


from __future__ import annotations

import typing
from collections.abc import Iterable

import numpy as np

__lowerCAmelCase	: int  				=typing.Union[Iterable[float], Iterable[int], np.ndarray]  # noqa: UP007
__lowerCAmelCase	: str  				=typing.Union[np.floataa, int, float]  # noqa: UP007


def        _UpperCamelCase							(      lowercase__    ,       lowercase__      ):
						return np.sqrt(np.sum((np.asarray(_lowerCamelCase      ) - np.asarray(_lowerCamelCase      )) ** 2      )      )


def        _UpperCamelCase							(      lowercase__    ,       lowercase__      ):
						return sum((va - va) ** 2 for va, va in zip(_lowerCamelCase    ,       _lowerCamelCase      )      ) ** (1 / 2)


if __name__ == "__main__":


						def        _UpperCamelCase							(      ):
												from timeit import timeit

												print('''Without Numpy'''      )
												print(
												    timeit(
												        '''euclidean_distance_no_np([1, 2, 3], [4, 5, 6])'''    ,       number=10000    ,       globals=globals()    ,       )      )
												print('''With Numpy'''      )
												print(
												    timeit(
												        '''euclidean_distance([1, 2, 3], [4, 5, 6])'''    ,       number=10000    ,       globals=globals()    ,       )      )
						benchmark()

from typing import Dict

import numpy as np
import torch

from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map

def 			lowercase_				(			_lowerCamelCase							:       Dict[str, torch.Tensor]):
    lowercase__ :   Any    					=				[]
    lowercase__ :   Optional[int]    					=				[]
    lowercase__ :   Tuple    					=				[]

    for rt in rc.restypes:
        lowercase__ :   Dict    					=				rc.restype_name_to_atomaa_names[rc.restype_atoa[rt]]
        restype_atomaa_to_atomaa_list.append([(rc.atom_order[name] if name else 0) for name in atom_names])
        lowercase__ :   str    					=				{name: i for i, name in enumerate(_lowerCamelCase)}
        restype_atomaa_to_atomaa_list.append(
            [(atom_name_to_idxaa[name] if name in atom_name_to_idxaa else 0) for name in rc.atom_types])

        restype_atomaa_mask_list.append([(1.0 if name else 0.0) for name in atom_names])

    # Add dummy mapping for restype 'UNK'
    restype_atomaa_to_atomaa_list.append([0] * 14)
    restype_atomaa_to_atomaa_list.append([0] * 37)
    restype_atomaa_mask_list.append([0.0] * 14)

    lowercase__ :   Union[str, Any]    					=				torch.tensor(
        _lowerCamelCase		,	dtype=torch.intaa		,	device=protein["aatype"].device		,	)
    lowercase__ :   str    					=				torch.tensor(
        _lowerCamelCase		,	dtype=torch.intaa		,	device=protein["aatype"].device		,	)
    lowercase__ :   List[str]    					=				torch.tensor(
        _lowerCamelCase		,	dtype=torch.floataa		,	device=protein["aatype"].device		,	)
    lowercase__ :   str    					=				protein["aatype"].to(torch.long)

    # create the mapping for (residx, atom14) --> atom37, i.e. an array
    # with shape (num_res, 14) containing the atom37 indices for this protein
    lowercase__ :   Dict    					=				restype_atomaa_to_atomaa[protein_aatype]
    lowercase__ :   str    					=				restype_atomaa_mask[protein_aatype]

    lowercase__ :   List[Any]    					=				residx_atomaa_mask
    lowercase__ :   Optional[Any]    					=				residx_atomaa_to_atomaa.long()

    # create the gather indices for mapping back
    lowercase__ :   str    					=				restype_atomaa_to_atomaa[protein_aatype]
    lowercase__ :   str    					=				residx_atomaa_to_atomaa.long()

    # create the corresponding mask
    lowercase__ :   Optional[Any]    					=				torch.zeros([21, 37]		,	dtype=torch.floataa		,	device=protein["aatype"].device)
    for restype, restype_letter in enumerate(rc.restypes):
        lowercase__ :   Tuple    					=				rc.restype_atoa[restype_letter]
        lowercase__ :   List[Any]    					=				rc.residue_atoms[restype_name]
        for atom_name in atom_names:
            lowercase__ :   Optional[int]    					=				rc.atom_order[atom_name]
            lowercase__ :   Tuple    					=				1

    lowercase__ :   Dict    					=				restype_atomaa_mask[protein_aatype]
    lowercase__ :   Any    					=				residx_atomaa_mask

    return protein

def 			lowercase_				(			_lowerCamelCase							:       Dict[str, torch.Tensor]):
    lowercase__ :   Tuple    					=				tree_map(lambda _lowerCamelCase: torch.tensor(_lowerCamelCase		,	device=batch["aatype"].device)		,	_lowerCamelCase		,	np.ndarray)
    lowercase__ :   List[str]    					=				tensor_tree_map(lambda _lowerCamelCase: np.array(_lowerCamelCase)		,	make_atomaa_masks(_lowerCamelCase))
    return out



