

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


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



@dataclasses.dataclass(frozen=lowerCAmelCase__       )
class       __snake_case  :
  __lowerCAmelCase     :	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'.
  __lowerCAmelCase     :	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.
  __lowerCAmelCase     :	np.ndarray  # [num_res, num_atom_type]

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

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

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

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

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






def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		str       ):





    """simple docstring"""


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

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





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						[]

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

    SCREAMING_SNAKE_CASE_									=						prot.parents
    SCREAMING_SNAKE_CASE_									=						prot.parents_chain_index
    if parents is not None and parents_chain_index is not None:
        SCREAMING_SNAKE_CASE_									=						[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:
        SCREAMING_SNAKE_CASE_									=						['N/A']

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

    return pdb_headers


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		Protein ,   _SCREAMING_SNAKE_CASE					:		str       ):





    """simple docstring"""


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

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

    SCREAMING_SNAKE_CASE_									=						42
    if prot.parents is not None and len(prot.parents       ) > 0:
        SCREAMING_SNAKE_CASE_									=						[]
        if prot.parents_chain_index is not None:
            SCREAMING_SNAKE_CASE_									=						{}
            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       )

            SCREAMING_SNAKE_CASE_									=						max([int(_SCREAMING_SNAKE_CASE       ) for chain_idx in parent_dict]       )
            for i in range(max_idx + 1       ):
                SCREAMING_SNAKE_CASE_									=						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:
        SCREAMING_SNAKE_CASE_									=						[['N/A']]

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

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

    SCREAMING_SNAKE_CASE_									=						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       ):
                SCREAMING_SNAKE_CASE_									=						parents_per_chain[chain_counter]
            else:
                SCREAMING_SNAKE_CASE_									=						['N/A']

            out_pdb_lines.append(make_parent_line(_SCREAMING_SNAKE_CASE       )       )

    return "\n".join(_SCREAMING_SNAKE_CASE       )


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		Protein       ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						residue_constants.restypes + ['X']

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

    SCREAMING_SNAKE_CASE_									=						residue_constants.atom_types

    SCREAMING_SNAKE_CASE_									=						[]

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

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

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

    SCREAMING_SNAKE_CASE_									=						aatype.shape[0]
    SCREAMING_SNAKE_CASE_									=						1
    SCREAMING_SNAKE_CASE_									=						0
    SCREAMING_SNAKE_CASE_									=						string.ascii_uppercase
    SCREAMING_SNAKE_CASE_									=						None
    # Add all atom sites.
    for i in range(_SCREAMING_SNAKE_CASE       ):
        SCREAMING_SNAKE_CASE_									=						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

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

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

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

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

        if should_terminate:
            # Close the chain.
            SCREAMING_SNAKE_CASE_									=						'TER'
            SCREAMING_SNAKE_CASE_									=						(
                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       (  _SCREAMING_SNAKE_CASE					:		Protein       ):





    """simple docstring"""


    return residue_constants.STANDARD_ATOM_MASK[prot.aatype]





def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		FeatureDict ,   _SCREAMING_SNAKE_CASE					:		ModelOutput ,   _SCREAMING_SNAKE_CASE					:		Optional[np.ndarray] = None ,   _SCREAMING_SNAKE_CASE					:		Optional[np.ndarray] = None ,   _SCREAMING_SNAKE_CASE					:		Optional[str] = None ,   _SCREAMING_SNAKE_CASE					:		Optional[Sequence[str]] = None ,   _SCREAMING_SNAKE_CASE					:		Optional[Sequence[int]] = 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 ,   )





import pytest

import datasets


# Import fixture modules as plugins
UpperCamelCase__  :      Union[str, Any]			=    ["tests.fixtures.files", "tests.fixtures.hub", "tests.fixtures.fsspec"]


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		Optional[Any] ,   _SCREAMING_SNAKE_CASE					:		Dict       ):





    """simple docstring"""


    for item in items:
        if any(marker in item.keywords for marker in ['integration', 'unit']       ):
            continue
        item.add_marker(pytest.mark.unit       )


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		Optional[int]       ):





    """simple docstring"""


    config.addinivalue_line('markers' ,   'torchaudio_latest: mark test to run with torchaudio>=0.12'       )


@pytest.fixture(autouse=_SCREAMING_SNAKE_CASE       )
def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		Any ,   _SCREAMING_SNAKE_CASE					:		str       ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						tmp_path_factory.getbasetemp() / 'cache'
    SCREAMING_SNAKE_CASE_									=						test_hf_cache_home / 'datasets'
    SCREAMING_SNAKE_CASE_									=						test_hf_cache_home / 'metrics'
    SCREAMING_SNAKE_CASE_									=						test_hf_cache_home / 'modules'
    monkeypatch.setattr('datasets.config.HF_DATASETS_CACHE' ,   str(_SCREAMING_SNAKE_CASE       )       )
    monkeypatch.setattr('datasets.config.HF_METRICS_CACHE' ,   str(_SCREAMING_SNAKE_CASE       )       )
    monkeypatch.setattr('datasets.config.HF_MODULES_CACHE' ,   str(_SCREAMING_SNAKE_CASE       )       )
    SCREAMING_SNAKE_CASE_									=						test_hf_datasets_cache / 'downloads'
    monkeypatch.setattr('datasets.config.DOWNLOADED_DATASETS_PATH' ,   str(_SCREAMING_SNAKE_CASE       )       )
    SCREAMING_SNAKE_CASE_									=						test_hf_datasets_cache / 'downloads' / 'extracted'
    monkeypatch.setattr('datasets.config.EXTRACTED_DATASETS_PATH' ,   str(_SCREAMING_SNAKE_CASE       )       )


@pytest.fixture(autouse=_SCREAMING_SNAKE_CASE ,   scope='session'       )
def 					_UpperCAmelCase       (  ):





    """simple docstring"""


    datasets.disable_progress_bar()


@pytest.fixture(autouse=_SCREAMING_SNAKE_CASE       )
def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		Any       ):





    """simple docstring"""


    monkeypatch.setattr('datasets.config.HF_UPDATE_DOWNLOAD_COUNTS' ,   _SCREAMING_SNAKE_CASE       )





@pytest.fixture
def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		Tuple       ):





    """simple docstring"""


    monkeypatch.setattr('sqlalchemy.util.deprecations.SILENCE_UBER_WARNING' ,   _SCREAMING_SNAKE_CASE       )


