Filters

This module contains functions for filtering node and edge iterables. It relies heavily on the concepts of functional programming and the concept of predicates.

Node Filters

A node filter is a function that takes two arguments: a pybel.BELGraph and a node tuple. It returns a boolean representing whether the node passed the given test.

This module contains a set of default functions for filtering lists of nodes and building node filtering functions.

A general use for a node filter function is to use the built-in filter() in code like filter(your_node_filter, graph)

pybel_tools.filters.node_filters.summarize_node_filter(graph, node_filters)

Prints a summary of the number of nodes passing a given set of filters

Parameters:

• graph (pybel.BELGraph) – A BEL graph
• node_filters (types.FunctionType or iter[types.FunctionType]) – A node filter or list/tuple of node filters

pybel_tools.filters.node_filters.node_inclusion_filter_builder(nbunch)

Builds a filter that only passes on nodes in the given list

Parameters:nbunch (iter[tuple]) – An iterable of BEL nodes Returns:A node filter (graph, node) -> bool Return type:types.FunctionType

pybel_tools.filters.node_filters.node_exclusion_filter_builder(nodes)

Builds a filter that fails on nodes in the given list

Parameters:nodes (list) – A list of nodes Returns:A node filter (graph, node) -> bool Return type:types.FunctionType

pybel_tools.filters.node_filters.function_inclusion_filter_builder(func)

Build a filter that only passes on nodes of the given function(s).

Parameters:func (str or iter[str]) – A BEL Function or list/set/tuple of BEL functions Returns:A node predicate Return type:(pybel.BELGraph, tuple) -> bool

pybel_tools.filters.node_filters.function_exclusion_filter_builder(func)

Build a filter that fails on nodes of the given function(s).

Parameters:func (str or list[str] or tuple[str] or set[str]) – A BEL Function or list/set/tuple of BEL functions Returns:A node predicate Return type:(pybel.BELGraph, tuple) -> bool

pybel_tools.filters.node_filters.function_namespace_inclusion_builder(func, namespace)

Build a filter function for matching the given BEL function with the given namespace or namespaces.

Parameters:

• func (str) – A BEL function
• or iter[str] namespace (str) – The namespace to serach by

Returns:

A node predicate

Return type:

(pybel.BELGraph, tuple) -> bool

pybel_tools.filters.node_filters.namespace_inclusion_builder(namespace)

Build a predicate for namespace inclusion.

Parameters:or iter[str] namespace (str) – A namespace or iter of namespaces Returns:A node predicate Return type:(pybel.BELGraph, tuple) -> bool

pybel_tools.filters.node_filters.data_contains_key_builder(key)

Build a filter that passes only on nodes that have the given key in their data dictionary.

Parameters:key (str) – A key for the node’s data dictionary Returns:A node predicate Return type:(pybel.BELGraph, tuple) -> bool

pybel_tools.filters.node_filters.node_has_label(graph, node)

Passes for nodes that have been annotated with a label

pybel_tools.filters.node_filters.node_missing_label(graph, node)

Fails for nodes that have been annotated with a label

pybel_tools.filters.node_filters.include_pathology_filter(graph, node)

A filter that passes for nodes that are pybel.constants.PATHOLOGY

pybel_tools.filters.node_filters.exclude_pathology_filter(graph, node)

A filter that fails for nodes that are pybel.constants.PATHOLOGY

pybel_tools.filters.node_filters.data_missing_key_builder(key)

Build a filter that passes only on nodes that don’t have the given key in their data dictionary.

Parameters:key (str) – A key for the node’s data dictionary Returns:A node filter (graph, node) -> bool Return type:(pybel.BELGraph, BaseEntity) -> bool

pybel_tools.filters.node_filters.build_node_data_search(key, data_predicate)

Pass for nodes who have the given key in their data dictionaries and whose associated values pass the given filter function.

Parameters:

• key (str) – The node data dictionary key to check
• data_predicate ((Any) -> bool) – The filter to apply to the node data dictionary

Returns:

A node predicate

Return type:

(pybel.BELGraph, BaseEntity) -> bool

pybel_tools.filters.node_filters.build_node_key_search(query, key)

Build a node filter that only passes for nodes whose values for the given key are superstrings of the query string(s).

Parameters:

• query (str or iter[str]) – The query string or strings to check if they’re in the node name
• key (str) – The key for the node data dictionary. Should refer only to entries that have str values

Returns:

A node predicate

Return type:

(pybel.BELGraph, BaseEntity) -> bool

Edge Filters

A edge filter is a function that takes five arguments: a pybel.BELGraph, a source node tuple, a target node tuple, a key, and a data dictionary. It returns a boolean representing whether the edge passed the given test.

This module contains a set of default functions for filtering lists of edges and building edge filtering functions.

A general use for an edge filter function is to use the built-in filter() in code like filter(your_edge_filter, graph.edges_iter(keys=True, data=True))

pybel_tools.filters.edge_filters.summarize_edge_filter(graph, edge_filters)

Prints a summary of the number of edges passing a given set of filters

Parameters:

• graph (pybel.BELGraph) – A BEL graph
• edge_filters ((pybel.BELGraph, BaseEntity, BaseEntity, str) -> bool or iter[(pybel.BELGraph, BaseEntity, BaseEntity, str) -> bool]) – A filter or list of filters

pybel_tools.filters.edge_filters.build_edge_data_filter(annotations, partial_match=True)

Build a filter that keeps edges whose data dictionaries are super-dictionaries to the given dictionary.

Parameters:

• annotations (dict) – The annotation query dict to match
• partial_match (bool) – Should the query values be used as partial or exact matches? Defaults to True.

Return type:

(pybel.BELGraph, BaseEntity, BaseEntity, str) -> bool

pybel_tools.filters.edge_filters.build_pmid_inclusion_filter(pmid)

Pass for edges with citations whose references are one of the given PubMed identifiers.

Parameters:pmid (str or iter[str]) – A PubMed identifier or list of PubMed identifiers to filter for Returns:An edge filter function (graph, node, node, key, data) -> bool Return type:(pybel.BELGraph, BaseEntity, BaseEntity, str) -> bool

pybel_tools.filters.edge_filters.build_pmid_exclusion_filter(pmid)

Fail for edges with citations whose references are one of the given PubMed identifiers.

Parameters:pmid (str or iter[str]) – A PubMed identifier or list of PubMed identifiers to filter against Returns:An edge filter function (graph, node, node, key, data) -> bool Return type:(pybel.BELGraph, BaseEntity, BaseEntity, str) -> bool

pybel_tools.filters.edge_filters.build_author_inclusion_filter(author)

Only passes for edges with author information that matches one of the given authors

Parameters:author (str or iter[str]) – The author or list of authors to filter by Returns:An edge filter Return type:(pybel.BELGraph, BaseEntity, BaseEntity, str) -> bool

pybel_tools.filters.edge_filters.build_source_namespace_filter(namespaces)

Only passes for edges whose source nodes have the given namespace or one of the given namespaces

Parameters:namespaces (str or iter[str]) – The namespace or namespaces to filter by Return type:(pybel.BELGraph, BaseEntity, BaseEntity, str) -> bool

pybel_tools.filters.edge_filters.build_target_namespace_filter(namespaces)

Only passes for edges whose target nodes have the given namespace or one of the given namespaces

Parameters:namespaces (str or iter[str]) – The namespace or namespaces to filter by Return type:(pybel.BELGraph, BaseEntity, BaseEntity, str) -> bool

pybel_tools.filters.edge_filters.build_annotation_dict_all_filter(annotations)

Build an edge predicate that passes for edges whose data dictionaries’s annotations entry are super-dictionaries to the given dictionary.

If no annotations are given, will always evaluate to true.

Parameters:annotations (dict[str,iter[str]]) – The annotation query dict to match Return type:(pybel.BELGraph, BaseEntity, BaseEntity, str) -> bool

pybel_tools.filters.edge_filters.build_annotation_dict_any_filter(annotations)

Build an edge predicate that passes for edges whose data dictionaries match the given dictionary.

If the given dictionary is empty, will always evaluate to true.

Parameters:annotations (dict[str,iter[str]]) – The annotation query dict to match Return type:(pybel.BELGraph, BaseEntity, BaseEntity, str) -> bool

pybel_tools.filters.edge_filters.has_pathology_causal(graph, u, v, k)

Check if the subject is a pathology and has a causal relationship with a non bioprocess/pathology.

Parameters:

• graph (pybel.BELGraph) – A BEL Graph
• u (BaseEntity) – A BEL node
• v (BaseEntity) – A BEL node
• k (str) – The edge key between the given nodes

Returns:

If the subject of this edge is a pathology and it participates in a causal reaction.

Return type:

bool