mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-24 05:21:09 +00:00
Merge pull request #97 from OmkarPathak/added_programs
Added Stack implementation and some traditional Stack problems
This commit is contained in:
commit
43b53f7751
40
data_structures/Graph/Graph.py
Normal file
40
data_structures/Graph/Graph.py
Normal file
|
@ -0,0 +1,40 @@
|
|||
# Author: OMKAR PATHAK
|
||||
|
||||
# We can use Python's dictionary for constructing the graph
|
||||
|
||||
class AdjacencyList(object):
|
||||
def __init__(self):
|
||||
self.List = {}
|
||||
|
||||
def addEdge(self, fromVertex, toVertex):
|
||||
# check if vertex is already present
|
||||
if fromVertex in self.List.keys():
|
||||
self.List[fromVertex].append(toVertex)
|
||||
else:
|
||||
self.List[fromVertex] = [toVertex]
|
||||
|
||||
def printList(self):
|
||||
for i in self.List:
|
||||
print(i,'->',' -> '.join([str(j) for j in self.List[i]]))
|
||||
|
||||
if __name__ == '__main__':
|
||||
al = AdjacencyList()
|
||||
al.addEdge(0, 1)
|
||||
al.addEdge(0, 4)
|
||||
al.addEdge(4, 1)
|
||||
al.addEdge(4, 3)
|
||||
al.addEdge(1, 0)
|
||||
al.addEdge(1, 4)
|
||||
al.addEdge(1, 3)
|
||||
al.addEdge(1, 2)
|
||||
al.addEdge(2, 3)
|
||||
al.addEdge(3, 4)
|
||||
|
||||
al.printList()
|
||||
|
||||
# OUTPUT:
|
||||
# 0 -> 1 -> 4
|
||||
# 1 -> 0 -> 4 -> 3 -> 2
|
||||
# 2 -> 3
|
||||
# 3 -> 4
|
||||
# 4 -> 1 -> 3
|
61
data_structures/Graph/P01_BreadthFirstSearch.py
Normal file
61
data_structures/Graph/P01_BreadthFirstSearch.py
Normal file
|
@ -0,0 +1,61 @@
|
|||
# Author: OMKAR PATHAK
|
||||
|
||||
class Graph():
|
||||
def __init__(self):
|
||||
self.vertex = {}
|
||||
|
||||
# for printing the Graph vertexes
|
||||
def printGraph(self):
|
||||
for i in self.vertex.keys():
|
||||
print(i,' -> ', ' -> '.join([str(j) for j in self.vertex[i]]))
|
||||
|
||||
# for adding the edge beween two vertexes
|
||||
def addEdge(self, fromVertex, toVertex):
|
||||
# check if vertex is already present,
|
||||
if fromVertex in self.vertex.keys():
|
||||
self.vertex[fromVertex].append(toVertex)
|
||||
else:
|
||||
# else make a new vertex
|
||||
self.vertex[fromVertex] = [toVertex]
|
||||
|
||||
def BFS(self, startVertex):
|
||||
# Take a list for stoting already visited vertexes
|
||||
visited = [False] * len(self.vertex)
|
||||
|
||||
# create a list to store all the vertexes for BFS
|
||||
queue = []
|
||||
|
||||
# mark the source node as visited and enqueue it
|
||||
visited[startVertex] = True
|
||||
queue.append(startVertex)
|
||||
|
||||
while queue:
|
||||
startVertex = queue.pop(0)
|
||||
print(startVertex, end = ' ')
|
||||
|
||||
# mark all adjacent nodes as visited and print them
|
||||
for i in self.vertex[startVertex]:
|
||||
if visited[i] == False:
|
||||
queue.append(i)
|
||||
visited[i] = True
|
||||
|
||||
if __name__ == '__main__':
|
||||
g = Graph()
|
||||
g.addEdge(0, 1)
|
||||
g.addEdge(0, 2)
|
||||
g.addEdge(1, 2)
|
||||
g.addEdge(2, 0)
|
||||
g.addEdge(2, 3)
|
||||
g.addEdge(3, 3)
|
||||
|
||||
g.printGraph()
|
||||
print('BFS:')
|
||||
g.BFS(2)
|
||||
|
||||
# OUTPUT:
|
||||
# 0 -> 1 -> 2
|
||||
# 1 -> 2
|
||||
# 2 -> 0 -> 3
|
||||
# 3 -> 3
|
||||
# BFS:
|
||||
# 2 0 3 1
|
61
data_structures/Graph/P02_DepthFirstSearch.py
Normal file
61
data_structures/Graph/P02_DepthFirstSearch.py
Normal file
|
@ -0,0 +1,61 @@
|
|||
# Author: OMKAR PATHAK
|
||||
|
||||
class Graph():
|
||||
def __init__(self):
|
||||
self.vertex = {}
|
||||
|
||||
# for printing the Graph vertexes
|
||||
def printGraph(self):
|
||||
print(self.vertex)
|
||||
for i in self.vertex.keys():
|
||||
print(i,' -> ', ' -> '.join([str(j) for j in self.vertex[i]]))
|
||||
|
||||
# for adding the edge beween two vertexes
|
||||
def addEdge(self, fromVertex, toVertex):
|
||||
# check if vertex is already present,
|
||||
if fromVertex in self.vertex.keys():
|
||||
self.vertex[fromVertex].append(toVertex)
|
||||
else:
|
||||
# else make a new vertex
|
||||
self.vertex[fromVertex] = [toVertex]
|
||||
|
||||
def DFS(self):
|
||||
# visited array for storing already visited nodes
|
||||
visited = [False] * len(self.vertex)
|
||||
|
||||
# call the recursive helper function
|
||||
for i in range(len(self.vertex)):
|
||||
if visited[i] == False:
|
||||
self.DFSRec(i, visited)
|
||||
|
||||
def DFSRec(self, startVertex, visited):
|
||||
# mark start vertex as visited
|
||||
visited[startVertex] = True
|
||||
|
||||
print(startVertex, end = ' ')
|
||||
|
||||
# Recur for all the vertexes that are adjacent to this node
|
||||
for i in self.vertex.keys():
|
||||
if visited[i] == False:
|
||||
self.DFSRec(i, visited)
|
||||
|
||||
if __name__ == '__main__':
|
||||
g = Graph()
|
||||
g.addEdge(0, 1)
|
||||
g.addEdge(0, 2)
|
||||
g.addEdge(1, 2)
|
||||
g.addEdge(2, 0)
|
||||
g.addEdge(2, 3)
|
||||
g.addEdge(3, 3)
|
||||
|
||||
g.printGraph()
|
||||
print('DFS:')
|
||||
g.DFS()
|
||||
|
||||
# OUTPUT:
|
||||
# 0 -> 1 -> 2
|
||||
# 1 -> 2
|
||||
# 2 -> 0 -> 3
|
||||
# 3 -> 3
|
||||
# DFS:
|
||||
# 0 1 2 3
|
27
data_structures/Stacks/Balanced_Parentheses.py
Normal file
27
data_structures/Stacks/Balanced_Parentheses.py
Normal file
|
@ -0,0 +1,27 @@
|
|||
# Author: OMKAR PATHAK
|
||||
|
||||
import Stack
|
||||
|
||||
def parseParenthesis(string):
|
||||
balanced = 1
|
||||
index = 0
|
||||
myStack = Stack.Stack(len(string))
|
||||
while (index < len(string)) and (balanced == 1):
|
||||
check = string[index]
|
||||
if check == '(':
|
||||
myStack.push(check)
|
||||
else:
|
||||
if myStack.isEmpty():
|
||||
balanced = 0
|
||||
else:
|
||||
myStack.pop()
|
||||
index += 1
|
||||
|
||||
if balanced == 1 and myStack.isEmpty():
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
|
||||
if __name__ == '__main__':
|
||||
print(parseParenthesis('((()))')) # True
|
||||
print(parseParenthesis('((())')) # False
|
48
data_structures/Stacks/Infix_To_Postfix_Conversion.py
Normal file
48
data_structures/Stacks/Infix_To_Postfix_Conversion.py
Normal file
|
@ -0,0 +1,48 @@
|
|||
# Author: OMKAR PATHAK
|
||||
|
||||
import Stack
|
||||
|
||||
def isOperand(char):
|
||||
return (ord(char) >= ord('a') and ord(char) <= ord('z')) or (ord(char) >= ord('A') and ord(char) <= ord('Z'))
|
||||
|
||||
def precedence(char):
|
||||
if char == '+' or char == '-':
|
||||
return 1
|
||||
elif char == '*' or char == '/':
|
||||
return 2
|
||||
elif char == '^':
|
||||
return 3
|
||||
else:
|
||||
return -1
|
||||
|
||||
def infixToPostfix(myExp, myStack):
|
||||
postFix = []
|
||||
for i in range(len(myExp)):
|
||||
if (isOperand(myExp[i])):
|
||||
postFix.append(myExp[i])
|
||||
elif(myExp[i] == '('):
|
||||
myStack.push(myExp[i])
|
||||
elif(myExp[i] == ')'):
|
||||
topOperator = myStack.pop()
|
||||
while(not myStack.isEmpty() and topOperator != '('):
|
||||
postFix.append(topOperator)
|
||||
topOperator = myStack.pop()
|
||||
else:
|
||||
while (not myStack.isEmpty()) and (precedence(myExp[i]) <= precedence(myStack.peek())):
|
||||
postFix.append(myStack.pop())
|
||||
myStack.push(myExp[i])
|
||||
|
||||
while(not myStack.isEmpty()):
|
||||
postFix.append(myStack.pop())
|
||||
return ' '.join(postFix)
|
||||
|
||||
if __name__ == '__main__':
|
||||
myExp = 'a+b*(c^d-e)^(f+g*h)-i'
|
||||
myExp = [i for i in myExp]
|
||||
print('Infix:',' '.join(myExp))
|
||||
myStack = Stack.Stack(len(myExp))
|
||||
print('Postfix:',infixToPostfix(myExp, myStack))
|
||||
|
||||
# OUTPUT:
|
||||
# Infix: a + b * ( c ^ d - e ) ^ ( f + g * h ) - i
|
||||
# Postfix: a b c d ^ e - f g h * + ^ * + i -
|
50
data_structures/Stacks/Stack.py
Normal file
50
data_structures/Stacks/Stack.py
Normal file
|
@ -0,0 +1,50 @@
|
|||
# Author: OMKAR PATHAK
|
||||
|
||||
class Stack(object):
|
||||
def __init__(self, limit = 10):
|
||||
self.stack = []
|
||||
self.limit = limit
|
||||
|
||||
# for printing the stack contents
|
||||
def __str__(self):
|
||||
return ' '.join([str(i) for i in self.stack])
|
||||
|
||||
# for pushing an element on to the stack
|
||||
def push(self, data):
|
||||
if len(self.stack) >= self.limit:
|
||||
print('Stack Overflow')
|
||||
else:
|
||||
self.stack.append(data)
|
||||
|
||||
# for popping the uppermost element
|
||||
def pop(self):
|
||||
if len(self.stack) <= 0:
|
||||
return -1
|
||||
else:
|
||||
return self.stack.pop()
|
||||
|
||||
# for peeking the top-most element of the stack
|
||||
def peek(self):
|
||||
if len(self.stack) <= 0:
|
||||
return -1
|
||||
else:
|
||||
return self.stack[len(self.stack) - 1]
|
||||
|
||||
# to check if stack is empty
|
||||
def isEmpty(self):
|
||||
return self.stack == []
|
||||
|
||||
# for checking the size of stack
|
||||
def size(self):
|
||||
return len(self.stack)
|
||||
|
||||
if __name__ == '__main__':
|
||||
myStack = Stack()
|
||||
for i in range(10):
|
||||
myStack.push(i)
|
||||
print(myStack)
|
||||
myStack.pop() # popping the top element
|
||||
print(myStack)
|
||||
myStack.peek() # printing the top element
|
||||
myStack.isEmpty()
|
||||
myStack.size()
|
56
sorts/bucket_sort.py
Normal file
56
sorts/bucket_sort.py
Normal file
|
@ -0,0 +1,56 @@
|
|||
#!/usr/bin/env python
|
||||
# Author: OMKAR PATHAK
|
||||
# This program will illustrate how to implement bucket sort algorithm
|
||||
|
||||
# Wikipedia says: Bucket sort, or bin sort, is a sorting algorithm that works by distributing the
|
||||
# elements of an array into a number of buckets. Each bucket is then sorted individually, either using
|
||||
# a different sorting algorithm, or by recursively applying the bucket sorting algorithm. It is a
|
||||
# distribution sort, and is a cousin of radix sort in the most to least significant digit flavour.
|
||||
# Bucket sort is a generalization of pigeonhole sort. Bucket sort can be implemented with comparisons
|
||||
# and therefore can also be considered a comparison sort algorithm. The computational complexity estimates
|
||||
# involve the number of buckets.
|
||||
|
||||
# Time Complexity of Solution:
|
||||
# Best Case O(n); Average Case O(n); Worst Case O(n)
|
||||
|
||||
from P26_InsertionSort import insertionSort
|
||||
import math
|
||||
|
||||
DEFAULT_BUCKET_SIZE = 5
|
||||
|
||||
def bucketSort(myList, bucketSize=DEFAULT_BUCKET_SIZE):
|
||||
if(len(myList) == 0):
|
||||
print('You don\'t have any elements in array!')
|
||||
|
||||
minValue = myList[0]
|
||||
maxValue = myList[0]
|
||||
|
||||
# For finding minimum and maximum values
|
||||
for i in range(0, len(myList)):
|
||||
if myList[i] < minValue:
|
||||
minValue = myList[i]
|
||||
elif myList[i] > maxValue:
|
||||
maxValue = myList[i]
|
||||
|
||||
# Initialize buckets
|
||||
bucketCount = math.floor((maxValue - minValue) / bucketSize) + 1
|
||||
buckets = []
|
||||
for i in range(0, bucketCount):
|
||||
buckets.append([])
|
||||
|
||||
# For putting values in buckets
|
||||
for i in range(0, len(myList)):
|
||||
buckets[math.floor((myList[i] - minValue) / bucketSize)].append(myList[i])
|
||||
|
||||
# Sort buckets and place back into input array
|
||||
sortedArray = []
|
||||
for i in range(0, len(buckets)):
|
||||
insertionSort(buckets[i])
|
||||
for j in range(0, len(buckets[i])):
|
||||
sortedArray.append(buckets[i][j])
|
||||
|
||||
return sortedArray
|
||||
|
||||
if __name__ == '__main__':
|
||||
sortedArray = bucketSort([12, 23, 4, 5, 3, 2, 12, 81, 56, 95])
|
||||
print(sortedArray)
|
Loading…
Reference in New Issue
Block a user