# Path: flare/struc.py
# class Structure:
# class StructureSource(object):
# class ForceSource(object):
# class Trajectory(StructureSource, ForceSource):
#     def __init__(
#         self,
#         cell: "ndarray",
#         species: Union[List[str], List[int]],
#         positions: "ndarray",
#         mass_dict: dict = None,
#         prev_positions: "ndarray" = None,
#         species_labels: List[str] = None,
#         forces=None,
#         stds=None,
#         energy: float = None,
#     ):
#     def positions(self):
#     def wrapped_positions(self):
#     def positions(self, position_array):
#     def cell(self):
#     def vec1(self):
#     def vec2(self):
#     def vec3(self):
#     def cell_transpose(self):
#     def cell_transpose_inverse(self):
#     def cell_dot(self):
#     def cell_dot_inverse(self):
#     def cell(self, cell_array):
#     def get_cell_dot(cell_array):
#     def raw_to_relative(
#         positions: "ndarray", cell_transpose: "ndarray", cell_dot_inverse: "ndarray"
#     ) -> "ndarray":
#     def relative_to_raw(
#         relative_positions: "ndarray",
#         cell_transpose_inverse: "ndarray",
#         cell_dot: "ndarray",
#     ) -> "ndarray":
#     def wrap_positions(self) -> "ndarray":
#     def indices_of_specie(self, specie: Union[int, str]) -> List[int]:
#     def __str__(self) -> str:
#     def __len__(self) -> int:
#     def as_dict(self) -> dict:
#     def as_str(self) -> str:
#     def from_dict(dictionary: dict) -> "flare.struc.Structure":
#     def from_ase_atoms(atoms: "ase.Atoms", cell=None) -> "flare.struc.Structure":
#     def to_ase_atoms(self) -> "ase.Atoms":
#     def to_pmg_structure(self):
#     def from_pmg_structure(structure: "pymatgen Structure") -> "flare Structure":
#     def is_valid(self, tolerance: float = 0.5) -> bool:
#     def to_xyz(
#         self,
#         extended_xyz: bool = True,
#         print_stds: bool = False,
#         print_forces: bool = False,
#         print_max_stds: bool = False,
#         print_energies: bool = False,
#         predict_energy=None,
#         dft_forces=None,
#         dft_energy=None,
#         target_atoms=None,
#         timestep=-1,
#         write_file: str = "",
#         append: bool = False,
#     ) -> str:
#     def from_file(
#         file_name: str, format: str = "", as_trajectory: bool = False
#     ) -> Union["flare.struc.Structure", List["flare.struc.Structure"]]:
#     def __eq__(self, other):
#     def __init__(self):
#     def get_next_structure(self) -> Structure:
#     def write_file(self):
#     def __init__(self):
#     def get_next_force(self, *args, **kwargs) -> "np.ndarray":
#     def pre_force(self, *args, **kwargs):
#     def __init__(
#         self, frames: List[Structure] = None, iterate_strategy: Union[int, str] = 1
#     ):
#     def get_next_structure(self) -> Union[Structure, None]:
#     def cur_frame(self):
#     def cur_forces(self):
#     def get_next_force(self, index: int = -1) -> "np.ndarray":
#     def __getitem__(self, item):
#     def __len__(self):
#     def __next__(self):
#     def __iter__(self):
#     def append(self, frame: Structure):
# def get_unique_species(species: List[Any]) -> (List, List[int]):


import os
import time
import numpy as np
from subprocess import call
from flare import struc
from typing import List
    for i in range(positions_index, positions_index + nat):
        line_string = lines[i].strip().split()
        species.append(line_string[0])

        pos_string = " ".join(line_string[1:4])

        positions.append(np.fromstring(pos_string, sep=" "))
    # Check position IO
    assert positions != [], "Positions failed to load"
    positions = np.array(positions)

    # see conversions.nb for conversion from amu to md units
    massconvert = 0.000103642695727
    masses = {}
    for i in range(species_index, species_index + len(set(species))):
        # Expects lines of format like: H 1.0 H_pseudo_name.ext
        line = lines[i].strip().split()
        masses[line[0]] = float(line[1]) * massconvert

    return positions, species, cell, masses


def dft_input_to_structure(dft_input: str):
    """Parses a qe input and returns the atoms in the
    file as a Structure object

    :param dft_input: QE Input file to parse
    :return: class Structure
    """
    positions, species, cell, masses = parse_dft_input(dft_input)

# Path: flare/struc.py
# class Structure:
# class StructureSource(object):
# class ForceSource(object):
# class Trajectory(StructureSource, ForceSource):
#     def __init__(
#         self,
#         cell: "ndarray",
#         species: Union[List[str], List[int]],
#         positions: "ndarray",
#         mass_dict: dict = None,
#         prev_positions: "ndarray" = None,
#         species_labels: List[str] = None,
#         forces=None,
#         stds=None,
#         energy: float = None,
#     ):
#     def positions(self):
#     def wrapped_positions(self):
#     def positions(self, position_array):
#     def cell(self):
#     def vec1(self):
#     def vec2(self):
#     def vec3(self):
#     def cell_transpose(self):
#     def cell_transpose_inverse(self):
#     def cell_dot(self):
#     def cell_dot_inverse(self):
#     def cell(self, cell_array):
#     def get_cell_dot(cell_array):
#     def raw_to_relative(
#         positions: "ndarray", cell_transpose: "ndarray", cell_dot_inverse: "ndarray"
#     ) -> "ndarray":
#     def relative_to_raw(
#         relative_positions: "ndarray",
#         cell_transpose_inverse: "ndarray",
#         cell_dot: "ndarray",
#     ) -> "ndarray":
#     def wrap_positions(self) -> "ndarray":
#     def indices_of_specie(self, specie: Union[int, str]) -> List[int]:
#     def __str__(self) -> str:
#     def __len__(self) -> int:
#     def as_dict(self) -> dict:
#     def as_str(self) -> str:
#     def from_dict(dictionary: dict) -> "flare.struc.Structure":
#     def from_ase_atoms(atoms: "ase.Atoms", cell=None) -> "flare.struc.Structure":
#     def to_ase_atoms(self) -> "ase.Atoms":
#     def to_pmg_structure(self):
#     def from_pmg_structure(structure: "pymatgen Structure") -> "flare Structure":
#     def is_valid(self, tolerance: float = 0.5) -> bool:
#     def to_xyz(
#         self,
#         extended_xyz: bool = True,
#         print_stds: bool = False,
#         print_forces: bool = False,
#         print_max_stds: bool = False,
#         print_energies: bool = False,
#         predict_energy=None,
#         dft_forces=None,
#         dft_energy=None,
#         target_atoms=None,
#         timestep=-1,
#         write_file: str = "",
#         append: bool = False,
#     ) -> str:
#     def from_file(
#         file_name: str, format: str = "", as_trajectory: bool = False
#     ) -> Union["flare.struc.Structure", List["flare.struc.Structure"]]:
#     def __eq__(self, other):
#     def __init__(self):
#     def get_next_structure(self) -> Structure:
#     def write_file(self):
#     def __init__(self):
#     def get_next_force(self, *args, **kwargs) -> "np.ndarray":
#     def pre_force(self, *args, **kwargs):
#     def __init__(
#         self, frames: List[Structure] = None, iterate_strategy: Union[int, str] = 1
#     ):
#     def get_next_structure(self) -> Union[Structure, None]:
#     def cur_frame(self):
#     def cur_forces(self):
#     def get_next_force(self, index: int = -1) -> "np.ndarray":
#     def __getitem__(self, item):
#     def __len__(self):
#     def __next__(self):
#     def __iter__(self):
#     def append(self, frame: Structure):
# def get_unique_species(species: List[Any]) -> (List, List[int]):


# Path: flare/dft_interface/qe_util.py
import os
import time
import numpy as np
from subprocess import call
from flare import struc
from typing import List

    for i in range(positions_index, positions_index + nat):
        line_string = lines[i].strip().split()
        species.append(line_string[0])

        pos_string = " ".join(line_string[1:4])

        positions.append(np.fromstring(pos_string, sep=" "))
    # Check position IO
    assert positions != [], "Positions failed to load"
    positions = np.array(positions)

    # see conversions.nb for conversion from amu to md units
    massconvert = 0.000103642695727
    masses = {}
    for i in range(species_index, species_index + len(set(species))):
        # Expects lines of format like: H 1.0 H_pseudo_name.ext
        line = lines[i].strip().split()
        masses[line[0]] = float(line[1]) * massconvert

    return positions, species, cell, masses


def dft_input_to_structure(dft_input: str):
    """Parses a qe input and returns the atoms in the
    file as a Structure object

    :param dft_input: QE Input file to parse
    :return: class Structure
    """
    positions, species, cell, masses = parse_dft_input(dft_input)

    _, coded_species = struc.get_unique_species(species)