This commit is contained in:
robin 2019-01-11 16:58:58 +08:00
commit aee7f91373
34 changed files with 1592 additions and 168 deletions

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@ -79,6 +79,8 @@ void test_checkCircle() {
SinglyLinkedNode* node = malloc(sizeof(SinglyLinkedNode));
node->data = i;
current->next = node;
//reset current node
current = node;
}
current->next = h;

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@ -1,133 +1,70 @@
from typing import Optional
#
# 1) Insertion, deletion and random access of array
# 2) Assumes int for element type
#
# Author: Wenru
#
class MyArray:
"""A simple wrapper around List.
You cannot have -1 in the array.
"""
def __init__(self, capacity: int):
self._data = []
self._count = 0
self._capacity = capacity
def __getitem__(self, position: int) -> int:
"""Support for subscript.
Perhaps better than the find() method below.
"""
def __getitem__(self, position: int) -> object:
return self._data[position]
def find(self, index: int) -> Optional[int]:
def __setitem__(self, index: int, value: object):
self._data[index] = value
if index >= self._count or index <= -self._count:
def __len__(self) -> int:
return len(self._data)
def __iter__(self):
for item in self._data:
yield item
def find(self, index: int) -> object:
try:
return self._data[index]
except IndexError:
return None
return self._data[index]
def delete(self, index: int) -> bool:
if index >= self._count or index <= -self._count:
try:
self._data.pop(index)
return True
except IndexError:
return False
self._data[index:-1] = self._data[index + 1:]
self._count -= 1
# 真正将数据删除并覆盖原来的数据 ,这个需要增加
self._data = self._data[0:self._count]
print('delete function', self._data)
return True
def insert(self, index: int, value: int) -> bool:
# if index >= self._count or index <= -self._count: return False
if self._capacity == self._count:
if len(self) >= self._capacity:
return False
# 如果还有空间,那么插入位置大于当前的元素个数,可以插入最后的位置
if index >= self._count:
self._data.append(value)
# 同上如果位置小于0 可以插入第0个位置.
if index < 0:
print(index)
self._data.insert(0, value)
self._count += 1
return True
def insert_v2(self, index: int, value: int) -> bool:
"""
支持任意位置插入
:param index:
:param value:
:return:
"""
# 数组空间已满
if self._capacity == self._count:
return False
# 插入位置大于当前的元素个数,可以插入最后的位置
if index >= self._count:
self._data.append(value)
elif index < 0:
# 位置小于 0 可以插入第 个位置
self._data.insert(0, value)
else:
# 挪动 index 至 _count 位到 index+1 至 _count+1 位
# 插入第 index
self._data[index+1:self._count+1] = self._data[index:self._count]
self._data[index] = value
self._count += 1
return True
def insert_to_tail(self, value: int) -> bool:
if self._count == self._capacity:
return False
if self._count == len(self._data):
self._data.append(value)
else:
self._data[self._count] = value
self._count += 1
return True
def __repr__(self) -> str:
return " ".join(str(num) for num in self._data[:self._count])
return self._data.insert(index, value)
def print_all(self):
for num in self._data[:self._count]:
print(f"{num}", end=" ")
print("\n", flush=True)
for item in self:
print(item)
def test_myarray():
array_a = MyArray(6)
for num in range(6):
array_a.insert_to_tail(num)
assert array_a.find(0) == 0
assert array_a[0] == 0
array_a.delete(0)
assert array_a[0] == 1
array = MyArray(5)
array.insert(0, 3)
array.insert(0, 4)
array.insert(1, 5)
array.insert(3, 9)
array.insert(3, 10)
assert array.insert(0, 100) is False
assert len(array) == 5
assert array.find(1) == 5
assert array.delete(4) is True
array.print_all()
if __name__ == "__main__":
a = MyArray(6)
for i in range(6):
a.insert_to_tail(i)
a.delete(2)
print(a)
a.insert_to_tail(7)
print(a)
print('origin', a)
a.delete(4)
print('delete ', a)
a.insert(100, 10000)
print(a)
test_myarray()

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@ -23,7 +23,7 @@ def counting_sort(a: List[int]):
a_sorted[index] = num
counts[num] -= 1
a = a_sorted
a[:] = a_sorted
if __name__ == "__main__":

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@ -0,0 +1,51 @@
#!/usr/bin/python
# -*- coding: UTF-8 -*-
inversion_num = 0
def merge_sort_counting(nums, start, end):
if start >= end:
return
mid = (start + end)//2
merge_sort_counting(nums, start, mid)
merge_sort_counting(nums, mid+1, end)
merge(nums, start, mid, end)
def merge(nums, start, mid, end):
global inversion_num
i = start
j = mid+1
tmp = []
while i <= mid and j <= end:
if nums[i] <= nums[j]:
inversion_num += j - mid - 1
tmp.append(nums[i])
i += 1
else:
tmp.append(nums[j])
j += 1
while i <= mid:
# 这时nums[i]的逆序数是整个nums[mid+1: end+1]的长度
inversion_num += end - mid
tmp.append(nums[i])
i += 1
while j <= end:
tmp.append(nums[j])
j += 1
nums[start: end+1] = tmp
if __name__ == '__main__':
print('--- count inversion number using merge sort ---')
# nums = [5, 0, 4, 2, 3, 1, 6, 8, 7]
nums = [5, 0, 4, 2, 3, 1, 3, 3, 3, 6, 8, 7]
print('nums : {}'.format(nums))
merge_sort_counting(nums, 0, len(nums)-1)
print('sorted: {}'.format(nums))
print('inversion number: {}'.format(inversion_num))

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@ -0,0 +1,59 @@
#!/usr/bin/python
# -*- coding: UTF-8 -*-
from typing import List
# 背包选取的物品列表
picks = []
picks_with_max_value = []
def bag(capacity: int, cur_weight: int, items_info: List, pick_idx: int):
"""
回溯法解01背包穷举
:param capacity: 背包容量
:param cur_weight: 背包当前重量
:param items_info: 物品的重量和价值信息
:param pick_idx: 当前物品的索引
:return:
"""
# 考察完所有物品,或者在中途已经装满
if pick_idx >= len(items_info) or cur_weight == capacity:
global picks_with_max_value
if get_value(items_info, picks) > \
get_value(items_info, picks_with_max_value):
picks_with_max_value = picks.copy()
else:
item_weight = items_info[pick_idx][0]
if cur_weight + item_weight <= capacity: # 选
picks[pick_idx] = 1
bag(capacity, cur_weight + item_weight, items_info, pick_idx + 1)
picks[pick_idx] = 0 # 不选
bag(capacity, cur_weight, items_info, pick_idx + 1)
def get_value(items_info: List, pick_items: List):
values = [_[1] for _ in items_info]
return sum([a*b for a, b in zip(values, pick_items)])
if __name__ == '__main__':
# [(weight, value), ...]
items_info = [(3, 5), (2, 2), (1, 4), (1, 2), (4, 10)]
capacity = 8
print('--- items info ---')
print(items_info)
print('\n--- capacity ---')
print(capacity)
picks = [0] * len(items_info)
bag(capacity, 0, items_info, 0)
print('\n--- picks ---')
print(picks_with_max_value)
print('\n--- value ---')
print(get_value(items_info, picks_with_max_value))

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@ -0,0 +1,57 @@
#!/usr/bin/python
# -*- coding: UTF-8 -*-
# 棋盘尺寸
BOARD_SIZE = 8
solution_count = 0
queen_list = [0] * BOARD_SIZE
def eight_queens(cur_column: int):
"""
输出所有符合要求的八皇后序列
用一个长度为8的数组代表棋盘的列数组的数字则为当前列上皇后所在的行数
:return:
"""
if cur_column >= BOARD_SIZE:
global solution_count
solution_count += 1
# 解
print(queen_list)
else:
for i in range(BOARD_SIZE):
if is_valid_pos(cur_column, i):
queen_list[cur_column] = i
eight_queens(cur_column + 1)
def is_valid_pos(cur_column: int, pos: int) -> bool:
"""
因为采取的是每列放置1个皇后的做法
所以检查的时候不必检查列的合法性只需要检查行和对角
1. 检查数组在下标为cur_column之前的元素是否已存在pos
2. 对角检查数组在下标为cur_column之前的元素其行的间距pos - QUEEN_LIST[i]
和列的间距cur_column - i是否一致
:param cur_column:
:param pos:
:return:
"""
i = 0
while i < cur_column:
# 同行
if queen_list[i] == pos:
return False
# 对角线
if cur_column - i == abs(pos - queen_list[i]):
return False
i += 1
return True
if __name__ == '__main__':
print('--- eight queens sequence ---')
eight_queens(0)
print('\n--- solution count ---')
print(solution_count)

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@ -0,0 +1,42 @@
#!/usr/bin/python
# -*- coding: UTF-8 -*-
from typing import List
permutations_list = [] # 全局变量,用于记录每个输出
def permutations(nums: List, n: int, pick_count: int):
"""
从nums选取n个数的全排列
回溯法用一个栈记录当前路径信息
当满足n==0说明栈中的数已足够输出并终止遍历
:param nums:
:param n:
:param pick_count:
:return:
"""
if n == 0:
print(permutations_list)
else:
for i in range(len(nums) - pick_count):
permutations_list[pick_count] = nums[i]
nums[i], nums[len(nums) - pick_count - 1] = nums[len(nums) - pick_count - 1], nums[i]
permutations(nums, n-1, pick_count+1)
nums[i], nums[len(nums) - pick_count - 1] = nums[len(nums) - pick_count - 1], nums[i]
if __name__ == '__main__':
nums = [1, 2, 3, 4]
n = 3
print('--- list ---')
print(nums)
print('\n--- pick num ---')
print(n)
print('\n--- permutation list ---')
permutations_list = [0] * n
permutations(nums, n, 0)

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@ -0,0 +1,35 @@
#!/usr/bin/python
# -*- coding: UTF-8 -*-
is_match = False
def rmatch(r_idx: int, m_idx: int, regex: str, main: str):
global is_match
if is_match:
return
if r_idx >= len(regex): # 正则串全部匹配好了
is_match = True
return
if m_idx >= len(main) and r_idx < len(regex): # 正则串没匹配完,但是主串已经没得匹配了
is_match = False
return
if regex[r_idx] == '*': # * 匹配1个或多个任意字符递归搜索每一种情况
for i in range(m_idx, len(main)):
rmatch(r_idx+1, i+1, regex, main)
elif regex[r_idx] == '?': # ? 匹配0个或1个任意字符两种情况
rmatch(r_idx+1, m_idx+1, regex, main)
rmatch(r_idx+1, m_idx, regex, main)
else: # 非特殊字符需要精确匹配
if regex[r_idx] == main[m_idx]:
rmatch(r_idx+1, m_idx+1, regex, main)
if __name__ == '__main__':
regex = 'ab*eee?d'
main = 'abcdsadfkjlekjoiwjiojieeecd'
rmatch(0, 0, regex, main)
print(is_match)

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@ -0,0 +1,25 @@
"""
Author: Wenru Dong
"""
from typing import List
def eight_queens() -> None:
solutions = []
def backtracking(queens_at_column: List[int], index_sums: List[int], index_diffs: List[int]) -> None:
row = len(queens_at_column)
if row == 8:
solutions.append(queens_at_column)
return
for col in range(8):
if col in queens_at_column or row + col in index_sums or row - col in index_diffs: continue
backtracking(queens_at_column + [col], index_sums + [row + col], index_diffs + [row - col])
backtracking([], [], [])
print(*(" " + " ".join("*" * i + "Q" + "*" * (8 - i - 1) + "\n" for i in solution) for solution in solutions), sep="\n")
if __name__ == "__main__":
eight_queens()

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@ -0,0 +1,66 @@
#!/usr/bin/python
# -*- coding: UTF-8 -*-
from typing import List, Tuple
def bag(items_info: List[int], capacity: int) -> int:
"""
固定容量的背包计算能装进背包的物品组合的最大重量
:param items_info: 每个物品的重量
:param capacity: 背包容量
:return: 最大装载重量
"""
n = len(items_info)
memo = [[-1]*(capacity+1) for i in range(n)]
memo[0][0] = 1
if items_info[0] <= capacity:
memo[0][items_info[0]] = 1
for i in range(1, n):
for cur_weight in range(capacity+1):
if memo[i-1][cur_weight] != -1:
memo[i][cur_weight] = memo[i-1][cur_weight] # 不选
if cur_weight + items_info[i] <= capacity: # 选
memo[i][cur_weight + items_info[i]] = 1
for w in range(capacity, -1, -1):
if memo[-1][w] != -1:
return w
def bag_with_max_value(items_info: List[Tuple[int, int]], capacity: int) -> int:
"""
固定容量的背包计算能装进背包的物品组合的最大价值
:param items_info: 物品的重量和价值
:param capacity: 背包容量
:return: 最大装载价值
"""
n = len(items_info)
memo = [[-1]*(capacity+1) for i in range(n)]
memo[0][0] = 0
if items_info[0][0] <= capacity:
memo[0][items_info[0][0]] = items_info[0][1]
for i in range(1, n):
for cur_weight in range(capacity+1):
if memo[i-1][cur_weight] != -1:
memo[i][cur_weight] = memo[i-1][cur_weight]
if cur_weight + items_info[i][0] <= capacity:
memo[i][cur_weight + items_info[i][0]] = max(memo[i][cur_weight + items_info[i][0]],
memo[i-1][cur_weight] + items_info[i][1])
return max(memo[-1])
if __name__ == '__main__':
# [weight, ...]
items_info = [2, 2, 4, 6, 3]
capacity = 9
print(bag(items_info, capacity))
# [(weight, value), ...]
items_info = [(3, 5), (2, 2), (1, 4), (1, 2), (4, 10)]
capacity = 8
print(bag_with_max_value(items_info, capacity))

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@ -0,0 +1,30 @@
"""
Author: Wenru Dong
"""
from typing import List
def knapsack01(weights: List[int], values: List[int], capacity: int) -> int:
# Denote the state as (i, c), where i is the stage number,
# and c is the capacity available. Denote f(i, c) to be the
# maximum value when the capacity available is c, and Item 0
# to Item i-1 are to be packed.
# The goal is to find f(n-1, W), where W is the total capacity.
# Then the DP functional equation is:
# f(i, c) = max(xᵢvᵢ + f(i-1, c-xᵢwᵢ)), xᵢ ∈ D, i ≥ 0,
# f(-1, c) = 0, 0 ≤ c ≤ W,
# where
# / {0}, if wᵢ > c
# D = D(i, c) =
# \ {0, 1}, if wᵢ ≤ c
prev = [0] * (capacity + 1)
for w, v in zip(weights, values):
prev = [c >= w and max(prev[c], prev[c-w] + v) for c in range(capacity + 1)]
return prev[-1]
if __name__ == "__main__":
# To find the maximum weight that can be packed,
# set values equal to the weights
print(knapsack01([2, 2, 4, 6, 3], [2, 2, 4, 6, 3], 9))

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@ -0,0 +1,64 @@
#!/usr/bin/python
# -*- coding: UTF-8 -*-
from typing import List
Layer_nums = List[int]
def yh_triangle(nums: List[Layer_nums]) -> int:
"""
从根节点开始向下走过程中经过的节点只需存储经过它时最小的路径和
:param nums:
:return:
"""
assert len(nums) > 0
n = len(nums) # 层数
memo = [[0]*n for i in range(n)]
memo[0][0] = nums[0][0]
for i in range(1, n):
for j in range(i+1):
# 每一层首尾两个数字,只有一条路径可以到达
if j == 0:
memo[i][j] = memo[i-1][j] + nums[i][j]
elif j == i:
memo[i][j] = memo[i-1][j-1] + nums[i][j]
else:
memo[i][j] = min(memo[i-1][j-1] + nums[i][j], memo[i-1][j] + nums[i][j])
return min(memo[n-1])
def yh_triangle_space_optimization(nums: List[Layer_nums]) -> int:
assert len(nums) > 0
n = len(nums)
memo = [0] * n
memo[0] = nums[0][0]
for i in range(1, n):
for j in range(i, -1, -1):
if j == i:
memo[j] = memo[j-1] + nums[i][j]
elif j == 0:
memo[j] = memo[j] + nums[i][j]
else:
memo[j] = min(memo[j-1] + nums[i][j], memo[j] + nums[i][j])
return min(memo)
def yh_triangle_bottom_up(nums: List[Layer_nums]) -> int:
assert len(nums) > 0
n = len(nums)
memo = nums[-1].copy()
for i in range(n-1, 0, -1):
for j in range(i):
memo[j] = min(memo[j] + nums[i-1][j], memo[j+1] + nums[i-1][j])
return memo[0]
if __name__ == '__main__':
nums = [[3], [2, 6], [5, 4, 2], [6, 0, 3, 2]]
print(yh_triangle(nums))
print(yh_triangle_space_optimization(nums))
print(yh_triangle_bottom_up(nums))

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@ -0,0 +1,45 @@
#!/usr/bin/python
# -*- coding: UTF-8 -*-
from typing import List
def coins_dp(values: List[int], target: int) -> int:
# memo[i]表示target为i的时候所需的最少硬币数
memo = [0] * (target+1)
# 0元的时候为0个
memo[0] = 0
for i in range(1, target+1):
min_num = 999999
# 对于values中的所有n
# memo[i]为 min(memo[i-n1], memo[i-n2], ...) + 1
for n in values:
if i >= n:
min_num = min(min_num, 1 + memo[i-n])
else: # values中的数值要从小到大排序
break
memo[i] = min_num
# print(memo)
return memo[-1]
min_num = 999999
def coins_backtracking(values: List[int], target: int, cur_value: int, coins_count: int):
if cur_value == target:
global min_num
min_num = min(coins_count, min_num)
else:
for n in values:
if cur_value + n <= target:
coins_backtracking(values, target, cur_value+n, coins_count+1)
if __name__ == '__main__':
values = [1, 3, 5]
target = 23
print(coins_dp(values, target))
coins_backtracking(values, target, 0, 0)
print(min_num)

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@ -0,0 +1,39 @@
"""
Author: Wenru Dong
"""
from typing import List
from itertools import accumulate
def min_dist(weights: List[List[int]]) -> int:
"""Find the minimum weight path from the weights matrix."""
m, n = len(weights), len(weights[0])
table = [[0] * n for _ in range(m)]
# table[i][j] is the minimum distance (weight) when
# there are i vertical moves and j horizontal moves
# left.
table[0] = list(accumulate(reversed(weights[-1])))
for i, v in enumerate(accumulate(row[-1] for row in reversed(weights))):
table[i][0] = v
for i in range(1, m):
for j in range(1, n):
table[i][j] = weights[~i][~j] + min(table[i - 1][j], table[i][j - 1])
return table[-1][-1]
def min_dist_recur(weights: List[List[int]]) -> int:
m, n = len(weights), len(weights[0])
table = [[0] * n for _ in range(m)]
def min_dist_to(i: int, j: int) -> int:
if i == j == 0: return weights[0][0]
if table[i][j]: return table[i][j]
min_left = float("inf") if j - 1 < 0 else min_dist_to(i, j - 1)
min_up = float("inf") if i - 1 < 0 else min_dist_to(i - 1, j)
return weights[i][j] + min(min_left, min_up)
return min_dist_to(m - 1, n - 1)
if __name__ == "__main__":
weights = [[1, 3, 5, 9], [2, 1, 3, 4], [5, 2, 6, 7], [6, 8, 4, 3]]
print(min_dist(weights))
print(min_dist_recur(weights))

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@ -0,0 +1,58 @@
#!/usr/bin/python
# -*- coding: UTF-8 -*-
from typing import List
def longest_increasing_subsequence(nums: List[int]) -> int:
"""
最长子上升序列的一种DP解法从回溯解法转化思路类似于有限物品的背包问题
每一次决策都算出当前可能的lis的长度重复子问题合并合并策略是lis的末尾元素最小
时间复杂度O(n^2)
空间复杂度O(n^2)可优化至O(n)
没leetcode上的参考答案高效提供另一种思路作为参考
https://leetcode.com/problems/longest-increasing-subsequence/solution/
:param nums:
:return:
"""
if not nums:
return 0
n = len(nums)
# memo[i][j] 表示第i次决策长度为j的lis的 最小的 末尾元素数值
# 每次决策都根据上次决策的所有可能转化空间上可以类似背包优化为O(n)
memo = [[-1] * (n+1) for _ in range(n)]
# 第一列全赋值为0表示每次决策都不选任何数
for i in range(n):
memo[i][0] = 0
# 第一次决策选数组中的第一个数
memo[0][1] = nums[0]
for i in range(1, n):
for j in range(1, n+1):
# case 1: 长度为j的lis在上次决策后存在nums[i]比长度为j-1的lis末尾元素大
if memo[i-1][j] != -1 and nums[i] > memo[i-1][j-1]:
memo[i][j] = min(nums[i], memo[i-1][j])
# case 2: 长度为j的lis在上次决策后存在nums[i]比长度为j-1的lis末尾元素小/等
if memo[i-1][j] != -1 and nums[i] <= memo[i-1][j-1]:
memo[i][j] = memo[i-1][j]
if memo[i-1][j] == -1:
# case 3: 长度为j的lis不存在nums[i]比长度为j-1的lis末尾元素大
if nums[i] > memo[i-1][j-1]:
memo[i][j] = nums[i]
# case 4: 长度为j的lis不存在nums[i]比长度为j-1的lis末尾元素小/等
break
for i in range(n, -1, -1):
if memo[-1][i] != -1:
return i
if __name__ == '__main__':
# 要求输入的都是大于0的正整数(可优化至支持任意整数)
nums = [2, 9, 3, 6, 5, 1, 7]
print(longest_increasing_subsequence(nums))

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@ -0,0 +1,31 @@
"""
Author: Wenru Dong
"""
def levenshtein_dp(s: str, t: str) -> int:
m, n = len(s), len(t)
table = [[0] * (n + 1) for _ in range(m + 1)]
table[0] = [j for j in range(m + 1)]
for i in range(m + 1):
table[i][0] = i
for i in range(1, m + 1):
for j in range(1, n + 1):
table[i][j] = min(1 + table[i - 1][j], 1 + table[i][j - 1], int(s[i - 1] != t[j - 1]) + table[i - 1][j - 1])
return table[-1][-1]
def common_substring_dp(s: str, t: str) -> int:
m, n = len(s), len(t)
table = [[0] * (n + 1) for _ in range(m + 1)]
for i in range(1, m + 1):
for j in range(1, n + 1):
table[i][j] = max(table[i - 1][j], table[i][j - 1], int(s[i - 1] == t[j - 1]) + table[i - 1][j - 1])
return table[-1][-1]
if __name__ == "__main__":
s = "mitcmu"
t = "mtacnu"
print(levenshtein_dp(s, t))
print(common_substring_dp(s, t))

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@ -0,0 +1,63 @@
"""
Author: Wenru Dong
"""
from collections import deque
from itertools import filterfalse
class Graph:
def __init__(self, num_vertices: int):
self._num_vertices = num_vertices
self._adjacency = [[] for _ in range(num_vertices)]
def add_edge(self, s: int, t: int) -> None:
self._adjacency[s].append(t)
def tsort_by_kahn(self) -> None:
in_degree = [0] * self._num_vertices
for v in range(self._num_vertices):
if len(self._adjacency[v]):
for neighbour in self._adjacency[v]:
in_degree[neighbour] += 1
q = deque(filterfalse(lambda x: in_degree[x], range(self._num_vertices)))
while q:
v = q.popleft()
print(f"{v} -> ", end="")
for neighbour in self._adjacency[v]:
in_degree[neighbour] -= 1
if not in_degree[neighbour]:
q.append(neighbour)
print("\b\b\b ")
def tsort_by_dfs(self) -> None:
inverse_adjacency = [[] for _ in range(self._num_vertices)]
for v in range(self._num_vertices):
if len(self._adjacency[v]):
for neighbour in self._adjacency[v]:
inverse_adjacency[neighbour].append(v)
visited = [False] * self._num_vertices
def dfs(vertex: int) -> None:
if len(inverse_adjacency[vertex]):
for v in inverse_adjacency[vertex]:
if not visited[v]:
visited[v] = True
dfs(v)
print(f"{vertex} -> ", end="")
for v in range(self._num_vertices):
if not visited[v]:
visited[v] = True
dfs(v)
print("\b\b\b ")
if __name__ == "__main__":
dag = Graph(4)
dag.add_edge(1, 0)
dag.add_edge(2, 1)
dag.add_edge(1, 3)
dag.tsort_by_kahn()
dag.tsort_by_dfs()

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@ -0,0 +1,64 @@
"""
Dijkstra algorithm
Author: Wenru Dong
"""
from dataclasses import dataclass
from queue import PriorityQueue
@dataclass
class Edge:
start_id: int
end_id: int
weight: int
@dataclass(order=True)
class Vertex:
distance_to_start = float("inf")
vertex_id: int
class Graph:
def __init__(self, num_vertices: int):
self._num_vertices = num_vertices
self._adjacency = [[] for _ in range(num_vertices)]
def add_edge(self, from_vertex: int, to_vertex: int, weight: int) -> None:
self._adjacency[from_vertex].append(Edge(from_vertex, to_vertex, weight))
def dijkstra(self, from_vertex: int, to_vertex: int) -> None:
vertices = [Vertex(i) for i in range(self._num_vertices)]
vertices[from_vertex].distance_to_start = 0
visited = [False] * self._num_vertices
predecessor = [-1] * self._num_vertices
q = PriorityQueue()
q.put(vertices[from_vertex])
visited[from_vertex] = True
while not q.empty():
min_vertex = q.get()
if min_vertex.vertex_id == to_vertex:
break
for edge in self._adjacency[min_vertex.vertex_id]:
next_vertex = vertices[edge.end_id]
if min_vertex.distance_to_start + edge.weight < next_vertex.distance_to_start:
next_vertex.distance_to_start = min_vertex.distance_to_start + edge.weight
predecessor[next_vertex.vertex_id] = min_vertex.vertex_id
if not visited[next_vertex.vertex_id]:
q.put(next_vertex)
visited[next_vertex.vertex_id] = True
path = lambda x: path(predecessor[x]) + [str(x)] if from_vertex != x else [str(from_vertex)]
print("->".join(path(to_vertex)))
if __name__ == "__main__":
graph = Graph(6)
graph.add_edge(0, 1, 10)
graph.add_edge(0, 4, 15)
graph.add_edge(1, 2, 15)
graph.add_edge(1, 3, 2)
graph.add_edge(2, 5, 5)
graph.add_edge(3, 2, 1)
graph.add_edge(3, 5, 12)
graph.add_edge(4, 5, 10)
graph.dijkstra(0, 5)

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@ -8,63 +8,63 @@ import scala.util.control.Breaks.{break, breakable}
* Author: yangchuz
*/
object Sorts {
def main(args: Array[String]): Unit ={
// println(bubbleSort(Array(0, 6, 2, 3, 8, 5, 6, 7), 8).mkString(", "))
// println(insertSort(Array(0, 6, 2, 3, 8, 5, 6, 7), 8).mkString(", "))
println(selectionSort(Array(0, 6, 2, 3, 8, 5, 6, 7), 8).mkString(", "))
}
def bubbleSort(arr: Array[Int], n:Int): Array[Int] = {
val n = arr.length
def bubbleSort(items: Array[Int]): Array[Int] = {
val length = items.length
breakable {
for(i <- (n-1) to (1, -1)){
var flag = false
for(j <- 0 until i){
if(arr(j) > arr(j+1)){
val tmp = arr(j)
arr(j) = arr(j+1)
arr(j+1) = tmp
flag = true
for (i <- Range(0, length)) {
var exit = true
for (j <- Range(0, length - i - 1)) {
if (items(j + 1) < items(j)) {
val temp = items(j + 1)
items(j + 1) = items(j)
items(j) = temp
exit = false
}
}
if(!flag){
if (exit) {
break
}
}
}
arr
items
}
def insertSort(arr: Array[Int], n:Int): Array[Int] = {
for(i <- 1 until n){
val tmp = arr(i)
breakable{
for(j <- (i-1) to (0, -1)){
if(tmp < arr(j)){
arr(j+1) = arr(j)
}else{
arr(j+1) = tmp
def insertSort(items: Array[Int]): Array[Int] = {
val length = items.length
for (i <- Range(1, length)) {
val value = items(i)
var j = i - 1
breakable {
while (j >= 0) {
if (items(j) > value) {
items(j + 1) = items(j)
} else {
break
}
j -= 1
}
}
items(j + 1) = value
}
arr
items
}
def selectionSort(arr: Array[Int], n:Int): Array[Int] = {
for(i <- 0 until n){
var min = i
for(j <- (i + 1) until n){
if(arr(j) < arr(min)){
min = j
def selectionSort(items: Array[Int]): Array[Int] = {
val length = items.length
for (i <- Range(0, length)) {
var minIndex = i
for (j <- Range(i + 1, length)) {
if (items(j) < items(minIndex)) {
minIndex = j
}
}
val tmp = arr(i)
arr(i) = arr(min)
arr(min) = tmp
//put the min value to the front
val temp = items(i)
items(i) = items(minIndex)
items(minIndex) = temp
}
arr
items
}
}

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@ -0,0 +1,60 @@
package ch12_sorts
object MergeSort {
def mergeSort(items: Array[Int]): Array[Int] = {
_mergeSort(items, 0, items.length - 1)
items
}
private[this] def _mergeSort(items: Array[Int], p: Int, r: Int): Unit = {
if (p >= r) {
return
}
val q = p + (r - p) / 2
_mergeSort(items, p, q)
_mergeSort(items, q + 1, r)
_merge(items, p, q, r)
}
private[this] def _merge(items: Array[Int], p: Int, q: Int, r: Int): Unit = {
//start of first half
var i = p
//start of second half
var j = q + 1
var k = 0
//temp array to hold the data
val tempArray = new Array[Int](r - p + 1)
while (i <= q && j <= r) {
if (items(i) <= items(j)) {
tempArray(k) = items(i)
i += 1
} else {
tempArray(k) = items(j)
j += 1
}
k += 1
}
var start = i
var end = q
if (j <= r) {
start = j
end = r
}
for (n <- start to end) {
tempArray(k) = items(n)
k += 1
}
//copy tempArray back to items
for (n <- 0 to r - p) {
items(p + n) = tempArray(n)
}
}
}

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@ -0,0 +1,54 @@
package ch12_sorts
object QuickSort {
//find the K th smallest element int the array
def findKthElement(items: Array[Int], k: Int): Int = {
_findKthElement(items, k, 0, items.length - 1)
}
private[this] def _findKthElement(items: Array[Int], k: Int, p: Int, r: Int): Int = {
val q = _partition(items, p, r)
if (k == q + 1) {
items(q)
} else if (k < q + 1) {
_findKthElement(items, k, p, q - 1)
} else {
_findKthElement(items, k, q + 1, r)
}
}
def quickSort(items: Array[Int]): Array[Int] = {
_quickSort(items, 0, items.length - 1)
items
}
private[this] def _quickSort(items: Array[Int], p: Int, r: Int): Unit = {
if (p >= r) {
return
}
val q = _partition(items, p, r)
_quickSort(items, p, q - 1)
_quickSort(items, q + 1, r)
}
private[this] def _partition(items: Array[Int], p: Int, r: Int): Int = {
val pivot = items(r)
var i = p
for (j <- Range(p, r)) {
if (items(j) < pivot) {
val temp = items(i)
items(i) = items(j)
items(j) = temp
i += 1
}
}
val temp = items(i)
items(i) = items(r)
items(r) = temp
i
}
}

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@ -1,20 +1,50 @@
package ch15_bsearch
object BSearch {
def search(nums: Array[Int], target: Int): Int = {
var low = 0
var high = nums.length - 1
while(low <= high){
val mid = low + ((high - low) >> 2)
if(nums(mid) > target){
high = mid - 1
} else if (nums(mid) < target){
low = mid + 1
} else {
return mid
}
}
import scala.math.abs
return -1
object BSearch {
def search(items: Array[Int], target: Int): Int = {
var low = 0
var high = items.length - 1
while (low <= high) {
val mid = low + (high - low) / 2
if (items(mid) == target) {
return mid
} else if (items(mid) > target) {
high = mid - 1
} else {
low = mid + 1
}
}
-1
}
def sqrt(x: Double, precision: Double): Double = {
require(precision > 0, "precision must > 0")
require(x > 0, "input value for sqrt must > 0")
var low = 0.0
var high = x
val actualPrecision = precision / 10
if (x > 0 && x < 1) {
low = x
high = 1
}
while (high - low > actualPrecision) {
val mid = low + (high - low) / 2
if (abs(mid * mid - x) < actualPrecision) {
//find it
return mid
} else if (mid * mid > x) {
high = mid
} else {
low = mid
}
}
throw new IllegalStateException("could not determine the sqrt value for " + x)
}
}

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@ -1,22 +1,23 @@
package ch15_bsearch
object BSearchRecursive {
def search(nums: Array[Int], target: Int): Int = {
return searchInternal(nums, target, 0, nums.length - 1)
def search(items: Array[Int], target: Int): Int = {
_search(items, target, 0, items.length - 1)
}
private[this] def _search(items: Array[Int], target: Int, low: Int, high: Int): Int = {
if (low > high) {
return -1
}
def searchInternal(nums:Array[Int], target: Int, low: Int, high: Int): Int = {
if(low <= high){
val mid = low + ((high - low) >> 2)
if(nums(mid) > target){
searchInternal(nums, target, low, mid - 1)
} else if (nums(mid) < target){
searchInternal(nums, target, mid + 1, high)
} else {
return mid
}
}else{
return -1
}
val mid = low + (high - low) / 2
if (items(mid) == target) {
mid
} else if (items(mid) > target) {
_search(items, target, low, mid - 1)
} else {
_search(items, target, mid + 1, high)
}
}
}

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@ -0,0 +1,87 @@
package ch16_bsearch
object BSearch {
//find the first index of given value
//-1 if not found
def findFirstValue(items: Array[Int], target: Int): Int = {
require(items.length > 0, "given array is empty")
var low = 0
var high = items.length - 1
while (low <= high) {
val mid = low + (high - low) / 2
if (items(mid) > target) {
high = mid - 1
} else if (items(mid) < target) {
low = mid + 1
} else {
//find the value in the array
if (mid == 0 || items(mid - 1) != target) {
return mid
} else {
high = mid - 1
}
}
}
-1
}
def findLastValue(items: Array[Int], target: Int): Int = {
var low = 0
var high = items.length - 1
while (low <= high) {
val mid = low + (high - low) / 2
if (items(mid) > target) {
high = mid - 1
} else if (items(mid) < target) {
low = mid + 1
} else {
//find the target value
if (mid == items.length - 1 || items(mid + 1) != target) {
return mid
} else {
low = mid + 1
}
}
}
-1
}
def findFirstGreaterThan(items: Array[Int], target: Int): Int = {
var low = 0
var high = items.length
while (low <= high) {
val mid = low + (high - low) / 2
if (items(mid) >= target) {
//find the range
if (mid == 0 || items(mid - 1) < target) {
return mid
} else {
high = mid - 1
}
} else {
low = mid + 1
}
}
-1
}
def findLastSmallerThan(items: Array[Int], target: Int): Int = {
var low = 0
var high = items.length - 1
while (low <= high) {
var mid = low + (high - low) / 2
if (items(mid) <= target) {
//find the range
if (mid == items.length - 1 || items(mid + 1) > target) {
return mid
} else {
low = mid + 1
}
} else {
high = mid - 1
}
}
-1
}
}

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@ -0,0 +1,99 @@
package ch17_skip_list
import scala.util.Random
class Node(var data: Int, var forwards: Array[Node], var maxLevel: Int)
class SkipList(var head: Node, var skipListLevel: Int) {
def this() = this(new Node(-1, new Array[Node](16), 0), 1)
val MAX_LEVEL = 16
val random = new Random()
def find(value: Int): Option[Node] = {
var p = head
for (i <- skipListLevel - 1 to 0 by -1) {
while (p.forwards(i) != null && p.forwards(i).data < value) {
p = p.forwards(i)
}
}
if (p.forwards(0) != null && p.forwards(0).data == value) {
Some(p.forwards(0))
} else {
None
}
}
def insert(value: Int): Unit = {
//init the new node
val level = randomLevel()
val newNode = new Node(value, new Array[Node](level), level)
//use updtes array to record all nodes in all level before the inserted node
val updates: Array[Node] = new Array[Node](level)
var p = head
for (i <- level - 1 to 0 by -1) {
while (p.forwards(i) != null && p.forwards(i).data < value) {
p = p.forwards(i)
}
updates(i) = p
}
for (i <- Range(0, level)) {
newNode.forwards(i) = updates(i).forwards(i)
updates(i).forwards(i) = newNode
}
if (level > skipListLevel) {
skipListLevel = level
}
}
def delete(value: Int): Unit = {
var p = head
val updates: Array[Node] = new Array[Node](skipListLevel)
//try to locate the given node with the value
for (i <- skipListLevel - 1 to 0 by -1) {
while (p.forwards(i) != null && p.forwards(i).data < value) {
p = p.forwards(i)
}
updates(i) = p
}
if (p.forwards(0) != null && p.forwards(0).data == value) {
//find the value node, start to delete the node from the skip list
for (i <- skipListLevel - 1 to 0 by -1) {
if (updates(i).forwards(i) != null && updates(i).forwards(i).data == value) {
updates(i).forwards(i) = updates(i).forwards(i).forwards(i)
}
}
}
}
def randomLevel(): Int = {
var level = 1
for (i <- Range(1, MAX_LEVEL)) {
if (random.nextInt() % 2 == 1) {
level += 1
}
}
level
}
def mkString(): String = {
val builder = new StringBuilder
var p = head
while (p.forwards(0) != null) {
p = p.forwards(0)
builder.append(p.data)
}
builder.mkString
}
}

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@ -0,0 +1,149 @@
package ch20_linked_hash_map
class Node[K, V](var key: Option[K], var data: Option[V], var prev: Option[Node[K, V]], var next: Option[Node[K, V]],
var hNext: Option[Node[K, V]]) {
def this(key: Option[K], data: Option[V]) = this(key, data, None, None, None)
}
/**
* LRU cache - https://leetcode.com/problems/lru-cache/ see unit test from LRUCacheTest
*
* @author email2liyang@gmail.com
*/
class LRUCache[K, V](var head: Node[K, V], var tail: Node[K, V], var table: Array[Node[K, V]],
capacity: Int = 1000, var elementCount: Int = 0) {
head.next = Some(tail)
tail.prev = Some(head)
def this(capacity: Int) = this(new Node(None, None), new Node(None, None), new Array[Node[K, V]](capacity), capacity)
def get(key: K): Option[V] = {
val index = indexFor(key.hashCode())
var hNode = table(index)
if (hNode == null) {
None
} else {
while (!hNode.key.get.equals(key) && hNode.hNext.isDefined) {
hNode = hNode.hNext.get
}
if (hNode.key.get.equals(key)) {
//move this to the end of the linked list
moveHNodeToTail(hNode)
hNode.data
} else {
None
}
}
}
//put data into the linked hash map
//1: check if the data exist in the linked list
//2: if it's not exist , append it in the linked list
//3: if it's exist in the list, move it to the tail of the linked list
//4: return old value if it's exist
def put(key: K, value: V): Option[V] = {
if (elementCount == capacity) {
deleteLRUElement()
}
val node = new Node(Some(key), Some(value))
val index = indexFor(key.hashCode())
var hNode = table(index)
var result: Option[V] = None
if (hNode == null) {
//if it's not exist , append it in the linked list
node.prev = tail.prev
node.next = Some(tail)
tail.prev.get.next = Some(node)
tail.prev = Some(node)
table(index) = node
elementCount += 1
} else {
//we find a key conflict in the hash table
//start to loop the hNode to match the key
while (!hNode.key.get.equals(key) && hNode.hNext.isDefined) {
hNode = hNode.hNext.get
}
if (hNode.key.get.equals(key)) {
//find the old data from the hash table
result = hNode.data
hNode.data = Some(value)
//move the node to the tail of the linked list
moveHNodeToTail(hNode)
//hNext pointer stay untouched
} else {
//could not find the old data
//put the new node into the tail of the linked list
node.prev = tail.prev
node.next = Some(tail)
tail.prev.get.next = Some(node)
tail.prev = Some(node)
//put it the tail of the hash table's list
//iterator to the end of hNode
while (hNode.hNext.isDefined) {
hNode = hNode.hNext.get
}
hNode.hNext = Some(node)
elementCount += 1
}
}
result
}
private[this] def moveHNodeToTail(hNode: Node[K, V]) = {
hNode.prev.get.next = hNode.next
hNode.next.get.prev = hNode.prev
hNode.prev = tail.prev
hNode.next = Some(tail)
tail.prev.get.next = Some(hNode)
tail.prev = Some(hNode)
}
private[this] def deleteLRUElement(): Unit = {
//cache is full, start to delete element from the head
val node = head.next.get
//delete it from head
node.next.get.prev = Some(head)
head.next = node.next
//deal with hNext in the table
val index = indexFor(node.key.get.hashCode())
var hNode = table(index)
//deal with first element in the hash table
if (hNode.key.get.equals(node.key.get)) {
hNode.hNext match {
case Some(n) => table(index) = n
case None => table(index) = null
}
} else {
//deal with not first element in the hash table
var hNodePrev = hNode
hNode = hNode.next.get
while (!hNode.key.get.equals(node.key.get)) {
hNode = hNode.next.get
hNodePrev = hNodePrev.next.get
}
//now hNodePrev is the previous hNode in the hashtable
//remove the hNode
hNodePrev.next = hNode.next
hNode.next match {
case Some(n) => n.prev = Some(hNodePrev)
case None =>
}
}
elementCount -= 1
}
private[this] def indexFor(hash: Int): Int = {
hash % table.length
}
}

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@ -0,0 +1,64 @@
package ch11_sorts
import ch12_sorts.{MergeSort, QuickSort}
import org.scalatest.{FlatSpec, Matchers}
import scala.util.Random
class SortsTest extends FlatSpec with Matchers {
behavior of "SortsTest in ch11"
it should "bubbleSort int arrays" in {
var array = Array(4, 5, 6, 3, 2, 1)
array = Sorts.bubbleSort(array)
array.mkString("") should equal("123456")
array = Array(4)
array = Sorts.bubbleSort(array)
array.mkString("") should equal("4")
}
it should "insertSort int arrays" in {
var array = Array(4, 5, 6, 1, 3, 2)
array = Sorts.insertSort(array)
array.mkString("") should equal("123456")
array = Array(4)
array = Sorts.insertSort(array)
array.mkString("") should equal("4")
}
it should "selectionSort int arrays" in {
var array = Array(4, 5, 6, 1, 3, 2)
array = Sorts.insertSort(array)
array.mkString("") should equal("123456")
array = Array(4)
array = Sorts.insertSort(array)
array.mkString("") should equal("4")
}
it should "compare the sort algo" in {
val length = 50000
val array = new Array[Int](length)
val rnd = new Random()
for (i <- Range(0, length)) {
array(i) = rnd.nextInt()
}
timed("bubbleSort", Sorts.bubbleSort, array.clone())
timed("insertSort", Sorts.insertSort, array.clone())
timed("selectionSort", Sorts.selectionSort, array.clone())
timed("mergeSort", MergeSort.mergeSort, array.clone())
timed("quickSort", QuickSort.quickSort, array.clone())
}
def reportElapsed(name: String, time: Long): Unit = println(name + " takes in " + time + "ms")
def timed(name: String, f: (Array[Int]) => Unit, array: Array[Int]): Unit = {
val start = System.currentTimeMillis()
try f(array) finally reportElapsed(name, System.currentTimeMillis - start)
}
}

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package ch12_sorts
import org.scalatest.{FlatSpec, Matchers}
class MergeSortTest extends FlatSpec with Matchers {
behavior of "SortsTest in ch12"
it should "mergeSort int arrays" in {
var array = Array(4, 5, 6, 3, 2, 1)
array = MergeSort.mergeSort(array)
array.mkString("") should equal("123456")
array = Array(4)
array = MergeSort.mergeSort(array)
array.mkString("") should equal("4")
array = Array(4, 2)
array = MergeSort.mergeSort(array)
array.mkString("") should equal("24")
}
}

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package ch12_sorts
import org.scalatest.{FlatSpec, Matchers}
class QuickSortTest extends FlatSpec with Matchers {
behavior of "QuickSortTest"
it should "quickSort" in {
var array = Array(4, 5, 6, 3, 2, 1)
array = QuickSort.quickSort(array)
array.mkString("") should equal("123456")
array = Array(4)
array = QuickSort.quickSort(array)
array.mkString("") should equal("4")
array = Array(4, 2)
array = QuickSort.quickSort(array)
array.mkString("") should equal("24")
}
it should "find the Kth element in the array" in {
val array = Array(4, 2, 5, 12, 3)
QuickSort.findKthElement(array, 3) should equal(4)
QuickSort.findKthElement(array, 5) should equal(12)
QuickSort.findKthElement(array, 1) should equal(2)
}
}

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package ch15_bsearch
import ch12_sorts.QuickSort
import org.scalatest.{FlatSpec, Matchers}
import scala.util.Random
class BSearchRecursiveTest extends FlatSpec with Matchers {
behavior of "BSearchRecursiveTest"
it should "search with exist value" in {
val length = 50000
val array = new Array[Int](length)
val rnd = new Random()
for (i <- Range(0, length)) {
array(i) = rnd.nextInt()
}
val target = array(2698)
BSearchRecursive.search(QuickSort.quickSort(array), target) should be > -1
}
}

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package ch15_bsearch
import ch12_sorts.QuickSort
import org.scalatest.{FlatSpec, Matchers}
import scala.util.Random
class BSearchTest extends FlatSpec with Matchers {
behavior of "BSearchTest"
it should "search with exist value" in {
val length = 50000
val array = new Array[Int](length)
val rnd = new Random()
for (i <- Range(0, length)) {
array(i) = rnd.nextInt()
}
val target = array(2698)
BSearch.search(QuickSort.quickSort(array), target) should be > -1
}
it should "calculate sqrt value -1 " in {
val x = 4
val precision = 0.000001
BSearch.sqrt(x, precision) should equal(2.0)
}
it should "calculate sqrt value -2 " in {
val x = 0.04
val precision = 0.000001
BSearch.sqrt(x, precision) should equal(0.2 +- precision)
}
}

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package ch16_bsearch
import org.scalatest.{FlatSpec, Matchers}
class BSearchTest extends FlatSpec with Matchers {
behavior of "BSearchTest"
it should "findFirstValue" in {
val items = Array(1, 3, 4, 5, 6, 8, 8, 8, 11, 18)
BSearch.findFirstValue(items, 8) should equal(5)
}
it should "findLastValue" in {
val items = Array(1, 3, 4, 5, 6, 8, 8, 8, 11, 18)
BSearch.findLastValue(items, 8) should equal(7)
}
it should "findFirstGreaterThan" in {
val items = Array(1, 3, 4, 5, 6, 8, 8, 8, 11, 18)
BSearch.findFirstGreaterThan(items, 2) should equal(1)
BSearch.findFirstGreaterThan(items, 8) should equal(5)
}
it should "findLastSmallerThan" in {
val items = Array(1, 3, 4, 5, 6, 8, 8, 8, 11, 18)
BSearch.findLastSmallerThan(items, 2) should equal(0)
BSearch.findLastSmallerThan(items, 8) should equal(7)
}
}

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package ch17_skip_list
import org.scalatest.{FlatSpec, Matchers}
import scala.util.Random
class SkipListTest extends FlatSpec with Matchers {
behavior of "SkipListTest"
it should "insert skip list" in {
val list = new SkipList()
for (i <- Range(0, 10)) {
list.insert(i)
}
list.mkString() should equal("0123456789")
}
it should "delete skip list" in {
val list = new SkipList()
for (i <- Range(0, 10)) {
list.insert(i)
}
list.delete(5)
list.mkString() should equal("012346789")
}
it should "find value in skip list" in {
val list = new SkipList()
val length = 5000
val array = new Array[Int](length)
val rnd = new Random()
for (i <- Range(0, length)) {
array(i) = rnd.nextInt(length)
list.insert(array(i))
}
assert(list.find(array(rnd.nextInt(length - 1))).isDefined)
assert(list.find(array(rnd.nextInt(length - 1)) + length + 1).isEmpty)
}
}

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package ch20_linked_hash_map
import org.scalatest.{FlatSpec, Matchers}
class LRUCacheTest extends FlatSpec with Matchers {
behavior of "LRUCacheTest"
it should "put data and get back" in {
val cache = new LRUCache[Int, Int](2)
cache.put(1, 1)
cache.put(2, 2)
cache.get(1) should equal(Some(1)) // returns 1
cache.put(3, 3) // evicts key 2
cache.get(2) should equal(None) //should not find
cache.put(4, 4) // evicts key 1
cache.get(1) should equal(None) //should not find
cache.get(3) should equal(Some(3)) // returns 3
cache.get(4) should equal(Some(4)) // returns 4
}
}