# Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Utils for minimization."""
import io
from alphafold.common import residue_constants
from Bio import PDB
import numpy as np


def overwrite_b_factors(pdb_str: str, bfactors: np.ndarray) -> str:
  """Overwrites the B-factors in pdb_str with contents of bfactors array.

  Args:
    pdb_str: An input PDB string.
    bfactors: A numpy array with shape [1, n_residues, 37]. We assume that the
      B-factors are per residue; i.e. that the nonzero entries are identical in
      [0, i, :].

  Returns:
    A new PDB string with the B-factors replaced.
  """
  if bfactors.shape[-1] != residue_constants.atom_type_num:
    raise ValueError(
        f'Invalid final dimension size for bfactors: {bfactors.shape[-1]}.')

  parser = PDB.PDBParser(QUIET=True)
  handle = io.StringIO(pdb_str)
  structure = parser.get_structure('', handle)

  curr_resid = ('', '', '')
  idx = -1
  for atom in structure.get_atoms():
    atom_resid = atom.parent.get_id()
    if atom_resid != curr_resid:
      idx += 1
      if idx >= bfactors.shape[0]:
        raise ValueError('Index into bfactors exceeds number of residues. '
                         'B-factors shape: {shape}, idx: {idx}.')
    curr_resid = atom_resid
    atom.bfactor = bfactors[idx, residue_constants.atom_order['CA']]

  new_pdb = io.StringIO()
  pdb_io = PDB.PDBIO()
  pdb_io.set_structure(structure)
  pdb_io.save(new_pdb)
  return new_pdb.getvalue()


def assert_equal_nonterminal_atom_types(
    atom_mask: np.ndarray, ref_atom_mask: np.ndarray):
  """Checks that pre- and post-minimized proteins have same atom set."""
  # Ignore any terminal OXT atoms which may have been added by minimization.
  oxt = residue_constants.atom_order['OXT']
  no_oxt_mask = np.ones(shape=atom_mask.shape, dtype=bool)
  no_oxt_mask[..., oxt] = False
  np.testing.assert_almost_equal(ref_atom_mask[no_oxt_mask],
                                 atom_mask[no_oxt_mask])
