Python RDLogger.logger方法代码示例

# 需要导入模块: from rdkit import RDLogger [as 别名]
# 或者: from rdkit.RDLogger import logger [as 别名]
def findDuplicates (sdf, name, out):

    lg = RDLogger.logger()
    lg.setLevel(RDLogger.ERROR)
    
    suppl = Chem.SDMolSupplier(sdf,removeHs=False, sanitize=False)

    idlist = []
    nmlist = []
    smlist = []

    print 'reading SDFile...'
    counter = 0
    for mol in suppl:

        counter+=1
        
        if mol is None: continue
        try:
            inchi = Chem.MolToInchi(mol)
            inkey = Chem.InchiToInchiKey(inchi)
            smile = Chem.MolToSmiles(mol)
        except:
            continue

        try:
            ni = mol.GetProp(name)
        except:
            ni = 'mol%0.8d' %counter

        idlist.append(inkey[:-3])
        nmlist.append(ni)
        smlist.append(smile)
    
    n = len(idlist)

    print 'analizing duplicates...'

    fo = open (out,'w+')
    fo.write('i\tj\tnamei\tnamej\tsmilesi\tsmilesj\n')
    duplicates = 0
    for i in range (n):
        for j in range (i+1,n):
            if idlist[i]==idlist[j]:
                line=str(i)+'\t'+str(j)+'\t'+nmlist[i]+'\t'+nmlist[j]+'\t'+smlist[i]+'\t'+smlist[j]
                fo.write(line+'\n')
                duplicates+=1
    fo.close()

    print '\n%d duplicate molecules found' %duplicates

# 需要导入模块: from rdkit import RDLogger [as 别名]
# 或者: from rdkit.RDLogger import logger [as 别名]
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#

INCHI_AVAILABLE = True

import rdinchi
import logging
from rdkit import RDLogger
logger = RDLogger.logger()

logLevelToLogFunctionLookup = {
        logging.INFO : logger.info,
        logging.DEBUG : logger.debug,
        logging.WARNING : logger.warning,
        logging.CRITICAL : logger.critical,
        logging.ERROR : logger.error
        }

class InchiReadWriteError(Exception):
    pass

def MolFromInchi(inchi, sanitize=True, removeHs=True, logLevel=None,
        treatWarningAsError=False):
    """Construct a molecule from a InChI string

# 需要导入模块: from rdkit import RDLogger [as 别名]
# 或者: from rdkit.RDLogger import logger [as 别名]
from __future__ import print_function

from rdkit import RDLogger
lg = RDLogger.logger()
lg.setLevel(4)

import rdkit.Chem as Chem
import rdkit.Chem.AllChem as AllChem
from rdkit import DataStructs
import pandas as pd
import numpy as np
from tqdm import tqdm
import json
import sys

from retrosim.utils.generate_retro_templates import process_an_example
from retrosim.data.get_data import get_data_df, split_data_df

from joblib import Parallel, delayed
import multiprocessing
num_cores = multiprocessing.cpu_count()

from rdchiral.main import rdchiralRun, rdchiralReaction, rdchiralReactants
import os

SCRIPT_ROOT = os.path.dirname(__file__)
PROJ_ROOT = os.path.dirname(SCRIPT_ROOT)

############### DEFINITIONS FOR VALIDATION SEARCH ########################
all_getfp_labels = ['Morgan2noFeat', 'Morgan3noFeat', 'Morgan2Feat', 'Morgan3Feat']
all_similarity_labels = ['Tanimoto', 'Dice', 'TverskyA', 'TverskyB',]

# 需要导入模块: from rdkit import RDLogger [as 别名]
# 或者: from rdkit.RDLogger import logger [as 别名]
#   @@ 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.
#
from rdkit import Chem
from rdkit.Chem import AllChem
from rdkit.Chem import Lipinski,Descriptors,Crippen
from rdkit.Dbase.DbConnection import DbConnect
from rdkit.Dbase import DbModule
import re

#set up the logger:
import rdkit.RDLogger as logging
logger = logging.logger()
logger.setLevel(logging.INFO)

def ProcessMol(mol,typeConversions,globalProps,nDone,nameProp='_Name',nameCol='compound_id',
               redraw=False,keepHs=False,
               skipProps=False,addComputedProps=False,
               skipSmiles=False,
               uniqNames=None,namesSeen=None):
  if not mol:
    raise ValueError('no molecule')
  if keepHs:
    Chem.SanitizeMol(mol)
  try:
    nm = mol.GetProp(nameProp)
  except KeyError:
    nm = None

# 需要导入模块: from rdkit import RDLogger [as 别名]
# 或者: from rdkit.RDLogger import logger [as 别名]
def UFFConstrainedOptimize(mol, moving_atoms=None, fixed_atoms=None,
                           cutoff=5., verbose=False):
    """Minimize a molecule using UFF forcefield with a set of moving/fixed
    atoms. If both moving and fixed atoms are provided, fixed_atoms parameter
    will be ignored.  The minimization is done in-place (without copying
    molecule).

    Parameters
    ----------
        mol: rdkit.Chem.rdchem.Mol
            Molecule to be minimized.
        moving_atoms: array-like (default=None)
            Indices of freely moving atoms. If None, fixed atoms are assigned
            based on `fixed_atoms`. These two arguments are mutually exclusive.
        fixed_atoms: array-like (default=None)
            Indices of fixed atoms. If None, fixed atoms are assigned based on
            `moving_atoms`. These two arguments are mutually exclusive.
        cutoff: float (default=10.)
            Distance cutoff for the UFF minimization

    Returns
    -------
        mol: rdkit.Chem.rdchem.Mol
            Molecule with mimimized `moving_atoms`
    """
    logger = RDLogger.logger()

    if not verbose:
        logger.setLevel(RDLogger.CRITICAL)

    if moving_atoms is None and fixed_atoms is None:
        raise ValueError('You must supply at least one set of moving/fixed '
                         'atoms.')

    all_atoms = set(range(mol.GetNumAtoms()))
    if moving_atoms is None:
        moving_atoms = list(all_atoms.difference(fixed_atoms))
    else:
        fixed_atoms = list(all_atoms.difference(moving_atoms))
    # extract submolecules containing atoms within cutoff
    mol_conf = mol.GetConformer(-1)
    pos = np.array([mol_conf.GetAtomPosition(i)
                   for i in range(mol_conf.GetNumAtoms())])
    mask = (cdist(pos, pos[moving_atoms]) <= cutoff).any(axis=1)
    amap = np.where(mask)[0].tolist()

    # expand to whole residues
    pocket_residues = OrderedDict()
    protein_residues = GetResidues(mol)
    for res_id in protein_residues.keys():
        if any(1 for res_aix in protein_residues[res_id]
               if res_aix in amap):
            pocket_residues[res_id] = protein_residues[res_id]
    amap = list(chain(*pocket_residues.values()))

    # TODO: above certain threshold its making a submolis redundant
    submol = AtomListToSubMol(mol, amap, includeConformer=True)
    # initialize ring info
    Chem.GetSSSR(submol)
    ff = UFFGetMoleculeForceField(submol, vdwThresh=cutoff,
                                  ignoreInterfragInteractions=False)
    for submol_id, atom_id in enumerate(amap):
        if atom_id not in moving_atoms:
            ff.AddFixedPoint(submol_id)
    ff.Initialize()
    ff.Minimize(energyTol=1e-4, forceTol=1e-3, maxIts=2000)

    # get the positions backbone
    conf = mol.GetConformer(-1)
    submol_conf = submol.GetConformer(-1)
    for submol_idx, mol_idx in enumerate(amap,):
        conf.SetAtomPosition(mol_idx, submol_conf.GetAtomPosition(submol_idx))

    # FIXME: there's no getLevel method, so we set to default level
    if not verbose:
        logger.setLevel(RDLogger.INFO)

    return mol

# 需要导入模块: from rdkit import RDLogger [as 别名]
# 或者: from rdkit.RDLogger import logger [as 别名]
"""SyGMa: Systematically Generating potential Metabolites"""

from builtins import str
import argparse
import sygma
import sys
from rdkit import Chem, RDLogger
RDLogger.logger().setLevel(RDLogger.ERROR)
import logging
logging.basicConfig()
logger = logging.getLogger('sygma')

def run_sygma(args, file=sys.stdout):
    logger.setLevel(args.loglevel.upper())
    scenario = sygma.Scenario([
        [sygma.ruleset['phase1'], args.phase1],
        [sygma.ruleset['phase2'], args.phase2]
    ])

    parent = Chem.MolFromSmiles(args.parentmol)
    metabolic_tree = scenario.run(parent)
    metabolic_tree.calc_scores()
    if args.outputtype == "sdf":
        metabolic_tree.write_sdf(file)
    elif args.outputtype == "smiles":
        file.write("\n".join([m+" "+str(s) for m,s in metabolic_tree.to_smiles()])+'\n')
    return None

def get_sygma_parser():
    ap = argparse.ArgumentParser(description=__doc__)
    ap.add_argument('--version', action='version', version='%(prog)s ' + sygma.__version__)