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BST.py
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198 lines (166 loc) · 5.09 KB
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import copy
from DataStructure.tree.BinaryTree import BinaryTree
# 二叉查找树
class BST(BinaryTree):
root = None
def __init__(self, key, data):
"""
初始化树
:param data: 节点值
"""
self.key = key
self.data = data
super().__init__(key)
def __str__(self):
return str({
'key': str(self.key),
'data': str(self.data)
})
# 再书中找到一个值
def get(self, key):
"""
:param key: 需要找到的值
:return: 节点
"""
def inner_func(node, _key):
"""
:param node: 节点
:param _key: 值
:return: 找到值时返回节点，未找到时,递归或者返回None
"""
if node is None:
return None
if _key > node.key:
return inner_func(node.r_child, _key)
elif _key < node.key:
return inner_func(node.l_child, _key)
else:
return node
return inner_func(self.root, key)
def put(self, key, value):
"""
如果 key存在就更新 value，如果 key 不存在就插入新节点
如果根节点不存在就创建一个 BST 实例
:param key:
:param value:
:return:
"""
if self.root is None:
return BST(key, value)
def inner_func(node, _key, _value):
if node is None:
return BST(_key, _value)
if _key > node.key:
node.r_child = inner_func(node.r_child, _key, _value)
elif _key < node.key:
node.l_child = inner_func(node.l_child, _key, _value)
else:
node.data = _value
return node
return inner_func(self.root, key, value)
def select(self, num):
"""
选出第num小的元素
:param num:
:return: 节点
"""
def inner_select(node, _num):
if node is None:
return
t = node.l_child.size()
if _num < t:
return inner_select(node.l_child, _num)
elif _num > t:
return inner_select(node.r_child, _num - t - 1)
else:
return node
return inner_select(self.root, num)
def min(self):
def inner_min(node):
if node.l_child is None:
return node
else:
return inner_min(node.l_child)
return inner_min(self)
def rank(self, key):
"""
获得给定键的排名
:param key:
:return:
"""
def inner_rank(node, _key):
if node is None:
return
if _key > node.key:
return inner_rank(node.r_child, _key)
elif _key < node.key:
return 1 + node.l_child.size() + inner_rank(node.l_child, _key)
else:
if node.l_child is None:
return 0
else:
return node.l_child.size()
return inner_rank(self.root, key)
def delete(self, key):
"""
删除指定 key 的键
:param key:
:return:
"""
def delete_min_node(node):
if node.l_child is None:
return node.r_child
node.l_child = delete_min_node(node.l_child)
return node
def inner_delete(node, _key):
if node is None:
return
if _key > node.key:
node.r_child = inner_delete(node.r_child, _key)
elif _key < node.key:
node.l_child = inner_delete(node.l_child, _key)
else:
if node.r_child is None:
return node.l_child
elif node.l_child is None:
return node.r_child
temp = copy.copy(node)
node = min(temp.right)
node.r_child = delete_min_node(temp.r_child)
node.l_child = temp.l_chlid
return node
return delete_min_node(self)
def find_keys(self, low, high):
"""
查找范围内所有的数
:param low:
:param high:
:return:
"""
BST_list = []
def inner_find_keys(node, _low, _high):
if node is None:
return
if _low < node.key:
inner_find_keys(node.l_child, _low, _high)
if _low <= node.key <= _high:
BST_list.append(node)
if _high > node.key:
inner_find_keys(node.r_child, _low, _high)
inner_find_keys(self, low, high)
return BST_list
if __name__ == '__main__':
root = BST(50, "2")
root.put(3, "5")
root.put(5, "5")
root.put(80, "5")
root.put(60, "5")
root.print_tree()
print(root.get(60))
print(root.select(2))
print(root.rank(5))
root.delete(5)
print(root.min())
root.print_tree()
for node in root.find_keys(50, 100):
print(node)