position_nr=np.argmax(times_nr>=(t0_nr-0.1))#The 0.1 is to compensate the stepsize-off issue of the nr data - it gives better alignment between the NR data and our mock fit, and shouldn't interfere with our results because we are still using the time points in the NR data!
# 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.