GP Predict Point

Questions
7

Could you post you entire model? If you want your predicted values (i am assuming the predictive mean and standard deviation) you can first use the conditional method to generate new points

with model:
f_pred = gp.conditional("f_pred", X_new)

with model:
pred_samples = pm.sample_posterior_predictive(trace, vars=[f_pred], samples=1000)

where X_new could be over the same range as you original data. Then you can loop over your pred samples to get their mean and standard deviation at those X_new points

mu = np.zeros(len(X_new))
sd = np.zeros(len(X_new))

for i in range(0,len(X_new)):
  mu[i] = np.mean(pred_samples["f_pred"][:,i])
  sd[i] = np.std(pred_samples["f_pred"][:,i])