
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple

import numpy as np

from . import residue_constants


lowercase__	:List[str]										=					Mapping[str, np.ndarray]
lowercase__	:Optional[int]										=					Mapping[str, Any]  # Is a nested dict.
lowercase__	:Any										=					0.01







@dataclasses.dataclass(frozen=SCREAMING_SNAKE_CASE__	)
class        lowercase	:
       lowercase_ : np.ndarray  # [num_res, num_atom_type, 3]

       # Amino-acid type for each residue represented as an integer between 0 and
       # 20, where 20 is 'X'.
       lowercase_ : np.ndarray  # [num_res]

       # Binary float mask to indicate presence of a particular atom. 1.0 if an atom
       # is present and 0.0 if not. This should be used for loss masking.
       lowercase_ : np.ndarray  # [num_res, num_atom_type]

       # Residue index as used in PDB. It is not necessarily continuous or 0-indexed.
       lowercase_ : np.ndarray  # [num_res]

       # B-factors, or temperature factors, of each residue (in sq. angstroms units),
       # representing the displacement of the residue from its ground truth mean
       # value.
       lowercase_ : np.ndarray  # [num_res, num_atom_type]

       # Chain indices for multi-chain predictions
       lowercase_ : Optional[np.ndarray]       =None

       # Optional remark about the protein. Included as a comment in output PDB
       # files
       lowercase_ : Optional[str]       =None

       # Templates used to generate this protein (prediction-only)
       lowercase_ : Optional[Sequence[str]]       =None

       # Chain corresponding to each parent
       lowercase_ : Optional[Sequence[int]]       =None



def  UpperCamelCase					(							lowerCAmelCase__	):
     '''simple docstring'''
     lowercase					=		R'''(\[[A-Z]+\]\n)'''
     lowercase					=		[tag.strip() for tag in re.split(_SCREAMING_SNAKE_CASE				,    _SCREAMING_SNAKE_CASE	) if len(_SCREAMING_SNAKE_CASE	) > 0]
     lowercase					=		zip(tags[0::2]				,    [l.split('''\n'''	) for l in tags[1::2]]	)

     lowercase					=		['''N''', '''CA''', '''C''']
     lowercase					=		None
     lowercase					=		None
     lowercase					=		None
     for g in groups:
          if "[PRIMARY]" == g[0]:
               lowercase					=		g[1][0].strip()
               for i in range(len(_SCREAMING_SNAKE_CASE	)	):
                    if seq[i] not in residue_constants.restypes:
                         lowercase					=		'''X'''  # FIXME: strings are immutable
               lowercase					=		np.array(
                   [residue_constants.restype_order.get(_SCREAMING_SNAKE_CASE				,    residue_constants.restype_num	) for res_symbol in seq]	)
          elif "[TERTIARY]" == g[0]:
               lowercase					=		[]
               for axis in range(3	):
                    tertiary.append(list(map(_SCREAMING_SNAKE_CASE				,    g[1][axis].split()	)	)	)
               lowercase					=		np.array(_SCREAMING_SNAKE_CASE	)
               lowercase					=		np.zeros((len(tertiary[0]	) // 3, residue_constants.atom_type_num, 3)	).astype(np.floataa	)
               for i, atom in enumerate(_SCREAMING_SNAKE_CASE	):
                    lowercase					=		np.transpose(tertiary_np[:, i::3]	)
               atom_positions *= PICO_TO_ANGSTROM
          elif "[MASK]" == g[0]:
               lowercase					=		np.array(list(map({'''-''': 0, '''+''': 1}.get				,    g[1][0].strip()	)	)	)
               lowercase					=		np.zeros(
                   (
                       len(_SCREAMING_SNAKE_CASE	),
                       residue_constants.atom_type_num,
                   )	).astype(np.floataa	)
               for i, atom in enumerate(_SCREAMING_SNAKE_CASE	):
                    lowercase					=		1
               atom_mask *= mask[..., None]

     assert aatype is not None

     return Protein(
         atom_positions=_SCREAMING_SNAKE_CASE				,    atom_mask=_SCREAMING_SNAKE_CASE				,    aatype=_SCREAMING_SNAKE_CASE				,    residue_index=np.arange(len(_SCREAMING_SNAKE_CASE	)	)				,    b_factors=_SCREAMING_SNAKE_CASE				,    )



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__ = 0	):
     '''simple docstring'''
     lowercase					=		[]

     lowercase					=		prot.remark
     if remark is not None:
          pdb_headers.append(f'REMARK {remark}'	)

     lowercase					=		prot.parents
     lowercase					=		prot.parents_chain_index
     if parents is not None and parents_chain_index is not None:
          lowercase					=		[p for i, p in zip(_SCREAMING_SNAKE_CASE				,    _SCREAMING_SNAKE_CASE	) if i == chain_id]

     if parents is None or len(_SCREAMING_SNAKE_CASE	) == 0:
          lowercase					=		['''N/A''']

     pdb_headers.append(f'PARENT {" ".join(_SCREAMING_SNAKE_CASE	)}'	)

     return pdb_headers



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__	):
     '''simple docstring'''
     lowercase					=		[]
     lowercase					=		pdb_str.split('''\n'''	)

     lowercase					=		prot.remark
     if remark is not None:
          out_pdb_lines.append(f'REMARK {remark}'	)

     lowercase					=		42
     if prot.parents is not None and len(prot.parents	) > 0:
          lowercase					=		[]
          if prot.parents_chain_index is not None:
               lowercase					=		{}
               for p, i in zip(prot.parents				,    prot.parents_chain_index	):
                    parent_dict.setdefault(str(_SCREAMING_SNAKE_CASE	)				,    []	)
                    parent_dict[str(_SCREAMING_SNAKE_CASE	)].append(_SCREAMING_SNAKE_CASE	)

               lowercase					=		max([int(_SCREAMING_SNAKE_CASE	) for chain_idx in parent_dict]	)
               for i in range(max_idx + 1	):
                    lowercase					=		parent_dict.get(str(_SCREAMING_SNAKE_CASE	)				,    ['''N/A''']	)
                    parents_per_chain.append(_SCREAMING_SNAKE_CASE	)
          else:
               parents_per_chain.append(list(prot.parents	)	)
     else:
          lowercase					=		[['''N/A''']]

     def make_parent_line(lowerCAmelCase__	) -> str:
          return f'PARENT {" ".join(_SCREAMING_SNAKE_CASE	)}'

     out_pdb_lines.append(make_parent_line(parents_per_chain[0]	)	)

     lowercase					=		0
     for i, l in enumerate(_SCREAMING_SNAKE_CASE	):
          if "PARENT" not in l and "REMARK" not in l:
               out_pdb_lines.append(_SCREAMING_SNAKE_CASE	)
          if "TER" in l and "END" not in lines[i + 1]:
               chain_counter += 1
               if not chain_counter >= len(_SCREAMING_SNAKE_CASE	):
                    lowercase					=		parents_per_chain[chain_counter]
               else:
                    lowercase					=		['''N/A''']

               out_pdb_lines.append(make_parent_line(_SCREAMING_SNAKE_CASE	)	)

     return "\n".join(_SCREAMING_SNAKE_CASE	)



def  UpperCamelCase					(							lowerCAmelCase__	):
     '''simple docstring'''
     lowercase					=		residue_constants.restypes + ['''X''']

     def res_atoa(lowerCAmelCase__	) -> str:
          return residue_constants.restype_atoa.get(restypes[r]				,    '''UNK'''	)

     lowercase					=		residue_constants.atom_types

     lowercase					=		[]

     lowercase					=		prot.atom_mask
     lowercase					=		prot.aatype
     lowercase					=		prot.atom_positions
     lowercase					=		prot.residue_index.astype(np.intaa	)
     lowercase					=		prot.b_factors
     lowercase					=		prot.chain_index

     if np.any(aatype > residue_constants.restype_num	):
          raise ValueError('''Invalid aatypes.'''	)

     lowercase					=		get_pdb_headers(_SCREAMING_SNAKE_CASE	)
     if len(_SCREAMING_SNAKE_CASE	) > 0:
          pdb_lines.extend(_SCREAMING_SNAKE_CASE	)

     lowercase					=		aatype.shape[0]
     lowercase					=		1
     lowercase					=		0
     lowercase					=		string.ascii_uppercase
     lowercase					=		None
     # Add all atom sites.
     for i in range(_SCREAMING_SNAKE_CASE	):
          lowercase					=		res_atoa(aatype[i]	)
          for atom_name, pos, mask, b_factor in zip(_SCREAMING_SNAKE_CASE				,    atom_positions[i]				,    atom_mask[i]				,    b_factors[i]	):
               if mask < 0.5:
                    continue

               lowercase					=		'''ATOM'''
               lowercase					=		atom_name if len(_SCREAMING_SNAKE_CASE	) == 4 else f' {atom_name}'
               lowercase					=		''''''
               lowercase					=		''''''
               lowercase					=		1.00
               lowercase					=		atom_name[0]  # Protein supports only C, N, O, S, this works.
               lowercase					=		''''''

               lowercase					=		'''A'''
               if chain_index is not None:
                    lowercase					=		chain_tags[chain_index[i]]

               # PDB is a columnar format, every space matters here!
               lowercase					=		(
                   f'{record_type:<6}{atom_index:>5} {name:<4}{alt_loc:>1}'
                   f'{res_name_a:>3} {chain_tag:>1}'
                   f'{residue_index[i]:>4}{insertion_code:>1}   '
                   f'{pos[0]:>8.3f}{pos[1]:>8.3f}{pos[2]:>8.3f}'
                   f'{occupancy:>6.2f}{b_factor:>6.2f}          '
                   f'{element:>2}{charge:>2}'
               )
               pdb_lines.append(_SCREAMING_SNAKE_CASE	)
               atom_index += 1

          lowercase					=		i == n - 1
          if chain_index is not None:
               if i != n - 1 and chain_index[i + 1] != prev_chain_index:
                    lowercase					=		True
                    lowercase					=		chain_index[i + 1]

          if should_terminate:
               # Close the chain.
               lowercase					=		'''TER'''
               lowercase					=		(
                   f'{chain_end:<6}{atom_index:>5}      {res_atoa(aatype[i]	):>3} {chain_tag:>1}{residue_index[i]:>4}'
               )
               pdb_lines.append(_SCREAMING_SNAKE_CASE	)
               atom_index += 1

               if i != n - 1:
                    # "prev" is a misnomer here. This happens at the beginning of
                    # each new chain.
                    pdb_lines.extend(get_pdb_headers(_SCREAMING_SNAKE_CASE				,    _SCREAMING_SNAKE_CASE	)	)

     pdb_lines.append('''END'''	)
     pdb_lines.append(''''''	)
     return "\n".join(_SCREAMING_SNAKE_CASE	)



def  UpperCamelCase					(							lowerCAmelCase__	):
     '''simple docstring'''
     return residue_constants.STANDARD_ATOM_MASK[prot.aatype]



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__ = None				,    lowerCAmelCase__ = None				,    lowerCAmelCase__ = None				,    lowerCAmelCase__ = None				,    lowerCAmelCase__ = None				,    ):
     '''simple docstring'''
     return Protein(
         aatype=features['''aatype''']				,    atom_positions=result['''final_atom_positions''']				,    atom_mask=result['''final_atom_mask''']				,    residue_index=features['''residue_index'''] + 1				,    b_factors=b_factors if b_factors is not None else np.zeros_like(result['''final_atom_mask''']	)				,    chain_index=_SCREAMING_SNAKE_CASE				,    remark=_SCREAMING_SNAKE_CASE				,    parents=_SCREAMING_SNAKE_CASE				,    parents_chain_index=_SCREAMING_SNAKE_CASE				,    )






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowercase__	:Tuple										=					{
    "configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
    "tokenization_biogpt": ["BioGptTokenizer"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__	:Union[str, Any]										=					[
							    "BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "BioGptForCausalLM",
							    "BioGptForTokenClassification",
							    "BioGptForSequenceClassification",
							    "BioGptModel",
							    "BioGptPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
							from .tokenization_biogpt import BioGptTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_biogpt import (
														    BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BioGptForCausalLM,
														    BioGptForSequenceClassification,
														    BioGptForTokenClassification,
														    BioGptModel,
														    BioGptPreTrainedModel,
														)


else:
							import sys

							lowercase__	:Any										=					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




