Commit a498685b authored by nd-02110114's avatar nd-02110114
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📝 update docs

parent 76097654
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+6 −6
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@@ -214,8 +214,8 @@ class MolecularFeaturizer(Featurizer):
  Child classes need to implement the _featurize method for
  calculating features for a single molecule.

  Notes
  -----
  Note
  ----
  The subclasses of this class require RDKit to be installed.
  """

@@ -294,8 +294,8 @@ class MaterialStructureFeaturizer(Featurizer):
  classes need to implement the _featurize method for calculating
  features for a single crystal structure.

  Notes
  -----
  Note
  ----
  Some subclasses of this class will require pymatgen and matminer to be
  installed.
  """
@@ -360,8 +360,8 @@ class MaterialCompositionFeaturizer(Featurizer):
  classes need to implement the _featurize method for calculating
  features for a single crystal composition.

  Notes
  -----
  Note
  ----
  Some subclasses of this class will require pymatgen and matminer to be
  installed.
  """
+2 −2
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@@ -36,8 +36,8 @@ class ElemNetFeaturizer(MaterialCompositionFeaturizer):
  >>> featurizer = ElemNetFeaturizer()
  >>> features = featurizer.featurize([comp])

  Notes
  -----
  Note
  ----
  This class requires Pymatgen to be installed.
  """

+2 −2
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@@ -16,8 +16,8 @@ class MACCSKeysFingerprint(MolecularFeaturizer):
     Journal of chemical information and computer sciences 42.6 (2002): 1273-1280.
  .. [2] https://github.com/rdkit/rdkit/blob/master/rdkit/Chem/MACCSkeys.py

  Notes
  -----
  Note
  ----
  This class requires RDKit to be installed.
  """

+1 −1
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@@ -15,7 +15,7 @@ class PubChemFingerprint(MolecularFeaturizer):
  ----------
  .. [1] ftp://ftp.ncbi.nlm.nih.gov/pubchem/specifications/pubchem_fingerprints.pdf

  Notes
  Note
  -----
  This class requires RDKit and PubChemPy to be installed.
  PubChemPy use REST API to get the fingerprint, so you need the internet access.
+47 −5
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@@ -34,12 +34,12 @@ These featurizers work with datasets of molecules.
Graph Convolution Featurizers
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

MolGraphConvFeaturizer
**********************
We are simplifying our graph convolution models by a joint data representation (:code:`GraphData`)
in a future version of DeepChem, so we provide several featurizers.

.. autoclass:: deepchem.feat.MolGraphConvFeaturizer
  :members:
  :inherited-members:
:code:`ConvMolFeaturizer` and :code:`WeaveFeaturizer` are used with graph convolution models
which inherited :code:`KerasModel`. On the other hand, :code:`MolGraphConvFeaturizer` is used
with graph convolution models which inherited :code;`TorchModel`.

ConvMolFeaturizer
*****************
@@ -55,6 +55,13 @@ WeaveFeaturizer
  :members:
  :inherited-members:

MolGraphConvFeaturizer
**********************

.. autoclass:: deepchem.feat.MolGraphConvFeaturizer
  :members:
  :inherited-members:

Utilities
*********

@@ -366,3 +373,38 @@ UserDefinedFeaturizer
.. autoclass:: deepchem.feat.UserDefinedFeaturizer
  :members:
  :inherited-members:

Base Featurizers (for develop)
------------------------------

Featurizer
^^^^^^^^^^

The :code:`dc.feat.Featurizer` class is the abstract parent class for all featurizers.

.. autoclass:: deepchem.feat.Featurizer
  :members:

MolecularFeaturizer
^^^^^^^^^^^^^^^^^^^

.. autoclass:: deepchem.feat.MolecularFeaturizer
  :members:

MaterialCompositionFeaturizer
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. autoclass:: deepchem.feat.MaterialCompositionFeaturizer
  :members:

MaterialStructureFeaturizer
^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. autoclass:: deepchem.feat.MaterialStructureFeaturizer
  :members:

ComplexFeaturizer
^^^^^^^^^^^^^^^^^

.. autoclass:: deepchem.feat.ComplexFeaturizer
  :members:
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