1 files changed, 140 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_node_classification.py b/.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_node_classification.py
new file mode 100644
index 00000000..2e1fc79d
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_node_classification.py
@@ -0,0 +1,140 @@
+import pytest
+
+pytest.importorskip("numpy")
+pytest.importorskip("scipy")
+
+import networkx as nx
+from networkx.algorithms import node_classification
+
+
+class TestHarmonicFunction:
+    def test_path_graph(self):
+        G = nx.path_graph(4)
+        label_name = "label"
+        G.nodes[0][label_name] = "A"
+        G.nodes[3][label_name] = "B"
+        predicted = node_classification.harmonic_function(G, label_name=label_name)
+        assert predicted[0] == "A"
+        assert predicted[1] == "A"
+        assert predicted[2] == "B"
+        assert predicted[3] == "B"
+
+    def test_no_labels(self):
+        with pytest.raises(nx.NetworkXError):
+            G = nx.path_graph(4)
+            node_classification.harmonic_function(G)
+
+    def test_no_nodes(self):
+        with pytest.raises(nx.NetworkXError):
+            G = nx.Graph()
+            node_classification.harmonic_function(G)
+
+    def test_no_edges(self):
+        with pytest.raises(nx.NetworkXError):
+            G = nx.Graph()
+            G.add_node(1)
+            G.add_node(2)
+            node_classification.harmonic_function(G)
+
+    def test_digraph(self):
+        with pytest.raises(nx.NetworkXNotImplemented):
+            G = nx.DiGraph()
+            G.add_edge(0, 1)
+            G.add_edge(1, 2)
+            G.add_edge(2, 3)
+            label_name = "label"
+            G.nodes[0][label_name] = "A"
+            G.nodes[3][label_name] = "B"
+            node_classification.harmonic_function(G)
+
+    def test_one_labeled_node(self):
+        G = nx.path_graph(4)
+        label_name = "label"
+        G.nodes[0][label_name] = "A"
+        predicted = node_classification.harmonic_function(G, label_name=label_name)
+        assert predicted[0] == "A"
+        assert predicted[1] == "A"
+        assert predicted[2] == "A"
+        assert predicted[3] == "A"
+
+    def test_nodes_all_labeled(self):
+        G = nx.karate_club_graph()
+        label_name = "club"
+        predicted = node_classification.harmonic_function(G, label_name=label_name)
+        for i in range(len(G)):
+            assert predicted[i] == G.nodes[i][label_name]
+
+    def test_labeled_nodes_are_not_changed(self):
+        G = nx.karate_club_graph()
+        label_name = "club"
+        label_removed = {0, 1, 2, 3, 4, 5, 6, 7}
+        for i in label_removed:
+            del G.nodes[i][label_name]
+        predicted = node_classification.harmonic_function(G, label_name=label_name)
+        label_not_removed = set(range(len(G))) - label_removed
+        for i in label_not_removed:
+            assert predicted[i] == G.nodes[i][label_name]
+
+
+class TestLocalAndGlobalConsistency:
+    def test_path_graph(self):
+        G = nx.path_graph(4)
+        label_name = "label"
+        G.nodes[0][label_name] = "A"
+        G.nodes[3][label_name] = "B"
+        predicted = node_classification.local_and_global_consistency(
+            G, label_name=label_name
+        )
+        assert predicted[0] == "A"
+        assert predicted[1] == "A"
+        assert predicted[2] == "B"
+        assert predicted[3] == "B"
+
+    def test_no_labels(self):
+        with pytest.raises(nx.NetworkXError):
+            G = nx.path_graph(4)
+            node_classification.local_and_global_consistency(G)
+
+    def test_no_nodes(self):
+        with pytest.raises(nx.NetworkXError):
+            G = nx.Graph()
+            node_classification.local_and_global_consistency(G)
+
+    def test_no_edges(self):
+        with pytest.raises(nx.NetworkXError):
+            G = nx.Graph()
+            G.add_node(1)
+            G.add_node(2)
+            node_classification.local_and_global_consistency(G)
+
+    def test_digraph(self):
+        with pytest.raises(nx.NetworkXNotImplemented):
+            G = nx.DiGraph()
+            G.add_edge(0, 1)
+            G.add_edge(1, 2)
+            G.add_edge(2, 3)
+            label_name = "label"
+            G.nodes[0][label_name] = "A"
+            G.nodes[3][label_name] = "B"
+            node_classification.harmonic_function(G)
+
+    def test_one_labeled_node(self):
+        G = nx.path_graph(4)
+        label_name = "label"
+        G.nodes[0][label_name] = "A"
+        predicted = node_classification.local_and_global_consistency(
+            G, label_name=label_name
+        )
+        assert predicted[0] == "A"
+        assert predicted[1] == "A"
+        assert predicted[2] == "A"
+        assert predicted[3] == "A"
+
+    def test_nodes_all_labeled(self):
+        G = nx.karate_club_graph()
+        label_name = "club"
+        predicted = node_classification.local_and_global_consistency(
+            G, alpha=0, label_name=label_name
+        )
+        for i in range(len(G)):
+            assert predicted[i] == G.nodes[i][label_name]