dpdata is a python package for manipulating data formats of software in computational science, including DeePMD-kit, VASP, LAMMPS, GROMACS, Gaussian. dpdata only works with python 3.x.

Installation

One can download the source code of dpdata by

git clone https://github.com/deepmodeling/dpdata.git dpdata

then use setup.py to install the module

cd dpdata
python setup.py install

dpdata can also by install via pip

pip3 install dpdata

Quick start

This section gives some examples on how dpdata works. Firstly one needs to import the module in a python 3.x compatible code.

import dpdata

The typicall workflow of dpdata is

1. Load data from vasp or lammps or deepmd-kit data files.
2. Manipulate data
3. Dump data to in a desired format

Load data

d_poscar = dpdata.System('POSCAR', fmt = 'vasp/poscar')

or let dpdata infer the format (vasp/poscar) of the file from the file name extension

d_poscar = dpdata.System('my.POSCAR')

The number of atoms, atom types, coordinates are loaded from the POSCAR and stored to a data System called d_poscar. A data System (a concept used by deepmd-kit) contains frames that has the same number of atoms of the same type. The order of the atoms should be consistent among the frames in one System. It is noted that POSCAR only contains one frame. If the multiple frames stored in, for example, a OUTCAR is wanted,

d_outcar = dpdata.LabeledSystem('OUTCAR')

The labels provided in the OUTCAR, i.e. energies, forces and virials (if any), are loaded by LabeledSystem. It is noted that the forces of atoms are always assumed to exist. LabeledSystem is a derived class of System.

The System or LabeledSystem can be constructed from the following file formats with the format key in the table passed to argument fmt:

Software	format	multi frames	labeled	class	format key
vasp	poscar	False	False	System	'vasp/poscar'
vasp	outcar	True	True	LabeledSystem	'vasp/outcar'
vasp	xml	True	True	LabeledSystem	'vasp/xml'
lammps	lmp	False	False	System	'lammps/lmp'
lammps	dump	True	False	System	'lammps/dump'
deepmd	raw	True	False	System	'deepmd/raw'
deepmd	npy	True	False	System	'deepmd/npy'
deepmd	raw	True	True	LabeledSystem	'deepmd/raw'
deepmd	npy	True	True	LabeledSystem	'deepmd/npy'
gaussian	log	False	True	LabeledSystem	'gaussian/log'
gaussian	log	True	True	LabeledSystem	'gaussian/md'
siesta	output	False	True	LabeledSystem	'siesta/output'
siesta	aimd_output	True	True	LabeledSystem	'siesta/aimd_output'
cp2k	output	False	True	LabeledSystem	'cp2k/output'
cp2k	aimd_output	True	True	LabeledSystem	'cp2k/aimd_output'
QE	log	False	True	LabeledSystem	'qe/pw/scf'
QE	log	True	False	System	'qe/cp/traj'
QE	log	True	True	LabeledSystem	'qe/cp/traj'
Fhi-aims	output	True	True	LabeledSystem	'fhi_aims/md'
Fhi-aims	output	False	True	LabeledSystem	'fhi_aims/scf'
quip/gap	xyz	True	True	MultiSystems	'quip/gap/xyz'
PWmat	atom.config	False	False	System	'pwmat/atom.config'
PWmat	movement	True	True	LabeledSystem	'pwmat/movement'
PWmat	OUT.MLMD	True	True	LabeledSystem	'pwmat/out.mlmd'
Amber	multi	True	True	LabeledSystem	'amber/md'
Amber/sqm	sqm.out	False	False	System	'sqm/out'
Gromacs	gro	True	False	System	'gromacs/gro'
ABACUS	STRU	False	True	LabeledSystem	'abacus/scf'
ABACUS	cif	True	True	LabeledSystem	'abacus/md'

The Class dpdata.MultiSystems can read data from a dir which may contains many files of different systems, or from single xyz file which contains different systems.

Use dpdata.MultiSystems.from_dir to read from a directory, dpdata.MultiSystems will walk in the directory Recursively and find all file with specific file_name. Supports all the file formats that dpdata.LabeledSystem supports.

Use dpdata.MultiSystems.from_file to read from single file. Now only support quip/gap/xyz format file.

For example, for quip/gap xyz files, single .xyz file may contain many different configurations with different atom numbers and atom type.

The following commands relating to Class dpdata.MultiSystems may be useful.

# load data

xyz_multi_systems = dpdata.MultiSystems.from_file(file_name='tests/xyz/xyz_unittest.xyz',fmt='quip/gap/xyz')
vasp_multi_systems = dpdata.MultiSystems.from_dir(dir_name='./mgal_outcar', file_name='OUTCAR', fmt='vasp/outcar')

# use wildcard
vasp_multi_systems = dpdata.MultiSystems.from_dir(dir_name='./mgal_outcar', file_name='*OUTCAR', fmt='vasp/outcar')

# print the multi_system infomation
print(xyz_multi_systems)
print(xyz_multi_systems.systems) # return a dictionaries

# print the system infomation
print(xyz_multi_systems.systems['B1C9'].data)

# dump a system's data to ./my_work_dir/B1C9_raw folder
xyz_multi_systems.systems['B1C9'].to_deepmd_raw('./my_work_dir/B1C9_raw')

# dump all systems
xyz_multi_systems.to_deepmd_raw('./my_deepmd_data/')

You may also use the following code to parse muti-system:

from dpdata import LabeledSystem,MultiSystems
from glob import glob
"""
process multi systems
"""
fs=glob('./*/OUTCAR')  # remeber to change here !!!
ms=MultiSystems()
for f in fs:
    try:
        ls=LabeledSystem(f)
    except:
        print(f)
    if len(ls)>0:
        ms.append(ls)

ms.to_deepmd_raw('deepmd')
ms.to_deepmd_npy('deepmd')

Access data

These properties stored in System and LabeledSystem can be accessed by operator [] with the key of the property supplied, for example

coords = d_outcar['coords']

Available properties are (nframe: number of frames in the system, natoms: total number of atoms in the system)

key	type	dimension	are labels	description
'atom_names'	list of str	ntypes	False	The name of each atom type
'atom_numbs'	list of int	ntypes	False	The number of atoms of each atom type
'atom_types'	np.ndarray	natoms	False	Array assigning type to each atom
'cells'	np.ndarray	nframes x 3 x 3	False	The cell tensor of each frame
'coords'	np.ndarray	nframes x natoms x 3	False	The atom coordinates
'energies'	np.ndarray	nframes	True	The frame energies
'forces'	np.ndarray	nframes x natoms x 3	True	The atom forces
'virials'	np.ndarray	nframes x 3 x 3	True	The virial tensor of each frame

Dump data

The data stored in System or LabeledSystem can be dumped in 'lammps/lmp' or 'vasp/poscar' format, for example:

d_outcar.to('lammps/lmp', 'conf.lmp', frame_idx=0)

The first frames of d_outcar will be dumped to 'conf.lmp'

d_outcar.to('vasp/poscar', 'POSCAR', frame_idx=-1)

The last frames of d_outcar will be dumped to 'POSCAR'.

The data stored in LabeledSystem can be dumped to deepmd-kit raw format, for example

d_outcar.to('deepmd/raw', 'dpmd_raw')

Or a simpler command:

dpdata.LabeledSystem('OUTCAR').to('deepmd/raw', 'dpmd_raw')

Frame selection can be implemented by

dpdata.LabeledSystem('OUTCAR').sub_system([0,-1]).to('deepmd/raw', 'dpmd_raw')

by which only the first and last frames are dumped to dpmd_raw.

replicate

dpdata will create a super cell of the current atom configuration.

dpdata.System('./POSCAR').replicate((1,2,3,) )

tuple(1,2,3) means don't copy atom configuration in x direction, make 2 copys in y direction, make 3 copys in z direction.

perturb

By the following example, each frame of the original system (dpdata.System('./POSCAR')) is perturbed to generate three new frames. For each frame, the cell is perturbed by 5% and the atom positions are perturbed by 0.6 Angstrom. atom_pert_style indicates that the perturbation to the atom positions is subject to normal distribution. Other available options to atom_pert_style areuniform (uniform in a ball), and const (uniform on a sphere).

perturbed_system = dpdata.System('./POSCAR').perturb(pert_num=3, 
    cell_pert_fraction=0.05, 
    atom_pert_distance=0.6, 
    atom_pert_style='normal')
print(perturbed_system.data)

replace

By the following example, Random 8 Hf atoms in the system will be replaced by Zr atoms with the atom postion unchanged.

s=dpdata.System('tests/poscars/POSCAR.P42nmc',fmt='vasp/poscar')
s.replace('Hf', 'Zr', 8)
s.to_vasp_poscar('POSCAR.P42nmc.replace')

BondOrderSystem

A new class BondOrderSystem which inherits from class System is introduced in dpdata. This new class contains information of chemical bonds and formal charges (stored in BondOrderSystem.data['bonds'], BondOrderSystem.data['formal_charges']). Now BondOrderSystem can only read from .mol/.sdf formats, because of its dependency on rdkit (which means rdkit must be installed if you want to use this function). Other formats, such as pdb, must be converted to .mol/.sdf format (maybe with software like open babel).

import dpdata
system_1 = dpdata.BondOrderSystem("tests/bond_order/CH3OH.mol", fmt="mol") # read from .mol file
system_2 = dpdata.BondOrderSystem("tests/bond_order/methane.sdf", fmt="sdf") # read from .sdf file

In sdf file, all molecules must be of the same topology (i.e. conformers of the same molecular configuration). BondOrderSystem also supports initialize from a rdkit.Chem.rdchem.Mol object directly.

from rdkit import Chem
from rdkit.Chem import AllChem
import dpdata

mol = Chem.MolFromSmiles("CC")
mol = Chem.AddHs(mol)
AllChem.EmbedMultipleConfs(mol, 10)
system = dpdata.BondOrderSystem(rdkit_mol=mol)

Bond Order Assignment

The BondOrderSystem implements a more robust sanitize procedure for rdkit Mol, as defined in dpdata.rdkit.santizie.Sanitizer. This class defines 3 level of sanitization process by: low, medium and high. (default is medium).

• low: use rdkit.Chem.SanitizeMol() function to sanitize molecule.
• medium: before using rdkit, the programm will first assign formal charge of each atom to avoid inappropriate valence exceptions. However, this mode requires the rightness of the bond order information in the given molecule.
• high: the program will try to fix inappropriate bond orders in aromatic hetreocycles, phosphate, sulfate, carboxyl, nitro, nitrine, guanidine groups. If this procedure fails to sanitize the given molecule, the program will then try to call obabel to pre-process the mol and repeat the sanitization procedure. That is to say, if you wan't to use this level of sanitization, please ensure obabel is installed in the environment. According to our test, our sanitization procedure can successfully read 4852 small molecules in the PDBBind-refined-set. It is necessary to point out that the in the molecule file (mol/sdf), the number of explicit hydrogens has to be correct. Thus, we recommend to use obabel xxx -O xxx -h to pre-process the file. The reason why we do not implement this hydrogen-adding procedure in dpdata is that we can not ensure its correctness.

import dpdata
    
for sdf_file in glob.glob("bond_order/refined-set-ligands/obabel/*sdf"):
    syst = dpdata.BondOrderSystem(sdf_file, sanitize_level='high', verbose=False)

Formal Charge Assignment

BondOrderSystem implement a method to assign formal charge for each atom based on the 8-electron rule (see below). Note that it only supports common elements in bio-system: B,C,N,O,P,S,As

import dpdata

syst = dpdata.BondOrderSystem("tests/bond_order/CH3NH3+.mol", fmt='mol')
print(syst.get_formal_charges()) # return the formal charge on each atom
print(syst.get_charge()) # return the total charge of the system

If a valence of 3 is detected on carbon, the formal charge will be assigned to -1. Because for most cases (in alkynyl anion, isonitrile, cyclopentadienyl anion), the formal charge on 3-valence carbon is -1, and this is also consisent with the 8-electron rule.

Plugins

One can follow a simple example to add their own format by creating and installing plugins. It's critical to add the Format class to entry_points['dpdata.plugins'] in setup.py:

    entry_points={
        'dpdata.plugins': [
            'random=dpdata_random:RandomFormat'
        ]
    },