Source code for pysisyphus.interpolate.IDPP

from scipy.spatial.distance import pdist

# from pysisyphus.constants import BOHR2ANG, ANG2BOHR
from pysisyphus.calculators.IDPPCalculator import IDPPCalculator
from pysisyphus.constants import BOHR2ANG, ANG2BOHR
from pysisyphus.cos.NEB import NEB
from pysisyphus.helpers import align_geoms
from pysisyphus.optimizers.FIRE import FIRE
from pysisyphus.interpolate.Interpolator import Interpolator

# [1]
# See

[docs] class IDPP(Interpolator):
[docs] def interpolate(self, initial_geom, final_geom, **kwargs): # Do an initial linear interpolation to generate all geometries/images # that will be refined later by IDPP interpolation. linear_interpol = super().interpolate(initial_geom, final_geom) idpp_geoms = [initial_geom] + linear_interpol + [final_geom] align_geoms(idpp_geoms) # Interestingly IDPP calculations work much better when done # in Angstroem instead of in Bohr. for geom in idpp_geoms: geom.coords *= BOHR2ANG # We want to interpolate between these two condensed distance matrices initial_pd = pdist(initial_geom.coords3d) final_pd = pdist(final_geom.coords3d) steps = 1 + self.between pd_diff = (final_pd - initial_pd) / steps for i, geom in enumerate(idpp_geoms): geom.set_calculator(IDPPCalculator(initial_pd + i * pd_diff)) neb = NEB(idpp_geoms) opt_kwargs = { "max_cycles": 1000, "rms_force": 1e-2, "align": False, "check_coord_diffs": False, } opt = FIRE(neb, **opt_kwargs) for geom in idpp_geoms: # Delete IDPP calculator, energies and forces geom.clear() geom.coords *= ANG2BOHR interpolated_geoms = idpp_geoms[1:-1] return interpolated_geoms