import rdflib
from rdflib import Graph, RDFS, Namespace
import FAIRLinked.InterfaceMDS.load_mds_ontology
from FAIRLinked.InterfaceMDS.load_mds_ontology import load_mds_ontology_graph
[docs]
def term_search_general(mds_ontology_graph=None, query_term=None, search_types=None, ttl_extr=False, ttl_path=None):
"""
Search an RDF ontology for subjects with a specified predicate and optional query term.
Args:
mds_ontology_graph (rdflib.Graph, optional): An existing RDF graph. If None, one will be loaded.
query_term (str, optional): Term to match against the object of the predicate.
If None, all values will be returned for the given search types.
search_types (list[str]): List of search types: "Domain", "SubDomain", or "Study Stage".
ttl_extr (int, optional): If not 0, extract the search results into a new graph. Defaults to 0.
ttl_path (str, optional): The file path to save the extracted turtle (.ttl) file.
Required if ttl_extr is not 0.
Prints:
- A list of labels for matching subjects, grouped by search type.
"""
if ttl_extr is True and ttl_path is None:
raise ValueError("A file path must be provided via ttl_path to save the results when ttl_extr is enabled.")
# Define namespace
MDS = Namespace("https://cwrusdle.bitbucket.io/mds/")
# Load ontology
if mds_ontology_graph is None:
mds_ontology_graph = load_mds_ontology_graph()
# Predicate map
type_to_pred = {
"Domain": MDS.hasDomain,
"SubDomain": MDS.hasSubDomain,
"Study Stage": MDS.hasStudyStage,
}
if search_types is None:
print("No search types specified.")
return
if query_term is not None:
query_term = query_term.lower()
any_matches = False
results_graph = Graph() if ttl_extr is True else None
for search_type in search_types:
if search_type not in type_to_pred:
print(f"Unsupported search type: {search_type}")
continue
pred = type_to_pred[search_type]
matches = set()
for subj, obj in mds_ontology_graph.subject_objects(predicate=pred):
if query_term is None or str(obj).lower() == query_term:
matches.add(subj)
if matches:
any_matches = True
print(f"\nTerms with {search_type}" + (f" matching '{query_term}'" if query_term else "") + ":")
for s in sorted(matches, key=lambda x: str(x)):
label = mds_ontology_graph.value(subject=s, predicate=RDFS.label)
label_str = str(label) if label else f"[no label for {s}]"
print(f" {label_str}")
# Add the found triple to our single results graph
if results_graph is not None:
results_graph.add((subj, None, None))
if ttl_extr == 1:
results_graph.serialize(destination=ttl_path, format="turtle")
if not any_matches:
print("No matches found.")
[docs]
def filter_interface(args):
"""
Term search using Domain, SubDomain, or Study Stage. For complete list of Domains and SubDomains,
run the following commands in bash:
FAIRLinked view-domains
FAIRLinked dir-make.
The current list of Study Stages include:
Synthesis,
Formulation,
Materials Processing,
Sample,
Tool,
Recipe,
Result,
Analysis,
Modelling.
For more details about Study Stages, please view go see https://cwrusdle.bitbucket.io/.
"""
if args.ontology_path == "default":
ontology_graph = load_mds_ontology_graph()
else:
ontology_graph = Graph()
ontology_graph.parse(args.ontology_path)
if args.ttl_extr == "F":
args.ttl_extr = False
elif args.ttl_extra == "T":
args.ttl_extr = True
term_search_general(mds_ontology_graph=ontology_graph,
query_term=args.query_term,
search_types=args.search_types,
ttl_extr=args.ttl_extr,
ttl_path=args.ttl_path)