
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 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   Dict[str, torch.Tensor]:
       lowercase							:					List[str]	     =				[]
       lowercase							:					List[str]	     =				[]
       lowercase							:					Any	     =				[]

       for rt in rc.restypes:
              lowercase							:					int	     =				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							:					List[str]	     =				{name: i for i, name in enumerate(SCREAMING_SNAKE_CASE__    )}
              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							:					Optional[Any]	     =				torch.tensor(
           SCREAMING_SNAKE_CASE__ ,     dtype=torch.intaa ,     device=protein["""aatype"""].device ,     )
       lowercase							:					Tuple	     =				torch.tensor(
           SCREAMING_SNAKE_CASE__ ,     dtype=torch.intaa ,     device=protein["""aatype"""].device ,     )
       lowercase							:					Dict	     =				torch.tensor(
           SCREAMING_SNAKE_CASE__ ,     dtype=torch.floataa ,     device=protein["""aatype"""].device ,     )
       lowercase							:					List[Any]	     =				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							:					List[str]	     =				restype_atomaa_to_atomaa[protein_aatype]
       lowercase							:					Any	     =				restype_atomaa_mask[protein_aatype]

       lowercase							:					Dict	     =				residx_atomaa_mask
       lowercase							:					int	     =				residx_atomaa_to_atomaa.long()

       # create the gather indices for mapping back
       lowercase							:					Any	     =				restype_atomaa_to_atomaa[protein_aatype]
       lowercase							:					Optional[int]	     =				residx_atomaa_to_atomaa.long()

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

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

       return protein







def 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   Dict[str, np.ndarray]:
       lowercase							:					Optional[Any]	     =				tree_map(lambda SCREAMING_SNAKE_CASE__    : torch.tensor(SCREAMING_SNAKE_CASE__ ,     device=batch["""aatype"""].device    ) ,     SCREAMING_SNAKE_CASE__ ,     np.ndarray    )
       lowercase							:					Any	     =				tensor_tree_map(lambda SCREAMING_SNAKE_CASE__    : np.array(SCREAMING_SNAKE_CASE__    ) ,     make_atomaa_masks(SCREAMING_SNAKE_CASE__    )    )
       return out


def 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   int:
       assert (
           isinstance(SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    ) and number_of_steps > 0
       ), f"number_of_steps needs to be positive integer, your input {number_of_steps}"
       if number_of_steps == 1:
              return 1
       lowercase     ,      lowercase							:					Tuple	     =				1, 1
       for _ in range(number_of_steps - 1    ):
              lowercase     ,      lowercase							:					str	     =				current + previous, current
       return current


if __name__ == "__main__":
  import doctest

  doctest.testmod()
