def generate_H_V_T(epsilon,L,vo,q_point):
metrico = metric("unit_e",vo)
Ho = Hamiltonian(vo, metrico)
q = q_point.point_clone()
p = Ho.T.generate_momentum(q)
H_0_out = Ho.evaluate(q,p)
H_list = [H_0_out["H"]]
V_list = [H_0_out["V"]]
T_list = [H_0_out["T"]]
for _ in range(L):
print("iter {}".format(_))
q,p,stat = abstract_leapfrog_ult(q, p, epsilon, Ho)
if stat["explode_grad"]:
break
# out = abstract_leapfrog_ult(q,p,epsilon,Ho)
# out = abstract_NUTS(q,epsilon,Ham,abstract_leapfrog_ult,5)
H_out = Ho.evaluate(q, p)
current_H = H_out["H"]
current_T = H_out["T"]
current_V = H_out["V"]
if abs(current_H - H_list[0]) > 1000:
break
print("current V is {}".format(current_V))
print("current H {}".format(current_H))
print("current T {}".format(current_T))
# current_V, current_T, current_H = Ho.evaluate_all(q, p)
# print("current H2 {}".format(Ho.evaluate(q,p)))
H_list.append(current_H)
V_list.append(current_V)
T_list.append(current_T)
out = {"H_list":H_list,"V_list":V_list,"T_list":T_list}
return(out)
else:
return((V(q)+T(p)))
# first verify they have the same Hamiltonian function
print("exact H {}".format(H(q,p,True)))
v_obj = V_pima_inidan_logit()
metric_obj = metric("unit_e",v_obj)
Ham = Hamiltonian(v_obj,metric_obj)
q_point = Ham.V.q_point.point_clone()
p_point = Ham.T.p_point.point_clone()
q_point.flattened_tensor.copy_(inputq)
p_point.flattened_tensor.copy_(inputp)
print("abstract H {}".format(Ham.evaluate(q_point,p_point)))
print("input q diff{}".format((q.data-q_point.flattened_tensor).sum()))
print("input p diff {}".format((p.data-p_point.flattened_tensor).sum()))
L=10
for i in range(L):
outq,outp = leapfrog_ult(q,p,0.1,H)
outq_a,outp_a,stat = abstract_leapfrog_ult(q_point,p_point,0.1,Ham)
q, p = outq, outp
q_point, p_point = outq_a, outp_a
diffq = ((outq.data - outq_a.flattened_tensor)*(outq.data - outq_a.flattened_tensor)).sum()
diffp = ((outp.data - outp_a.flattened_tensor)*(outp.data - outp_a.flattened_tensor)).sum()
print("diff outq {}".format(diffq))
print("diff outp {}".format(diffp))