Binární vyhledávací strom v Pythonu

kód Pythonu pro binární vyhledávací strom

#Complete Binary Search Tree Using Python 3

class node:
    def  __init__(self,data):
        self.data=data
        self.left=None
        self.right=None

class binarytree:
    def __init__(self):
        self.root=None

#INSERT

    def insert(self,data):
        if self.root==None:				
            self.root=node(data)
        else:
            self._insert(data,self.root)
    def _insert(self,data,cur_node):
        if data<cur_node.data:
            if cur_node.left==None:			
                cur_node.left=node(data)
            else:
                self._insert(data,cur_node.left) 
        elif data>cur_node.data:			
            if cur_node.right==None:
                cur_node.right=node(data)
            else:
                self._insert(data,cur_node.right)
        else:
            print('Data In Treee Already')

#REMOVE

    def remove(self,data):
        if self.root!=None:
            self._remove(data,self.root)
    def _remove(self,data,cur_node):
        if cur_node == None:
            return cur_node
        if data<cur_node.data:
            cur_node.left=self._remove(data,cur_node.left)
        elif data>cur_node.data:
            cur_node.right=self._remove(data,cur_node.right)
        else:
            if cur_node.left is None and cur_node.right is None:
                print('Removing Leaf Node')
                if cur_node==self.root:
                    self.root=None
                del cur_node
                return None
            if cur_node.left is None:
                print('Removing None with Right Child')
                if cur_node==self.root:
                    self.root=cur_node.right
                tempnode=cur_node.right
                del cur_node
                return tempnode
            elif cur_node.right is None:
                print('Removing None with Left Child')
                if cur_node==self.root:
                    self.root=cur_node.left
                tempnode=cur_node.left
                del cur_node
                return tempnode
            print('Removing Node with 2 Children')
            tempnode=self.getpred(cur_node.left)
            cur_node.data=tempnode.data
            cur_node.left=self._remove(cur_node.data,cur_node.left)
        return cur_node
    def getpred(self,cur_node):
        if cur_node.right!=None:
            return self.getpred(cur_node.right)
        return cur_node

#INORDER TRAVERSAL

    def inorder(self):
        if self.root!=None:
            self._inorder(self.root)
    def _inorder(self,cur_node):
        if cur_node!=None:
            self._inorder(cur_node.left)
            print(cur_node.data)
            self._inorder(cur_node.right)

#PREORDER TRAVERSAL

    def preorder(self):
        if self.root!=None:
            self._preorder(self.root)
    def _preorder(self,cur_node):
        if cur_node!=None:
            print(cur_node.data)
            self._preorder(cur_node.left)
            self._preorder(cur_node.right)

#POSTORDER TRAVERSAL

    def postorder(self):
        if self.root!=None:
            self._postorder(self.root)
    def _postorder(self,cur_node):
        if cur_node!=None:
            self._postorder(cur_node.left)
            self._postorder(cur_node.right)
            print(cur_node.data)

#MINIMUM VALUE

    def minval(self):
        if self.root!=None:
            return self._minval(self.root)
    def _minval(self,cur_node):
        if cur_node.left!=None:
            return self._minval(cur_node.left)
        return cur_node.data

#MAXIMUM VALUE

    def maxval(self):
        if self.root!=None:
            return self._maxval(self.root)
    def _maxval(self,cur_node):
        if cur_node.right!=None:
            return self._maxval(cur_node.right)
        return cur_node.data

tree=binarytree()

tree.insert(100)
tree.insert(90)					#			 100
tree.insert(110)				#			/	\
tree.insert(95)					#          90   110
tree.insert(30)					#		  /  \
								#		30    95 
tree.remove(110)
tree.remove(90)

tree.inorder()
#tree.preorder()
#tree.postorder()

print(tree.minval())
print(tree.maxval())

binární vyhledávací strom v pythonu

Binary Search Tree at this link:
  
https://github.com/shreyasvedpathak/Data-Structure-Python/tree/master/BinaryTrees

Binární vyhledávací strom v pythonu

# বাইনারি সার্চ ট্রি-এর ক্ষেত্রে ২ টি বিষয় মাথায় রাখতে হবে:
'''
১. যদি ট্রি-তে আগে থেকে কোনো নোড না থাকে (অর্থাৎ বর্তমান root নোড none থাকবে),
            তাহলে নতুন যোগ করা নোডটিই হবে ট্রি- এর root নোড । আবার-
২. নতুন নোডটি যদি root নোডের সরাসরি চাইল্ড হয়, তাহলেও root  নোডের  পরিবর্তন ঘটবে।
            এ কারণেই আমরা root নোডকে রিটার্ন করি।
'''
# There are two things to keep in mind when it comes to binary search trees:
'''
1. If the tree does not already have a node (ie the existing root node will have none), 
                then the newly added node will be the root node of the tree. Again
2. If the new node is a direct child of the root node, the root node will also change. 
                This is why we return to the root node.
'''

# second system:

class TreeNode:
    def __init__(self,data):
        self.data = data
        self.parent = None
        self.left = None
        self.right = None

    def __repr__(self):
        return repr(self.data)

    def add_left(self, node):
        self.left = node
        if node is not None:
            node.parent = self

    def add_right(self, node):
        self.right = node
        node.parent = self

# now bst_insert:
def bst_insert(root,node):
    last_node = None
    current_node = root
    while current_node is not None:
        last_node = current_node
        if node.data < current_node.data:
            current_node = current_node.left
        else:
            current_node = current_node.right
    if last_node is None:
        # tree was empty. node is the only node, hence root
        root = node # new node add
    elif node.data < last_node.data:
        last_node.add_left(node)
    else:
        last_node.add_right(node)
    return root
'''
              _10_
             /    \
            5      17
           /      /  \
          3      12  19
         / \             
        1   4         
   
'''
# now create_bst:
def create_bst():
    root = TreeNode(10)
    for item in [5,17,3,7,12,19,1,4]:
        node = TreeNode(item)
        root = bst_insert(root, node)
    return root

# In_order tree traverse:
def in_order(node):
    if node.left:
        in_order(node.left)
    print(node)
    if node.right:
        in_order(node.right)

# bst- tree minimum node:
def bst_minimum(root):
    while root.left is not None:
        root = root.left
    print(root)

# Node transfer:
def bst_transfer(root, current_node, new_node):
    if current_node.parent is None:
        root = new_node
    elif current_node == current_node.parent.left:
        current_node.parent.add_left(new_node)
    else:
        current_node.parent.add_right(new_node)
    return root

# Node delete:
def bst_delete(root,node):
    if node.left is None:
        root = bst_transfer(root,node,node.right)
    elif node.right is None:
        root = bst_transfer(root,node,node.left)

    else:
        min_node = bst_minimum(node.right)
        if min_node.parent != node:
            root = bst_transfer(root,min_node,min_node.right)
            min_node.add_right(node.right)
        root = bst_transfer(root,node,min_node)
        min_node.add_left(node.left)
    return root



# এখন আমরা BST-তে কোনো ডেটা খুঁজে বের করার ফাংশন টি লিখে ফেলি।
# Now we write the function to find any data in BST.
def best_search(node,key):
    while node is not None:
        if node.data == key:
            return node
        if key < node.data:
            node = node.left
        else:
            node = node.right
    return node

# Now check to your code:
if __name__ == "__main__":
    root = create_bst()
    print("Tree is root =",root)
    print()

    print("BST:")
    in_order(root)

    for key in [1,5,10]:
        node = best_search(root,key)
        print("will delete =", node)
        root = bst_delete(root,node)
        print("BST:")
        in_order(root)

binární strom v pythonu

Binary Tree implementation at this link:
  
https://github.com/shreyasvedpathak/Data-Structure-Python/tree/master/BinaryTrees

Binární Vyhledávací strom implementace v pythonu

"""
	              17
		    /    \
		   /      \
		  /	   \		  
		 4         20
		/\	   /\	
	       /  \       /  \
	      /    \     /    \
	     1      9   18    23
			        \
				 \
				  \ 
				   34
							 
"""							 

# Binary Search Tree implementation in Python

class BinaryTreeNode():
    def __init__(self, data):
        self.data = data
        self.left = None
        self.right = None
        
    def add_child(self, data):
        if data == self.data: # check if the of new data exist already in the tree, if yes don't add
            return
        
        if data < self.data:
            # Add to left subtree
            if self.left:
                self.left.add_child(data) # Recursively call the add_child method to add the data to an appropriate place
            else:
                self.left = BinaryTreeNode(data)
        else:
            # Add to right subtree
            if self.right:
                self.right.add_child(data) # Recursively call the add_child method to add the data to an appropriate place
            else:
                self.right = BinaryTreeNode(data)
    
    # Visit Left subtree, then Root node and finaly Right subtree
    def in_order_traversal(self):  # Left - Root - Right
        elements = []
        
        # Getting all elements of the Left Subtree    
        if self.left:
            elements += self.left.in_order_traversal() # Recursively get all the elements of the left subtree and add them into the list
        elements.append(self.data) # Adding the root node to the list
        
        # Getting all elements of the Right Subtree    
        if self.right:
            elements += self.right.in_order_traversal() # Recursively get all the elements of the right subtree and add them into the list
        return elements
        
    # Get all elements from the Root node then the left subtree and finanally the Right subtree 
    def pre_order_traversal(self): # Root - Left - Right
        elements = []
        
        elements.append(self.data)
        
        if self.left:
            elements += self.left.pre_order_traversal()  # Recursively get all the elements of the left subtree and add them into the list
        
        if self.right:
            elements += self.right.pre_order_traversal()  # Recursively get all the elements of the right subtree and add them into the list

        
        return elements # get the Root node element
        
    # Get all elements from the Right subtree then the left subtree and finally the Root node    
    def post_order_traversal(self):
        elements = []
        
        if self.left:
            elements += self.left.post_order_traversal()  # Recursively get all the elements of the left subtree and add them into the list
        
        if self.right:
            elements += self.right.post_order_traversal()  # Recursively get all the elements of the right subtree and add them into the list
            
        elements.append(self.data) # Get the Root node element
        
        return elements
        
        
    def search_element(self, elem): # complexity of log n O(log n)
        if self.data == elem:
            return True
        elif elem < self.data:
            # This means if present, element would be on the left 
            if self.left:
               return self.left.search_element(elem)  
            else:
                return False
            
        else:
            # This means if present, element would be on the right
            if self.right:
                return self.right.search_element(elem)  
            else:
                return False
    
    
    def sum_of_all_elements_in_tree(self):
        return sum(self.in_order_traversal())
        
    def max_element_in_tree(self):
        return max(self.in_order_traversal())    
    
    def min_element_in_tree(self):
        return min(self.in_order_traversal())    
    
    
# Tree Builder helper method
def build_binary_tree(lst_elem: list):
    if len(lst_elem) >1:
        root_node = BinaryTreeNode(lst_elem[0])
        for i in lst_elem[1:]:
            root_node.add_child(i)
       
        #root_node.search_element(20)
        #print(root_node.in_order_traversal())
        return root_node
    else:
        return print("Insufficient number of elements")
        

if __name__ == '__main__':
   mt = build_binary_tree([17, -5, 4, 1, 20, 9, -1, 23, 18, 0, 34])
   print("In Order Traversal", mt.in_order_traversal())
   print("Post Order Traversal", mt.post_order_traversal())
   print("Pre Order Traversal", mt.pre_order_traversal())
   print(mt.search_element(20))
   print("Sum of all elemnts in tree", mt.sum_of_all_elements_in_tree())
   print("Max element in tree is", mt.max_element_in_tree())
   print("Min element in tree is", mt.min_element_in_tree())

binární strom v Pythonu

Binary Tree implementation at this link:
  
https://github.com/shreyasvedpathak/Data-Structure-Python/tree/master/BinaryTrees

binární vyhledávání v Pythonu

def binary_search(group, suspect):
  group.sort()
  midpoint = len(group)//2
  while(True):
    if(group[midpoint] == suspect):
      return midpoint
    if(suspect > group[midpoint]):
            group = group[midpoint]
    if(suspect < group[midpoint]):
      group = group[0: midpoint]
    midpoint = (len(group)//2)

class BSTNode:
    def __init__(self, key=None):
        self.left = None
        self.right = None
        self.key = key
# Insert method can add a list of nodes to the BST
    def insert(self, keyList):
       for i in keyList:
          self.insertKey(i)
# This insertKey 
    def insertKey(self, key):
        if not self.key:
            self.key = key
            return
        if self.key == key:
            return
        if key < self.key:
            if self.left:
                self.left.insertKey(key)
                return
            self.left = BSTNode(key)
            return
        if self.right:
            self.right.insertKey(key)
            return
        self.right = BSTNode(key)
    def display(self):
        lines, *_ = self._display_aux()
        for line in lines:
            print(line)

    def _display_aux(self):
        """Returns list of strings, width, height, and horizontal coordinate of the root."""
        # No child.
        if self.right is None and self.left is None:
            line = '%s' % self.key
            width = len(line)
            height = 1
            middle = width // 2
            return [line], width, height, middle

        # Only left child.
        if self.right is None:
            lines, n, p, x = self.left._display_aux()
            s = '%s' % self.key
            u = len(s)
            first_line = (x + 1) * ' ' + (n - x - 1) * '_' + s
            second_line = x * ' ' + '/' + (n - x - 1 + u) * ' '
            shifted_lines = [line + u * ' ' for line in lines]
            return [first_line, second_line] + shifted_lines, n + u, p + 2, n + u // 2

        # Only right child.
        if self.left is None:
            lines, n, p, x = self.right._display_aux()
            s = '%s' % self.key
            u = len(s)
            first_line = s + x * '_' + (n - x) * ' '
            second_line = (u + x) * ' ' + '\\' + (n - x - 1) * ' '
            shifted_lines = [u * ' ' + line for line in lines]
            return [first_line, second_line] + shifted_lines, n + u, p + 2, u // 2

        # Two children.
        left, n, p, x = self.left._display_aux()
        right, m, q, y = self.right._display_aux()
        s = '%s' % self.key
        u = len(s)
        first_line = (x + 1) * ' ' + (n - x - 1) * '_' + s + y * '_' + (m - y) * ' '
        second_line = x * ' ' + '/' + (n - x - 1 + u + y) * ' ' + '\\' + (m - y - 1) * ' '
        if p < q:
            left += [n * ' '] * (q - p)
        elif q < p:
            right += [m * ' '] * (p - q)
        zipped_lines = zip(left, right)
        lines = [first_line, second_line] + [a + u * ' ' + b for a, b in zipped_lines]
        return lines, n + m + u, max(p, q) + 2, n + u // 2
    #Inorder Walk    
    def inorder(self):
        if self.left:
            self.left.inorder()
        print(self.key)
        if self.right:
            self.right.inorder()
a = BSTNode()
a.insert([5,7,4,3,5,1,3,6]) #inserting some random numbers in the form of list
a.inorder()
a.display()

vložit binární vyhledávací strom

void BSNode::insert(std::string value) {

	if (this->_data == value) {
		_count++;
		return;
	}

	if (this->_data > value) {
		if (this->getLeft() == nullptr) {
			this->_left = new BSNode(value);
		}
		this->getLeft()->insert(value);
		return;
	}

	if (this->getRight() == nullptr) {
		this->_right = new BSNode(value);
		return;
	}
	this->getRight()->insert(value);
}

binární vyhledávací strom v Pythonu

Binary Search Tree at this link:
  
https://github.com/shreyasvedpathak/Data-Structure-Python/tree/master/BinaryTrees