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MoleculeNetDataset2018.py
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import os
from kgcnn.data.moleculenet import MoleculeNetDataset
from kgcnn.data.download import DownloadDataset
class MoleculeNetDataset2018(MoleculeNetDataset, DownloadDataset):
r"""Downloader for `MoleculeNet <https://moleculenet.org/>`__ datasets.
This class inherits from :obj:`MoleculeNetDataset` .
QM datasets are however excluded from this class as they have specific `kgcnn.data.datasets` which inherits from
:obj:`QMDatasets` .
MoleculeNet is a benchmark specially designed for testing machine learning methods of molecular properties.
Their work curates a number of dataset collections. All methods and datasets are integrated as parts
of the open source `DeepChem <https://deepchem.io/>`__ package (MIT license).
Stats:
.. list-table::
:widths: 20 10 10 10
:header-rows: 1
* - Name
- #graphs
- #features
- #classes
* - ESOL
- 1,128
- 9
- 1
* - FreeSolv
- 642
- 9
- 1
* - Lipophilicity
- 4,200
- 9
- 1
* - PCBA
- 437,929
- 9
- 128
* - MUV
- 93,087
- 9
- 17
* - HIV
- 41,127
- 9
- 1
* - BACE
- 1513
- 9
- 1
* - BBPB
- 2,050
- 9
- 1
* - Tox21
- 7,831
- 9
- 12
* - ToxCast
- 8,597
- 9
- 617
* - SIDER
- 1,427
- 9
- 27
* - ClinTox
- 1,484
- 9
- 2
References:
(1) Zhenqin Wu, Bharath Ramsundar, Evan N. Feinberg, Joseph Gomes, Caleb Geniesse, Aneesh S. Pappu, Karl
Leswing, Vijay Pande, MoleculeNet: A Benchmark for Molecular Machine Learning, arXiv preprint,
arXiv: 1703.00564, 2017.
"""
datasets_download_info = {
"ESOL": {"dataset_name": "ESOL", "download_file_name": 'delaney-processed.csv', "data_directory_name": "ESOL"},
"FreeSolv": {"dataset_name": "FreeSolv", "data_directory_name": "FreeSolv", "download_file_name": 'SAMPL.csv'},
"Lipop": {"dataset_name": "Lipop", "data_directory_name": "Lipop", "download_file_name": 'Lipophilicity.csv'},
"PCBA": {"dataset_name": "PCBA", "data_directory_name": "PCBA", "download_file_name": 'pcba.csv.gz',
"extract_gz": True, "extract_file_name": 'pcba.csv'},
"MUV": {"dataset_name": "MUV", "data_directory_name": "MUV", "download_file_name": 'muv.csv.gz',
"extract_gz": True, "extract_file_name": 'muv.csv'},
"HIV": {"dataset_name": "HIV", "data_directory_name": "HIV", "download_file_name": 'HIV.csv'},
"BACE": {"dataset_name": "BACE", "data_directory_name": "BACE", "download_file_name": 'bace.csv'},
"BBBP": {"dataset_name": "BBBP", "data_directory_name": "BBBP", "download_file_name": 'BBBP.csv'},
"Tox21": {"dataset_name": "Tox21", "data_directory_name": "Tox21", "download_file_name": 'tox21.csv.gz',
"extract_gz": True, "extract_file_name": 'tox21.csv'},
"ToxCast": {"dataset_name": "ToxCast", "data_directory_name": "ToxCast",
"download_file_name": 'toxcast_data.csv.gz', "extract_gz": True,
"extract_file_name": 'toxcast_data.csv'},
"SIDER": {"dataset_name": "SIDER", "data_directory_name": "SIDER", "download_file_name": 'sider.csv.gz',
"extract_gz": True, "extract_file_name": 'sider.csv'},
"ClinTox": {"dataset_name": "ClinTox", "data_directory_name": "ClinTox", "download_file_name": 'clintox.csv.gz',
"extract_gz": True, "extract_file_name": 'clintox.csv'},
}
datasets_prepare_data_info = {
"ESOL": {"make_conformers": True, "add_hydrogen": True},
"FreeSolv": {"make_conformers": True, "add_hydrogen": True},
"Lipop": {"make_conformers": True, "add_hydrogen": True},
"PCBA": {"make_conformers": True, "add_hydrogen": True},
"MUV": {"make_conformers": True, "add_hydrogen": True},
"HIV": {"make_conformers": True, "add_hydrogen": True},
"BACE": {"make_conformers": True, "add_hydrogen": True, "smiles_column_name": "mol"},
"BBBP": {"make_conformers": True, "add_hydrogen": True, "smiles_column_name": "smiles"},
"Tox21": {"make_conformers": True, "add_hydrogen": True, "smiles_column_name": "smiles"},
"ToxCast": {"make_conformers": True, "add_hydrogen": True, "smiles_column_name": "smiles"},
"SIDER": {"make_conformers": True, "add_hydrogen": True, "smiles_column_name": "smiles"},
"ClinTox": {"make_conformers": True, "add_hydrogen": True, "smiles_column_name": "smiles"}
}
datasets_read_in_memory_info = {
"ESOL": {"add_hydrogen": False, "has_conformers": True,
"label_column_name": "measured log solubility in mols per litre"},
"FreeSolv": {"add_hydrogen": False, "has_conformers": True, "label_column_name": "expt"},
"Lipop": {"add_hydrogen": False, "has_conformers": True, "label_column_name": "exp"},
"PCBA": {"add_hydrogen": False, "has_conformers": False, "label_column_name": slice(0, 128)},
"MUV": {"add_hydrogen": False, "has_conformers": True, "label_column_name": slice(0, 17)},
"HIV": {"add_hydrogen": False,"has_conformers": True, "label_column_name": "HIV_active"},
"BACE": {"add_hydrogen": False, "has_conformers": True, "label_column_name": "Class"},
"BBBP": { "add_hydrogen": False, "has_conformers": True, "label_column_name": "p_np"},
"Tox21": {"add_hydrogen": False, "has_conformers": True, "label_column_name": slice(0, 12)},
"ToxCast": {"add_hydrogen": False, "has_conformers": True, "label_column_name": slice(1, 618)},
"SIDER": {"add_hydrogen": False, "has_conformers": True, "label_column_name": slice(1, 28)},
"ClinTox": {"add_hydrogen": False, "has_conformers": True, "label_column_name": [1, 2]}
}
def __init__(self, dataset_name: str, reload: bool = False, verbose: int = 10):
"""Initialize a `MoleculeNetDataset2018` instance from string identifier.
Args:
dataset_name (str): Name of a dataset.
reload (bool): Download the dataset again and prepare data on disk.
verbose (int): Print progress or info for processing where 60=silent. Default is 10.
"""
if not isinstance(dataset_name, str):
raise ValueError("Please provide string identifier for TUDataset.")
MoleculeNetDataset.__init__(self, verbose=verbose, dataset_name=dataset_name)
# Prepare download
if dataset_name in self.datasets_download_info:
self.download_info = self.datasets_download_info[dataset_name]
self.download_info.update({"download_url": "https://deepchemdata.s3-us-west-1.amazonaws.com/datasets/" +
self.download_info["download_file_name"]})
else:
raise ValueError("Can not resolve '%s' as a Molecule. Pick: " % dataset_name,
self.datasets_download_info.keys(),
"For new dataset, add to `datasets_download_info` list manually.")
DownloadDataset.__init__(self, **self.download_info, reload=reload, verbose=verbose)
self.data_directory = os.path.join(self.data_main_dir, self.data_directory_name)
self.file_name = self.download_file_name if self.extract_file_name is None else self.extract_file_name
self.dataset_name = dataset_name
self.require_prepare_data = True
self.fits_in_memory = True
if self.require_prepare_data:
self.prepare_data(overwrite=reload, **self.datasets_prepare_data_info[self.dataset_name])
if self.fits_in_memory:
self.read_in_memory(**self.datasets_read_in_memory_info[self.dataset_name])
# data = MoleculeNetDataset2018("ESOL", reload=True)
# data = MoleculeNetDataset2018("PCBA", reload=False)
# data = MoleculeNetDataset2018("ClinTox", reload=True)
# data = MoleculeNetDataset2018("Tox21", reload=True)
# data = MoleculeNetDataset2018("HIV", reload=True)