Source code for dpgen2.exploration.selector.conf_selector_frame

import copy
from collections import (
    Counter,
)
from pathlib import (
    Path,
)
from typing import (
    List,
    Optional,
    Tuple,
    Union,
)

import dpdata
import numpy as np
from dflow.python.opio import (
    HDF5Dataset,
)

from dpgen2.exploration.render import (
    TrajRender,
)
from dpgen2.exploration.report import (
    ExplorationReport,
)

from . import (
    ConfFilters,
    ConfSelector,
)


[docs] class ConfSelectorFrames(ConfSelector): """Select frames from trajectories as confs. Parameters: trust_level: TrustLevel The trust level conf_filter: ConfFilters The configuration filter """ def __init__( self, traj_render: TrajRender, report: ExplorationReport, max_numb_sel: Optional[int] = None, conf_filters: Optional[ConfFilters] = None, ): self.max_numb_sel = max_numb_sel self.conf_filters = conf_filters self.traj_render = traj_render self.report = report
[docs] def select( self, trajs: Union[List[Path], List[HDF5Dataset]], model_devis: Union[List[Path], List[HDF5Dataset]], type_map: Optional[List[str]] = None, optional_outputs: Optional[List[Path]] = None, ) -> Tuple[List[Path], ExplorationReport]: """Select configurations Parameters ---------- trajs : List[Path] A `list` of `Path` to trajectory files generated by LAMMPS model_devis : List[Path] A `list` of `Path` to model deviation files generated by LAMMPS. Format: each line has 7 numbers they are used as # frame_id md_v_max md_v_min md_v_mean md_f_max md_f_min md_f_mean where `md` stands for model deviation, v for virial and f for force type_map : List[str] The `type_map` of the systems optional_outputs : List[Path] Optional outputs of the exploration Returns ------- confs : List[Path] The selected confgurations, stored in a folder in deepmd/npy format, can be parsed as dpdata.MultiSystems. The `list` only has one item. report : ExplorationReport The exploration report recoding the status of the exploration. """ ntraj = len(trajs) assert ntraj == len(model_devis) md_model_devi = self.traj_render.get_model_devi(model_devis) self.report.clear() self.report.record(md_model_devi) id_cand_list = self.report.get_candidate_ids(self.max_numb_sel) ms = self.traj_render.get_confs( trajs, id_cand_list, type_map, self.conf_filters, optional_outputs, ) out_path = Path("confs") out_path.mkdir(exist_ok=True) ms.to_deepmd_npy(out_path) # type: ignore return [out_path], copy.deepcopy(self.report)