Emcee with gaussian prior gives NaN
I’ve been using emcee to sampel my parameter, at first my prior were all uniform
def logprior_BAO(theta): A, B, C, D, epsilon, rd = theta if A > 0 and B > 0 and C > 0 and D > 0 and epsilon > -5 and 146.96<=rd<=147.58: return 0.0 return -np.inf and it work perfectly fine. then, I change the rd prior to Gaussian,
def logprior_BAO(theta): A, B, C, D, epsilon, rd = theta #flat priors if not A > 0 and B > 0 and C > 0 and D > 0 and epsilon > -5: return -np.inf #gaussian prior rd mu = 147.27 sigma = 0.31 return np.log(1.0/(np.sqrt(2*np.pi)*sigma))-0.5*(rd-mu)**2/sigma**2 and the program gives me this error
ValueError Traceback (most recent call last) <ipython-input-9-b9ee20e97036> in <module> 3 move = emcee.moves.StretchMove(a=a_parameter) 4 sampler = emcee.EnsembleSampler(nwalker, ndims, logposterior,args=argslist, moves=move) ----> 5 sampler.run_mcmc(initial, nsteps, progress=True) ~\anaconda3\lib\site-packages\emcee\ensemble.py in run_mcmc(self, initial_state, nsteps, **kwargs) 382 383 results = None --> 384 for results in self.sample(initial_state, iterations=nsteps, **kwargs): 385 pass 386 ~\anaconda3\lib\site-packages\emcee\ensemble.py in sample(self, initial_state, log_prob0, rstate0, blobs0, iterations, tune, skip_initial_state_check, thin_by, thin, store, progress) 283 state.blobs = blobs0 284 if state.log_prob is None: --> 285 state.log_prob, state.blobs = self.compute_log_prob(state.coords) 286 if np.shape(state.log_prob) != (self.nwalkers,): 287 raise ValueError("incompatible input dimensions") ~\anaconda3\lib\site-packages\emcee\ensemble.py in compute_log_prob(self, coords) 454 # Check for log_prob returning NaN. 455 if np.any(np.isnan(log_prob)): --> 456 raise ValueError("Probability function returned NaN") 457 458 return log_prob, blob ValueError: Probability function returned NaN Could anybody tell me why this is happening, and how to fix it? I will appreciate your answer, thanks
