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* flake8 --max-line-length=88 * fixup! Format Python code with psf/black push Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
84 lines
2.6 KiB
Python
84 lines
2.6 KiB
Python
from collections import deque
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def tarjan(g):
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"""
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Tarjan's algo for finding strongly connected components in a directed graph
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Uses two main attributes of each node to track reachability, the index of that node
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within a component(index), and the lowest index reachable from that node(lowlink).
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We then perform a dfs of the each component making sure to update these parameters
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for each node and saving the nodes we visit on the way.
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If ever we find that the lowest reachable node from a current node is equal to the
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index of the current node then it must be the root of a strongly connected
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component and so we save it and it's equireachable vertices as a strongly
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connected component.
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Complexity: strong_connect() is called at most once for each node and has a
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complexity of O(|E|) as it is DFS.
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Therefore this has complexity O(|V| + |E|) for a graph G = (V, E)
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"""
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n = len(g)
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stack = deque()
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on_stack = [False for _ in range(n)]
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index_of = [-1 for _ in range(n)]
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lowlink_of = index_of[:]
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def strong_connect(v, index, components):
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index_of[v] = index # the number when this node is seen
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lowlink_of[v] = index # lowest rank node reachable from here
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index += 1
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stack.append(v)
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on_stack[v] = True
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for w in g[v]:
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if index_of[w] == -1:
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index = strong_connect(w, index, components)
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lowlink_of[v] = (
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lowlink_of[w] if lowlink_of[w] < lowlink_of[v] else lowlink_of[v]
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)
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elif on_stack[w]:
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lowlink_of[v] = (
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lowlink_of[w] if lowlink_of[w] < lowlink_of[v] else lowlink_of[v]
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)
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if lowlink_of[v] == index_of[v]:
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component = []
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w = stack.pop()
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on_stack[w] = False
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component.append(w)
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while w != v:
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w = stack.pop()
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on_stack[w] = False
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component.append(w)
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components.append(component)
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return index
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components = []
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for v in range(n):
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if index_of[v] == -1:
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strong_connect(v, 0, components)
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return components
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def create_graph(n, edges):
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g = [[] for _ in range(n)]
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for u, v in edges:
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g[u].append(v)
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return g
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if __name__ == "__main__":
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# Test
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n_vertices = 7
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source = [0, 0, 1, 2, 3, 3, 4, 4, 6]
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target = [1, 3, 2, 0, 1, 4, 5, 6, 5]
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edges = [(u, v) for u, v in zip(source, target)]
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g = create_graph(n_vertices, edges)
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assert [[5], [6], [4], [3, 2, 1, 0]] == tarjan(g)
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