标签:速度 sam 遍历数组 array range 条件 比较 shm run
Given an array of integers, return indices of the two numbers such that they add up to a specific target.
You may assume that each input would have exactly one solution, and you may not use the same element twice.
Example:
Given nums = [2, 7, 11, 15], target = 9,
Because nums[0] + nums[1] = 2 + 7 = 9,
return [0, 1].
给定一个数组nums和一个目标值target,求数组中相加等于target的两个数的下标。一个预置条件是每一个target在数据中都只有一个解,并且一个元素不能被使用两次。
比较容易直接想到的是暴力遍历法:
Java版:
class Solution {
public int[] twoSum(int[] nums, int target) {
for (int i = 0; i < nums.length; i++) {
for (int j = i + 1; j < nums.length; j++) {
if (nums[i] + nums[j] == target) {
return new int[]{i, j};
}
}
}
return new int[2];
}
}
提交后得到的结果:
Python3版:
class Solution:
def twoSum(self, nums: List[int], target: int) -> List[int]:
for i, num_a in enumerate(nums):
for j in range(i+1, len(nums)):
if num_a + nums[j] == target:
return [i, j]
return []
提交后得到的结果:
可以看到,Python相比较Java来说,运行速度确实慢很多。
上述的代码的想法就是利用i和j双重遍历数组,时间复杂度为O(n2),空间复杂度为O(1)。
为了降低时间复杂度,我们用空间换时间。定义一个map。
Java版:
class Solution {
public int[] twoSum(int[] nums, int target) {
Map<Integer, Integer> map = new HashMap<>();
for (int i = 0; i < nums.length; i++) {
int diff = target - nums[i];
if (map.containsKey(diff)) {
return new int[]{map.get(diff), i};
}
map.put(nums[i], i);
}
throw new IllegalArgumentException("No two sum solution");
}
}
提交后得到的结果:
Python3版:
class Solution:
def twoSum(self, nums: List[int], target: int) -> List[int]:
d = {}
for i, num in enumerate(nums):
diff = target - num
if diff in d:
return [d.get(diff), i]
d[num] = i
raise RuntimeError("No two sum solution")
提交后得到的结果:
可以看到用一个哈希map或者说是dict,可以大幅度节省时间,这是因为此时时间复杂变为了O(n),空间复杂度也是O(n)
标签:速度 sam 遍历数组 array range 条件 比较 shm run
原文地址:https://www.cnblogs.com/9plus/p/11421417.html