


"""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


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





@dataclasses.dataclass(frozen=lowerCamelCase__)
class        __A       :





							'''simple docstring'''

							__lowercase:						List[str]							 =      42  # [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:						int							 =      42  # [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:						Any							 =      42  # [num_res, num_atom_type]

							# Residue index as used in PDB. It is not necessarily continuous or 0-indexed.
							__lowercase:						Any							 =      42  # [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:						Optional[int]							 =      42  # [num_res, num_atom_type]

							# Chain indices for multi-chain predictions
							__lowercase:						int							 =      None

							# Optional remark about the protein. Included as a comment in output PDB
							# files
							__lowercase:						int							 =      None

							# Templates used to generate this protein (prediction-only)
							__lowercase:						Any							 =      None

							# Chain corresponding to each parent
							__lowercase:						List[Any]							 =      None







def   _a			( _SCREAMING_SNAKE_CASE			)      ->			Protein:
							snake_case_          =						r"(\[[A-Z]+\]\n)"
							snake_case_          =						[tag.strip() for tag in re.split(_lowerCAmelCase			,	_lowerCAmelCase			) if len(_lowerCAmelCase			) > 0]
							snake_case_          =						zip(tags[0::2]			,	[l.split("""\n"""			) for l in tags[1::2]]			)

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

							assert aatype is not None

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







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE = 0			)      ->			List[str]:
							snake_case_          =						[]

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

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

							if parents is None or len(_lowerCAmelCase			) == 0:
														snake_case_          =						["N/A"]

							pdb_headers.append(f"""PARENT {" ".join(_lowerCAmelCase			)}"""			)

							return pdb_headers







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			str:
							snake_case_          =						[]
							snake_case_          =						pdb_str.split("""\n"""			)

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

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

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

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

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

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

																					out_pdb_lines.append(make_parent_line(_lowerCAmelCase			)			)

							return "\n".join(_lowerCAmelCase			)







def   _a			( _SCREAMING_SNAKE_CASE			)      ->			str:
							snake_case_          =						residue_constants.restypes + ["X"]

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

							snake_case_          =						residue_constants.atom_types

							snake_case_          =						[]

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

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

							snake_case_          =						get_pdb_headers(_lowerCAmelCase			)
							if len(_lowerCAmelCase			) > 0:
														pdb_lines.extend(_lowerCAmelCase			)

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

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

																					snake_case_          =						"A"
																					if chain_index is not None:
																												snake_case_          =						chain_tags[chain_index[i]]

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

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

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

							pdb_lines.append("""END"""			)
							pdb_lines.append(""""""			)
							return "\n".join(_lowerCAmelCase			)







def   _a			( _SCREAMING_SNAKE_CASE			)      ->			np.ndarray:
							return residue_constants.STANDARD_ATOM_MASK[prot.aatype]







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE = None			,	_SCREAMING_SNAKE_CASE = None			,	_SCREAMING_SNAKE_CASE = None			,	_SCREAMING_SNAKE_CASE = None			,	_SCREAMING_SNAKE_CASE = None			,	)      ->			Protein:
							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=_lowerCAmelCase			,	remark=_lowerCAmelCase			,	parents=_lowerCAmelCase			,	parents_chain_index=_lowerCAmelCase			,	)








"""simple docstring"""
def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			str:
							return "\n".join(
							    f"""{number} * {i} = {number * i}""" for i in range(1			,	number_of_terms + 1			)			)


if __name__ == "__main__":
				print(multiplication_table(number=5, number_of_terms=10))



