xirongxudlut 2020-04-19
class Array(object): def __init__(self, size=32, init=None): self._size = size self._items = [init] * self._size def __getitem__(self, index): return self._items[index] def __setitem__(self, index, value): self._items[index] = value def __len__(self): return self._size def clear(self, value=None): for i in range(len(self._items)): self._items[i] = value def __iter__(self): for item in self._items: yield item class Slot(object): """定义一个 hash 表 数组的槽 注意,一个槽有三种状态,看你能否想明白 1.从未使用 HashMap.UNUSED。此槽没有被使用和冲突过,查找时只要找到 UNUSED 就不用再继续探查了 2.使用过但是 remove 了,此时是 HashMap.EMPTY,该探查点后边的元素扔可能是有key 3.槽正在使用 Slot 节点 """ def __init__(self, key, value): self.key, self.value = key, value class HashTable(object): # 表示从未被使用过 UNUSED = None # 使用过,但是被删除了 EMPTY = Slot(None, None) def __init__(self): self._table = Array(8, init=HashTable.UNUSED) self.length = 0 # 负载因子 @property def _load_factor(self): return self.length/float(len(self._table)) def __len__(self): return self.length # 哈希函数 用内置的哈希哈数进行哈希一下,然后对数组长度取模 def _hash(self, key): return abs(hash(key)) % len(self._table) def _find_key(self, key): # 得到第一个值的位置 index = self._hash(key) _len = len(self._table) # 当这个槽不是未使用过的,才接着往下找;如果是未使用过的,这个key肯定不存在 while self._table[index] is not HashTable.UNUSED: # 槽使用过,但是被删除了 if self._table[index] is HashTable.EMPTY: # cpython解决哈希冲突的一种方式 index = (index*5 + 1) % _len continue elif self._table[index] == key: return index else: index = (index * 5 + 1) % _len return None # 检测槽是否能被插入 def _slot_can_insert(self, index): return (self._table[index] is HashTable.EMPTY or self._table[index] is HashTable.UNUSED) # 找到能被插入的槽的index def _find_slot_insert(self, key): # 得到第一个值的位置 index = self._hash(key) _len = len(self._table) while not self._slot_can_insert(index): index = (index * 5 + 1) % _len return index # in 操作符 def __contains__(self, key): index = self._find_key(key) return index is not None def add(self, key, value): if key in self: index = self._find_key(key) # 更新值 self._table[index].value = value return False else: index = self._find_slot_insert(key) self._table[index] = Slot(key, value) self.length += 1 if self._load_factor > 0.8: return self._rehash() return True def _rehash(self): oldtable = self._table newsize = len(self._table) * 2 # 新的table self._table = Array(newsize, HashTable.UNUSED) self.length = 0 for slot in oldtable: if slot is not HashTable.UNUSED and slot is not HashTable.EMPTY: index = self._find_slot_insert(slot.key) self._table[index] = slot self.length += 1 def get(self, key, default=None): index = self._find_key(key) if index is None: return default else: return self._table[index].value def remove(self, key): index = self._find_key(key) if index is None: raise KeyError value = self._table[index].value self.length -= 1 # 把槽设置为空槽 self._table[index] = HashTable.EMPTY return value def __iter__(self): for slot in self._table: if slot not in (HashTable.UNUSED, HashTable.EMPTY): yield slot.value class SetADT(HashTable): def add(self, key): return super(SetADT, self).add(key, True) def __and__(self, other_set): # 求交集 new_set = SetADT() for element_a in self: if element_a in other_set: new_set.add(element_a) return new_set def __sub__(self, other_set): # 求差集 new_set = SetADT() for element_a in self: if element_a not in other_set: new_set.add(element_a) return new_set def __or__(self, other_set): # 求交集 new_set = SetADT() for element_a in self: new_set.add(element_a) for element_b in other_set: new_set.add(element_b) return new_set
theta = np.zeros #theta = array,构造全为零的行向量。grad[0,j] = np.sum/len #∑term / m. return value > threshol