对于二叉查找树的每个节点Node,它的左子树中所有的关键字都小于Node的关键字,而右子树中的所有关键字都大于Node的关键字。
二叉查找树的平均深度是O(log N)。
1.初始化
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class
BinarySearchTree( object ):
def
__init__( self ,key):
self .key = key
self .left = None
self .right = None
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2.Find
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def find( self ,x):
if
x = = self .key:
return
self
elif
x< self .key and
self .left:
return
self .left.find(x)
elif
x> self .key and
self .right:
return
self .right.find(x)
else :
return
None |
3.FindMin和FindMax
分别返回树中的最小元素与最大元素的位置。FindMin,从根开始并且只要有左儿子就向左进行查找,终止点是最小元素。FindMax则向右进行。
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def findMin( self ):
if
self .left:
return
self .left.findMin()
else :
return
self
def findMax( self ):
tree = self
if
tree:
while
tree.right:
tree = tree.right
return
tree
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4.Insert
为了将x插入到树Tree中,先用find查找,如果找到x,则什么也不做。否则,将x插入到遍历路径的最后一点。
来自《Problem Solving with Algorithms and Data Structures》的图片:
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def insert( self ,x):
if
x< self .key:
if
self .left:
self .left.insert(x)
else :
tree = BinarySearchTree(x)
self .left = tree
elif
x> self .key:
if
self .right:
self .right.insert(x)
else :
tree = BinarySearchTree(x)
self .right = tree
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5.Delete
删除某节点有3种情况:
5.1 如果节点是一片树叶,那么可以立即被删除。
来自《Problem Solving with Algorithms and Data Structures》的图片:
5.2 如果节点只有一个儿子,则将此节点parent的指针指向此节点的儿子,然后删除。
来自《Problem Solving with Algorithms and Data Structures》的图片:
5.3 如果节点有两个儿子,则将其右子树的最小数据代替此节点的数据,并将其右子树的最小数据(不可能有左儿子,只有一个右儿子)删除。
来自《Problem Solving with Algorithms and Data Structures》的图片:
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def delete( self ,x):
if
self .find(x):
if
x< self .key:
self .left = self .left.delete(x)
return
self
elif
x> self .key:
self .right = self .right.delete(x)
return
self
elif
self .left and
self .right:
key = self .right.findMin().key
self .key = key
self .right = self .right.delete(key)
return
self
else :
if
self .left:
return
self .left
else :
return
self .right
else :
return
self
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全部代码
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class
BinarySearchTree( object ):
def
__init__( self ,key):
self .key = key
self .left = None
self .right = None
def
find( self ,x):
if
x = = self .key:
return
self
elif
x< self .key and
self .left:
return
self .left.find(x)
elif
x> self .key and
self .right:
return
self .right.find(x)
else :
return
None def
findMin( self ):
if
self .left:
return
self .left.findMin()
else :
return
self
def
findMax( self ):
tree = self
if
tree:
while
tree.right:
tree = tree.right
return
tree
def
insert( self ,x):
if
x< self .key:
if
self .left:
self .left.insert(x)
else :
tree = BinarySearchTree(x)
self .left = tree
elif
x> self .key:
if
self .right:
self .right.insert(x)
else :
tree = BinarySearchTree(x)
self .right = tree
def
delete( self ,x):
if
self .find(x):
if
x< self .key:
self .left = self .left.delete(x)
return
self
elif
x> self .key:
self .right = self .right.delete(x)
return
self
elif
self .left and
self .right:
key = self .right.findMin().key
self .key = key
self .right = self .right.delete(key)
return
self
else :
if
self .left:
return
self .left
else :
return
self .right
else :
return
self
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另一种类似于链表的写法
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class
TreeNode( object ):
def
__init__( self ,key,left = None ,right = None ,parent = None ):
self .key = key
self .left = left
self .right = right
self .parent = parent
def
hasLeftChild( self ):
return
self .left
def
hasRightChild( self ):
return
self .right
def
isLeftChild( self ):
return
self .parent and
self .parent.left = = self
def
isRightChild( self ):
return
self .parent and
self .parent.right = = self
class
BSTree( object ):
def
__init__( self ):
self .root = None
self .size = 0
def
length( self ):
return
self .size
def
insert( self ,x):
node = TreeNode(x)
if
not self .root:
self .root = node
self .size + = 1
else :
currentNode = self .root
while
True :
if
x<currentNode.key:
if
currentNode.left:
currentNode = currentNode.left
else :
currentNode.left = node
node.parent = currentNode
self .size + = 1
break
elif
x>currentNode.key:
if
currentNode.right:
currentNode = currentNode.right
else :
currentNode.right = node
node.parent = currentNode
self .size + = 1
break
def
find( self ,key):
if
self .root:
res = self ._find(key, self .root)
if
res:
return
res
else :
return
None
else :
return
None
def
_find( self ,key,node):
if
not node:
return
None
elif
node.key = = key:
return
node
elif
key<node.key:
return
self ._find(key,node.left)
else :
return
self ._find(key,node.right)
def
findMin( self ):
if
self .root:
current = self .root
while
current.left:
current = current.left
return
current
else :
return
None
def
_findMin( self ,node):
if
node:
current = node
while
current.left:
current = current.left
return
current
def
findMax( self ):
if
self .root:
current = self .root
while
current.right:
current = current.right
return
current
else :
return
None
def
delete( self ,key):
if
self .size> 1 :
nodeToRemove = self .find(key)
if
nodeToRemove:
self .remove(nodeToRemove)
self .size - = 1
else :
raise
KeyError, ‘Error, key not in tree‘
elif
self .size = = 1
and self .root.key = = key:
self .root = None
self .size - = 1
else :
raise
KeyError, ‘Error, key not in tree‘
def
remove( self ,node):
if
not node.left and
not node.right: #node为树叶
if
node = = node.parent.left:
node.parent.left = None
else :
node.parent.right = None
elif
node.left and
node.right: #有两个儿子
minNode = self ._findMin(node.right)
node.key = minNode.key
self .remove(minNode)
else : #有一个儿子
if
node.hasLeftChild():
if
node.isLeftChild():
node.left.parent = node.parent
node.parent.left = node.left
elif
node.isRightChild():
node.left.parent = node.parent
node.parent.right = node.left
else : #node为根
self .root = node.left
node.left.parent = None
node.left = None
else :
if
node.isLeftChild():
node.right.parent = node.parent
node.parent.left = node.right
elif
node.isRightChild():
node.right.parent = node.parent
node.parent.right = node.right
else : #node为根
self .root = node.right
node.right.parent = None
node.right = None
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