def mcfit(logpost,bounds,args=(),sampler=None,proposal=None,N=10000,burnin=1000,seed=None,outfile=None):
"""
Fit args using MCMC and return samples from the PDF.
"""
if sampler == None:
# sampler = MCSampler()
sampler = EnsembleSampler(100)
try:
bounds = np.array(bounds)
# if np.shape(bounds)[1] != 2:
# raise MCError("provide bounds on the parameter space")
if proposal == None:
proposal = (bounds[:,1]-bounds[:,0])/10.
return sampler.sample_pdf(logpost,bounds,proposal,N,burnin,args,outfile=outfile,seed=None)
except (MCError,ProposalErr): # as e:
print "MCMC exception raised with message: "+e.value
