data.rst

.. _apidata:

Dataset
=======

.. currentmodule:: dgl.data

Utils
-----

.. autosummary::
    :toctree: ../../generated/

    utils.get_download_dir
    utils.download
    utils.check_sha1
    utils.extract_archive
    utils.split_dataset
    utils.save_graphs
    utils.load_graphs
    utils.load_labels

.. autoclass:: dgl.data.utils.Subset
    :members: __getitem__, __len__

Dataset Classes
---------------

Stanford sentiment treebank dataset
```````````````````````````````````

For more information about the dataset, see `Sentiment Analysis <https://nlp.stanford.edu/sentiment/index.html>`__.

.. autoclass:: SST
    :members: __getitem__, __len__


Karate Club dataset
```````````````````````````````````

.. autoclass:: KarateClub
    :members: __getitem__, __len__


Citation Network dataset
```````````````````````````````````

.. autoclass:: CitationGraphDataset
    :members: __getitem__, __len__


Cora Citation Network dataset
```````````````````````````````````

.. autoclass:: CoraDataset
    :members: __getitem__, __len__


CoraFull dataset
```````````````````````````````````

.. autoclass:: CoraFull
    :members: __getitem__, __len__


Amazon Co-Purchase dataset
```````````````````````````````````

.. autoclass:: AmazonCoBuy
    :members: __getitem__, __len__


Coauthor dataset
```````````````````````````````````

.. autoclass:: Coauthor
    :members: __getitem__, __len__


BitcoinOTC dataset
```````````````````````````````````

.. autoclass:: BitcoinOTC
    :members: __getitem__, __len__


ICEWS18 dataset
```````````````````````````````````

.. autoclass:: ICEWS18
    :members: __getitem__, __len__


QM7b dataset
```````````````````````````````````

.. autoclass:: QM7b
    :members: __getitem__, __len__



GDELT dataset
```````````````````````````````````

.. autoclass:: GDELT
    :members: __getitem__, __len__


Mini graph classification dataset
`````````````````````````````````

.. autoclass:: MiniGCDataset
    :members: __getitem__, __len__, num_classes


Graph kernel dataset
````````````````````

For more information about the dataset, see `Benchmark Data Sets for Graph Kernels <https://ls11-www.cs.tu-dortmund.de/staff/morris/graphkerneldatasets>`__.

.. autoclass:: TUDataset
    :members: __getitem__, __len__


Graph isomorphism network dataset
```````````````````````````````````

A compact subset of graph kernel dataset

.. autoclass:: GINDataset
    :members: __getitem__, __len__


Protein-Protein Interaction dataset
```````````````````````````````````

.. autoclass:: PPIDataset
    :members: __getitem__, __len__

Molecular Graphs
----------------

To work on molecular graphs, make sure you have installed `RDKit 2018.09.3 <https://www.rdkit.org/docs/Install.html>`__.

Data Loading and Processing Utils
`````````````````````````````````

We adapt several utilities for processing molecules from
`DeepChem <https://github.com/deepchem/deepchem/blob/master/deepchem>`__.

.. autosummary::
    :toctree: ../../generated/

    chem.add_hydrogens_to_mol
    chem.get_mol_3D_coordinates
    chem.load_molecule
    chem.multiprocess_load_molecules

Featurization Utils for Single Molecule
```````````````````````````````````````

For the use of graph neural networks, we need to featurize nodes (atoms) and edges (bonds).

General utils:

.. autosummary::
    :toctree: ../../generated/

    chem.one_hot_encoding
    chem.ConcatFeaturizer
    chem.ConcatFeaturizer.__call__

Utils for atom featurization:

.. autosummary::
    :toctree: ../../generated/

    chem.atom_type_one_hot
    chem.atomic_number_one_hot
    chem.atomic_number
    chem.atom_degree_one_hot
    chem.atom_degree
    chem.atom_total_degree_one_hot
    chem.atom_total_degree
    chem.atom_implicit_valence_one_hot
    chem.atom_implicit_valence
    chem.atom_hybridization_one_hot
    chem.atom_total_num_H_one_hot
    chem.atom_total_num_H
    chem.atom_formal_charge_one_hot
    chem.atom_formal_charge
    chem.atom_num_radical_electrons_one_hot
    chem.atom_num_radical_electrons
    chem.atom_is_aromatic_one_hot
    chem.atom_is_aromatic
    chem.atom_chiral_tag_one_hot
    chem.atom_mass
    chem.BaseAtomFeaturizer
    chem.BaseAtomFeaturizer.feat_size
    chem.BaseAtomFeaturizer.__call__
    chem.CanonicalAtomFeaturizer

Utils for bond featurization:

.. autosummary::
    :toctree: ../../generated/

    chem.bond_type_one_hot
    chem.bond_is_conjugated_one_hot
    chem.bond_is_conjugated
    chem.bond_is_in_ring_one_hot
    chem.bond_is_in_ring
    chem.bond_stereo_one_hot
    chem.BaseBondFeaturizer
    chem.BaseBondFeaturizer.feat_size
    chem.BaseBondFeaturizer.__call__
    chem.CanonicalBondFeaturizer

Graph Construction for Single Molecule
``````````````````````````````````````

Several methods for constructing DGLGraphs from SMILES/RDKit molecule objects are listed below:

.. autosummary::
    :toctree: ../../generated/

    chem.mol_to_graph
    chem.smiles_to_bigraph
    chem.mol_to_bigraph
    chem.smiles_to_complete_graph
    chem.mol_to_complete_graph
    chem.k_nearest_neighbors

Graph Construction and Featurization for Ligand-Protein Complex
```````````````````````````````````````````````````````````````

Constructing DGLHeteroGraphs and featurize for them.

.. autosummary::
    :toctree: ../../generated/

    chem.ACNN_graph_construction_and_featurization

Dataset Classes
```````````````

If your dataset is stored in a ``.csv`` file, you may find it helpful to use

.. autoclass:: dgl.data.chem.CSVDataset
    :members: __getitem__, __len__

Currently four datasets are supported:

* Tox21
* TencentAlchemyDataset
* PubChemBioAssayAromaticity
* PDBBind

.. autoclass:: dgl.data.chem.Tox21
    :members: __getitem__, __len__, task_pos_weights

.. autoclass:: dgl.data.chem.TencentAlchemyDataset
    :members: __getitem__, __len__, set_mean_and_std

.. autoclass:: dgl.data.chem.PubChemBioAssayAromaticity
    :members: __getitem__, __len__

.. autoclass:: dgl.data.chem.PDBBind
    :members: __getitem__, __len__

Dataset Splitting
`````````````````

We provide support for some common data splitting methods:

* consecutive split
* random split
* molecular weight split
* Bemis-Murcko scaffold split
* single-task-stratified split

.. autoclass:: dgl.data.chem.ConsecutiveSplitter
    :members: train_val_test_split, k_fold_split

.. autoclass:: dgl.data.chem.RandomSplitter
    :members: train_val_test_split, k_fold_split

.. autoclass:: dgl.data.chem.MolecularWeightSplitter
    :members: train_val_test_split, k_fold_split

.. autoclass:: dgl.data.chem.ScaffoldSplitter
    :members: train_val_test_split, k_fold_split

.. autoclass:: dgl.data.chem.SingleTaskStratifiedSplitter
    :members: train_val_test_split, k_fold_split