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"""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])
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