Binary Search Tree e Heap
Nella lezione del 3/12, abbiamo visto i BST, mentre in quella di lunedi' vedremo l'Heap. A partire da queste strutture dati, potremo costruire l'algoritmo di ordinamento noto come Heapsort.
Qui trovate vari esempi di Heap e Heapsort in Python.
Binary Search Tree e Heap
In today's lecture, we have seen the BST. We will see the Heap data structure next time, as well as the Heapsort algorithm.
Here you can find the Heap and Heapsort examples in Python.
Binary Search Tree Implementation
#!/usr/bin/python class BinNode(object): def __init__(self,parent,key,content=None): self.data = content self.key = key self.left = None self.right = None self.parent= parent def __getitem__(self,side): if side in [ 0, 'left', 'l' ] : return self.left elif side in [ 1, 'right', 'r' ] : return self.right raise KeyError, side def __setitem__(self,side,item): if not isinstance(item,BinNode) : raise TypeError, item if side in [ 0, 'left', 'l' ] : self.left = item elif side in [ 1, 'right', 'r' ] : self.right = item else : raise KeyError, side def isLeaf(self): return not (self.left or self.right) def search(self,key): if self.key==key : return self if key<self.key : return self.left.search(key) if self.left else None else : return self.right.search(key) if self.right else None def insert(self,key,content=None): if key<self.key : if self.left : self.left.insert(key,content) else : self.left = BinNode(self,key,content) else : if self.right : self.right.insert(key,content) else : self.right = BinNode(self,key,content) def min(self): x=self while x.left : x=x.left return x def max(self): x=self while x.right : x=x.right return x def next(self): if self.right : return self.right.min() x,y=self,self.parent while y and x == y.right : x,y=y,y.parent return y def prev(self): if self.left : return self.left.max() x,y=self,self.parent while y and x == y.left : x,y=y,y.parent return y def delete(self,node): root = self y = node if not node.left or not node.right else node.next() x = y.left if y.left else y.right if x : x.parent = y.parent if not y.parent : root =x elif y.parent.left == y : y.parent.left = x else : y.parent.right = x if y != node : node.key = y.key node.data = y.data return root, y def __str__(self) : return '{ '+`self.key`+' : '+`self.data`+' }' def preorder(node,action,direction=['l','r']): '''Preorder, defaults to left to right; action must be a function specific for the elements''' action(node) if node[direction[0]] : preorder(node[direction[0]],action,direction) if node[direction[1]] : preorder(node[direction[1]],action,direction) def postorder(node,action,direction=['l','r']): '''Preorder, defaults to left to right; action must be a function specific for the elements''' if node[direction[0]] : preorder(node[direction[0]],action,direction) if node[direction[1]] : preorder(node[direction[1]],action,direction) action(node) def inorder(node,action,direction=['l','r']): '''Preorder, defaults to left to right; action must be a function specific for the elements''' if node.isLeaf() : action(node) else : if node[direction[0]] : inorder(node[direction[0]],action,direction) action(node) if node[direction[1]] : inorder(node[direction[1]],action,direction) if __name__ == '__main__' : def action(node): print node.key, from random import choice root = BinNode(None,choice(range(12))) for i in range(5) : root.insert(choice(range(12))) inorder(root,action) print '' print 'max', root.max().key print 'min', root.min().key x=root.min() for i in range(5) : print x.key, x=x.next() print x.key for i in range(5) : x = root.search(choice(range(12))) if x : root,deleted=root.delete(x) print 'deleted', deleted.key inorder(root,action)