




"""simple docstring"""

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


a         =      Mapping[str, np.ndarray]
a         =      Mapping[str, Any]  # Is a nested dict.
a         =      0.0_1





@dataclasses.dataclass(frozen=__lowerCAmelCase							)
class     lowercase_	:



	'''simple docstring'''
	UpperCAmelCase   :					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'.
	UpperCAmelCase   :					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.
	UpperCAmelCase   :					np.ndarray  # [num_res, num_atom_type]

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

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

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

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

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






def 						_snake_case					( _snake_case							: str							)   -> Protein:






						'''simple docstring'''


						_A        =       R'(\[[A-Z]+\]\n)'
						_A        =       [tag.strip() for tag in re.split(__A    ,  __A							) if len(__A							) > 0]
						_A        =       zip(tags[0::2]    ,  [l.split('\n'							) for l in tags[1::2]]							)

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

						assert aatype is not None

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






def 						_snake_case					( _snake_case							: Protein    ,  _snake_case							: int = 0							)   -> List[str]:






						'''simple docstring'''


						_A        =       []

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

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

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

						pdb_headers.append(F'''PARENT {" ".join(__A							)}'''							)

						return pdb_headers






def 						_snake_case					( _snake_case							: Protein    ,  _snake_case							: str							)   -> str:






						'''simple docstring'''


						_A        =       []
						_A        =       pdb_str.split('\n'							)

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

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

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

						def make_parent_line(_snake_case							: Sequence[str]							) -> str:
												return F'''PARENT {" ".join(__A							)}'''

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

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

																		out_pdb_lines.append(make_parent_line(__A							)							)

						return "\n".join(__A							)






def 						_snake_case					( _snake_case							: Protein							)   -> str:






						'''simple docstring'''


						_A        =       residue_constants.restypes + ['X']

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

						_A        =       residue_constants.atom_types

						_A        =       []

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

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

						_A        =       get_pdb_headers(__A							)
						if len(__A							) > 0:
												pdb_lines.extend(__A							)

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

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

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

																		# PDB is a columnar format, every space matters here!
																		_A        =       (
																		    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(__A							)
																		atom_index += 1

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

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

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






def 						_snake_case					( _snake_case							: Protein							)   -> np.ndarray:






						'''simple docstring'''


						return residue_constants.STANDARD_ATOM_MASK[prot.aatype]







def 						_snake_case					( _snake_case							: FeatureDict    ,  _snake_case							: ModelOutput    ,  _snake_case							: Optional[np.ndarray] = None    ,  _snake_case							: Optional[np.ndarray] = None    ,  _snake_case							: Optional[str] = None    ,  _snake_case							: Optional[Sequence[str]] = None    ,  _snake_case							: Optional[Sequence[int]] = None    ,  )   -> Protein:






						'''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=__A    ,  remark=__A    ,  parents=__A    ,  parents_chain_index=__A    ,  )







"""simple docstring"""

import argparse
from collections import defaultdict

import yaml


a         =      '''docs/source/en/_toctree.yml'''






def 						_snake_case					( _snake_case							: List[Any]							)   -> Optional[Any]:






      '''simple docstring'''


      _A        =       defaultdict(_snake_case							)
      _A        =       []
      _A        =       []
      for doc in doc_list:
            if "local" in doc:
                  counts[doc["local"]] += 1

            if doc["title"].lower() == "overview":
                  overview_doc.append({'local': doc['local'], 'title': doc['title']}							)
            else:
                  new_doc_list.append(_snake_case							)

      _A        =       new_doc_list
      _A        =       [key for key, value in counts.items() if value > 1]

      _A        =       []
      for duplicate_key in duplicates:
            _A        =       list({doc['title'] for doc in doc_list if doc['local'] == duplicate_key}							)
            if len(_snake_case							) > 1:
                  raise ValueError(
                      F'''{duplicate_key} is present several times in the documentation table of content at '''
                      '`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the '
                      'others.'							)
            # Only add this once
            new_doc.append({'local': duplicate_key, 'title': titles[0]}							)

      # Add none duplicate-keys
      new_doc.extend([doc for doc in doc_list if 'local' not in counts or counts[doc['local']] == 1]							)
      _A        =       sorted(_snake_case    ,  key=lambda _snake_case							: s["title"].lower()							)

      # "overview" gets special treatment and is always first
      if len(_snake_case							) > 1:
            raise ValueError('{doc_list} has two \'overview\' docs which is not allowed.'							)

      overview_doc.extend(_snake_case							)

      # Sort
      return overview_doc






def 						_snake_case					( _snake_case							: Tuple=False							)   -> List[Any]:






      '''simple docstring'''


      with open(_snake_case    ,  encoding='utf-8'							) as f:
            _A        =       yaml.safe_load(f.read()							)

      # Get to the API doc
      _A        =       0
      while content[api_idx]["title"] != "API":
            api_idx += 1
      _A        =       content[api_idx]['sections']

      # Then to the model doc
      _A        =       0
      while api_doc[scheduler_idx]["title"] != "Schedulers":
            scheduler_idx += 1

      _A        =       api_doc[scheduler_idx]['sections']
      _A        =       clean_doc_toc(_snake_case							)

      _A        =       False
      if new_scheduler_doc != scheduler_doc:
            _A        =       True
            if overwrite:
                  _A        =       new_scheduler_doc

      if diff:
            if overwrite:
                  _A        =       api_doc
                  with open(_snake_case    ,  'w'    ,  encoding='utf-8'							) as f:
                        f.write(yaml.dump(_snake_case    ,  allow_unicode=_snake_case							)							)
            else:
                  raise ValueError(
                      'The model doc part of the table of content is not properly sorted, run `make style` to fix this.'							)






def 						_snake_case					( _snake_case							: str=False							)   -> Union[str, Any]:






      '''simple docstring'''


      with open(_snake_case    ,  encoding='utf-8'							) as f:
            _A        =       yaml.safe_load(f.read()							)

      # Get to the API doc
      _A        =       0
      while content[api_idx]["title"] != "API":
            api_idx += 1
      _A        =       content[api_idx]['sections']

      # Then to the model doc
      _A        =       0
      while api_doc[pipeline_idx]["title"] != "Pipelines":
            pipeline_idx += 1

      _A        =       False
      _A        =       api_doc[pipeline_idx]['sections']
      _A        =       []

      # sort sub pipeline docs
      for pipeline_doc in pipeline_docs:
            if "section" in pipeline_doc:
                  _A        =       pipeline_doc['section']
                  _A        =       clean_doc_toc(_snake_case							)
                  if overwrite:
                        _A        =       new_sub_pipeline_doc
            new_pipeline_docs.append(_snake_case							)

      # sort overall pipeline doc
      _A        =       clean_doc_toc(_snake_case							)

      if new_pipeline_docs != pipeline_docs:
            _A        =       True
            if overwrite:
                  _A        =       new_pipeline_docs

      if diff:
            if overwrite:
                  _A        =       api_doc
                  with open(_snake_case    ,  'w'    ,  encoding='utf-8'							) as f:
                        f.write(yaml.dump(_snake_case    ,  allow_unicode=_snake_case							)							)
            else:
                  raise ValueError(
                      'The model doc part of the table of content is not properly sorted, run `make style` to fix this.'							)


if __name__ == "__main__":
       a         =      argparse.ArgumentParser()
       parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
       a         =      parser.parse_args()

       check_scheduler_doc(args.fix_and_overwrite)
       check_pipeline_doc(args.fix_and_overwrite)

