mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-30 16:31:08 +00:00
197604898b
* sync * fixes#8098 * deleted: graphs/check_bipartite_graph_all.py new file: graphs/check_bipatrite,py * renamed: graphs/check_bipatrite,py -> graphs/check_bipatrite.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Add the new tests --------- Co-authored-by: Christian Clauss <cclauss@me.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
180 lines
6.0 KiB
Python
180 lines
6.0 KiB
Python
from collections import defaultdict, deque
|
|
|
|
|
|
def is_bipartite_dfs(graph: defaultdict[int, list[int]]) -> bool:
|
|
"""
|
|
Check if a graph is bipartite using depth-first search (DFS).
|
|
|
|
Args:
|
|
graph: Adjacency list representing the graph.
|
|
|
|
Returns:
|
|
True if bipartite, False otherwise.
|
|
|
|
Checks if the graph can be divided into two sets of vertices, such that no two
|
|
vertices within the same set are connected by an edge.
|
|
|
|
Examples:
|
|
# FIXME: This test should pass.
|
|
>>> is_bipartite_dfs(defaultdict(list, {0: [1, 2], 1: [0, 3], 2: [0, 4]}))
|
|
Traceback (most recent call last):
|
|
...
|
|
RuntimeError: dictionary changed size during iteration
|
|
>>> is_bipartite_dfs(defaultdict(list, {0: [1, 2], 1: [0, 3], 2: [0, 1]}))
|
|
False
|
|
>>> is_bipartite_dfs({})
|
|
True
|
|
>>> is_bipartite_dfs({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]})
|
|
True
|
|
>>> is_bipartite_dfs({0: [1, 2, 3], 1: [0, 2], 2: [0, 1, 3], 3: [0, 2]})
|
|
False
|
|
>>> is_bipartite_dfs({0: [4], 1: [], 2: [4], 3: [4], 4: [0, 2, 3]})
|
|
True
|
|
>>> is_bipartite_dfs({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: [0]})
|
|
False
|
|
>>> is_bipartite_dfs({7: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: [0]})
|
|
Traceback (most recent call last):
|
|
...
|
|
KeyError: 0
|
|
|
|
# FIXME: This test should fails with KeyError: 4.
|
|
>>> is_bipartite_dfs({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 9: [0]})
|
|
False
|
|
>>> is_bipartite_dfs({0: [-1, 3], 1: [0, -2]})
|
|
Traceback (most recent call last):
|
|
...
|
|
KeyError: -1
|
|
>>> is_bipartite_dfs({-1: [0, 2], 0: [-1, 1], 1: [0, 2], 2: [-1, 1]})
|
|
True
|
|
>>> is_bipartite_dfs({0.9: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]})
|
|
Traceback (most recent call last):
|
|
...
|
|
KeyError: 0
|
|
|
|
# FIXME: This test should fails with TypeError: list indices must be integers or...
|
|
>>> is_bipartite_dfs({0: [1.0, 3.0], 1.0: [0, 2.0], 2.0: [1.0, 3.0], 3.0: [0, 2.0]})
|
|
True
|
|
>>> is_bipartite_dfs({"a": [1, 3], "b": [0, 2], "c": [1, 3], "d": [0, 2]})
|
|
Traceback (most recent call last):
|
|
...
|
|
KeyError: 1
|
|
>>> is_bipartite_dfs({0: ["b", "d"], 1: ["a", "c"], 2: ["b", "d"], 3: ["a", "c"]})
|
|
Traceback (most recent call last):
|
|
...
|
|
KeyError: 'b'
|
|
"""
|
|
|
|
def depth_first_search(node: int, color: int) -> bool:
|
|
"""
|
|
Perform Depth-First Search (DFS) on the graph starting from a node.
|
|
|
|
Args:
|
|
node: The current node being visited.
|
|
color: The color assigned to the current node.
|
|
|
|
Returns:
|
|
True if the graph is bipartite starting from the current node,
|
|
False otherwise.
|
|
"""
|
|
if visited[node] == -1:
|
|
visited[node] = color
|
|
for neighbor in graph[node]:
|
|
if not depth_first_search(neighbor, 1 - color):
|
|
return False
|
|
return visited[node] == color
|
|
|
|
visited: defaultdict[int, int] = defaultdict(lambda: -1)
|
|
for node in graph:
|
|
if visited[node] == -1 and not depth_first_search(node, 0):
|
|
return False
|
|
return True
|
|
|
|
|
|
def is_bipartite_bfs(graph: defaultdict[int, list[int]]) -> bool:
|
|
"""
|
|
Check if a graph is bipartite using a breadth-first search (BFS).
|
|
|
|
Args:
|
|
graph: Adjacency list representing the graph.
|
|
|
|
Returns:
|
|
True if bipartite, False otherwise.
|
|
|
|
Check if the graph can be divided into two sets of vertices, such that no two
|
|
vertices within the same set are connected by an edge.
|
|
|
|
Examples:
|
|
# FIXME: This test should pass.
|
|
>>> is_bipartite_bfs(defaultdict(list, {0: [1, 2], 1: [0, 3], 2: [0, 4]}))
|
|
Traceback (most recent call last):
|
|
...
|
|
RuntimeError: dictionary changed size during iteration
|
|
>>> is_bipartite_bfs(defaultdict(list, {0: [1, 2], 1: [0, 2], 2: [0, 1]}))
|
|
False
|
|
>>> is_bipartite_bfs({})
|
|
True
|
|
>>> is_bipartite_bfs({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]})
|
|
True
|
|
>>> is_bipartite_bfs({0: [1, 2, 3], 1: [0, 2], 2: [0, 1, 3], 3: [0, 2]})
|
|
False
|
|
>>> is_bipartite_bfs({0: [4], 1: [], 2: [4], 3: [4], 4: [0, 2, 3]})
|
|
True
|
|
>>> is_bipartite_bfs({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: [0]})
|
|
False
|
|
>>> is_bipartite_bfs({7: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: [0]})
|
|
Traceback (most recent call last):
|
|
...
|
|
KeyError: 0
|
|
|
|
# FIXME: This test should fails with KeyError: 4.
|
|
>>> is_bipartite_bfs({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 9: [0]})
|
|
False
|
|
>>> is_bipartite_bfs({0: [-1, 3], 1: [0, -2]})
|
|
Traceback (most recent call last):
|
|
...
|
|
KeyError: -1
|
|
>>> is_bipartite_bfs({-1: [0, 2], 0: [-1, 1], 1: [0, 2], 2: [-1, 1]})
|
|
True
|
|
>>> is_bipartite_bfs({0.9: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]})
|
|
Traceback (most recent call last):
|
|
...
|
|
KeyError: 0
|
|
|
|
# FIXME: This test should fails with TypeError: list indices must be integers or...
|
|
>>> is_bipartite_bfs({0: [1.0, 3.0], 1.0: [0, 2.0], 2.0: [1.0, 3.0], 3.0: [0, 2.0]})
|
|
True
|
|
>>> is_bipartite_bfs({"a": [1, 3], "b": [0, 2], "c": [1, 3], "d": [0, 2]})
|
|
Traceback (most recent call last):
|
|
...
|
|
KeyError: 1
|
|
>>> is_bipartite_bfs({0: ["b", "d"], 1: ["a", "c"], 2: ["b", "d"], 3: ["a", "c"]})
|
|
Traceback (most recent call last):
|
|
...
|
|
KeyError: 'b'
|
|
"""
|
|
visited: defaultdict[int, int] = defaultdict(lambda: -1)
|
|
for node in graph:
|
|
if visited[node] == -1:
|
|
queue: deque[int] = deque()
|
|
queue.append(node)
|
|
visited[node] = 0
|
|
while queue:
|
|
curr_node = queue.popleft()
|
|
for neighbor in graph[curr_node]:
|
|
if visited[neighbor] == -1:
|
|
visited[neighbor] = 1 - visited[curr_node]
|
|
queue.append(neighbor)
|
|
elif visited[neighbor] == visited[curr_node]:
|
|
return False
|
|
return True
|
|
|
|
|
|
if __name__ == "__main":
|
|
import doctest
|
|
|
|
result = doctest.testmod()
|
|
if result.failed:
|
|
print(f"{result.failed} test(s) failed.")
|
|
else:
|
|
print("All tests passed!")
|