimeWarning: divide by zero encountered in true_divide
tmp = U_sq/data_sq[:,:,j];
../proxtoolbox/ProxOperators/proxoperators.py:265: RuntimeWarning: invalid value encountered in true_divide
tmp = U_sq/data_sq[:,:,j];

Therefore I had a look at the following line in JWST_data_processor:

k[:,:,i]=np.round(k[:,:,i])

From my understanding it is very likely to get zeros when rounding.

I noted that after commenting out above line, there were no further warnings and the algorithm did converge nicely.