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Initialize set with source in DFS (#1872)
* Update dfs.py
* Add type hints, rearrange doc-strings and comments
* fixup! Format Python code with psf/black push
* dfs -> depth_first_search
Co-Authored-By: Christian Clauss <cclauss@me.com>
* dfs -> depth_first_search
* Add doctest for DFS
* fixup! Format Python code with psf/black push
* Rename dfs.py to depth_first_search_dictionary.py
* updating DIRECTORY.md
* Rename depth_first_search_dictionary.py to depth_first_search_dfs.py
* updating DIRECTORY.md
* Rename depth_first_search.py to depth_first_search_2.py
* updating DIRECTORY.md
* Rename depth_first_search_dfs.py to depth_first_search.py
* updating DIRECTORY.md
Co-authored-by: John Law <johnlaw.po@gmail.com>
Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
Co-authored-by: Christian Clauss <cclauss@me.com>
This commit is contained in:
Sanders Lin
GitHub
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7aaf79cc23
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@ -212,7 +212,7 @@
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* [Check Bipartite Graph Bfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/check_bipartite_graph_bfs.py)
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* [Check Bipartite Graph Dfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/check_bipartite_graph_dfs.py)
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* [Depth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/depth_first_search.py)
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* [Dfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/dfs.py)
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* [Depth First Search 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/depth_first_search_2.py)
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* [Dijkstra](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra.py)
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* [Dijkstra 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra_2.py)
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* [Dijkstra Algorithm](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra_algorithm.py)
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@ -1,65 +1,59 @@
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#!/usr/bin/python
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"""The DFS function simply calls itself recursively for every unvisited child of
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its argument. We can emulate that behaviour precisely using a stack of iterators.
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Instead of recursively calling with a node, we'll push an iterator to the node's
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children onto the iterator stack. When the iterator at the top of the stack
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terminates, we'll pop it off the stack.
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""" Author: OMKAR PATHAK """
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Pseudocode:
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all nodes initially unexplored
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mark s as explored
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for every edge (s, v):
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if v unexplored:
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DFS(G, v)
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"""
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from typing import Set, Dict
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class Graph:
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def __init__(self):
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self.vertex = {}
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def depth_first_search(graph: Dict, start: str) -> Set[int]:
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"""Depth First Search on Graph
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# for printing the Graph vertices
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def printGraph(self):
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print(self.vertex)
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for i in self.vertex.keys():
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print(i, " -> ", " -> ".join([str(j) for j in self.vertex[i]]))
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:param graph: directed graph in dictionary format
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:param vertex: starting vectex as a string
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:returns: the trace of the search
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>>> G = { "A": ["B", "C", "D"], "B": ["A", "D", "E"],
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... "C": ["A", "F"], "D": ["B", "D"], "E": ["B", "F"],
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... "F": ["C", "E", "G"], "G": ["F"] }
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>>> start = "A"
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>>> output_G = list({'A', 'B', 'C', 'D', 'E', 'F', 'G'})
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>>> all(x in output_G for x in list(depth_first_search(G, "A")))
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True
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>>> all(x in output_G for x in list(depth_first_search(G, "G")))
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True
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"""
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explored, stack = set(start), [start]
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while stack:
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v = stack.pop()
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# one difference from BFS is to pop last element here instead of first one
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for w in graph[v]:
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if w not in explored:
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explored.add(w)
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stack.append(w)
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return explored
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# for adding the edge between two vertices
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def addEdge(self, fromVertex, toVertex):
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# check if vertex is already present,
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if fromVertex in self.vertex.keys():
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self.vertex[fromVertex].append(toVertex)
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else:
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# else make a new vertex
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self.vertex[fromVertex] = [toVertex]
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def DFS(self):
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# visited array for storing already visited nodes
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visited = [False] * len(self.vertex)
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# call the recursive helper function
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for i in range(len(self.vertex)):
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if visited[i] == False:
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self.DFSRec(i, visited)
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def DFSRec(self, startVertex, visited):
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# mark start vertex as visited
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visited[startVertex] = True
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print(startVertex, end=" ")
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# Recur for all the vertices that are adjacent to this node
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for i in self.vertex.keys():
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if visited[i] == False:
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self.DFSRec(i, visited)
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G = {
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"A": ["B", "C", "D"],
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"B": ["A", "D", "E"],
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"C": ["A", "F"],
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"D": ["B", "D"],
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"E": ["B", "F"],
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"F": ["C", "E", "G"],
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"G": ["F"],
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}
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if __name__ == "__main__":
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g = Graph()
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g.addEdge(0, 1)
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g.addEdge(0, 2)
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g.addEdge(1, 2)
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g.addEdge(2, 0)
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g.addEdge(2, 3)
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g.addEdge(3, 3)
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import doctest
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g.printGraph()
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print("DFS:")
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g.DFS()
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# OUTPUT:
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# 0 -> 1 -> 2
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# 1 -> 2
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# 2 -> 0 -> 3
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# 3 -> 3
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# DFS:
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# 0 1 2 3
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doctest.testmod()
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print(depth_first_search(G, "A"))
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65
graphs/depth_first_search_2.py
Normal file
65
graphs/depth_first_search_2.py
Normal file
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@ -0,0 +1,65 @@
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#!/usr/bin/python
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""" Author: OMKAR PATHAK """
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class Graph:
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def __init__(self):
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self.vertex = {}
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# for printing the Graph vertices
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def printGraph(self):
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print(self.vertex)
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for i in self.vertex.keys():
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print(i, " -> ", " -> ".join([str(j) for j in self.vertex[i]]))
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# for adding the edge between two vertices
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def addEdge(self, fromVertex, toVertex):
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# check if vertex is already present,
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if fromVertex in self.vertex.keys():
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self.vertex[fromVertex].append(toVertex)
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else:
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# else make a new vertex
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self.vertex[fromVertex] = [toVertex]
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def DFS(self):
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# visited array for storing already visited nodes
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visited = [False] * len(self.vertex)
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# call the recursive helper function
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for i in range(len(self.vertex)):
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if visited[i] == False:
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self.DFSRec(i, visited)
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def DFSRec(self, startVertex, visited):
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# mark start vertex as visited
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visited[startVertex] = True
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print(startVertex, end=" ")
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# Recur for all the vertices that are adjacent to this node
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for i in self.vertex.keys():
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if visited[i] == False:
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self.DFSRec(i, visited)
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if __name__ == "__main__":
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g = Graph()
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g.addEdge(0, 1)
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g.addEdge(0, 2)
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g.addEdge(1, 2)
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g.addEdge(2, 0)
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g.addEdge(2, 3)
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g.addEdge(3, 3)
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g.printGraph()
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print("DFS:")
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g.DFS()
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# OUTPUT:
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# 0 -> 1 -> 2
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# 1 -> 2
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# 2 -> 0 -> 3
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# 3 -> 3
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# DFS:
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# 0 1 2 3
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@ -1,44 +0,0 @@
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"""pseudo-code"""
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"""
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DFS(graph G, start vertex s):
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// all nodes initially unexplored
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mark s as explored
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for every edge (s, v):
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if v unexplored:
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DFS(G, v)
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"""
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def dfs(graph, start):
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"""The DFS function simply calls itself recursively for every unvisited child of its argument. We can emulate that
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behaviour precisely using a stack of iterators. Instead of recursively calling with a node, we'll push an iterator
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to the node's children onto the iterator stack. When the iterator at the top of the stack terminates, we'll pop
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it off the stack."""
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explored, stack = set(), [start]
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while stack:
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v = (
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stack.pop()
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) # one difference from BFS is to pop last element here instead of first one
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if v in explored:
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continue
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explored.add(v)
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for w in graph[v]:
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if w not in explored:
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stack.append(w)
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return explored
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G = {
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"A": ["B", "C"],
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"B": ["A", "D", "E"],
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"C": ["A", "F"],
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"D": ["B"],
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"E": ["B", "F"],
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"F": ["C", "E"],
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}
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print(dfs(G, "A"))
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