clean up example

docs/molecule.rst

@@ -23,3 +23,12 @@ The two other keyword arguments (``calculator`` and ``basis``) refers to the QM
 used to describe the electronic strucrure of the molecule. The calculator refers to a particular QM package and so far only
 ``pyscf`` and ``adf`` are supported. ``basis``  refers to the basis set used for the calculation.
 The value of the keyword argument should be a valid name of an **all electron** basis set.
+
+Load from HDF5
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Creating a molecule will automatically geneate a HDF5 file containing all the information
+about the molecule (geometry, basis, etc ...). It is possible to load this hdf5 file in molecule
+
+>>> mol = Molecule(load='H2_adf_dzp.hdf5')
+

example/h2.py

@@ -3,10 +3,8 @@
 from qmctorch.wavefunction import Orbital, Molecule
 from qmctorch.solver import SolverOrbital
 from qmctorch.sampler import Metropolis
-
 from qmctorch.utils import set_torch_double_precision
-
-from qmctorch.utils import (plot_energy, plot_data, plot_walkers_traj)
+from qmctorch.utils import (plot_energy, plot_data)
 
 # bond distance : 0.74 A -> 1.38 a
 # optimal H positions +0.69 and -0.69
@@ -21,10 +19,6 @@
                basis='dzp',
                unit='bohr')
 
-# load the molecule from a previous hdf5
-# mol = Molecule(load='H2_pyscf_dzp.hdf5')
-
-
 # define the wave function
 wf = Orbital(mol, kinetic='jacobi',
              configs='cas(2,2)',
@@ -33,18 +27,18 @@
 wf.jastrow.weight.data[0] = 1.
 
 # sampler
-sampler = Metropolis(nwalkers=50,
-                     nstep=200, step_size=0.2,
+sampler = Metropolis(nwalkers=2000,
+                     nstep=2000, step_size=0.2,
                      ntherm=-1, ndecor=100,
                      nelec=wf.nelec, init=mol.domain('atomic'),
                      move={'type': 'all-elec', 'proba': 'normal'})
 
 
 # optimizer
-lr_dict = [{'params': wf.jastrow.parameters(), 'lr': 1E-3},
+lr_dict = [{'params': wf.jastrow.parameters(), 'lr': 3E-3},
            {'params': wf.ao.parameters(), 'lr': 1E-6},
            {'params': wf.mo.parameters(), 'lr': 1E-3},
-           {'params': wf.fc.parameters(), 'lr': 1E-3}]
+           {'params': wf.fc.parameters(), 'lr': 2E-3}]
 opt = optim.Adam(lr_dict, lr=1E-3)
 
 # scheduler
@@ -54,38 +48,21 @@
 solver = SolverOrbital(wf=wf, sampler=sampler,
                        optimizer=opt, scheduler=None)
 
-
 # perform a single point calculation
-# obs = solver.single_point()
-
-# compute the sampling trajectory
-# solver.sampler.ntherm = 1000
-# solver.sampler.ndecor = 100
-# pos = solver.sampler(solver.wf.pdf)
-# obs = solver.sampling_traj(pos)
-# plot_walkers_traj(obs.local_energy)
-
-
-# # optimize the wave function
-# solver.configure(task='wf_opt', freeze=['ao', 'mo'])
-# solver.track_observable(['local_energy'])
-
-# solver.configure_resampling(
-#     mode='update', resample_every=1, nstep_update=25)
-# solver.ortho_mo = False
-# data = solver.run(5, batchsize=None,
-#                   loss='energy',
-#                   grad='manual',
-#                   clip_loss=False)
-
-# plot_energy(solver.observable.local_energy, e0=-
-#             1.1645, show_variance=True)
-# plot_data(solver.observable, obsname='jastrow.weight')
-
-# optimize the geometry
-solver.configure(task='geo_opt')
-solver.track_observable(['local_energy', 'atomic_distances'])
-data = solver.run(5, batchsize=None,
-                  loss='energy',
-                  grad='manual',
-                  clip_loss=False)
+obs = solver.single_point()
+
+# optimize the wave function
+solver.configure(task='wf_opt', freeze=['ao', 'mo'])
+solver.track_observable(['local_energy'])
+
+solver.configure_resampling(mode='update',
+                            resample_every=1,
+                            nstep_update=50)
+solver.ortho_mo = False
+obs = solver.run(250, batchsize=None,
+                 loss='energy',
+                 grad='manual',
+                 clip_loss=False)
+
+plot_energy(obs.local_energy, e0=-1.1645, show_variance=True)
+plot_data(solver.observable, obsname='jastrow.weight')

example/h2o_sampling.py

@@ -13,7 +13,7 @@
              use_jastrow=True)
 
 # sampler
-sampler = Metropolis(nwalkers=100, nstep=300, step_size=0.25,
+sampler = Metropolis(nwalkers=100, nstep=500, step_size=0.25,
                      nelec=wf.nelec, ndim=wf.ndim,
                      init=mol.domain('atomic'),
                      move={'type': 'one-elec', 'proba': 'normal'})
@@ -26,7 +26,7 @@
 
 # reconfigure sampler
 solver.sampler.ntherm = 0
-solver.sampler.ndecor = 3
+solver.sampler.ndecor = 5
 
 # compute the sampling traj
 pos = solver.sampler(solver.wf.pdf)