"""
This type stub file was generated by pyright.
"""

from rdkit.Chem import *
from rdkit.Chem.ChemicalFeatures import *
from rdkit.Chem.rdChemReactions import *
from rdkit.Chem.rdDepictor import *
from rdkit.Chem.rdDistGeom import *
from rdkit.Chem.rdForceFieldHelpers import *
from rdkit.Chem.rdMolAlign import *
from rdkit.Chem.rdMolDescriptors import *
from rdkit.Chem.rdMolTransforms import *
from rdkit.Chem.rdPartialCharges import *
from rdkit.Chem.rdReducedGraphs import *
from rdkit.Chem.rdShapeHelpers import *
from rdkit.Chem.rdqueries import *
from rdkit.Chem.rdMolEnumerator import *
from rdkit.RDLogger import logger

from rdkit.Chem import Mol

""" Import all RDKit chemistry modules

"""
logger = ...


def TransformMol(mol, tform, confId=..., keepConfs=...):  # -> None:
    """  Applies the transformation (usually a 4x4 double matrix) to a molecule
      if keepConfs is False then all but that conformer are removed
      """
    ...


def ComputeMolShape(mol, confId=..., boxDim=..., spacing=..., **kwargs):
    """ returns a grid representation of the molecule's shape
      """
    ...


def ComputeMolVolume(mol, confId=..., gridSpacing=..., boxMargin=...):
    """ Calculates the volume of a particular conformer of a molecule
      based on a grid-encoding of the molecular shape.

      A bit of demo as well as a test of github #1883:

      >>> from rdkit import Chem
      >>> from rdkit.Chem import AllChem
      >>> mol = Chem.AddHs(Chem.MolFromSmiles('C'))
      >>> AllChem.EmbedMolecule(mol)
      0
      >>> ComputeMolVolume(mol)
      28...
      >>> mol = Chem.AddHs(Chem.MolFromSmiles('O'))
      >>> AllChem.EmbedMolecule(mol)
      0
      >>> ComputeMolVolume(mol)
      20...

      """
    ...


# -> Any:
def GetConformerRMS(mol, confId1, confId2, atomIds=..., prealigned=...):
    """ Returns the RMS between two conformations.
      By default, the conformers will be aligned to the first conformer
      before the RMS calculation and, as a side-effect, the second will be left
      in the aligned state.

      Arguments:
        - mol:        the molecule
        - confId1:    the id of the first conformer
        - confId2:    the id of the second conformer
        - atomIds:    (optional) list of atom ids to use a points for
                      alingment - defaults to all atoms
        - prealigned: (optional) by default the conformers are assumed
                      be unaligned and the second conformer be aligned
                      to the first

      """
    ...


# -> list[Unknown]:
def GetConformerRMSMatrix(mol, atomIds=..., prealigned=...):
    """ Returns the RMS matrix of the conformers of a molecule.
      As a side-effect, the conformers will be aligned to the first
      conformer (i.e. the reference) and will left in the aligned state.

      Arguments:
        - mol:     the molecule
        - atomIds: (optional) list of atom ids to use a points for
                   alingment - defaults to all atoms
        - prealigned: (optional) by default the conformers are assumed
                      be unaligned and will therefore be aligned to the
                      first conformer

      Note that the returned RMS matrix is symmetrical, i.e. it is the
      lower half of the matrix, e.g. for 5 conformers::

        rmsmatrix = [ a,
                      b, c,
                      d, e, f,
                      g, h, i, j]

      where a is the RMS between conformers 0 and 1, b is the RMS between
      conformers 0 and 2, etc.
      This way it can be directly used as distance matrix in e.g. Butina
      clustering.

      """
    ...


# -> Generator[ProductReactants | Unknown, None, None]:
def EnumerateLibraryFromReaction(reaction, sidechainSets, returnReactants=...):
    """ Returns a generator for the virtual library defined by
      a reaction and a sequence of sidechain sets

      >>> from rdkit import Chem
      >>> from rdkit.Chem import AllChem
      >>> s1=[Chem.MolFromSmiles(x) for x in ('NC','NCC')]
      >>> s2=[Chem.MolFromSmiles(x) for x in ('OC=O','OC(=O)C')]
      >>> rxn = AllChem.ReactionFromSmarts('[O:2]=[C:1][OH].[N:3]>>[O:2]=[C:1][N:3]')
      >>> r = AllChem.EnumerateLibraryFromReaction(rxn,[s2,s1])
      >>> [Chem.MolToSmiles(x[0]) for x in list(r)]
      ['CNC=O', 'CCNC=O', 'CNC(C)=O', 'CCNC(C)=O']

      Note that this is all done in a lazy manner, so "infinitely" large libraries can
      be done without worrying about running out of memory. Your patience will run out first:

      Define a set of 10000 amines:

      >>> amines = (Chem.MolFromSmiles('N'+'C'*x) for x in range(10000))

      ... a set of 10000 acids

      >>> acids = (Chem.MolFromSmiles('OC(=O)'+'C'*x) for x in range(10000))

      ... now the virtual library (1e8 compounds in principle):

      >>> r = AllChem.EnumerateLibraryFromReaction(rxn,[acids,amines])

      ... look at the first 4 compounds:

      >>> [Chem.MolToSmiles(next(r)[0]) for x in range(4)]
      ['NC=O', 'CNC=O', 'CCNC=O', 'CCCNC=O']


      """
    ...


def ConstrainedEmbed(mol, core, useTethers=..., coreConfId=..., randomseed=..., getForceField=..., **kwargs):
    """ generates an embedding of a molecule where part of the molecule
      is constrained to have particular coordinates

      Arguments
        - mol: the molecule to embed
        - core: the molecule to use as a source of constraints
        - useTethers: (optional) if True, the final conformation will be
            optimized subject to a series of extra forces that pull the
            matching atoms to the positions of the core atoms. Otherwise
            simple distance constraints based on the core atoms will be
            used in the optimization.
        - coreConfId: (optional) id of the core conformation to use
        - randomSeed: (optional) seed for the random number generator


      An example, start by generating a template with a 3D structure:

      >>> from rdkit.Chem import AllChem
      >>> template = AllChem.MolFromSmiles("c1nn(Cc2ccccc2)cc1")
      >>> AllChem.EmbedMolecule(template)
      0
      >>> AllChem.UFFOptimizeMolecule(template)
      0

      Here's a molecule:

      >>> mol = AllChem.MolFromSmiles("c1nn(Cc2ccccc2)cc1-c3ccccc3")

      Now do the constrained embedding
      >>> newmol=AllChem.ConstrainedEmbed(mol, template)

      Demonstrate that the positions are the same:

      >>> newp=newmol.GetConformer().GetAtomPosition(0)
      >>> molp=mol.GetConformer().GetAtomPosition(0)
      >>> list(newp-molp)==[0.0,0.0,0.0]
      True
      >>> newp=newmol.GetConformer().GetAtomPosition(1)
      >>> molp=mol.GetConformer().GetAtomPosition(1)
      >>> list(newp-molp)==[0.0,0.0,0.0]
      True

      """
    ...


def AssignBondOrdersFromTemplate(refmol: Mol, mol: Mol) -> Mol:
    """ assigns bond orders to a molecule based on the
      bond orders in a template molecule

      Arguments
        - refmol: the template molecule
        - mol: the molecule to assign bond orders to

      An example, start by generating a template from a SMILES
      and read in the PDB structure of the molecule

      >>> import os
      >>> from rdkit.Chem import AllChem
      >>> template = AllChem.MolFromSmiles("CN1C(=NC(C1=O)(c2ccccc2)c3ccccc3)N")
      >>> mol = AllChem.MolFromPDBFile(os.path.join(RDConfig.RDCodeDir, 'Chem', 'test_data', '4DJU_lig.pdb'))
      >>> len([1 for b in template.GetBonds() if b.GetBondTypeAsDouble() == 1.0])
      8
      >>> len([1 for b in mol.GetBonds() if b.GetBondTypeAsDouble() == 1.0])
      22

      Now assign the bond orders based on the template molecule

      >>> newMol = AllChem.AssignBondOrdersFromTemplate(template, mol)
      >>> len([1 for b in newMol.GetBonds() if b.GetBondTypeAsDouble() == 1.0])
      8

      Note that the template molecule should have no explicit hydrogens
      else the algorithm will fail.

      It also works if there are different formal charges (this was github issue 235):

      >>> template=AllChem.MolFromSmiles('CN(C)C(=O)Cc1ccc2c(c1)NC(=O)c3ccc(cc3N2)c4ccc(c(c4)OC)[N+](=O)[O-]')
      >>> mol = AllChem.MolFromMolFile(os.path.join(RDConfig.RDCodeDir, 'Chem', 'test_data', '4FTR_lig.mol'))
      >>> AllChem.MolToSmiles(mol)
      'COC1CC(C2CCC3C(O)NC4CC(CC(O)N(C)C)CCC4NC3C2)CCC1N(O)O'
      >>> newMol = AllChem.AssignBondOrdersFromTemplate(template, mol)
      >>> AllChem.MolToSmiles(newMol)
      'COc1cc(-c2ccc3c(c2)Nc2ccc(CC(=O)N(C)C)cc2NC3=O)ccc1[N+](=O)[O-]'

      """
    ...


if __name__ == '__main__':
    ...
