# plt.hist(eloc.detach().numpy(), bins=50)
# plt.show()
# pos = solver.sample(ntherm=0, ndecor=10)
# obs = solver.sampling_traj(pos)
# plot_energy(obs, e0=-8.)
if 0:
solver.configure(task='wf_opt', freeze=['ao', 'mo'])
solver.observable(['local_energy'])
solver.initial_sampling(ntherm=1000, ndecor=100)
solver.resampling(nstep=25,
step_size=0.2,
resample_from_last=True,
resample_every=1,
tqdm=False)
solver.ortho_mo = False
data = solver.run(50,
batchsize=None,
loss='energy',
grad='manual',
clip_loss=True)
save_observalbe('lih.pkl', solver.obs_dict)
e, v = plot_energy(solver.obs_dict, e0=-8.06, show_variance=True)
plot_data(solver.obs_dict, obs='jastrow.weight')
# Tc = plot_walkers_traj(obs)
# plot_block(obs)
# save_observalbe('obs.pkl', obs)
# obs = load_observable('obs.pkl')
# plot_energy(obs, e0=-1.1645, show_variance=True)
# optimize the wave function
if 0:
solver.configure(task='wf_opt', freeze=['ao', 'mo'])
solver.observable(['local_energy'])
solver.initial_sampling(ntherm=1000, ndecor=100)
solver.resampling(nstep=20,
ntherm=-1,
step_size=0.2,
resample_from_last=True,
resample_every=1,
tqdm=True)
solver.ortho_mo = False
data = solver.run(50,
batchsize=None,
loss='energy',
grad='manual',
clip_loss=False)
save_observalbe('h2.pkl', solver.obs_dict)
e, v = plot_energy(solver.obs_dict, e0=-1.1645, show_variance=True)
plot_data(solver.obs_dict, obs='jastrow.weight')
# # optimize the geometry