This is a common algorithm question. I'm trying to find the inorder successor in a binary search tree. Here's my code
def inorderSuccessor(self, root, p):
"""
:type root: TreeNode
:type p: TreeNode
:rtype: TreeNode
"""
# if Node has a right child, go all the way down
if p.right:
curr = p
while curr.left:
curr = curr.left
return curr
# first ancestor whose left child the node is
ans = None
curr = root
while curr is not p:
if curr.val < p.val:
curr = curr.right
else:
ans = curr
curr = curr.left
return ans
The problem is that this doesn't work when p is the highest node in the tree. I've been scratching my head over how to get this edge case going.
You can implement a method within your BST Class as below
def InOrderSucc(self,childNode):
if(self.search(childNode)):
if not (self.data == childNode):
return(self.right.InOrderSucc(childNode))
else:
if(self.right):
return(self.right.data)
else:
return None
else:
return False
where childNode is the Node you are requesting to find its InOrder Successor, Noting that the InOrder Successor will always be the right Child.
Related
I'm just getting started with binary trees and I have this task where I have to do a preorder iterative traversal search for a given binary tree '[1,null,2,3]'.
I tried to use a new binarytree module that I found, but it didn't worked and I saw a youtube video where some guy did it recursively but I just can't figure out.
#Input = [1,null, 2,3]
# 1
# \
# 2
# /
# 3
#Expected output = [1,2,3]
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution:
def preorderTraversal(self, root: TreeNode) -> List[int]:
I'm just clueless, I wrote an algorithm but I can't turn it into actual functional code. Also I don't understand how the root: TreeNode works. Does it turn every element of the list into a TreeNode object? So far my best try had been this and it's obviously wrong in many ways.
def preorderTraversal(self, root: TreeNode) -> List[int]:
result = []
for i in root:
if i =! root[0] and root.left =! None:
root.left = i
if root.left =! null:
root.left.left = i
elif root.left == null:
root.right.left = i
elif root.left
result.append(i)
elif root.right == None:
root.right = i
else:
continue
A few points:
Function preorderTraversal should have no self parameter; it is not a method of a class.
I have modified the TreeNode class to make it more convenient to specify its children TreeNode objects.
Function preorderTraversal takes as an argument a TreeNode object. As I mentioned in a comment, your statement, #Input = [1,null, 2,3], is difficult to make sense of.
You need to keep a last in/first out (LIFO) stack of unvisited TreeNode objects to implement an iterative (rather than recursive solution). In the code below, variable nodes serves that purpose.
The code:
from typing import List
class TreeNode:
def __init__(self, val, left=None, right=None):
self.x = val
self.left = left
self.right = right
n3 = TreeNode(3)
n2 = TreeNode(2, left=n3)
n1 = TreeNode(1, right=n2)
def preorderTraversal(root: TreeNode) -> List[int]:
result = []
nodes = []
nodes.append(root) # initial node to visit
while len(nodes): # any nodes left top visit?
node = nodes.pop() # get topmost element, which is the next node to visit
result.append(node.x) # "output" its value before children are visited
if node.right is not None:
# show this node must be visited
nodes.append(node.right) # push first so it is popped after node.left
if node.left is not None:
# show this node must be visited
nodes.append(node.left)
return result
print(preorderTraversal(n1))
Prints:
[1, 2, 3]
Or a more complicated tree:
10
/ \
8 2
/ \ /
3 5 2
n3 = TreeNode(3)
n5 = TreeNode(5)
n8 = TreeNode(8, left=n3, right=n5)
n2a = TreeNode(2)
n2b = TreeNode(2, left=n2a)
n10 = TreeNode(10, left=n8, right=n2b)
print(preorderTraversal(n10))
Prints:
[10, 8, 3, 5, 2, 2]
You can use the queue data structure for it.
queue = []
result = []
queue.append(root)
while queue:
node = queue.pop()
result.append(node.val)
if node.left is not None:
queue.insert(0, node.left)
if node.right is not None:
queue.insert(0, node.right)
return result
This is a problem from leetcode platform, here is my solution. Runtime: 28 ms, faster than 81.08% of Python3 online submissions for Binary Tree Preorder Traversal.
class Solution:
def preorderTraversal(self, root: TreeNode) -> List[int]:
if not root:
return []
return [root.val] + self.preorderTraversal(root.left) + self.preorderTraversal(root.right)
In python 3
class BinaryTree:
"""
=== Private Attributes ===
#type _root: object | None
#type _left: BinaryTree | None
#type _right: BinaryTree | None
"""
def __init__(self, root, left, right):
if root is None:
# store an empty BinaryTree
self._root = None
self._left = None
self._right = None
else:
self._root = root
self._left = left
self._right = right
def is_empty(self):
return self._root is None
I know how to traverse this binary tree recursively, but I'm wondering how to do it without recursion
You can use stack method to do tree traversal without recursion.
I am giving example for inorder
def inOrder(root):
# Set current to root of binary tree
current = root
s = [] # initialze stack
done = 0
while(not done):
# Reach the left most Node of the current Node
if current is not None:
# Place pointer to a tree node on the stack
# before traversing the node's left subtree
s.append(current)
current = current.left
# BackTrack from the empty subtree and visit the Node
# at the top of the stack; however, if the stack is
# empty you are done
else:
if(len(s) >0 ):
current = s.pop()
print current.data,
# We have visited the node and its left
# subtree. Now, it's right subtree's turn
current = current.right
else:
done = 1
For more explanation you can consider https://www.youtube.com/watch?v=xLQKdq0Ffjg&t=755s tutorial
I'm trying to traverse a binary tree using depth first traversal and breadth first traversal, but I'm running into trouble. My node and tree implementation seems to be fine, I'm just not sure how to properly traverse the tree depth-wise and breadth-wise.
class Node:
def __init__(self, val):
self.l = None
self.r = None
self.v = val
class Tree:
def __init__(self):
self.root = None
def getRoot(self):
return self.root
def add(self, val):
if(self.root == None):
self.root = Node(val)
else:
self._add(val, self.root)
def _add(self, val, node):
if(val < node.v):
if(node.l != None):
self._add(val, node.l)
else:
node.l = Node(val)
else:
if(node.r != None):
self._add(val, node.r)
else:
node.r = Node(val)
def find(self, val):
if(self.root != None):
return self._find(val, self.root)
else:
return None
def _find(self, val, node):
if(val == node.v):
return node
elif(val < node.v and node.l != None):
self._find(val, node.l)
elif(val > node.v and node.r != None):
self._find(val, node.r)
def printTree(self):
if(self.root != None):
self._printTree(self.root)
def _printTree(self, node):
if(node != None):
self._printTree(node.l)
print(str(node.v) + ' ')
self._printTree(node.r)
# This doesn't work - graph is not subscriptable
def dfs(self, graph, start):
visited, stack = set(), [start]
while stack:
vertex = stack.pop()
if vertex not in visited:
visited.add(vertex)
stack.extend(graph[vertex] - visited)
return visited
# Haven't tried BFS. Would use a queue, but unsure of the details.
If it is a tree, visited can be a list since trees are non-circular, so there no need to check whether you have visited a node before and, more importantly, you want to maintain the order of your traversal.
def dfs(self, tree):
if tree.root is None:
return []
visited, stack = [], [tree.root]
while stack:
node = stack.pop()
visited.append(node)
stack.extend(filter(None, [node.r, node.l]))
# append right first, so left will be popped first
return visited
Your DFS implementation is slightly incorrect. As written, you've actually mimicked a queue, not a stack.
Your current code actually works fairly well for breadth-first search. It forces the siblings of a node to be evaluated before its children:
def bfs(self, graph, start):
visited, queue = set(), [start]
while queue:
vertex = queue.pop()
if vertex not in visited:
visited.add(vertex)
# new nodes are added to end of queue
queue.extend(graph[vertex] - visited)
return visited
The logic for DFS requires a stack to behave like this: when a new node comes, you need to add it to the left of the list, rather than the right. This way, you force the traversal of a node's descendants before the node's siblings.
def dfs(self, graph, start):
visited, stack = set(), [start]
while stack:
vertex = stack.pop()
if vertex not in visited:
visited.add(vertex)
# new nodes are added to the start of stack
stack = graph[vertex] - visited + stack
return visited
Other Issues
The specific issue you are facing beyond this is that you haven't specified what graph is.
If graph is an object that doesn't support lookup, then you could implement that using a __getitem__() method in the class definition.
Typically, people are content to use a dictionary to implement this. Something like {Node: [<list of node's children], ... } should more than suffice.
I am making a linkedlist, and I had to add in some different functions such as max, min , count and index for my list. I now have to add a remove function which is this snippet of code.
def removeItem(self, position):
''' removeItem removes a selected, because python has a built in "garbage remover",
you don't have to physically delete the node, you only have to skip that node link and python will destroy it
by it self.'''
currentNode = self.head
previousNode = None
count = 0
while count != position:
#This is a quick check to make sure the next node isn't empty.
if currentNode.link is None:
print("Position Invalid")
return None
previousNode = currentNode
currentNode = currentNode.link
count += 1
#Node.Link should link to the next node in the sequence.
previousNode.link = currentNode.link
return currentNode
I am basically just trying to link over the next node in the sequence, so that the built-in garbage remover will remove that node from the sequence. However, I am getting the following error message, which I know has to do something with my instance.
C:\Python33\python.exe "C:/Users/koopt_000/Desktop/College/Sophomore Semester 2/Computer Science 231/Chapter4/Test.py"
900
1
1
2
<ListNode.ListNode object at 0x0000000002679320>
Process finished with exit code 0
Why is it printing out this weird ListNode.ListNode object at the end?
Here is my testing code:
from ListNode import ListNode
from LinkedList import LinkedList
node1 = ListNode(1)
node2 = ListNode(900)
node3 = ListNode(3)
node4 = ListNode(99)
node1.link = node2
node2.link = node3
node3.link = node4
linked_list = LinkedList((1, 900, 3, 99))
print(linked_list.__max__())
print(linked_list.__min__())
print(linked_list.getCount(900))
print(linked_list.getIndex(3))
print(linked_list.removeItem(3))
This is my code for my ListNode class:
# ListNode.py
class ListNode(object):
def __init__(self, item = None, link = None):
'''creates a ListNode with the specified data value and link
post: creates a ListNode with the specified data value and link'''
self.item = item
self.link = link
This is my code for my LinkedList class:
from ListNode import ListNode
class LinkedList(object):
#--------------------------------------------------------------
def __init__(self, seq=()):
""" Pre: Creates a Linked List
Post: Creates a list containing the items in the seq=()"""
if seq == ():
# If there is no items to be put into the list, then it creates an empty one.
self.head = None
else:
# Creates a node for the first item.
self.head = ListNode(seq[0], None)
# If there are remaining items, then they're added while keeping track of the last node.
last = self.head
for item in seq[1:]:
last.link = ListNode(item, None)
last = last.link
self.size = len(seq)
#-------------------------------------------------------------
def __len__(self):
'''Pre: Nothing.
Post: Returns the number of items in the list.'''
return self.size
#-------------------------------------------------------------
def __max__(self):
''' Goes through each node and compares what the max is for the linked list.
Post: Finds the max of the linked list and returns that value.'''
if self.head is None:
return None
max_value = self.head.item
node = self.head.link
while node is not None:
if node.item > max_value:
max_value = node.item
node = node.link
return max_value
#--------------------------------------------------------------
def __min__(self):
''' Goes through each node and compares what the min is for the linked list.
Post: Finds the min of the linked list and returns that value.'''
if self.head is None:
return None
min_value = self.head.item
node = self.head.link
while node is not None:
if node.item < min_value:
min_value = node.item
node = node.link
return min_value
#--------------------------------------------------------------
def getCount(self, yourData):
''' This function counts the amount of times a certain item is in the Linked List.'''
count = 0
node = self.head
for i in range(self.size):
data = node.item
if data is yourData:
count += 1
node = node.link
return count
#--------------------------------------------------------------
def getIndex(self, yourData):
''' getIndex finds the index of the selected item and returns that value. '''
node = self.head
if node is None:
return None
for i in range(self.size):
data = node.item
if data == yourData:
return i
node = node.link
raise IndexError
#--------------------------------------------------------------
def removeItem(self, position):
''' removeItem removes a selected, because python has a built in "garbage remover",
you don't have to physically delete the node, you only have to skip that node link and python will destroy it
by it self.'''
currentNode = self.head
previousNode = None
count = 0
while count != position:
#This is a quick check to make sure the next node isn't empty.
if currentNode.link == None:
print("Position Invalid")
return None
previousNode = currentNode
currentNode = currentNode.link
count += 1
#Node.Link should link to the next node in the sequence.
previousNode.link = currentNode.link
return currentNode
#--------------------------------------------------------------
If anyone could help me out to find out why my removeItem function isn't working that would be helpful!
On a side note, I'm also trying to make a doubly linked list of this list, I know I need to add a prev_node function into my ListNode function, but what else do I need to add? Thanks again!
If your method is returning a <LinkNode object at 0xmemoryaddr> string then it is working fine. You are printing the removed node, and Python is using the default repr() representation for that instance.
If you wanted to make it more readable, you could give the ListNode a object.__repr__ method:
def __repr__(self):
next = 'None' if not self.link else '...' # just to indicate
return 'ListNode({!r}, {})'.format(self.item, next)
This then will print ListNode(99, None) instead of the <ListNode object at 0xmemoryaddr> string Python defaulted to:
>>> ll = LinkedList((1, 900, 3, 99))
>>> ll.head
ListNode(1, ...)
>>> ll.head.link
ListNode(900, ...)
>>> ll.head.link.link
ListNode(3, ...)
>>> ll.head.link.link.link
ListNode(99, None)
One thing you do have to take into account: you need to adjust the length of the list too; on successful removal, subtract 1 from self.size.
So far I have
def tree_iterate():
parent, current = None, self.root
lst = []
while current is not None:
if current.left not None:
lst.append(current.item)
parent, current = current, current.left
if current.right not None:
lst.append(current.item)
parent, current = current, current.right
(sorry about spacing I'm quite new at this)
I'm not quite sure how to iterate on both sides of the tree when current has left and right, without using recursion. My main goal is to have a list of all the nodes in this BSTenter code here
To get a list of all nodes in the BST iteratively, use Breadth-First Search (BFS). Note that this won't give you the nodes in sorted order:
queue = [root]
result = []
while queue:
l = queue.pop(0)
result.append(l)
if l.left != None:
queue.append(l.left)
if l.right!= None:
queue.append(l.right)
If you want the nodes in sorted order, you will need to simulate inorder traversal using a stack:
result = []
stack = [root]
while stack:
stack[-1].visited = True
if stack[-1].left != None and not stack[-1].left.visited:
stack.append(stack[-1].left)
else:
node = stack.pop()
result.append(node)
if stack[-1].right != None:
stack.append(stack[-1].right)