added new graph metrics

tests/analysis/test_graphs.py

@@ -2,7 +2,12 @@ import networkx as nx
 import pytest
 
 from lang_main.analysis import graphs
-from lang_main.errors import EmptyEdgesError, EmptyGraphError, EdgePropertyNotContainedError
+from lang_main.errors import (
+    EdgePropertyNotContainedError,
+    EmptyEdgesError,
+    EmptyGraphError,
+    NodePropertyNotContainedError,
+)
 
 TK_GRAPH_NAME = 'TEST_TOKEN_GRAPH'
 
@@ -231,6 +236,49 @@ def test_add_weighted_degree():
     assert graph_obj.nodes[3][property_name] == 6
 
 
+def test_add_betweenness_centrality():
+    graph_obj = build_init_graph(token_graph=False)
+    property_name = 'betweenness_centrality'
+    graphs.add_betweenness_centrality(graph_obj, property_name=property_name)
+    assert round(graph_obj.nodes[1][property_name], 4) == pytest.approx(0.1667)
+    assert graph_obj.nodes[2][property_name] == 0
+    assert graph_obj.nodes[3][property_name] == 0
+
+
+def test_add_importance_metric():
+    graph_obj = build_init_graph(token_graph=False)
+    property_name_WD = 'degree_weighted'
+    graphs.add_weighted_degree(graph_obj, 'weight', property_name_WD)
+    property_name_BC = 'betweenness_centrality'
+    graphs.add_betweenness_centrality(graph_obj, property_name=property_name_BC)
+    property_name = 'importance'
+    graphs.add_importance_metric(
+        graph_obj,
+        property_name=property_name,
+        property_name_weighted_degree=property_name_WD,
+        property_name_betweenness=property_name_BC,
+    )
+    assert round(graph_obj.nodes[1][property_name], 4) == pytest.approx(2.3333)
+    assert graph_obj.nodes[2][property_name] == 0
+    assert graph_obj.nodes[3][property_name] == 0
+
+    with pytest.raises(NodePropertyNotContainedError):
+        graphs.add_importance_metric(
+            graph_obj,
+            property_name=property_name,
+            property_name_weighted_degree='prop_not_contained',
+            property_name_betweenness=property_name_BC,
+        )
+
+    with pytest.raises(NodePropertyNotContainedError):
+        graphs.add_importance_metric(
+            graph_obj,
+            property_name=property_name,
+            property_name_weighted_degree=property_name_WD,
+            property_name_betweenness='prop_not_contained',
+        )
+
+
 def test_static_graph_analysis():
     graph_obj = build_init_graph(token_graph=True)
     (graph_obj,) = graphs.static_graph_analysis(graph_obj)  # type: ignore
@@ -254,6 +302,20 @@ def test_pipe_add_graph_metrics():
     assert graph_collection[1].nodes[1][property_name] == 14
     assert graph_collection[1].nodes[2][property_name] == 10
     assert graph_collection[1].nodes[3][property_name] == 6
+    property_name = 'betweenness_centrality'
+    assert round(graph_collection[0].nodes[1][property_name], 4) == pytest.approx(0.1667)
+    assert graph_collection[0].nodes[2][property_name] == 0
+    assert graph_collection[0].nodes[3][property_name] == 0
+    assert round(graph_collection[1].nodes[1][property_name], 4) == pytest.approx(0.1667)
+    assert graph_collection[1].nodes[2][property_name] == 0
+    assert graph_collection[1].nodes[3][property_name] == 0
+    property_name = 'importance'
+    assert round(graph_collection[0].nodes[1][property_name], 4) == pytest.approx(2.3333)
+    assert graph_collection[0].nodes[2][property_name] == 0
+    assert graph_collection[0].nodes[3][property_name] == 0
+    assert round(graph_collection[1].nodes[1][property_name], 4) == pytest.approx(2.3333)
+    assert graph_collection[1].nodes[2][property_name] == 0
+    assert graph_collection[1].nodes[3][property_name] == 0
 
 
 def test_pipe_rescale_graph_edge_weights(tk_graph):