Hi everyone,

I have a model with a random variable that is sampled from uniform prior which has an entropy potential applied in order to transform the potential. Please see code below.

var_alpha = theano.shared(value = 1.5, borrow = False)

phi_e = pm.Uniform(‘phi_e’, lower = lb_phi_e, upper = ub_phi_e, shape = (ub_phi_e.size))

S1_phi_e = (phi_e/phi_e.sum()*np.log(phi_e/phi_e.sum())).sum()

pm.Potential(‘phi_e_potential’, np.exp(-var_alpha*S1_phi_e))

I’m interested in sampling the prior distribution to verify certain things about the model however, the prior_predictive_sample function or model.phi_e.random() all seem to return uniformly distributed samples. I would expect the potential to be applied …

If it’s not applied (i suspect this is the case from some other posts on here), how can I apply it to the random variables?