




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 SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       Tuple:



       """simple docstring"""

       A__       =    []
       A__       =    []
       A__       =    []

       for rt in rc.restypes:
              A__       =    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]						)
              A__       =    {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						)

       A__       =    torch.tensor(
           __lowerCAmelCase ,				dtype=torch.intaa ,				device=protein['''aatype'''].device ,				)
       A__       =    torch.tensor(
           __lowerCAmelCase ,				dtype=torch.intaa ,				device=protein['''aatype'''].device ,				)
       A__       =    torch.tensor(
           __lowerCAmelCase ,				dtype=torch.floataa ,				device=protein['''aatype'''].device ,				)
       A__       =    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
       A__       =    restype_atomaa_to_atomaa[protein_aatype]
       A__       =    restype_atomaa_mask[protein_aatype]

       A__       =    residx_atomaa_mask
       A__       =    residx_atomaa_to_atomaa.long()

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

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

       A__       =    restype_atomaa_mask[protein_aatype]
       A__       =    residx_atomaa_mask

       return protein







def SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       Dict:



       """simple docstring"""

       A__       =    tree_map(lambda lowercase_						: torch.tensor(__lowerCAmelCase ,				device=batch['''aatype'''].device						) ,				__lowerCAmelCase ,				np.ndarray						)
       A__       =    tensor_tree_map(lambda lowercase_						: np.array(__lowerCAmelCase						) ,				make_atomaa_masks(__lowerCAmelCase						)						)
       return out






'''simple docstring'''


import math






def        __lowerCAmelCase       (__lowerCAmelCase      ):
		return math.sqrt(__lowerCAmelCase      ) * math.sqrt(__lowerCAmelCase      ) == num






def        __lowerCAmelCase       (__lowerCAmelCase      ):
		_UpperCAmelCase						:				int	    =					0
		_UpperCAmelCase						:				Tuple	    =					n
		while left <= right:
				_UpperCAmelCase						:				int	    =					(left + right) // 2
				if mid**2 == n:
						return True
				elif mid**2 > n:
						_UpperCAmelCase						:				str	    =					mid - 1
				else:
						_UpperCAmelCase						:				List[str]	    =					mid + 1
		return False


if __name__ == "__main__":
						import doctest

						doctest.testmod()



