How to transfer pytensor into numpy

Questions v5
1

I want to calculate H_s in my model using E. I have obtained a model that predicts H_s using a Gaussian process, but when I try to sample E and obtain the corresponding H_s, I fail. My code is the following:

with pm.Model() as model2:
        ene_Mn_eg = df_Mn_eg['ene'].to_numpy()
        hyb_Mn_eg = df_Mn_eg['hyb'].to_numpy()
        lower_e = np.min(ene_Mn_eg)
        upper_e = np.max(ene_Mn_eg)
        E = []
        H_s =[]
        # E = pm.Uniform(f'E_{4}', lower=lower_e, upper = upper_e,shape=4)
        # with model:
        for i in range(4):
            E.append(pm.Uniform(f'E_{i}', lower=lower_e, upper = upper_e))
            mu, var = gp.predict(E[i], point=trace[-1], diag=True)
            std = np.sqrt(var)
            mu_H_s = mu

            H_s.append(pm.Normal(f'H_s_{i}',mu = mu_H_s, sigma=std))
        mu = hybridization_function(ene_Mn_eg, E, H_s)
        idata = pm.sample_prior_predictive()
        idata.extend(pm.sample())

IndexError: too many indices for array

Obviously, the shape of E is not directly usable for calculations, but I don’t know how to convert it, I can’t find the appropriate code.

I am looking forward to your reply. Thank you very much.