aboutsummaryrefslogtreecommitdiff
path: root/.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_efficiency.py
diff options
context:
space:
mode:
Diffstat (limited to '.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_efficiency.py')
-rw-r--r--.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_efficiency.py58
1 files changed, 58 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_efficiency.py b/.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_efficiency.py
new file mode 100644
index 00000000..9a2e7d04
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_efficiency.py
@@ -0,0 +1,58 @@
+"""Unit tests for the :mod:`networkx.algorithms.efficiency` module."""
+
+import networkx as nx
+
+
+class TestEfficiency:
+ def setup_method(self):
+ # G1 is a disconnected graph
+ self.G1 = nx.Graph()
+ self.G1.add_nodes_from([1, 2, 3])
+ # G2 is a cycle graph
+ self.G2 = nx.cycle_graph(4)
+ # G3 is the triangle graph with one additional edge
+ 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