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from functools import partial
import pytest
import networkx as nx
class TestBFS:
@classmethod
def setup_class(cls):
# simple graph
G = nx.Graph()
G.add_edges_from([(0, 1), (1, 2), (1, 3), (2, 4), (3, 4)])
cls.G = G
def test_successor(self):
assert dict(nx.bfs_successors(self.G, source=0)) == {0: [1], 1: [2, 3], 2: [4]}
def test_predecessor(self):
assert dict(nx.bfs_predecessors(self.G, source=0)) == {1: 0, 2: 1, 3: 1, 4: 2}
def test_bfs_tree(self):
T = nx.bfs_tree(self.G, source=0)
assert sorted(T.nodes()) == sorted(self.G.nodes())
assert sorted(T.edges()) == [(0, 1), (1, 2), (1, 3), (2, 4)]
def test_bfs_edges(self):
edges = nx.bfs_edges(self.G, source=0)
assert list(edges) == [(0, 1), (1, 2), (1, 3), (2, 4)]
def test_bfs_edges_reverse(self):
D = nx.DiGraph()
D.add_edges_from([(0, 1), (1, 2), (1, 3), (2, 4), (3, 4)])
edges = nx.bfs_edges(D, source=4, reverse=True)
assert list(edges) == [(4, 2), (4, 3), (2, 1), (1, 0)]
def test_bfs_edges_sorting(self):
D = nx.DiGraph()
D.add_edges_from([(0, 1), (0, 2), (1, 4), (1, 3), (2, 5)])
sort_desc = partial(sorted, reverse=True)
edges_asc = nx.bfs_edges(D, source=0, sort_neighbors=sorted)
edges_desc = nx.bfs_edges(D, source=0, sort_neighbors=sort_desc)
assert list(edges_asc) == [(0, 1), (0, 2), (1, 3), (1, 4), (2, 5)]
assert list(edges_desc) == [(0, 2), (0, 1), (2, 5), (1, 4), (1, 3)]
def test_bfs_tree_isolates(self):
G = nx.Graph()
G.add_node(1)
G.add_node(2)
T = nx.bfs_tree(G, source=1)
assert sorted(T.nodes()) == [1]
assert sorted(T.edges()) == []
def test_bfs_layers(self):
expected = {
0: [0],
1: [1],
2: [2, 3],
3: [4],
}
assert dict(enumerate(nx.bfs_layers(self.G, sources=[0]))) == expected
assert dict(enumerate(nx.bfs_layers(self.G, sources=0))) == expected
def test_bfs_layers_missing_source(self):
with pytest.raises(nx.NetworkXError):
next(nx.bfs_layers(self.G, sources="abc"))
with pytest.raises(nx.NetworkXError):
next(nx.bfs_layers(self.G, sources=["abc"]))
def test_descendants_at_distance(self):
for distance, descendants in enumerate([{0}, {1}, {2, 3}, {4}]):
assert nx.descendants_at_distance(self.G, 0, distance) == descendants
def test_descendants_at_distance_missing_source(self):
with pytest.raises(nx.NetworkXError):
nx.descendants_at_distance(self.G, "abc", 0)
class TestBreadthLimitedSearch:
@classmethod
def setup_class(cls):
# a tree
G = nx.Graph()
nx.add_path(G, [0, 1, 2, 3, 4, 5, 6])
nx.add_path(G, [2, 7, 8, 9, 10])
cls.G = G
# a disconnected graph
D = nx.Graph()
D.add_edges_from([(0, 1), (2, 3)])
nx.add_path(D, [2, 7, 8, 9, 10])
cls.D = D
def test_limited_bfs_successor(self):
assert dict(nx.bfs_successors(self.G, source=1, depth_limit=3)) == {
1: [0, 2],
2: [3, 7],
3: [4],
7: [8],
}
result = {
n: sorted(s) for n, s in nx.bfs_successors(self.D, source=7, depth_limit=2)
}
assert result == {8: [9], 2: [3], 7: [2, 8]}
def test_limited_bfs_predecessor(self):
assert dict(nx.bfs_predecessors(self.G, source=1, depth_limit=3)) == {
0: 1,
2: 1,
3: 2,
4: 3,
7: 2,
8: 7,
}
assert dict(nx.bfs_predecessors(self.D, source=7, depth_limit=2)) == {
2: 7,
3: 2,
8: 7,
9: 8,
}
def test_limited_bfs_tree(self):
T = nx.bfs_tree(self.G, source=3, depth_limit=1)
assert sorted(T.edges()) == [(3, 2), (3, 4)]
def test_limited_bfs_edges(self):
edges = nx.bfs_edges(self.G, source=9, depth_limit=4)
assert list(edges) == [(9, 8), (9, 10), (8, 7), (7, 2), (2, 1), (2, 3)]
def test_limited_bfs_layers(self):
assert dict(enumerate(nx.bfs_layers(self.G, sources=[0]))) == {
0: [0],
1: [1],
2: [2],
3: [3, 7],
4: [4, 8],
5: [5, 9],
6: [6, 10],
}
assert dict(enumerate(nx.bfs_layers(self.D, sources=2))) == {
0: [2],
1: [3, 7],
2: [8],
3: [9],
4: [10],
}
def test_limited_descendants_at_distance(self):
for distance, descendants in enumerate(
[{0}, {1}, {2}, {3, 7}, {4, 8}, {5, 9}, {6, 10}]
):
assert nx.descendants_at_distance(self.G, 0, distance) == descendants
for distance, descendants in enumerate([{2}, {3, 7}, {8}, {9}, {10}]):
assert nx.descendants_at_distance(self.D, 2, distance) == descendants
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