# $Id$
#
#  Copyright (C) 2006-2011  greg Landrum and Rational Discovery LLC
#
#   @@ All Rights Reserved @@
#  This file is part of the RDKit.
#  The contents are covered by the terms of the BSD license
#  which is included in the file license.txt, found at the root
#  of the RDKit source tree.
#
""" Import all RDKit chemistry modules

"""
import warnings
from collections import namedtuple

import numpy

from rdkit import DataStructs
from rdkit import ForceField
from rdkit import RDConfig
from rdkit import rdBase
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.Geometry import rdGeometry
from rdkit.RDLogger import logger

try:
  from rdkit.Chem.rdSLNParse import *
except ImportError:
  pass

Mol.Compute2DCoords = Compute2DCoords
Mol.ComputeGasteigerCharges = ComputeGasteigerCharges
logger = logger()


def TransformMol(mol, tform, confId=-1, keepConfs=False):
  """  Applies the transformation (usually a 4x4 double matrix) to a molecule
  if keepConfs is False then all but that conformer are removed
  """
  refConf = mol.GetConformer(confId)
  TransformConformer(refConf, tform)
  if not keepConfs:
    if confId == -1:
      confId = 0
    allConfIds = [c.GetId() for c in mol.GetConformers()]
    for cid in allConfIds:
      if not cid == confId:
        mol.RemoveConformer(cid)
    # reset the conf Id to zero since there is only one conformer left
    mol.GetConformer(confId).SetId(0)


def ComputeMolShape(mol, confId=-1, boxDim=(20, 20, 20), spacing=0.5, **kwargs):
  """ returns a grid representation of the molecule's shape
  """
  res = rdGeometry.UniformGrid3D(boxDim[0], boxDim[1], boxDim[2], spacing=spacing)
  EncodeShape(mol, res, confId, **kwargs)
  return res


def ComputeMolVolume(mol, confId=-1, gridSpacing=0.2, boxMargin=2.0):
  """ Calculates the volume of a particular conformer of a molecule
  based on a grid-encoding of the molecular shape.

  """
  mol = rdchem.Mol(mol)
  conf = mol.GetConformer(confId)
  CanonicalizeConformer(conf)
  box = ComputeConfBox(conf)
  sideLen = (box[1].x - box[0].x + 2 * boxMargin, box[1].y - box[0].y + 2 * boxMargin,
             box[1].z - box[0].z + 2 * boxMargin)
  shape = rdGeometry.UniformGrid3D(sideLen[0], sideLen[1], sideLen[2], spacing=gridSpacing)
  EncodeShape(mol, shape, confId, ignoreHs=False, vdwScale=1.0)
  voxelVol = gridSpacing**3
  occVect = shape.GetOccupancyVect()
  voxels = [1 for x in occVect if x == 3]
  vol = voxelVol * len(voxels)
  return vol


def GetBestRMS(ref, probe, refConfId=-1, probeConfId=-1, maps=None):
  """ Returns the optimal RMS for aligning two molecules, taking
  symmetry into account. As a side-effect, the probe molecule is
  left in the aligned state.

  Arguments:
    - ref: the reference molecule
    - probe: the molecule to be aligned to the reference
    - refConfId: (optional) reference conformation to use
    - probeConfId: (optional) probe conformation to use
    - maps: (optional) a list of lists of (probeAtomId,refAtomId)
      tuples with the atom-atom mappings of the two molecules.
      If not provided, these will be generated using a substructure
      search.

  Note:
  This function will attempt to align all permutations of matching atom
  orders in both molecules, for some molecules it will lead to 'combinatorial
  explosion' especially if hydrogens are present.
  Use 'rdkit.Chem.AllChem.AlignMol' to align molecules without changing the
  atom order.

  """
  if not maps:
    matches = ref.GetSubstructMatches(probe, uniquify=False)
    if not matches:
      raise ValueError('mol %s does not match mol %s' % (ref.GetProp('_Name'),
                                                         probe.GetProp('_Name')))
    if len(matches) > 1e6:
      warnings.warn("{} matches detected for molecule {}, this may lead to a performance slowdown.".
                    format(len(matches), probe.GetProp('_Name')))
    maps = [list(enumerate(match)) for match in matches]
  bestRMS = 1000.
  for amap in maps:
    rms = AlignMol(probe, ref, probeConfId, refConfId, atomMap=amap)
    if rms < bestRMS:
      bestRMS = rms
      bestMap = amap

  # finally repeate the best alignment :
  if bestMap != amap:
    AlignMol(probe, ref, probeConfId, refConfId, atomMap=bestMap)
  return bestRMS


def GetConformerRMS(mol, confId1, confId2, atomIds=None, prealigned=False):
  """ Returns the RMS between two conformations.
  By default, the conformers will be aligned to the first conformer
  of the molecule (i.e. the reference) before RMS calculation and,
  as a side-effect, 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 will therefore be aligned to the
                  first conformer

  """
  # align the conformers if necessary
  # Note: the reference conformer is always the first one
  if not prealigned:
    if atomIds:
      AlignMolConformers(mol, confIds=[confId1, confId2], atomIds=atomIds)
    else:
      AlignMolConformers(mol, confIds=[confId1, confId2])

  # calculate the RMS between the two conformations
  conf1 = mol.GetConformer(id=confId1)
  conf2 = mol.GetConformer(id=confId2)
  ssr = 0
  for i in range(mol.GetNumAtoms()):
    d = conf1.GetAtomPosition(i).Distance(conf2.GetAtomPosition(i))
    ssr += d * d
  ssr /= mol.GetNumAtoms()
  return numpy.sqrt(ssr)


def GetConformerRMSMatrix(mol, atomIds=None, prealigned=False):
  """ 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 symmetrically, 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]
  This way it can be directly used as distance matrix in e.g. Butina
  clustering.

  """
  # if necessary, align the conformers
  # Note: the reference conformer is always the first one
  rmsvals = []
  if not prealigned:
    if atomIds:
      AlignMolConformers(mol, atomIds=atomIds, RMSlist=rmsvals)
    else:
      AlignMolConformers(mol, RMSlist=rmsvals)
  else:  # already prealigned
    for i in range(1, mol.GetNumConformers()):
      rmsvals.append(GetConformerRMS(mol, 0, i, atomIds=atomIds, prealigned=prealigned))
  # loop over the conformations (except the reference one)
  cmat = []
  for i in range(1, mol.GetNumConformers()):
    cmat.append(rmsvals[i - 1])
    for j in range(1, i):
      cmat.append(GetConformerRMS(mol, i, j, atomIds=atomIds, prealigned=True))
  return cmat


def EnumerateLibraryFromReaction(reaction, sidechainSets, returnReactants=False):
  """ 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']


  """
  if len(sidechainSets) != reaction.GetNumReactantTemplates():
    raise ValueError('%d sidechains provided, %d required' %
                     (len(sidechainSets), reaction.GetNumReactantTemplates()))

  def _combiEnumerator(items, depth=0):
    for item in items[depth]:
      if depth + 1 < len(items):
        v = _combiEnumerator(items, depth + 1)
        for entry in v:
          l = [item]
          l.extend(entry)
          yield l
      else:
        yield [item]

  ProductReactants = namedtuple('ProductReactants', 'products,reactants')
  for chains in _combiEnumerator(sidechainSets):
    prodSets = reaction.RunReactants(chains)
    for prods in prodSets:
      if returnReactants:
        yield ProductReactants(prods, chains)
      else:
        yield prods


def ConstrainedEmbed(mol, core, useTethers=True, coreConfId=-1, randomseed=2342,
                     getForceField=UFFGetMoleculeForceField, **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

  """
  match = mol.GetSubstructMatch(core)
  if not match:
    raise ValueError("molecule doesn't match the core")
  coordMap = {}
  coreConf = core.GetConformer(coreConfId)
  for i, idxI in enumerate(match):
    corePtI = coreConf.GetAtomPosition(i)
    coordMap[idxI] = corePtI

  ci = EmbedMolecule(mol, coordMap=coordMap, randomSeed=randomseed, **kwargs)
  if ci < 0:
    raise ValueError('Could not embed molecule.')

  algMap = [(j, i) for i, j in enumerate(match)]

  if not useTethers:
    # clean up the conformation
    ff = getForceField(mol, confId=0)
    for i, idxI in enumerate(match):
      for j in range(i + 1, len(match)):
        idxJ = match[j]
        d = coordMap[idxI].Distance(coordMap[idxJ])
        ff.AddDistanceConstraint(idxI, idxJ, d, d, 100.)
    ff.Initialize()
    n = 4
    more = ff.Minimize()
    while more and n:
      more = ff.Minimize()
      n -= 1
    # rotate the embedded conformation onto the core:
    rms = AlignMol(mol, core, atomMap=algMap)
  else:
    # rotate the embedded conformation onto the core:
    rms = AlignMol(mol, core, atomMap=algMap)
    ff = getForceField(mol, confId=0)
    conf = core.GetConformer()
    for i in range(core.GetNumAtoms()):
      p = conf.GetAtomPosition(i)
      pIdx = ff.AddExtraPoint(p.x, p.y, p.z, fixed=True) - 1
      ff.AddDistanceConstraint(pIdx, match[i], 0, 0, 100.)
    ff.Initialize()
    n = 4
    more = ff.Minimize(energyTol=1e-4, forceTol=1e-3)
    while more and n:
      more = ff.Minimize(energyTol=1e-4, forceTol=1e-3)
      n -= 1
    # realign
    rms = AlignMol(mol, core, atomMap=algMap)
  mol.SetProp('EmbedRMS', str(rms))
  return mol


def AssignBondOrdersFromTemplate(refmol, 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-]'

  """
  refmol2 = rdchem.Mol(refmol)
  mol2 = rdchem.Mol(mol)
  # do the molecules match already?
  matching = mol2.GetSubstructMatch(refmol2)
  if not matching:  # no, they don't match
    # check if bonds of mol are SINGLE
    for b in mol2.GetBonds():
      if b.GetBondType() != BondType.SINGLE:
        b.SetBondType(BondType.SINGLE)
        b.SetIsAromatic(False)
    # set the bonds of mol to SINGLE
    for b in refmol2.GetBonds():
      b.SetBondType(BondType.SINGLE)
      b.SetIsAromatic(False)
    # set atom charges to zero;
    for a in refmol2.GetAtoms():
      a.SetFormalCharge(0)
    for a in mol2.GetAtoms():
      a.SetFormalCharge(0)

    matching = mol2.GetSubstructMatches(refmol2, uniquify=False)
    # do the molecules match now?
    if matching:
      if len(matching) > 1:
        logger.warning("More than one matching pattern found - picking one")
      matching = matching[0]
      # apply matching: set bond properties
      for b in refmol.GetBonds():
        atom1 = matching[b.GetBeginAtomIdx()]
        atom2 = matching[b.GetEndAtomIdx()]
        b2 = mol2.GetBondBetweenAtoms(atom1, atom2)
        b2.SetBondType(b.GetBondType())
        b2.SetIsAromatic(b.GetIsAromatic())
      # apply matching: set atom properties
      for a in refmol.GetAtoms():
        a2 = mol2.GetAtomWithIdx(matching[a.GetIdx()])
        a2.SetHybridization(a.GetHybridization())
        a2.SetIsAromatic(a.GetIsAromatic())
        a2.SetNumExplicitHs(a.GetNumExplicitHs())
        a2.SetFormalCharge(a.GetFormalCharge())
      SanitizeMol(mol2)
      if hasattr(mol2, '__sssAtoms'):
        mol2.__sssAtoms = None  # we don't want all bonds highlighted
    else:
      raise ValueError("No matching found")
  return mol2


# ------------------------------------
#
#  doctest boilerplate
#
def _runDoctests(verbose=None):  # pragma: nocover
  import sys
  import doctest
  failed, _ = doctest.testmod(optionflags=doctest.ELLIPSIS, verbose=verbose)
  sys.exit(failed)


if __name__ == '__main__':  # pragma: nocover
  _runDoctests()
