use emcee to generate ~N ind. samples

emcee_indSample.py

import emcee
import numpy as np

# TODO:
# write something using sampler.sample() instead of predefined niter to ensure we have enough uncorrelated sample after run..
nindependent = 0
nind = 500
niter = 1000
attempts = 10
counter = 0
if counter <= attempt:
    while nindependent < nind:
        print("Number of independent samples from last iteration: {:}".format(nindependent))
        try:
            pos0, lnprob0, rstate0 = sampler.run_mcmc(pzero, burnin)
        except ValueError:
            pos0, lnprob0, rstate0, _ = sampler.run_mcmc(pos0, niter, rstate=rstate0, lnprob0=lnprob0)

        try:
            nindependent = sampler.iterations/numpy.mean(sampler.acor)        
        except RuntimeError:
            print("acor didn't converge")
            nindependent = 0
        counter +=1
else:
    print("Need more iterations to reach {:d} independent samples.".format(nindependent))