Algorithm PDF in C programming

Comments

Post a Comment

Popular posts from this blog

DFS in python

# Python3 program to print DFS traversal # from a given given graph from collections import defaultdict # This class represents a directed graph using # adjacency list representation class Graph: # Constructor def __init__(self): # default dictionary to store graph self.graph = defaultdict(list) # function to add an edge to graph def addEdge(self, u, v): self.graph[u].append(v) # A function used by DFS def DFSUtil(self, v, visited): # Mark the current node as visited # and print it visited[v] = True print(v, end = ' ') # Recur for all the vertices # adjacent to this vertex for i in self.graph[v]: if visited[i] == False: self.DFSUtil(i, visited) # The function to do DFS traversal. It uses # recursive DFSUtil() def DFS(self, v): # Mark all the vertices as not visited visited = [False] * (len(self.graph)) # Call the recursive helper function # to print DFS traversal self.DFSUtil(v, visited) #...
Read more

BFS in Python

Breadth First Search in Python # Python3 Program to print BFS traversal # from a given source vertex. BFS(int s) # traverses vertices reachable from s. from collections import defaultdict # This class represents a directed graph # using adjacency list representation class Graph: # Constructor def __init__(self): # default dictionary to store graph self.graph = defaultdict(list) # function to add an edge to graph def addEdge(self,u,v): self.graph[u].append(v) # Function to print a BFS of graph def BFS(self, s): # Mark all the vertices as not visited visited = [False] * (len(self.graph)) # Create a queue for BFS queue = [] # Mark the source node as # visited and enqueue it queue.append(s) visited[s] = True while queue: # Dequeue a vertex from # queue and print it s = queue.pop(0) print (s, end = " ") # Get all adjacent vertices of the # dequeued vertex s. If a adjacent # has not been ...
Read more

Quick Sort In Python

# Python program for implementation of Quicksort Sort # This function takes last element as pivot, places # the pivot element at its correct position in sorted # array, and places all smaller (smaller than pivot) # to left of pivot and all greater elements to right # of pivot def partition(arr, low, high):     i = (low - 1)  # index of smaller element     pivot = arr[high]  # pivot     for j in range(low, high):         # If current element is smaller than or         # equal to pivot         if arr[j] <= pivot:             # increment index of smaller element             i = i + 1             arr[i], arr[j] = arr[j], arr[i]     arr[i + 1], arr[high] = arr[high], arr[i + 1]     return (i + 1) # The main function that implements Q...
Read more