AVL树,在Key插入时始终保持平衡的二叉查找树,并不是完全平衡,而是平衡因子在(-1,0,1)均称为平衡树。
平衡因子为1时,最少的节点的情况下,所容纳的节点数近似斐波那契数列,由公式推出AVL树最多搜索次数的时间复杂度为O(logn)。
AVL树插入时从叶节点插入,会影响父节点的平衡因子,根据不同情况调整。
class BinarySearchTree:
def __init__(self):
self.root = None
self.size = 0
def length(self):
return self.size
def __len__(self):
return self.size
def __iter__(self):
return self.root.__iter__()
def put(self, key, val):
if self.root:
self._put(key, val, self.root)
else:
self.root = TreeNode(key, val)
self.size += 1
def _put(self, key, val, currentnode):
if key < currentnode.key:
if currentnode.hasleftchild():
self._put(key, val, currentnode.leftchild)
else:
currentnode.leftchild = TreeNode(key, val, parent=currentnode)
self.updatebalance(currentnode.leftchild) # 若插入需重新计算平衡因子
else:
if currentnode.hasrightchild():
self._put(key, val, currentnode.rightchild)
else:
currentnode.rightchild = TreeNode(key, val, parent=currentnode)
self.updatebalance(currentnode.rightchild)
def updatebalance(self, node):
if node.balancefactor > 1 or node.balancefactor < -1:
self.rebalance(node) # 平衡因子超出,就重新平衡
return
if node.parent is not None:
if node.isleftchild():
node.parent.balancefactor += 1 # 增加左子节点,父节点的平衡因子+1
elif node.isrightchild():
node.parent.balancefactor -= 1
if node.parent.balancefactor != 0: # 父节点的平衡因子改变,则需要确定更新平衡因子
self.updatebalance(node.parent)
def rotateleft(self, rotroot): # 右重子树的左旋转
newroot = rotroot.rightchild # 先创建一个新的根节点,其值为原本的右子节点,无父节点,子节点。
rotroot.rightchild = newroot.leftchild # 为原根节点创建新的右子节点,值为新根节点的左子节点
if newroot.leftchild is not None: # 如果新根节点有左子节点,那左子节点的父节点为原根节点,链接完成。
newroot.leftchild.parent = rotroot
newroot.parent = rotroot.parent # 新根节点的父节点链接完成。
if rotroot.isroot(): # 原根节点为总的根节点,则根节点更新为新的根节点
self.root = newroot
else:
if rotroot.isleftchild(): # 原根节点是其父节点的左子节点,则将父节点的左子节点链接到新根节点
rotroot.parent.leftchild = newroot
else:
rotroot.parent.rightchild = newroot
newroot.leftchild = rotroot # 新根节点的左子节点为原根节点。
rotroot.parent = newroot # 原根节点的父节点链接, 旋转完成。
rotroot.balancefactor = rotroot.balancefactor + 1 - min(newroot.balancefactor, 0) # 计算平衡因子
newroot.balancefactor = newroot.balancefactor + 1 + max(rotroot.balancefactor, 0)
def rotateright(self, rotroot): # 左重子树的右旋转
newroot = rotroot.leftchild
rotroot.leftchild = newroot.rightchild
if newroot.rightchild is not None:
newroot.rightchild.parent = rotroot
newroot.parent = rotroot.parent
if rotroot.isroot():
self.root = newroot
else:
if rotroot.isleftchild():
rotroot.parent.leftchild = newroot
else:
rotroot.parent.rightchild = newroot
newroot.rightchild = rotroot
rotroot.parent = newroot
rotroot.balancefactor = rotroot.balancefactor + 1 - min(newroot.balancefactor, 0) # 计算平衡因子
newroot.balancefactor = newroot.balancefactor + 1 + max(rotroot.balancefactor, 0)
def rebalance(self, node):
if node.balancefactor < 0: # 右重子树
if node.rightchild.balancefactor > 0:
self.rotateright(node.rightchild)
self.rotateleft(node)
else:
self.rotateleft(node)
elif node.balancefactor > 0:
if node.leftchild.balancefactor < 0:
self.rotateleft(node.leftchild)
self.rotateright(node)
else:
self.rotateright(node)
def __setitem__(self, key, value):
self.put(key, value)
def get(self, key):
if self.root:
res = self._get(key, self.root)
if res:
return res.payload
else:
return None
else:
return None
def _get(self, key, currentnode):
if not currentnode:
return None
elif currentnode.key == key:
return currentnode
elif key < currentnode.key:
return self._get(key, currentnode.leftchild)
else:
return self._get(key, currentnode.rightchild)
def __getitem__(self, key):
return self.get(key)
def __contains__(self, key):
if self._get(key, self.root):
return True
else:
return False
def delete(self, key):
if self.size > 1:
nodetoremove = self._get(key, self.root)
print(nodetoremove.payload)
if nodetoremove:
self.remove(nodetoremove.key, 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, key, currentnode):
if currentnode.isleaf():
if currentnode == currentnode.parent.leftchild:
currentnode.parent.leftchild = None
else:
currentnode.parent.rightchild = None
elif currentnode.hasbothchildren():
succ = currentnode.findsuccessor()
succ.spliceout()
currentnode.key = succ.key
currentnode.payload = succ.payload
else:
if currentnode.hasleftchild():
if currentnode.isleftchild():
currentnode.leftchild.parent = currentnode.parent
currentnode.parent.leftchild = currentnode.leftchild
elif currentnode.isrightchild():
currentnode.leftchild.parent = currentnode.parent
currentnode.parent.rightchild = currentnode.leftchild
else:
currentnode.replacenodedata(currentnode.leftchild.key,currentnode.leftchild.payload,currentnode.leftchild.leftchild,currentnode.leftchild.rightchild)
else:
if currentnode.isleftchild():
currentnode.rightchild.parent = currentnode.parent
currentnode.parent.leftchild = currentnode.rightchild
elif currentnode.isrightchild():
currentnode.rightchild.parent = currentnode.parent
currentnode.parent.rightchild = currentnode.rightchild
else:
currentnode.replacenodedata(currentnode.rightchild.key,currentnode.rightchild.payload,currentnode.rightchild.leftchild,currentnode.rightchild.rightchild)
def __delitem__(self, key):
self.delete(key)
class TreeNode:
def __init__(self, key, val, left=None, right=None, parent=None, balancefactor=0):
self.key = key
self.payload = val
self.leftchild = left
self.rightchild = right
self.parent = parent
self.balancefactor = balancefactor
def hasleftchild(self):
return self.leftchild
def hasrightchild(self):
return self.rightchild
def isleftchild(self):
return self.parent and self.parent.leftchild == self
def isrightchild(self):
return self.parent and self.parent.rightchild == self
def isroot(self):
return not self.parent
def isleaf(self):
return not (self.rightchild or self.leftchild)
def hasanychildren(self):
return self.rightchild or self.leftchild
def hasbothchildren(self):
return self.rightchild and self.leftchild
def replace_node_data(self, key, value, lc, rc):
self.key = key
self.payload = value
self.leftchild = lc
self.rightchild = rc
if self.hasleftchild():
self.leftchild.parent = self
if self.hasrightchild():
self.rightchild.parent = self
def findsuccessor(self):
succ = None
if self.hasrightchild():
succ = self.rightchild.findmin()
return succ
def findmin(self):
current = self
while current.hasleftchild():
current = current.leftchild
return current
def spliceout(self):
if self.isleaf():
if self.isleftchild():
self.parent.leftchild = None
else:
self.parent.rightchild = None
elif self.hasanychildren():
if self.isleftchild():
self.parent.leftchild = self.leftchild
else:
self.parent.rightchild = self.leftchild
self.leftchild.parent = self.parent
else:
if self.isleftchild():
self.parent.leftchild = self.rightchild
else:
self.parent.rightchild = self.rightchild
self.rightchild.parent = self.parent
if __name__ == "__main__":
alist = [70, 31, 93, 94, 14, 23, 73, 24]
bst = BinarySearchTree()
bst.put(alist[0], 'tom')
bst.put(alist[1], 'mike')
bst.put(alist[2], 'sanji')
bst.put(alist[3], 'jim')
bst.put(alist[4], 'loyal')
bst.put(alist[5], 'solo')
bst.put(alist[6], 'namei')
bst.put(alist[7], 'tt')
# print(len(bst))
# bst.delete(alist[6])
# bst.delete(alist[0])
# print(bst.root.leftchild.leftchild.rightchild.key)
print(bst.root.key)
print(bst.root.leftchild.key)
print(bst.root.rightchild.key)
print(bst.root.leftchild.leftchild.key)
print(bst.root.leftchild.rightchild.key)
print(bst.root.leftchild.rightchild.rightchild.key)
print(bst.root.rightchild.leftchild.key)
print(bst.root.rightchild.rightchild.key)
### 这段代码得再看一遍,细细解读。
def put(self, key, val):
if self.root:
self._put(key, val, self.root) # 已有根节点,插入节点时,调用_put方法
else:
self.root = TreeNode(key, val) # 无根节点,插入值直接赋值给根节点
self.size += 1
def _put(self, key, val, currentnode): # 插入的值应该是不允许重复的
if key < currentnode.key: # 当前值从根节点开始,与插入值比较
if currentnode.hasleftchild():
self._put(key, val, currentnode.leftchild)
else:
currentnode.leftchild = TreeNode(key, val, parent=currentnode) # 当前值左子节点为空,则可插入
self.updatebalance(currentnode.leftchild) # 若插入需重新计算平衡因子
else:
if currentnode.hasrightchild():
self._put(key, val, currentnode.rightchild)
else:
currentnode.rightchild = TreeNode(key, val, parent=currentnode)
self.updatebalance(currentnode.rightchild)
def updatebalance(self, node):
if node.balancefactor > 1 or node.balancefactor < -1:
self.rebalance(node) # 平衡因子超出,就调整树,使其重新平衡
return
if node.parent is not None:
if node.isleftchild():
node.parent.balancefactor += 1 # 增加左子节点,父节点的平衡因子+1
elif node.isrightchild():
node.parent.balancefactor -= 1 # 增加右子节点,父节点的平衡因子-1
if node.parent.balancefactor != 0: # 父节点的平衡因子改变,则需要确定更新平衡因子
self.updatebalance(node.parent) # 递归计算
def rotateleft(self, rotroot): # 右重子树的左旋转
newroot = rotroot.rightchild # 先创建一个新的根节点,其值为原本的右子节点,无父节点,子节点。
rotroot.rightchild = newroot.leftchild # 为原根节点创建新的右子节点,值为新根节点的左子节点
if newroot.leftchild is not None: # 如果新根节点有左子节点,那左子节点的父节点为原根节点,链接完成。
newroot.leftchild.parent = rotroot
newroot.parent = rotroot.parent # 新根节点的父节点链接完成。
if rotroot.isroot(): # 原根节点为总的根节点,则根节点更新为新的根节点
self.root = newroot
else:
if rotroot.isleftchild(): # 原根节点是其父节点的左子节点,则将父节点的左子节点链接到新根节点
rotroot.parent.leftchild = newroot
else:
rotroot.parent.rightchild = newroot
newroot.leftchild = rotroot # 新根节点的左子节点为原根节点。
rotroot.parent = newroot # 原根节点的父节点链接, 旋转完成。
rotroot.balancefactor = rotroot.balancefactor + 1 - min(newroot.balancefactor, 0) # 计算平衡因子
newroot.balancefactor = newroot.balancefactor + 1 + max(rotroot.balancefactor, 0)
原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。
如有侵权,请联系 cloudcommunity@tencent.com 删除。
原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。
如有侵权,请联系 cloudcommunity@tencent.com 删除。