Added Kruskal's Algorithm (more organized than the one present) (#2218)

* Added Kruskal's Algorithm

* Added Type Hints

* fixup! Format Python code with psf/black push

* Added Type Hints V2

* Implemented suggestions + uniform naming convention

* removed redundant variable (self.nodes)

* updating DIRECTORY.md

Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
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Tapajyoti Bose 2020-08-12 15:46:17 +05:30 committed by GitHub
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* [Karger](https://github.com/TheAlgorithms/Python/blob/master/graphs/karger.py) * [Karger](https://github.com/TheAlgorithms/Python/blob/master/graphs/karger.py)
* [Minimum Spanning Tree Boruvka](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_boruvka.py) * [Minimum Spanning Tree Boruvka](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_boruvka.py)
* [Minimum Spanning Tree Kruskal](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_kruskal.py) * [Minimum Spanning Tree Kruskal](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_kruskal.py)
* [Minimum Spanning Tree Kruskal2](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_kruskal2.py)
* [Minimum Spanning Tree Prims](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_prims.py) * [Minimum Spanning Tree Prims](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_prims.py)
* [Multi Heuristic Astar](https://github.com/TheAlgorithms/Python/blob/master/graphs/multi_heuristic_astar.py) * [Multi Heuristic Astar](https://github.com/TheAlgorithms/Python/blob/master/graphs/multi_heuristic_astar.py)
* [Page Rank](https://github.com/TheAlgorithms/Python/blob/master/graphs/page_rank.py) * [Page Rank](https://github.com/TheAlgorithms/Python/blob/master/graphs/page_rank.py)

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from __future__ import annotations
class DisjointSetTreeNode:
# Disjoint Set Node to store the parent and rank
def __init__(self, key: int) -> None:
self.key = key
self.parent = self
self.rank = 0
class DisjointSetTree:
# Disjoint Set DataStructure
def __init__(self):
# map from node name to the node object
self.map = {}
def make_set(self, x: int) -> None:
# create a new set with x as its member
self.map[x] = DisjointSetTreeNode(x)
def find_set(self, x: int) -> DisjointSetTreeNode:
# find the set x belongs to (with path-compression)
elem_ref = self.map[x]
if elem_ref != elem_ref.parent:
elem_ref.parent = self.find_set(elem_ref.parent.key)
return elem_ref.parent
def link(self, x: int, y: int) -> None:
# helper function for union operation
if x.rank > y.rank:
y.parent = x
else:
x.parent = y
if x.rank == y.rank:
y.rank += 1
def union(self, x: int, y: int) -> None:
# merge 2 disjoint sets
self.link(self.find_set(x), self.find_set(y))
class GraphUndirectedWeighted:
def __init__(self):
# connections: map from the node to the neighbouring nodes (with weights)
self.connections = {}
def add_node(self, node: int) -> None:
# add a node ONLY if its not present in the graph
if node not in self.connections:
self.connections[node] = {}
def add_edge(self, node1: int, node2: int, weight: int) -> None:
# add an edge with the given weight
self.add_node(node1)
self.add_node(node2)
self.connections[node1][node2] = weight
self.connections[node2][node1] = weight
def kruskal(self) -> GraphUndirectedWeighted:
# Kruskal's Algorithm to generate a Minimum Spanning Tree (MST) of a graph
"""
Details: https://en.wikipedia.org/wiki/Kruskal%27s_algorithm
Example:
>>> graph = GraphUndirectedWeighted()
>>> graph.add_edge(1, 2, 1)
>>> graph.add_edge(2, 3, 2)
>>> graph.add_edge(3, 4, 1)
>>> graph.add_edge(3, 5, 100) # Removed in MST
>>> graph.add_edge(4, 5, 5)
>>> assert 5 in graph.connections[3]
>>> mst = graph.kruskal()
>>> assert 5 not in mst.connections[3]
"""
# getting the edges in ascending order of weights
edges = []
seen = set()
for start in self.connections:
for end in self.connections[start]:
if (start, end) not in seen:
seen.add((end, start))
edges.append((start, end, self.connections[start][end]))
edges.sort(key=lambda x: x[2])
# creating the disjoint set
disjoint_set = DisjointSetTree()
[disjoint_set.make_set(node) for node in self.connections]
# MST generation
num_edges = 0
index = 0
graph = GraphUndirectedWeighted()
while num_edges < len(self.connections) - 1:
u, v, w = edges[index]
index += 1
parentu = disjoint_set.find_set(u)
parentv = disjoint_set.find_set(v)
if parentu != parentv:
num_edges += 1
graph.add_edge(u, v, w)
disjoint_set.union(u, v)
return graph
if __name__ == "__main__":
import doctest
doctest.testmod()