Source code for ai2_kit.tool.dpdata
from ai2_kit.feat.spectrum.viber import dpdata_read_cp2k_viber_data
from ai2_kit.core.util import ensure_dir, expand_globs, list_sample, SAMPLE_METHOD, slice_from_str
from ai2_kit.core.log import get_logger
from typing import Optional
from dpdata.data_type import Axis, DataType
import numpy as np
import dpdata
logger = get_logger(__name__)
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def register_data_types():
if getattr(dpdata, '__registed__', False):
return
DATA_TYPES = [
DataType("fparam", np.ndarray, (Axis.NFRAMES, -1), required=False), # type: ignore
DataType("aparam", np.ndarray, (Axis.NFRAMES, Axis.NATOMS, -1), required=False), # type: ignore
DataType("efield", np.ndarray, (Axis.NFRAMES, Axis.NATOMS, 3), required=False), # type: ignore
DataType("ext_efield", np.ndarray, (Axis.NFRAMES, 3), required=False), # type: ignore
DataType("atomic_dipole", np.ndarray, (Axis.NFRAMES, -1), required=False), # type: ignore
DataType("atomic_polarizability", np.ndarray, (Axis.NFRAMES, -1), required=False), # type: ignore
]
dpdata.System.register_data_type(*DATA_TYPES) # type: ignore
dpdata.LabeledSystem.register_data_type(*DATA_TYPES) # type: ignore
dpdata.__registed__ = True # type: ignore
register_data_types()
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class DpdataTool:
def __init__(self, verbose = False, systems: Optional[list] = None):
self._systems = [] if systems is None else systems
self._verbose = verbose
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def read(self, *file_path_or_glob: str, **kwargs):
"""
read data from multiple paths, support glob pattern
default format is deepmd/npy
:param file_path_or_glob: path or glob pattern to locate data path
:param fmt: format to read, default is deepmd/npy
:param label: default is True, use dpdata.LabeledSystem if True, else use dpdata.System
:param kwargs: arguments to pass to dpdata.System or dpdata.LabeledSystem
"""
systems = read(*file_path_or_glob, **kwargs)
self._systems.extend(systems)
return self
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def filter(self, lambda_expr: str):
"""
filter data with lambda expression
:param lambda_expr: lambda expression to filter data
"""
fn = eval(lambda_expr)
self._systems = [system for system in self._systems if fn(system.data)]
return self
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def slice(self, expr: str):
"""
slice systems by python slice expression, for example
`10:`, `:10`, `::2`, etc
:param start: start index
:param stop: stop index
:param step: step
"""
s = slice_from_str(expr)
self._systems = self._systems[s]
return self
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def sample(self, size: int, method: SAMPLE_METHOD='even', **kwargs):
"""
sample data
:param size: size of sample, if size is larger than data size, return all data
:param method: method to sample, can be 'even', 'random', 'truncate', default is 'even'
:param seed: seed for random sample, only used when method is 'random'
Note that by default the seed is length of input list,
if you want to generate different sample each time, you should set random seed manually
"""
self._systems = list_sample(self._systems, size, method, **kwargs)
return self
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def write(self, out_path: str, fmt='deepmd/npy', merge: bool = True):
"""
write data to specific path, support deepmd/npy, deepmd/raw, deepmd/hdf5 formats
:param out_path: path to write data
:param fmt: format to write, default is deepmd/npy
:param merge: if True, merge all data use dpdata.MultiSystems, else write data without merging
"""
ensure_dir(out_path)
if len(self._systems) == 0:
raise ValueError('No data to merge')
if merge:
systems = dpdata.MultiSystems(self._systems[0])
else:
systems = self._systems[0]
for system in self._systems[1:]:
systems.append(system)
if fmt == 'deepmd/npy':
systems.to_deepmd_npy(out_path) # type: ignore
elif fmt == 'deepmd/raw':
systems.to_deepmd_raw(out_path) # type: ignore
elif fmt == 'deepmd/hdf5':
systems.to_deepmd_hdf5(out_path) # type: ignore
else:
raise ValueError(f'Unknown fmt {fmt}')
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def set_fparam(self, fparam):
"""
Set fparam for all systems
:param fparam: fparam to set, should be a scalar or vector, e.g. 1.0 or [1.0, 2.0]
"""
for system in self._systems:
set_fparam(system, fparam)
return self
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def eval(self, dp_model: str):
"""
Use deepmd model to label energy, force and viral
:param dp_model: path to deepmd frozen model
"""
from deepmd.infer import DeepPot
systems = dpdata.System()
systems.extend(self._systems) # merge systems to one
pot = DeepPot(dp_model, auto_batch_size=True) # type: ignore
# remap atypes to pot's type
atom_names = systems.get_atom_names()
target_atom_names = pot.get_type_map()
mapping = {i: target_atom_names.index(name) for i, name in enumerate(atom_names)}
vectorized_mapping = np.vectorize(mapping.get)
atypes = vectorized_mapping(systems.data['atom_types'])
coords = systems.data['coords']
cells = None if systems.nopbc else systems.data['cells']
e, f, v = pot.eval(coords=coords, cells=cells, atom_types=atypes) # type: ignore
n_atoms = systems.get_natoms()
n_frames = systems.get_nframes()
e = e.reshape((n_frames,))
f = f.reshape((n_frames, n_atoms, 3))
v = v.reshape((n_frames, 3, 3))
data = {**systems.data, 'energies': e, 'forces': f, "virials": v}
# replace system files
self._systems = []
self._systems.extend(dpdata.LabeledSystem.from_dict({'data':data})) # type: ignore
return self
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def to_ase(self):
"""
Convert dpdata format to ase format, and use ase tool to handle
"""
from .ase import AseTool
atoms_list = []
for sys in self._systems:
atoms_list.extend(sys.to_ase_structure())
return AseTool(atoms_list=atoms_list)
def _verbose_log(self, msg, **kwargs):
if self._verbose:
logger.info(msg, **kwargs)
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def set_fparam(system, fparam):
nframes = system.get_nframes()
system.data['fparam'] = np.tile(fparam, (nframes, 1))
return system
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def read(*file_path_or_glob: str, **kwargs):
"""
read data from multiple paths, support glob pattern
default format is deepmd/npy
:param file_path_or_glob: path or glob pattern to locate data path
:param fmt: format to read, default is deepmd/npy
:param label: default is True, use dpdata.LabeledSystem if True, else use dpdata.System
:parse ignore_error: if True, ignore error when read data, default is False
:param kwargs: arguments to pass to dpdata.System or dpdata.LabeledSystem
"""
kwargs.setdefault('fmt', 'deepmd/npy')
ignore_error = kwargs.setdefault('ignore_error', False)
files = expand_globs(file_path_or_glob)
if len(files) == 0:
raise FileNotFoundError(f'No file found in {file_path_or_glob}')
systems = []
for file in files:
try:
system = _read(file, **kwargs)
if system is not None:
systems.extend(system)
except Exception:
logger.exception(f'Fail to process file {file}, ignore and continue')
if not ignore_error:
raise
return systems
def _read(data_path: str, **kwargs):
# pop custom arguments or else it will be passed to dpdata.System and raise error
fmt = kwargs.pop('fmt', 'deepmd/npy')
fparam = kwargs.pop('fparam', None)
label = kwargs.pop('label', True)
if fmt == 'cp2k/viber':
try:
system = dpdata_read_cp2k_viber_data(data_path, **kwargs)
except Exception:
logger.exception(f'Fail to read cp2k/viber from {data_path}, ignore and continue')
return None
else:
system = dpdata.LabeledSystem(data_path, fmt=fmt, **kwargs) if label else dpdata.System(data_path, fmt=fmt, **kwargs)
if fparam is not None:
set_fparam(system, fparam)
return system