"""Tests for the :mod:`networkx.algorithms.triads` module."""
import itertools
from collections import defaultdict
from random import sample
import pytest
import networkx as nx
def test_all_triplets_deprecated():
G = nx.DiGraph([(1, 2), (2, 3), (3, 4)])
with pytest.deprecated_call():
nx.all_triplets(G)
def test_random_triad_deprecated():
G = nx.path_graph(3, create_using=nx.DiGraph)
with pytest.deprecated_call():
nx.random_triad(G)
def test_triadic_census():
"""Tests the triadic_census function."""
G = nx.DiGraph()
G.add_edges_from(["01", "02", "03", "04", "05", "12", "16", "51", "56", "65"])
expected = {
"030T": 2,
"120C": 1,
"210": 0,
"120U": 0,
"012": 9,
"102": 3,
"021U": 0,
"111U": 0,
"003": 8,
"030C": 0,
"021D": 9,
"201": 0,
"111D": 1,
"300": 0,
"120D": 0,
"021C": 2,
}
actual = nx.triadic_census(G)
assert expected == actual
def test_is_triad():
"""Tests the is_triad function"""
G = nx.karate_club_graph()
G = G.to_directed()
for i in range(100):
nodes = sample(sorted(G.nodes()), 3)
G2 = G.subgraph(nodes)
assert nx.is_triad(G2)
def test_all_triplets():
"""Tests the all_triplets function."""
G = nx.DiGraph()
G.add_edges_from(["01", "02", "03", "04", "05", "12", "16", "51", "56", "65"])
expected = [
f"{i},{j},{k}"
for i in range(7)
for j in range(i + 1, 7)
for k in range(j + 1, 7)
]
expected = [set(x.split(",")) for x in expected]
actual = [set(x) for x in nx.all_triplets(G)]
assert all(any(s1 == s2 for s1 in expected) for s2 in actual)
def test_all_triads():
"""Tests the all_triplets function."""
G = nx.DiGraph()
G.add_edges_from(["01", "02", "03", "04", "05", "12", "16", "51", "56", "65"])
expected = [
f"{i},{j},{k}"
for i in range(7)
for j in range(i + 1, 7)
for k in range(j + 1, 7)
]
expected = [G.subgraph(x.split(",")) for x in expected]
actual = list(nx.all_triads(G))
assert all(any(nx.is_isomorphic(G1, G2) for G1 in expected) for G2 in actual)
def test_triad_type():
"""Tests the triad_type function."""
# 0 edges (1 type)
G = nx.DiGraph({0: [], 1: [], 2: []})
assert nx.triad_type(G) == "003"
# 1 edge (1 type)
G = nx.DiGraph({0: [1], 1: [], 2: []})
assert nx.triad_type(G) == "012"
# 2 edges (4 types)
G = nx.DiGraph([(0, 1), (0, 2)])
assert nx.triad_type(G) == "021D"
G = nx.DiGraph({0: [1], 1: [0], 2: []})
assert nx.triad_type(G) == "102"
G = nx.DiGraph([(0, 1), (2, 1)])
assert nx.triad_type(G) == "021U"
G = nx.DiGraph([(0, 1), (1, 2)])
assert nx.triad_type(G) == "021C"
# 3 edges (4 types)
G = nx.DiGraph([(0, 1), (1, 0), (2, 1)])
assert nx.triad_type(G) == "111D"
G = nx.DiGraph([(0, 1), (1, 0), (1, 2)])
assert nx.triad_type(G) == "111U"
G = nx.DiGraph([(0, 1), (1, 2), (0, 2)])
assert nx.triad_type(G) == "030T"
G = nx.DiGraph([(0, 1), (1, 2), (2, 0)])
assert nx.triad_type(G) == "030C"
# 4 edges (4 types)
G = nx.DiGraph([(0, 1), (1, 0), (2, 0), (0, 2)])
assert nx.triad_type(G) == "201"
G = nx.DiGraph([(0, 1), (1, 0), (2, 0), (2, 1)])
assert nx.triad_type(G) == "120D"
G = nx.DiGraph([(0, 1), (1, 0), (0, 2), (1, 2)])
assert nx.triad_type(G) == "120U"
G = nx.DiGraph([(0, 1), (1, 0), (0, 2), (2, 1)])
assert nx.triad_type(G) == "120C"
# 5 edges (1 type)
G = nx.DiGraph([(0, 1), (1, 0), (2, 1), (1, 2), (0, 2)])
assert nx.triad_type(G) == "210"
# 6 edges (1 type)
G = nx.DiGraph([(0, 1), (1, 0), (1, 2), (2, 1), (0, 2), (2, 0)])
assert nx.triad_type(G) == "300"
def test_triads_by_type():
"""Tests the all_triplets function."""
G = nx.DiGraph()
G.add_edges_from(["01", "02", "03", "04", "05", "12", "16", "51", "56", "65"])
all_triads = nx.all_triads(G)
expected = defaultdict(list)
for triad in all_triads:
name = nx.triad_type(triad)
expected[name].append(triad)
actual = nx.triads_by_type(G)
assert set(actual.keys()) == set(expected.keys())
for tri_type, actual_Gs in actual.items():
expected_Gs = expected[tri_type]
for a in actual_Gs:
assert any(nx.is_isomorphic(a, e) for e in expected_Gs)
def test_random_triad():
"""Tests the random_triad function"""
G = nx.karate_club_graph()
G = G.to_directed()
for i in range(100):
assert nx.is_triad(nx.random_triad(G))
G = nx.DiGraph()
msg = "at least 3 nodes to form a triad"
with pytest.raises(nx.NetworkXError, match=msg):
nx.random_triad(G)
def test_triadic_census_short_path_nodelist():
G = nx.path_graph("abc", create_using=nx.DiGraph)
expected = {"021C": 1}
for nl in ["a", "b", "c", "ab", "ac", "bc", "abc"]:
triad_census = nx.triadic_census(G, nodelist=nl)
assert expected == {typ: cnt for typ, cnt in triad_census.items() if cnt > 0}
def test_triadic_census_correct_nodelist_values():
G = nx.path_graph(5, create_using=nx.DiGraph)
msg = r"nodelist includes duplicate nodes or nodes not in G"
with pytest.raises(ValueError, match=msg):
nx.triadic_census(G, [1, 2, 2, 3])
with pytest.raises(ValueError, match=msg):
nx.triadic_census(G, [1, 2, "a", 3])
def test_triadic_census_tiny_graphs():
tc = nx.triadic_census(nx.empty_graph(0, create_using=nx.DiGraph))
assert {} == {typ: cnt for typ, cnt in tc.items() if cnt > 0}
tc = nx.triadic_census(nx.empty_graph(1, create_using=nx.DiGraph))
assert {} == {typ: cnt for typ, cnt in tc.items() if cnt > 0}
tc = nx.triadic_census(nx.empty_graph(2, create_using=nx.DiGraph))
assert {} == {typ: cnt for typ, cnt in tc.items() if cnt > 0}
tc = nx.triadic_census(nx.DiGraph([(1, 2)]))
assert {} == {typ: cnt for typ, cnt in tc.items() if cnt > 0}
def test_triadic_census_selfloops():
GG = nx.path_graph("abc", create_using=nx.DiGraph)
expected = {"021C": 1}
for n in GG:
G = GG.copy()
G.add_edge(n, n)
tc = nx.triadic_census(G)
assert expected == {typ: cnt for typ, cnt in tc.items() if cnt > 0}
GG = nx.path_graph("abcde", create_using=nx.DiGraph)
tbt = nx.triads_by_type(GG)
for n in GG:
GG.add_edge(n, n)
tc = nx.triadic_census(GG)
assert tc == {tt: len(tbt[tt]) for tt in tc}
def test_triadic_census_four_path():
G = nx.path_graph("abcd", create_using=nx.DiGraph)
expected = {"012": 2, "021C": 2}
triad_census = nx.triadic_census(G)
assert expected == {typ: cnt for typ, cnt in triad_census.items() if cnt > 0}
def test_triadic_census_four_path_nodelist():
G = nx.path_graph("abcd", create_using=nx.DiGraph)
expected_end = {"012": 2, "021C": 1}
expected_mid = {"012": 1, "021C": 2}
a_triad_census = nx.triadic_census(G, nodelist=["a"])
assert expected_end == {typ: cnt for typ, cnt in a_triad_census.items() if cnt > 0}
b_triad_census = nx.triadic_census(G, nodelist=["b"])
assert expected_mid == {typ: cnt for typ, cnt in b_triad_census.items() if cnt > 0}
c_triad_census = nx.triadic_census(G, nodelist=["c"])
assert expected_mid == {typ: cnt for typ, cnt in c_triad_census.items() if cnt > 0}
d_triad_census = nx.triadic_census(G, nodelist=["d"])
assert expected_end == {typ: cnt for typ, cnt in d_triad_census.items() if cnt > 0}
def test_triadic_census_nodelist():
"""Tests the triadic_census function."""
G = nx.DiGraph()
G.add_edges_from(["01", "02", "03", "04", "05", "12", "16", "51", "56", "65"])
expected = {
"030T": 2,
"120C": 1,
"210": 0,
"120U": 0,
"012": 9,
"102": 3,
"021U": 0,
"111U": 0,
"003": 8,
"030C": 0,
"021D": 9,
"201": 0,
"111D": 1,
"300": 0,
"120D": 0,
"021C": 2,
}
actual = {k: 0 for k in expected}
for node in G.nodes():
node_triad_census = nx.triadic_census(G, nodelist=[node])
for triad_key in expected:
actual[triad_key] += node_triad_census[triad_key]
# Divide all counts by 3
for k, v in actual.items():
actual[k] //= 3
assert expected == actual
@pytest.mark.parametrize("N", [5, 10])
def test_triadic_census_on_random_graph(N):
G = nx.binomial_graph(N, 0.3, directed=True, seed=42)
tc1 = nx.triadic_census(G)
tbt = nx.triads_by_type(G)
tc2 = {tt: len(tbt[tt]) for tt in tc1}
assert tc1 == tc2
for n in G:
tc1 = nx.triadic_census(G, nodelist={n})
tc2 = {tt: sum(1 for t in tbt.get(tt, []) if n in t) for tt in tc1}
assert tc1 == tc2
for ns in itertools.combinations(G, 2):
ns = set(ns)
tc1 = nx.triadic_census(G, nodelist=ns)
tc2 = {
tt: sum(1 for t in tbt.get(tt, []) if any(n in ns for n in t)) for tt in tc1
}
assert tc1 == tc2
for ns in itertools.combinations(G, 3):
ns = set(ns)
tc1 = nx.triadic_census(G, nodelist=ns)
tc2 = {
tt: sum(1 for t in tbt.get(tt, []) if any(n in ns for n in t)) for tt in tc1
}
assert tc1 == tc2
