# Missing Number
# Given n and a list nums of all numbers 1, 2, ..., n omitting one number, find the missing number.
# https://cses.fi/problemset/task/1083
def find_missing_number(n, nums):
pass
find_missing_number(5, [2, 3, 1, 5]) # Correct answer: 4
解决这个问题,最自然想到的办法是用循环一个一个找出。但时间复杂度是O(n^2):
def find_missing_number(n, nums):
for i in range(1,n+1):
if i not in nums:
return i
find_missing_number(5, [2, 3, 1, 5]) # Correct answer: 4
优化版本:时间复杂度O(n)
def find_missing_number(n, nums):
return (1+n)*n/2 - sum(nums)
find_missing_number(5, [2, 3, 1, 5]) # Correct answer: 4
# Trailing Zeros
# Given n, find the number of trailing zeros in the factorial n!
# https://cses.fi/problemset/task/1618
def find_trailing_zeros(n):
pass
find_trailing_zeros(10) # Correct answer: 2
解决方法:一个数的阶乘(例如 n!
)末尾零的数量是由该数分解中包含的 2 和 5 的对数决定的。由于因子 2 比因子 5 更常见,所以末尾零的数量实际上是由因子 5 的数量决定的。为了找到一个数的阶乘中因子 5 的数量,我们可以不断地将该数除以 5,并将这些商相加,直到商为零。
def find_trailing_zeros(n):
count = 0
while n >= 5:
n //= 5
count += n
return count
find_trailing_zeros(10) # Correct answer: 2
# Maximum Subarray Sum
# Given an array, find the maximum sum of values in a contiguous, nonempty subarray
# https://cses.fi/problemset/task/1643
def max_subarray_sum(array):
pass
max_subarray_sum([-1, 3, -2, 5, 3, -5, 2, 2]) # Correct answer: 9
最自然的解决方法是循环:但时间复杂度为O(n^2)
def max_subarray_sum(array):
max = array[0]
for i in range(len(array)):
for j in range(i, len(array)):
temp = sum(array[i:j+1])
if temp > max:
max = temp
return max
max_subarray_sum([-1, 3, -2, 5, 3, -5, 2, 2]) # Correct answer: 9
优化:用动态规划,时间复杂度O(n)
def max_subarray_sum(array):
max_so_far = array[0]
max_ending_here = 0
max_element = array[0]
for i in range(len(array)):
max_ending_here = max(array[i], max_ending_here+array[i])
max_so_far = max(max_so_far, max_ending_here)
if max_ending_here < 0:
max_ending_here = 0
if array[i] > max_element:
max_element = array[i]
return max_so_far if max_so_far > 0 else max_element
max_subarray_sum([-1, 3, -2, 5, 3, -5, 2, 2]) # Correct answer: 9
# Sum of Two Values
# Given an array of integers, return positions of two values (at distinct positions) summing to x.
# If there are no solutions, print IMPOSSIBLE.
# https://cses.fi/problemset/task/1640. Also known as "Two Sum" in LeetCode.
def sum_of_two_values(x, array):
pass
sum_of_two_values(8, [2, 7, 5, 1]) # Correct answer: [1, 3]
自然的想法是两层循环,但时间复杂度为O(n^2)
def sum_of_two_values(x, array):
for i in range(len(array)):
for j in range(i+1, len(array)):
if x == array[i] + array[j]:
return[i, j]
print('IMPOSSIBLE')
sum_of_two_values(8, [2, 7, 5, 1]) # Correct answer: [1, 3]
优化:用哈希表,时间复杂度为O(n), 但空间复杂度从O(1)变成O(n)
def sum_of_two_values(x, array):
seen = {}
for i, number in enumerate(array):
complement = x - number
if complement in seen:
return [seen[complement], i]
seen[number] = i
print('IMPOSSIBLE')
sum_of_two_values(8, [2, 7, 5, 1]) # Correct answer: [1, 3]
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