LIKE CODING: MJ [49] Upsampling

LIKE CODING: MJ [49] Upsampling
you have an img data as an array, output the data for upsampling. For example, 
[1, 2, 3, 4, 5, 6] as width 3(2 rows) ==> upsample 2 times would be [1 1 2 2 3 3 1 1 2 2 3 3 4 4 5 5 6 6 4 4 5 5 6 6]

vector<int> unsampling(vector<int> &vec, int width, int times){

    int rows = (int)vec.size()/width;

 

    int m = rows*times, n = width*times;

    int index = 0;

    vector<int> ret(m*n);

    while(index<m*n){

        int i = index/n, j = index%n;

        ret[index++] = vec[i/times*width+(j/times)%width];

    }

    PrintVector(ret, "ret");

    return ret;

}

 

int main(){

    vector<int> vec = {1,2,3,4,5,6};

    unsampling(vec, 3, 2);

    return 0;

}

http://www.mitbbs.com/article_t/JobHunting/33110511.html
int cols = width * times;
int rows = input.size()/width + (input.size() % width == 0 ) ? 0 : 1;

vector<vector<int>>  ret(rows, vector<int>(cols, 0));
for (int i=0; i < rows; ++i) {
     for (int j=0; j < cols; ++j) {
         ret[i][j] = input[i*width+j/times];
     }
}

// do some boundary handling here
少两个loop，清晰点：）

一个for loop就可以啦
def upsampling(arr, width, times):
    new_width = width*times
    new_height = len(arr)/width*times
    ans = [None]*new_width*new_height

    for i in xrange(len(ans)):
        row, col = i/new_width/times, i%new_width/times
        ori_index = row*width + col
        ans[i] = arr[ori_index]
            
    return ans
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