Source code for torchdrug.datasets.muv

import os

from torchdrug import data, utils
from torchdrug.core import Registry as R
from torchdrug.utils import doc


[docs]@R.register("datasets.MUV") @doc.copy_args(data.MoleculeDataset.load_csv, ignore=("smiles_field", "target_fields")) class MUV(data.MoleculeDataset): """ Subset of PubChem BioAssay by applying a refined nearest neighbor analysis. Statistics: - #Molecule: 93,087 - #Classification task: 17 Parameters: path (str): path to store the dataset verbose (int, optional): output verbose level **kwargs """ url = "http://deepchem.io.s3-website-us-west-1.amazonaws.com/datasets/muv.csv.gz" md5 = "9c40bd41310991efd40f4d4868fa3ddf" target_fields = ["MUV-466", "MUV-548", "MUV-600", "MUV-644", "MUV-652", "MUV-689", "MUV-692", "MUV-712", "MUV-713", "MUV-733", "MUV-737", "MUV-810", "MUV-832", "MUV-846", "MUV-852", "MUV-858", "MUV-859"] def __init__(self, path, verbose=1, **kwargs): path = os.path.expanduser(path) if not os.path.exists(path): os.makedirs(path) self.path = path zip_file = utils.download(self.url, path, md5=self.md5) csv_file = utils.extract(zip_file) self.load_csv(csv_file, smiles_field="smiles", target_fields=self.target_fields, verbose=verbose, **kwargs)