def subset_data(df, heads, threshold):
if isinstance(heads, str):
heads = [heads]
data = df.copy()
data = data.loc[(data["head"].isin(heads))
& (data["confidence"] > threshold), ]
store = TripleStore()
for idx, rel in data.iterrows():
store.add_triple(rel["head"], rel["relation"], rel["tail"])
return store
def get_inspired():
sparql = SPARQLWrapper("http://dbpedia.org/sparql")
query_string = """
SELECT ?name_pe1_en ?rel_en ?name_pe2_en
WHERE {
{
SELECT ?name_p1 ?rel ?name_p2
WHERE {
?p1 a foaf:Person .
?p1 dbo:influencedBy ?p2 .
?p2 a foaf:Person .
?p1 foaf:name ?name_p1 .
?p2 foaf:name ?name_p2 .
dbo:influencedBy rdfs:label ?rel .
}
LIMIT 100
}
UNION
{
SELECT ?name_p1 ?rel ?name_p2
WHERE {
?p1 a foaf:Person .
?p1 dbo:influenced ?p2 .
?p2 a foaf:Person .
?p1 foaf:name ?name_p1 .
?p2 foaf:name ?name_p2 .
dbo:influenced rdfs:label ?rel .
}
LIMIT 100
}
FILTER ( LANG(?name_p1) = "en" && LANG(?rel) = "en" && LANG(?name_p2) = "en" )
BIND ( STR(?name_p1) AS ?name_pe1_en )
BIND ( STR(?rel) AS ?rel_en )
BIND ( STR(?name_p2) AS ?name_pe2_en )
}
"""
sparql.setQuery(query_string)
sparql.setReturnFormat(JSON)
results = sparql.query().convert()
store = TripleStore()
for result in results["results"]["bindings"]:
node1 = result["name_pe1_en"]["value"]
link = result["rel_en"]["value"]
node2 = result["name_pe2_en"]["value"]
store.add_triple(node1, link, node2)
return store
def load_persons(recource, store:TripleStore=None):
if store == None:
store = TripleStore()
sparql = SPARQLWrapper("http://dbpedia.org/sparql")
# queryString = "SELECT * WHERE { ?s ?p ?o. }"
target = f"<http://dbpedia.org/resource/{recource}>"
query_string = "PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> " \
"PREFIX dbo: <http://dbpedia.org/ontology/>" \
"SELECT ?label ?birthPlace ?birthDate ?deathDate ?picture ?abstract " \
f"WHERE {{ {target} " \
"rdfs:label ?label ." \
f"OPTIONAL {{ {target} " \
"dbo:birthPlace ?birthPlace;" \
"dbo:birthDate ?birthDate;" \
"dbo:deathDate ?deathDate;" \
"dbo:abstract ?abstract;" \
"dbo:thumbnail ?picture ." \
"}" \
"filter langMatches( lang(?label), 'EN' ) }" \
"LIMIT 1"
# st.write(query_string)
sparql.setQuery(query_string)
# sparql = SPARQLWrapper("http://dbpedia.org/sparql/resource/Asturias")
# sparql.setReturnFormat(N3)
sparql.setReturnFormat(JSON)
# sparql.setQuery(queryString)
results = sparql.query().convert()
abstract = ""
picture = ""
for result in results["results"]["bindings"]:
subj = result["label"]["value"]
if "picture" in result:
picture = result["picture"]["value"]
if "abstract" in result:
abstract = result["abstract"]["value"]
# pic, picture = circle_image(picture, size=(300, 300))
for label in result:
if not label == "picture" and not label == subj and not label == "abstract":
pred = label
if "http://dbpedia.org/resource/" in result[label]["value"]:
obj = result[label]["value"].rsplit("/", 1)[1]
else:
obj = result[label]["value"]
# st.write(subj, pred, obj)
store.add_triple(subj, pred, obj, picture)
return store, abstract
def do_query(recource):
sparql = SPARQLWrapper("http://dbpedia.org/sparql")
# queryString = "SELECT * WHERE { ?s ?p ?o. }"
query_string = "PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> " \
"PREFIX dbo: <http://dbpedia.org/ontology/>" \
"SELECT ?label ?birthPlace ?birthDate ?picture " \
f"WHERE {{ <http://dbpedia.org/resource/{recource}> " \
"rdfs:label ?label;" \
"dbo:birthPlace ?birthPlace;" \
"dbo:birthDate ?birthDate;" \
"dbo:thumbnail ?picture ." \
"filter langMatches( lang(?label), 'EN' ) }" \
"LIMIT 1"
# st.write(query_string)
sparql.setQuery(query_string)
# sparql = SPARQLWrapper("http://dbpedia.org/sparql/resource/Asturias")
# sparql.setReturnFormat(N3)
sparql.setReturnFormat(JSON)
# sparql.setQuery(queryString)
results = sparql.query().convert()
store = TripleStore()
for result in results["results"]["bindings"]:
subj = result["label"]["value"]
picture = result["picture"]["value"]
picture = circle_image(picture, size=(300, 300))
for label in result:
if not label == "picture" and not label ==subj:
pred = label
if "http://dbpedia.org/resource/" in result[label]["value"]:
obj = result[label]["value"].rsplit("/", 1)[1]
else:
obj = result[label]["value"]
# st.write(subj, pred, obj)
store.add_triple(subj, pred, obj, picture)
return list(store.nodes_set), list(store.edges_set)
def app():
footer()
st.title("Graph Example")
st.sidebar.title("Welcome")
query_type = st.sidebar.selectbox(
"Query Tpye: ", ["Inspirationals", "Marvel"]
) # could add more stuff here later on or add other endpoints in the sidebar.
config = Config(height=600,
width=700,
nodeHighlightBehavior=True,
highlightColor="#F7A7A6",
directed=True,
collapsible=True)
if query_type == "Inspirationals":
st.subheader("Inspirationals")
with st.spinner("Loading data"):
store = get_inspired()
st.write("Nodes loaded: " + str(len(store.getNodes())))
st.success("Done")
agraph(list(store.getNodes()), (store.getEdges()), config)
if query_type == "Marvel":
#based on http://marvel-force-chart.surge.sh/
with open("./marvel.json", encoding="utf8") as f:
marvel_file = json.loads(f.read())
marvel_store = TripleStore()
for sub_graph in marvel_file["children"]:
marvel_store.add_triple(marvel_file["name"],
"has_subgroup",
sub_graph["name"],
picture=marvel_file["img"])
for node in sub_graph["children"]:
node1 = node["hero"]
link = "blongs_to"
node2 = sub_graph["name"]
pic = node["img"]
marvel_store.add_triple(node1, link, node2, picture=pic)
agraph(list(marvel_store.getNodes()), (marvel_store.getEdges()),
config)
def beliefgraph_to_triplestore(graph, nodes: set):
store = TripleStore()
for triplet in graph.filtered_triplets:
if triplet.head in nodes:
store.add_triple(triplet.head, triplet.relation, triplet.tail)
return store
config = Config(height=500, width=700, nodeHighlightBehavior=True,
highlightColor="#F7A7A6", directed=True, collapsible=True)
=======
config = Config(height=500,
width=700,
nodeHighlightBehavior=True,
highlightColor="#F7A7A6",
directed=True,
collapsible=True,
link={'labelProperty': 'label', 'renderLabel': True}
)
>>>>>>> 6f6a9624da414e66674de21213f6c8f387db8519
if algo_type == "Shortest Path":
if chosen_person_a != "" and chosen_person_b != "" and chosen_person_a != chosen_person_b:
analysis_results = algos.shortest_path(chosen_person_a, chosen_person_b)
sp_store = TripleStore()
if len(analysis_results) > 0:
for idx, connection in enumerate(analysis_results):
n1 = connection.replace(" ", "_")
if idx + 1 < len(analysis_results):
n2 = analysis_results[idx + 1]
sp_store.add_triple(connection, "knows", n2, "")
sp_store, _ = load_persons(n1, sp_store)
agraph(list(sp_store.getNodes()), (sp_store.getEdges()), config)
else:
st.write("None connections found. Try something else.")
else:
st.write("Choose choose different persons first.")
else:
agraph(list(store.getNodes()), (store.getEdges()), config)