def test_dual_barabasi_albert(self, m1=1, m2=4, p=0.5):
"""
Tests that the dual BA random graph generated behaves consistently.
Tests the exceptions are raised as expected.
The graphs generation are repeated several times to prevent lucky shots
"""
seed = 42
repeats = 2
while repeats:
repeats -= 1
# This should be BA with m = m1
BA1 = barabasi_albert_graph(100, m1, seed)
DBA1 = dual_barabasi_albert_graph(100, m1, m2, 1, seed)
assert_equal(BA1.size(), DBA1.size())
# This should be BA with m = m2
BA2 = barabasi_albert_graph(100, m2, seed)
DBA2 = dual_barabasi_albert_graph(100, m1, m2, 0, seed)
assert_equal(BA2.size(), DBA2.size())
# Testing exceptions
dbag = dual_barabasi_albert_graph
assert_raises(NetworkXError, dbag, m1, m1, m2, 0)
assert_raises(NetworkXError, dbag, m2, m1, m2, 0)
assert_raises(NetworkXError, dbag, 100, m1, m2, -0.5)
assert_raises(NetworkXError, dbag, 100, m1, m2, 1.5)
def test_dual_barabasi_albert(self, m1=1, m2=4, p=0.5):
"""
Tests that the dual BA random graph generated behaves consistently.
Tests the exceptions are raised as expected.
The graphs generation are repeated several times to prevent lucky shots
"""
seed = 42
repeats = 2
while repeats:
repeats -= 1
# This should be BA with m = m1
BA1 = barabasi_albert_graph(100, m1, seed)
DBA1 = dual_barabasi_albert_graph(100, m1, m2, 1, seed)
assert BA1.size() == DBA1.size()
# This should be BA with m = m2
BA2 = barabasi_albert_graph(100, m2, seed)
DBA2 = dual_barabasi_albert_graph(100, m1, m2, 0, seed)
assert BA2.size() == DBA2.size()
# Testing exceptions
dbag = dual_barabasi_albert_graph
pytest.raises(NetworkXError, dbag, m1, m1, m2, 0)
pytest.raises(NetworkXError, dbag, m2, m1, m2, 0)
pytest.raises(NetworkXError, dbag, 100, m1, m2, -0.5)
pytest.raises(NetworkXError, dbag, 100, m1, m2, 1.5)
