for jsick

jsick.py

#!/usr/bin/env python

import numpy as np
import emcee


class ProbWrapper(object):
    def __init__(self, f):
        super(ProbWrapper, self).__init__()
        self._f = f
    
    def __call__(self, x, *args):
        return self._f(x, *args)[0]


def lnprob(x, ivar):
    return -0.5 * np.array([np.sum(ivar * x ** 2), ])

ndim, nwalkers = 10, 100
ivar = 1. / np.random.rand(ndim)
p0 = [np.random.rand(ndim) for i in range(nwalkers)]

lnprobwr = ProbWrapper(lnprob)
sampler = emcee.EnsembleSampler(nwalkers, ndim, lnprobwr, args=[ivar])
sampler.run_mcmc(p0, 1000)

lnprobs need to return zero-dim scalars.