"""Unit tests for the :mod:`networkx.algorithms.structuralholes` module.""" import math import pytest import networkx as nx class TestStructuralHoles: """Unit tests for computing measures of structural holes. The expected values for these functions were originally computed using the proprietary software `UCINET`_ and the free software `IGraph`_ , and then computed by hand to make sure that the results are correct. .. _UCINET: https://sites.google.com/site/ucinetsoftware/home .. _IGraph: http://igraph.org/ """ def setup(self): self.D = nx.DiGraph() self.D.add_edges_from([(0, 1), (0, 2), (1, 0), (2, 1)]) self.D_weights = {(0, 1): 2, (0, 2): 2, (1, 0): 1, (2, 1): 1} # Example from http://www.analytictech.com/connections/v20(1)/holes.htm self.G = nx.Graph() self.G.add_edges_from( [ ("A", "B"), ("A", "F"), ("A", "G"), ("A", "E"), ("E", "G"), ("F", "G"), ("B", "G"), ("B", "D"), ("D", "G"), ("G", "C"), ] ) self.G_weights = { ("A", "B"): 2, ("A", "F"): 3, ("A", "G"): 5, ("A", "E"): 2, ("E", "G"): 8, ("F", "G"): 3, ("B", "G"): 4, ("B", "D"): 1, ("D", "G"): 3, ("G", "C"): 10, } def test_constraint_directed(self): constraint = nx.constraint(self.D) assert constraint[0] == pytest.approx(1.003, abs=1e-3) assert constraint[1] == pytest.approx(1.003, abs=1e-3) assert constraint[2] == pytest.approx(1.389, abs=1e-3) def test_effective_size_directed(self): effective_size = nx.effective_size(self.D) assert effective_size[0] == pytest.approx(1.167, abs=1e-3) assert effective_size[1] == pytest.approx(1.167, abs=1e-3) assert effective_size[2] == pytest.approx(1, abs=1e-3) def test_constraint_weighted_directed(self): D = self.D.copy() nx.set_edge_attributes(D, self.D_weights, "weight") constraint = nx.constraint(D, weight="weight") assert constraint[0] == pytest.approx(0.840, abs=1e-3) assert constraint[1] == pytest.approx(1.143, abs=1e-3) assert constraint[2] == pytest.approx(1.378, abs=1e-3) def test_effective_size_weighted_directed(self): D = self.D.copy() nx.set_edge_attributes(D, self.D_weights, "weight") effective_size = nx.effective_size(D, weight="weight") assert effective_size[0] == pytest.approx(1.567, abs=1e-3) assert effective_size[1] == pytest.approx(1.083, abs=1e-3) assert effective_size[2] == pytest.approx(1, abs=1e-3) def test_constraint_undirected(self): constraint = nx.constraint(self.G) assert constraint["G"] == pytest.approx(0.400, abs=1e-3) assert constraint["A"] == pytest.approx(0.595, abs=1e-3) assert constraint["C"] == pytest.approx(1, abs=1e-3) def test_effective_size_undirected_borgatti(self): effective_size = nx.effective_size(self.G) assert effective_size["G"] == pytest.approx(4.67, abs=1e-2) assert effective_size["A"] == pytest.approx(2.50, abs=1e-2) assert effective_size["C"] == pytest.approx(1, abs=1e-2) def test_effective_size_undirected(self): G = self.G.copy() nx.set_edge_attributes(G, 1, "weight") effective_size = nx.effective_size(G, weight="weight") assert effective_size["G"] == pytest.approx(4.67, abs=1e-2) assert effective_size["A"] == pytest.approx(2.50, abs=1e-2) assert effective_size["C"] == pytest.approx(1, abs=1e-2) def test_constraint_weighted_undirected(self): G = self.G.copy() nx.set_edge_attributes(G, self.G_weights, "weight") constraint = nx.constraint(G, weight="weight") assert constraint["G"] == pytest.approx(0.299, abs=1e-3) assert constraint["A"] == pytest.approx(0.795, abs=1e-3) assert constraint["C"] == pytest.approx(1, abs=1e-3) def test_effective_size_weighted_undirected(self): G = self.G.copy() nx.set_edge_attributes(G, self.G_weights, "weight") effective_size = nx.effective_size(G, weight="weight") assert effective_size["G"] == pytest.approx(5.47, abs=1e-2) assert effective_size["A"] == pytest.approx(2.47, abs=1e-2) assert effective_size["C"] == pytest.approx(1, abs=1e-2) def test_constraint_isolated(self): G = self.G.copy() G.add_node(1) constraint = nx.constraint(G) assert math.isnan(constraint[1]) def test_effective_size_isolated(self): G = self.G.copy() G.add_node(1) nx.set_edge_attributes(G, self.G_weights, "weight") effective_size = nx.effective_size(G, weight="weight") assert math.isnan(effective_size[1]) def test_effective_size_borgatti_isolated(self): G = self.G.copy() G.add_node(1) effective_size = nx.effective_size(G) assert math.isnan(effective_size[1])