class_docstr: Unit tests for the multi-source dialect of Dijkstra's shortest
  path algorithms.
class_docstr_tok: ["Unit","tests","for","the","multi-source","dialect","of","Dijkstra","'s","shortest","path","algorithms","."]
code: def test_two_sources(self):
      edges = [(0, 1, 1), (1, 2, 1), (2, 3, 10), (3, 4, 1)]
      G = nx.Graph()
      G.add_weighted_edges_from(edges)
      sources = {0, 4}
      distances, paths = nx.multi_source_dijkstra(G, sources)
      expected_distances = {0: 0, 1: 1, 2: 2, 3: 1, 4: 0}
      expected_paths = {
          0: [0],
          1: [0, 1],
          2: [0, 1, 2],
          3: [4, 3],
          4: [4],
      }
      assert distances == expected_distances
      assert paths == expected_paths
  
imports: import pytest
  import networkx
  from networkx.utils import pairwise
label_desc: Use image node_id 5 for calling the TestMultiSourceDijkstra obj's underlying member method code with example usage: obj.test_two_sources() without return types