这是一个问题: codility.com/programmers/task/number_solitaire
以下链接是我的结果(50%来自Codility): https://codility.com/demo/results/training8AMJZH-RTA/
我的代码(首先,我试图使用Kadane的Algo解决这个问题):
class Solution {
public int solution(int[] A) {
int temp_max = Integer.MIN_VALUE;
int max = 0;
int k = 1;
if(A.length == 2) return A[0] + A[A.length-1];
for(int i = 1; i < A.length-1; i++) {
if(temp_max < A[i]) temp_max = A[i];
if(A[i] > 0) {
max += A[i];
temp_max = Integer.MIN_VALUE;
k = 0;
} else if(k % 6 == 0) {
max += temp_max;
temp_max = Integer.MIN_VALUE;
k = 0;
}
k++;
}
return A[0] + max + A[A.length-1];
}
以下是我在网上找到的解决方案(来自Codility结果的100%):
class Solution {
public int solution(int[] A) {
int[] store = new int[A.length];
store[0] = A[0];
for (int i = 1; i < A.length; i++) {
store[i] = store[i-1];
for (int minus = 2; minus <= 6; minus++) {
if (i >= minus) {
store[i] = Math.max(store[i], store[i - minus]);
} else {
break;
}
}
store[i] += A[i];
}
return store[A.length - 1];
}
}
我不知道我的代码有什么问题:(
我尝试了几个测试用例但是,与解决方案没有什么不同。我的代码
但是,痘痘测试结果显示我的不完全正确。 (https://codility.com/demo/results/training8AMJZH-RTA/)
请有人用我的代码解释我的问题~~
答案 0 :(得分:1)
因为您没有使用动态编程,所以您使用的是贪婪的算法。当范围内的最大数字不是正确的选择时,您的代码将失败。
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答案 1 :(得分:1)
根据发布的解决方案,我编写了不错的可读代码。性能不是最好。
public struct PersonStruct
{
public string Name { get; set; }
public int Year { get; set; }
}
答案 2 :(得分:1)
来自Java的可读解决方案:
public class Solution {
public static void main(String[] args) {
System.out.println(new Solution().solution(new int[]{1, -2, 0, 9, -1, -2}));
}
private int solution(int[] A) {
int N = A.length;
int[] dp = new int[N];
dp[0] = A[0];
for (int i = 1; i < N; i++) {
double sm = Double.NEGATIVE_INFINITY;
for (int j = 1; j <= 6; j++) {
if (i - j < 0) {
break;
}
double s1 = dp[i - j] + A[i];
sm = Double.max(s1, sm);
}
dp[i] = (int) sm;
}
return dp[N-1];
}
}
答案 3 :(得分:1)
这是一种类似于@ 0xAliHn的解决方案,但使用的内存更少。您只需要记住最近的6个动作即可。
def NumberSolitaire(A):
dp = [0] * 6
dp[-1] = A[0]
for i in range(1, len(A)):
maxVal = -100001
for k in range(1, 7):
if i-k >= 0:
maxVal = max(maxVal, dp[-k] + A[i])
dp.append(maxVal)
dp.pop(0)
return dp[-1]
答案 4 :(得分:0)
这是我的解决方案。我尝试使代码易于理解。它可能无法尽可能多地节省空间。
private static int solution(int A[])
{
// N // N is an integer within the range [2..100,000];
// A[] // each element of array A is an integer within the range [−10,000..10,000].
int N = A.length;
int[] bestResult = new int[N]; // record the current bestResult
Arrays.fill(bestResult, Integer.MIN_VALUE); // fill in with the smallest integer value
// initialize
bestResult[0] = A[0];
for (int i = 0;i < A.length;i++) {
// calculate six possible results every round
for (int j = i + 1; (j < A.length) && (i < A.length) && j < (i + 1) + 6; j++) {
// compare
int preMaxResult = bestResult[j]; // the max number so far
int nowMaxResult = bestResult[i] + A[j]; // the max number at bestResult[i] + A[j]
bestResult[j] = Math.max(preMaxResult, nowMaxResult);
}
}
return bestResult[bestResult.length-1];
}
答案 5 :(得分:0)
以下是简单的Python 3解决方案:
import sys
def solution(A):
dp = [0] * len(A)
dp[0] = A[0]
for i in range(1, len(A)):
maxVal = -sys.maxsize - 1
for k in range(1, 7):
if i-k >= 0:
maxVal = max(maxVal, dp[i-k] + A[i])
dp[i] = maxVal
return dp[len(A)-1]
答案 6 :(得分:0)
100%c ++解决方案( results)
#include <climits>
int solution(vector<int>& A) {
const int N = A.size();
if (N == 2)
return A[0] + A[1];
vector<int> MaxSum(N, INT_MIN);
MaxSum[0] = A[0];
for (int i = 1; i < N; i++) {
for (int dice = 1; dice <= 6; dice++) {
if (dice > i)
break;
MaxSum[i] = max(MaxSum[i], A[i] + MaxSum[i - dice]);
}
}
return MaxSum[N-1];
}
答案 7 :(得分:0)
100% 蟒蛇解决方案 借助上述答案和https://sapy.medium.com/cracking-the-coding-interview-30eb419c4c57
def solution(A):
# write your code in Python 3.6
# initialize maxUntil [0]*n
n = len(A)
maxUntil = [0 for i in range(n)]
maxUntil[0]=A[0]
# fill in maxUntil, remember to chack limits
for i in range(1, n): # for each
maxUntil[i] = maxUntil [i-1]
# check the max 6 to the left:
# for 1,..,6:
for dice in range(1,7):
if dice > i: # if dice bigger than loc - we are out of range
break
#else: check if bigger than cur elem, if so - update elem
maxUntil[i] = max(maxUntil[i],maxUntil[i-dice])
# add the current jump:
maxUntil[i] +=A[i]
# must reach the last sq:
return maxUntil[n-1]