comparison ob_spectrophore_search.py @ 5:26ce92f29349 draft default tip

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/chemicaltoolbox/openbabel commit d9c51279c061a1da948a2582d5b502ca7573adbf

4:2f5405da4884

"""
import argparse

import numpy as np
from openbabel import openbabel, pybel
openbabel.obErrorLog.StopLogging()
# TODO get rid of eval()

global spectrophore
spectrophore = pybel.ob.OBSpectrophore()


def parse_command_line():
    parser = argparse.ArgumentParser()
    parser.add_argument('--target', required=True, help='target file name in sdf format with Spectrophores(TM) descriptors stored as meta-data')
    parser.add_argument('--library', required=True, help='library of compounds with pre-computed physico-chemical properties, including Spectrophores(TM) in tabular format')
    parser.add_argument('-c', '--column', required=True, type=int, help='#column containing the Spectrophores(TM) descriptors in the library file')
    parser.add_argument('-o', '--output', required=True, help='output file name')
    parser.add_argument('-n', '--normalization', default="ZeroMeanAndUnitStd", choices=['No', 'ZeroMean', 'UnitStd', 'ZeroMeanAndUnitStd'], help='Normalization method')
    parser.add_argument('-a', '--accuracy', default="20", choices=['1', '2', '5', '10', '15', '20', '30', '36', '45', '60'], help='Accuracy expressed as angular stepsize')
    parser.add_argument('-s', '--stereo', default="No", choices=['No', 'Unique', 'Mirror', 'All'], help='Stereospecificity of the cage')
    parser.add_argument('-r', '--resolution', type=float, default="3.0", help='Resolution')
    return parser.parse_args()


def set_parameters(args):
    if args.normalization == 'No':
        spectrophore.SetNormalization(spectrophore.NoNormalization)
    else:
        spectrophore.SetNormalization(eval('spectrophore.NormalizationTowards' + args.normalization))
    spectrophore.SetAccuracy(eval('spectrophore.AngStepSize' + args.accuracy))
    spectrophore.SetStereo(eval('spectrophore.' + args.stereo + 'StereoSpecificProbes'))
    spectrophore.SetResolution(args.resolution)
    return True


def Compute_Spectrophores_distance(target_spectrophore, args):
    outfile = open(args.output, 'w')
    for mol in open(args.library, 'r'):
        try:
            distance = ((np.asarray(target_spectrophore, dtype=float) - np.asarray(mol.split('\t')[args.column - 1].strip().split(', '), dtype=float))**2).sum()
        except ValueError:
            distance = 0
        outfile.write('%s\t%f\n' % (mol.strip(), distance))
    outfile.close()


def __main__():
    """
        Computation of Spectrophores(TM) distances to a target molecule.
    """
    args = parse_command_line()
    # This sets up the parameters for the Spectrophore generation. Parameters are set to fit those of our standard parsing tool
    set_parameters(args)

    mol = next(pybel.readfile('sdf', args.target))
    target_spectrophore = mol.data["Spectrophores(TM)"].strip().split(', ')
    # Compute the paired-distance between every molecule in the library and the target
    Compute_Spectrophores_distance(target_spectrophore, args)


if __name__ == "__main__":

5:26ce92f29349

"""
import argparse

import numpy as np
from openbabel import openbabel, pybel

openbabel.obErrorLog.StopLogging()
# TODO get rid of eval()

global spectrophore
spectrophore = pybel.ob.OBSpectrophore()


def parse_command_line():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--target",
        required=True,
        help="target file name in sdf format with Spectrophores(TM) descriptors stored as meta-data",
    )
    parser.add_argument(
        "--library",
        required=True,
        help="library of compounds with pre-computed physico-chemical properties, including Spectrophores(TM) in tabular format",
    )
    parser.add_argument(
        "-c",
        "--column",
        required=True,
        type=int,
        help="#column containing the Spectrophores(TM) descriptors in the library file",
    )
    parser.add_argument("-o", "--output", required=True, help="output file name")
    parser.add_argument(
        "-n",
        "--normalization",
        default="ZeroMeanAndUnitStd",
        choices=["No", "ZeroMean", "UnitStd", "ZeroMeanAndUnitStd"],
        help="Normalization method",
    )
    parser.add_argument(
        "-a",
        "--accuracy",
        default="20",
        choices=["1", "2", "5", "10", "15", "20", "30", "36", "45", "60"],
        help="Accuracy expressed as angular stepsize",
    )
    parser.add_argument(
        "-s",
        "--stereo",
        default="No",
        choices=["No", "Unique", "Mirror", "All"],
        help="Stereospecificity of the cage",
    )
    parser.add_argument(
        "-r", "--resolution", type=float, default="3.0", help="Resolution"
    )
    return parser.parse_args()


def set_parameters(args):
    if args.normalization == "No":
        spectrophore.SetNormalization(spectrophore.NoNormalization)
    else:
        spectrophore.SetNormalization(
            eval("spectrophore.NormalizationTowards" + args.normalization)
        )
    spectrophore.SetAccuracy(eval("spectrophore.AngStepSize" + args.accuracy))
    spectrophore.SetStereo(eval("spectrophore." + args.stereo + "StereoSpecificProbes"))
    spectrophore.SetResolution(args.resolution)
    return True


def Compute_Spectrophores_distance(target_spectrophore, args):
    outfile = open(args.output, "w")
    for mol in open(args.library, "r"):
        try:
            distance = (
                (
                    np.asarray(target_spectrophore, dtype=float)
                    - np.asarray(
                        mol.split("\t")[args.column - 1].strip().split(", "),
                        dtype=float,
                    )
                )
                ** 2
            ).sum()
        except ValueError:
            distance = 0
        outfile.write("%s\t%f\n" % (mol.strip(), distance))
    outfile.close()


def __main__():
    """
    Computation of Spectrophores(TM) distances to a target molecule.
    """
    args = parse_command_line()
    # This sets up the parameters for the Spectrophore generation. Parameters are set to fit those of our standard parsing tool
    set_parameters(args)

    mol = next(pybel.readfile("sdf", args.target))
    target_spectrophore = mol.data["Spectrophores(TM)"].strip().split(", ")
    # Compute the paired-distance between every molecule in the library and the target
    Compute_Spectrophores_distance(target_spectrophore, args)


if __name__ == "__main__":