def make_sim_graphs(school_graphs, school_akws):
"""
Takes school graphs dict and school author-kw dict and makes a keyword similarity graph for each school.
Returns dict keyed by school name with sim graphs as values.
"""
school_simgraphs = {}
for school in school_graphs:
collab_graph = school_graphs[school]
akw = school_akws[school]
sim_graph = gu.make_sim_graph(akw, collab_graph)
school_simgraphs[school] = sim_graph
return school_simgraphs
def test_sim_graph_making(self):
akw = {
1: {"keywords": ["java", "python", "django"]},
2: {"keywords": ["java", "python", "graphs"]},
3: {"keywords": ["software", "graphs", "programming"]}
}
col_graph = nx.Graph()
col_graph.add_node(1, {"name": 'bob', 'in_school': True, 'paper_count': 12})
col_graph.add_node(2, {"name": 'alice', 'in_school': True, 'paper_count': 10})
col_graph.add_node(3, {"name": 'eve', 'in_school': True, 'paper_count': 20})
col_graph.add_edge(1, 3)
sim_graph = gu.make_sim_graph(akw, col_graph)
self.assertEqual(sim_graph.number_of_nodes(), 3)
self.assertEqual(sim_graph.number_of_edges(), 2)
self.assertTrue(sim_graph.has_edge(1, 2) and sim_graph.has_edge(2, 3))
self.assertTrue("java" in sim_graph[1][2]['sim_kw'] and "python" in sim_graph[1][2]['sim_kw'])
self.assertTrue("graphs" in sim_graph[2][3]['sim_kw'])