散列表不等概率平均查找长度
时间: 2023-12-21 11:30:03 浏览: 38
散列表不等概率平均查找长度是指在散列表中查找某个元素时,需要进行的平均比较次数。在散列表中,不同的元素可能会被映射到同一个散列表位置,这种情况被称为冲突。解决冲突的方法有很多种,其中一种是开放地址法。在开放地址法中,如果某个散列表位置已经被占用,就会按照某种规则去寻找下一个空闲位置,直到找到为止。这个过程被称为探测。
散列表不等概率平均查找长度的计算方法如下:
1. 假设散列表中有n个元素,m个散列表位置。
2. 对于每个元素,假设它被查找的概率为pi。
3. 对于每个元素,假设它在散列表中的探测长度为ci。
4. 则散列表不等概率平均查找长度为:ASL = Σ(pi * ci),i从1到n。
下面是一个使用线性探测法解决冲突的散列表的例子,其中包含了计算不等概率平均查找长度的代码:
```python
class HashTable:
def __init__(self, size):
self.size = size
self.keys = [None] * self.size
self.values = [None] * self.size
def put(self, key, value):
hash_value = self.hash_function(key)
if self.keys[hash_value] is None:
self.keys[hash_value] = key
self.values[hash_value] = value
elif self.keys[hash_value] == key:
self.values[hash_value] = value
else:
next_slot = self.rehash(hash_value)
while self.keys[next_slot] is not None and self.keys[next_slot] != key:
next_slot = self.rehash(next_slot)
if self.keys[next_slot] is None:
self.keys[next_slot] = key
self.values[next_slot] = value
else:
self.values[next_slot] = value
def get(self, key):
start_slot = self.hash_function(key)
if self.keys[start_slot] == key:
return self.values[start_slot]
else:
next_slot = self.rehash(start_slot)
while self.keys[next_slot] != key and next_slot != start_slot:
next_slot = self.rehash(next_slot)
if self.keys[next_slot] == key:
return self.values[next_slot]
else:
return None
def hash_function(self, key):
return key % self.size
def rehash(self, old_hash):
return (old_hash + 1) % self.size
def average_search_length(self, probabilities):
asl = 0
for i in range(len(self.keys)):
if self.keys[i] is not None:
asl += probabilities[self.keys[i]] * self.search_length(self.keys[i])
return asl
def search_length(self, key):
start_slot = self.hash_function(key)
position = start_slot
length = 1
while self.keys[position] != key:
position = self.rehash(position)
length += 1
return length
# 示例代码
table = HashTable(11)
table.put(54, "cat")
table.put(26, "dog")
table.put(93, "lion")
table.put(17, "tiger")
table.put(77, "bird")
table.put(31, "cow")
table.put(44, "goat")
table.put(55, "pig")
table.put(20, "chicken")
probabilities = {54: 0.1, 26: 0.05, 93: 0.05, 17: 0.2, 77: 0.1, 31: 0.1, 44: 0.1, 55: 0.1, 20: 0.1}
asl = table.average_search_length(probabilities)
print("散列表不等概率平均查找长度为:", asl)
```