Term

class pronto.Term

A term, corresponding to a node in the ontology graph.

Formally a Term frame is equivalent to a Class declaration in OWL2.

objects(r: pronto.relationship.Relationship) → Iterator[pronto.term.Term]

Iterate over the terms t verifying self · r · t.

Example

>>> go = pronto.Ontology.from_obo_library("go.obo")
>>> go['GO:0048870']
Term('GO:0048870', name='cell motility')
>>> list(go['GO:0048870'].objects(go['part_of']))
[Term('GO:0051674', name='localization of cell')]

Todo

Make Term.objects take in account holds_over_chain and transitive_over values of the relationship it is building an iterator with.

superclasses(distance: Optional[int] = None) → Iterator[pronto.term.Term]

Get an iterator over the superclasses of this Term.

In order to follow the semantics of rdf:subClassOf, which in turn respects the mathematical inclusion of subset inclusion, is_a is defined as a transitive relationship, hence has_subclass is also transitive by closure property. Therefore self is always yielded first when calling this method.

Parameters

distance (int, optional) – The maximum distance between this node and the yielded superclass (0 for the term itself, 1 for its immediate superclasses, etc.). Use None to explore transitively the entire directed graph.

Yields

Term – Superclasses of the selected term, breadth-first. The first element is always the term itself, use itertools.islice to skip it.

Example

>>> ms = pronto.Ontology.from_obo_library("ms.obo")
>>> sup = ms['MS:1000143'].superclasses()
>>> next(sup)
Term('MS:1000143', name='API 150EX')
>>> next(sup)
Term('MS:1000121', name='SCIEX instrument model')
>>> next(sup)
Term('MS:1000031', name='instrument model')

Note

The time complexity for this algorithm is in \(O(n)\), where \(n\) is the number of terms in the source ontology.

See also

The RDF Schema 1.1 specification, defining the rdfs:subClassOf property, which the is_a relationship is translated to in OWL2 language.

subclasses(distance: Optional[int] = None) → Iterator[pronto.term.Term]

Get an iterator over the subclasses of this Term.

Yields

Term – Subclasses of the selected term, breadth-first. The first element is always the term itself, use itertools.islice to skip it.

Example

>>> ms = pronto.Ontology.from_obo_library("ms.obo")
>>> sub = ms['MS:1000031'].subclasses()
>>> next(sub)
Term('MS:1000031', name='instrument model')
>>> next(sub)
Term('MS:1000121', name='SCIEX instrument model')
>>> next(sub)
Term('MS:1000122', name='Bruker Daltonics instrument model')

Note

This method has a runtime of \(O(n^2)\) where \(n\) is the number of terms in the source ontology. This is due to the fact that OBO and OWL only explicit superclassing relationship, so we have to build the graph of subclasses from the knowledge graph.

is_leaf() → bool

Check whether the term is a leaf in the ontology.

We define leaves as nodes in the ontology which do not have subclasses since the subclassing relationship is directed and can be used to create a DAG of all the terms in the ontology.

Example

>>> ms = pronto.Ontology.from_obo_library("ms.obo")
>>> ms['MS:1000031'].is_leaf()   # instrument model
False
>>> ms['MS:1001792'].is_leaf()   # Xevo TQ-S
True

property disjoint_from

The terms declared as disjoint from this term.

Two terms are disjoint if they have no instances or subclasses in common.

property intersection_of

The terms or term relationships this term is an intersection of.