# Logprior distribution. It defines the allowed range my variables can vary over.
#It works for the (xn*Exp[iyn]) version.
deflog_prior(theta):
#Warning: we are specifically working with nmax=1 so here individual prior to the parameters are manually adjusted. This does not apply to all other nmax's.
#The autocorrelation time, this time I don't intend to delete alpha0 and beta0, just keep the nan's there since we don't really use this data, only look at it. It's good to keep it for sanity check's sake.
atcrr=sampler.get_autocorr_time()[0]
df4=pd.DataFrame(atcrr,index=paramlabels,columns=[r'Autocorrelation time, vary='+str(vary_fund)+', nmax='+str(nmax)+', tshift='+str(tshift)+', '+str(npoints)+'pts'])