Added docstring and rst entry

FREESOLV_URL = 'https://deepchemdata.s3.us-west-1.amazonaws.com/datasets/freesolv.csv.gz'

FREESOLV_TASKS = ['y']

class _FreesolvLoader(_MolnetLoader):

  def create_dataset(self) -> Dataset:

    dataset_file = os.path.join(self.data_dir, 'freesolv.csv.gz')

    if not os.path.exists(dataset_file):

      dc.utils.data_utils.download_url(url=FREESOLV_URL, dest_dir=self.data_dir)

            loader = dc.data.CSVLoader(tasks = self.tasks, feature_field = 'smiles', featurizer = self.featurizer)

      loader = dc.data.CSVLoader(

          tasks=self.tasks, feature_field='smiles', featurizer=self.featurizer)

      return loader.create_dataset(dataset_file)

def load_freesolv(

    featurizer: Union[dc.feat.Featurizer, str] = dc.feat.MATFeaturizer(),

    splitter: Union[dc.splits.Splitter, str, None] = None,

    save_dir: Optional[str] = None,

    **kwargs

) -> Tuple[List[str], Tuple[Dataset, ...], List[dc.trans.Transformer]]:

  """Load Freesolv dataset

  The FreeSolv dataset is a collection of experimental and calculated hydration 

  free energies for small molecules in water, along with their experiemental values.

  Here, we are using a modified version of the dataset with the molecule smile string 

  and the corresponding experimental hydration free energies. 

  Random splitting is recommended for this dataset.

    loader = _FreesolvLoader(featurizer, splitter, transformers, FREESOLV_TASKS, data_dir, save_dir, **kwargs)

  The raw data csv file contains columns below:

  - "mol" - SMILES representation of the molecular structure

  - "y" - Experimental hydration free energy

  Parameters

  ----------

  featurizer: Featurizer or str

    the featurizer to use for processing the data.  Alternatively you can pass

    one of the names from dc.molnet.featurizers as a shortcut.

  splitter: Splitter or str

    the splitter to use for splitting the data into training, validation, and

    test sets.  Alternatively you can pass one of the names from

    dc.molnet.splitters as a shortcut.  If this is None, all the data

    will be included in a single dataset.

  transformers: list of TransformerGenerators or strings

    the Transformers to apply to the data.  Each one is specified by a

    TransformerGenerator or, as a shortcut, one of the names from

    dc.molnet.transformers.

  reload: bool

    if True, the first call for a particular featurizer and splitter will cache

    the datasets to disk, and subsequent calls will reload the cached datasets.

  data_dir: str

    a directory to save the raw data in

  save_dir: str

    a directory to save the dataset in

  References

  ----------

  .. [1] Łukasz Maziarka, et al. "Molecule Attention Transformer." NeurIPS 2019

     arXiv:2002.08264v1 [cs.LG].

  .. [2] Mobley DL, Guthrie JP. FreeSolv: 

     a database of experimental and calculated hydration free energies, with input files. 

     J Comput Aided Mol Des. 2014;28(7):711-720. doi:10.1007/s10822-014-9747-x

  """

  loader = _FreesolvLoader(featurizer, splitter, transformers, FREESOLV_TASKS,

                           data_dir, save_dir, **kwargs)

  return loader.load_dataset('freesolv', reload)

.. autofunction:: deepchem.molnet.load_cell_counting

Freesolv Dataset

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.. autofunction:: deepchem.molnet.load_freesolv

Chembl Datasets

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