dpdata is a python package for manipulating DeePMD-kit, VASP, LAMMPS data formats. dpdata only works with python 3.x.
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
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
- Load data from vasp or lammps or deepmd-kit data files.
- Manipulate data
- Dump data to in a desired format
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' |
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')
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 |
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
.
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.
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)
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')
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)
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 ensureobabel
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 useobabel 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)
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.
One can follow a simple example to add their own format by creating and installing plugins. It's crirical to add the Format class to entry_points['dpdata.plugins']
in setup.py
:
entry_points={
'dpdata.plugins': [
'random=dpdata_random:RandomFormat'
]
},