| """Unit tests for the :mod:`networkx.algorithms.efficiency` module.""" |
|
|
| import networkx as nx |
|
|
|
|
| class TestEfficiency: |
| def setup_method(self): |
| |
| self.G1 = nx.Graph() |
| self.G1.add_nodes_from([1, 2, 3]) |
| |
| self.G2 = nx.cycle_graph(4) |
| |
| self.G3 = nx.lollipop_graph(3, 1) |
|
|
| def test_efficiency_disconnected_nodes(self): |
| """ |
| When nodes are disconnected, efficiency is 0 |
| """ |
| assert nx.efficiency(self.G1, 1, 2) == 0 |
|
|
| def test_local_efficiency_disconnected_graph(self): |
| """ |
| In a disconnected graph the efficiency is 0 |
| """ |
| assert nx.local_efficiency(self.G1) == 0 |
|
|
| def test_efficiency(self): |
| assert nx.efficiency(self.G2, 0, 1) == 1 |
| assert nx.efficiency(self.G2, 0, 2) == 1 / 2 |
|
|
| def test_global_efficiency(self): |
| assert nx.global_efficiency(self.G2) == 5 / 6 |
|
|
| def test_global_efficiency_complete_graph(self): |
| """ |
| Tests that the average global efficiency of the complete graph is one. |
| """ |
| for n in range(2, 10): |
| G = nx.complete_graph(n) |
| assert nx.global_efficiency(G) == 1 |
|
|
| def test_local_efficiency_complete_graph(self): |
| """ |
| Test that the local efficiency for a complete graph with at least 3 |
| nodes should be one. For a graph with only 2 nodes, the induced |
| subgraph has no edges. |
| """ |
| for n in range(3, 10): |
| G = nx.complete_graph(n) |
| assert nx.local_efficiency(G) == 1 |
|
|
| def test_using_ego_graph(self): |
| """ |
| Test that the ego graph is used when computing local efficiency. |
| For more information, see GitHub issue #2710. |
| """ |
| assert nx.local_efficiency(self.G3) == 7 / 12 |
|
|
