Projekt_AI-Automatyczny_saper/venv/Lib/site-packages/networkx/algorithms/tests/test_structuralholes.py
2021-06-01 17:38:31 +02:00

134 lines
5.1 KiB
Python

"""Unit tests for the :mod:`networkx.algorithms.structuralholes` module."""
import math
import networkx as nx
from networkx.testing import almost_equal
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 almost_equal(constraint[0], 1.003, places=3)
assert almost_equal(constraint[1], 1.003, places=3)
assert almost_equal(constraint[2], 1.389, places=3)
def test_effective_size_directed(self):
effective_size = nx.effective_size(self.D)
assert almost_equal(effective_size[0], 1.167, places=3)
assert almost_equal(effective_size[1], 1.167, places=3)
assert almost_equal(effective_size[2], 1, places=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 almost_equal(constraint[0], 0.840, places=3)
assert almost_equal(constraint[1], 1.143, places=3)
assert almost_equal(constraint[2], 1.378, places=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 almost_equal(effective_size[0], 1.567, places=3)
assert almost_equal(effective_size[1], 1.083, places=3)
assert almost_equal(effective_size[2], 1, places=3)
def test_constraint_undirected(self):
constraint = nx.constraint(self.G)
assert almost_equal(constraint["G"], 0.400, places=3)
assert almost_equal(constraint["A"], 0.595, places=3)
assert almost_equal(constraint["C"], 1, places=3)
def test_effective_size_undirected_borgatti(self):
effective_size = nx.effective_size(self.G)
assert almost_equal(effective_size["G"], 4.67, places=2)
assert almost_equal(effective_size["A"], 2.50, places=2)
assert almost_equal(effective_size["C"], 1, places=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 almost_equal(effective_size["G"], 4.67, places=2)
assert almost_equal(effective_size["A"], 2.50, places=2)
assert almost_equal(effective_size["C"], 1, places=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 almost_equal(constraint["G"], 0.299, places=3)
assert almost_equal(constraint["A"], 0.795, places=3)
assert almost_equal(constraint["C"], 1, places=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 almost_equal(effective_size["G"], 5.47, places=2)
assert almost_equal(effective_size["A"], 2.47, places=2)
assert almost_equal(effective_size["C"], 1, places=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])