nfp.preprocessing.mol_preprocessor.SmilesPreprocessor

class SmilesPreprocessor(*args, explicit_hs=True, **kwargs)

Bases: nfp.preprocessing.mol_preprocessor.MolPreprocessor

Methods

construct_feature_matrices	Deprecated since version 0.3.0.
create_nx_graph	Given an input structure object, convert it to a networkx digraph with node, edge, and graph features assigned.
from_json	Set's the class's data with attributes taken from the save file
get_connectivity	Get the graph connectivity from the networkx graph
get_edge_features	Given a list of edge features from the nx.Graph, processes and concatenates them to an array.
get_graph_features	Process the nx.graph features into a dictionary of arrays.
get_node_features	Given a list of node features from the nx.Graph, processes and concatenates them to an array.
to_json	Serialize the classes's data to a json file

Attributes

atom_classes	The number of atom types found (includes the 0 null-atom type)
bond_classes	The number of bond types found (includes the 0 null-bond type)
output_signature
padding_values	Defaults to zero for each output
tfrecord_features	For loading preprocessed inputs from a tf records file

Parameters

explicit_hs (bool) –

create_nx_graph(smiles, *args, **kwargs)

Given an input structure object, convert it to a networkx digraph with node, edge, and graph features assigned.

Parameters

• structure – Any input graph object

• kwargs – keyword arguments passed from __call__, useful for specifying additional features in addition to the graph object.

• smiles (str) –

Returns

A networkx graph with the node, edge, and graph features set

Return type

nx.DiGraph

__call__(structure, *args, train=False, max_num_nodes=None, max_num_edges=None, **kwargs)

Convert an input graph structure into a featurized set of node, edge,

and graph-level features.

Parameters

• structure (Any) – An input graph structure (i.e., molecule, crystal, etc.)

• train (bool) – A training flag passed to Tokenizer member attributes

• max_num_nodes (Optional[int]) – A size attribute passed to get_node_features, defaults to the number of nodes in the current graph

• max_num_edges (Optional[int]) – A size attribute passed to get_edge_features, defaults to the number of edges in the current graph

• kwargs – Additional features or parameters passed to construct_nx_graph

Returns

A dictionary of key, array pairs as a single sample.

Return type

Dict[str, np.ndarray]

property atom_classes: int

The number of atom types found (includes the 0 null-atom type)

property bond_classes: int

The number of bond types found (includes the 0 null-bond type)

construct_feature_matrices(*args, train=False, **kwargs)

Deprecated since version 0.3.0: construct_feature_matrices will be removed in 0.4.0, use __call__ instead

Return type

Dict[str, numpy.ndarray]

from_json(filename)

Set’s the class’s data with attributes taken from the save file

Parameters

filename (str) –

Return type

None

static get_connectivity(graph, max_num_edges)

Get the graph connectivity from the networkx graph

Parameters

• graph (networkx.classes.digraph.DiGraph) – The input graph

• max_num_edges (int) – len(graph.edges), or the specified maximum number of graph edges

Returns

A dictionary of with the single ‘connectivity’ key, containing an (n,2) array of (node_index, node_index) pairs indicating the start and end nodes for each edge.

Return type

Dict[str, np.ndarray]

get_edge_features(edge_data, max_num_edges)

Given a list of edge features from the nx.Graph, processes and concatenates them to an array.

Parameters

• edge_data (list) – A list of edge data generated by nx_graph.edges(data=True)

• max_num_edges – If desired, this function should pad to a maximum number of edges passed from the __call__ function.

Returns

a dictionary of feature, array pairs, where array contains features for all edges in the graph.

Return type

Dict[str, np.ndarray]

get_graph_features(graph_data)

Process the nx.graph features into a dictionary of arrays.

Parameters

graph_data (dict) – A dictionary of graph data generated by nx_graph.graph

Returns

a dictionary of features for the graph

Return type

Dict[str, np.ndarray]

get_node_features(node_data, max_num_nodes)

Given a list of node features from the nx.Graph, processes and concatenates them to an array.

Parameters

• node_data (list) – A list of edge data generated by nx_graph.nodes(data=True)

• max_num_nodes – If desired, this function should pad to a maximum number of nodes passed from the __call__ function.

Returns

a dictionary of feature, array pairs, where array contains features for all nodes in the graph.

Return type

Dict[str, np.ndarray]

property padding_values: Dict[str, tensorflow.constant]

Defaults to zero for each output

property tfrecord_features: Dict[str, tensorflow.io.FixedLenFeature]

For loading preprocessed inputs from a tf records file

to_json(filename)

Serialize the classes’s data to a json file

Parameters

filename (str) –

Return type

None