Source code for esteem.tasks.qmd_trajectories

#!/usr/bin/env python
# coding: utf-8

# # Run main program

# In[ ]:


import sys
import ase.units

from esteem.trajectories import generate_md_trajectory, recalculate_trajectory
from esteem.trajectories import find_initial_geometry, get_trajectory_list


[docs]class QMDTrajTask: def __init__(self,**kwargs): self.wrapper = None self.script_settings = None self.task_command = 'qmd' self.train_params = {} args = self.make_parser().parse_args("") for arg in vars(args): setattr(self,arg,getattr(args,arg)) # Main routine
[docs] def run(self): """ Sets up and runs an ab initio molecular dynamics run on a given molecule (whose name is provided by ``args.seed``) in the ground or excited state (specified by ``args.target``). Results, including a trajectory file with the stored snapshots, are saved to files appending ``args.suffix`` to the seed and state, for use in future runs. The run is divided into equilibration (``args.nequil`` runs of ``args.qmd_steps`` MD steps each, with timestep ``args.qmd_timestep``), then snapshot generation (``args.nsnap`` runs of ``args.qmd_steps`` MD steps each, with timestep ``args.qmd_timestep``). A thermostat (wrapper-dependent) at temperature ``args.temp`` means we stay in the NVT ensemble. Constraints can be applied using ``args.constraints`` - the meaning depends on the underlying wrapper. Optionally can be used to recalculate singlepoint energies for the steps of a pre-existing trajectory. args: namespace or class Full set of arguments to the QMD_Trajectories task - see below for a listing. Key arguments include ``basis``, ``func``, ``qmd_timestep``, ``qmd_steps``, ``nsnap``, ``nequil``, ``temp``, ``constraints`` Generate with a call to qmd_trajectories.make_parser() wrapper: namespace or class List of functions for running components of the job, with members including: ``singlepoint``, ``geom_opt`` and ``qmd``. """ # Check input args are valid #validate_args(self) # Make sure trajectory choices are valid all_trajs = get_trajectory_list(self.ntraj) if self.which_trajs is None: which_trajs = all_trajs else: which_trajs = self.which_trajs for traj_label in which_trajs: if traj_label not in all_trajs: raise Exception(f"Invalid trajectory name: {traj_label}") # Set up calculator parameters dict calc_params = {"basis": self.basis, "func": self.func, "target": self.target, "disp": self.disp} if self.seed in self.charges: charge = self.charges[self.seed] else: charge = 0 # Perform QM calculations on an existing trajectory if self.input_suffix is not None: for traj_label in which_trajs: input_target = None # re-do if ever necessary to start from anything else input_traj_range = self.input_traj_range recalculate_trajectory(self.seed,self.target,traj_label,self.traj_suffix, input_target,self.input_suffix, self.wrapper,calc_params,charge=charge, solvent=self.solvent,input_traj_range=input_traj_range) return # Generate training data in ntraj labelled trajectories for traj_label in which_trajs: # Find (or relax) initial geometry if isinstance(self.target,list): targ = self.target[0] else: targ = self.target calc_params['target'] = targ model = find_initial_geometry(self.seed,geom_opt_func=None,calc_params={}, #self.wrapper.geom_opt,calc_params, which_traj=traj_label,ntraj=self.ntraj) if self.constraints is not None: if 'spring' in self.constraints: spring = self.constraints['spring'] if 'bond' in spring: # Extract atoms indices and bondlength from NWChem constraint # NWChem expects 1-indexed atom numbers, ASE expects 0-indexed # so subtract 1 atoms0 = int(spring.split()[1]) - 1 atoms1 = int(spring.split()[2]) - 1 bondlength = float(spring.split()[4])*ase.units.Bohr print('Setting distance: ',atoms0,atoms1,bondlength) model.set_distance(atoms0,atoms1,bondlength,fix=0) # Pass in routine to actually run MD into generic Snapshot MD driver generate_md_trajectory(model,self.seed,self.target,traj_label,self.traj_suffix, wrapper=self.wrapper,count_snaps=self.nsnap,count_equil=self.nequil, md_steps=self.qmd_steps,md_timestep=self.qmd_timestep,md_friction=None, temp=self.temp,calc_params=calc_params, solvent=self.solvent,charge=charge,constraints=self.constraints, store_full_traj=True)
# Create parser to read command line values def make_parser(self): import argparse main_help = ('''Generate trajectory files by running QMD or by recalculating energies and forces at previously evaluated trajectory points.''') epi_help = ('') parser = argparse.ArgumentParser(description=main_help,epilog=epi_help) parser.add_argument('--seed','-s',type=str,help='') parser.add_argument('--traj_suffix','-S',default='training',type=str,help='String to append to names of trajectories') parser.add_argument('--geom_prefix','-G',default='',type=str,help='String to append to filenames for initial geometries') parser.add_argument('--basis','-b',default='6-311++G**',type=str,help='Basis set definition (or other run parameter)') parser.add_argument('--func','-f',default='PBE0',type=str,help='Exchange-Correlation functional (or other run parameter)') parser.add_argument('--disp','-d',default=True,type=bool,help='Apply Grimme-D3 Dispersion') parser.add_argument('--target','-t',default=None,type=int,help='Excited state index (None for ground state)') parser.add_argument('--charges','-C',default={},nargs='?',type=dict,help='Charges on molecular species. Not for command-line use') parser.add_argument('--restart','-r',default=False,type=bool,help='If the trajectory has been run for one excited state already, setting this to true attempts to make the calculator restart at each geometry') parser.add_argument('--md_timestep','-q',default=0.5,type=float,help='Molecular dynamics timestep (wrapper-dependent units, fs for NWChem)') parser.add_argument('--md_steps','-Q',default=100,type=int,help='Number of timesteps in each molecular dynamics run') parser.add_argument('--temp','-T',default=300.0,type=float,help='Thermostat temperature (NVT ensemble)') parser.add_argument('--ntraj','-n',default=1,type=int,help='Total number of named (A_Z,a-z) trajectories') parser.add_argument('--nsnap','-N',default=100,type=int,help='Number of snapshot runs') parser.add_argument('--solvent','-i',default=None,type=str,help='Solvent for implicit solvent runs.') parser.add_argument('--solvent_settings',default=None,type=str,help='Solvent settings for implicit solvent runs.') parser.add_argument('--input_suffix','-I',default=None,type=str,help='Appended string to identify input trajectory: if present, the run will resample an existing trajectory') parser.add_argument('--input_traj_range','-R',default=None,type=int,help='Range of snapshots to use from input trajectory') parser.add_argument('--nequil','-e',default=5,type=int,help='Number of equilibration runs.') parser.add_argument('--which-trajs','-w',default=None,type=str,help='Which trajectories should be generated, named with letters A-Z, a-z') parser.add_argument('--constraints','-c',default=None,type=str,help='Constraints (wrapper-dependent)') parser.add_argument('--dynamics','-X',default=None,type=str,help='Dynamics (ASE Dynamics class)') return parser # Notes on defaults: # 1 a.u. = 0.02419 fs, 100 steps of 10 aut = 24fs between snapshots def validate_args(args): default_args = make_parser().parse_args("") for arg in vars(args): if arg not in default_args: raise Exception(f"Unrecognised argument '{arg}'")
# # Handle Inputs # In[ ]: def get_parser(): qmdtraj = QMDTrajTask() return qmdtraj.make_parser() if __name__ == '__main__': # Set up NWChem by default from esteem.wrappers import nwchem qm_wrapper = nwchem.NWChemWrapper() qm_wrapper.nwchem_setup() # Parse command line arguments parser = make_parser() args = parser.parse_args() print(args) # Run main program main(args,qm_wrapper)