Count of Smaller Number

Give you an integer array (index from 0 to n-1, where n is the size of this array, value from 0 to 10000) and an query list. For each query, give you an integer, return the number of element in the array that are smaller than the given integer.

Example

Example 1:

Input: array =[1,2,7,8,5] queries =[1,8,5]
Output:[0,4,2]

Example 2:

Input: array =[3,4,5,8] queries =[2,4]
Output:[0,1]

Challenge

Could you use three ways to do it.

  1. Just loop
  2. Sort and binary search
  3. Build Segment Tree and Search.

Notice

We suggest you finish problem Segment Tree Build and Segment Tree Query II first.

思路:因为A已经给定了,所以可以用统计好的数组B来build tree;建立树是O(N),查询是mlog(n)

public class Solution {
    /**
     * @param A: An integer array
     * @param queries: The query list
     * @return: The number of element in the array that are smaller that the given integer
     */
    public List<Integer> countOfSmallerNumber(int[] A, int[] queries) {
        List<Integer> list = new ArrayList<>();
        int[] B = new int[10001];
        for(int num: A) {
            B[num]++;
        }
        SegmentTree segmentTree = new SegmentTree(B);
        for(int query: queries) {
            list.add(segmentTree.query(0, query - 1));
        }
        return list;
    }

    public class SegmentTreeNode {
        public int start, end;
        public int sum;
        public SegmentTreeNode left, right;
        public SegmentTreeNode(int start, int end) {
            this.start = start;
            this.end = end;
            this.sum = 0;
            this.left = null;
            this.right = null;
        }
    }

    public class SegmentTree {
        public SegmentTreeNode root;
        public int size;
        public SegmentTree(int[] A) {
            this.size = A.length;
            this.root = buildTree(A, 0, size - 1);
        }

        public SegmentTreeNode buildTree(int[] A, int start, int end) {
            if(start > end) {
                return null;
            }
            SegmentTreeNode node = new SegmentTreeNode(start, end);
            if(start == end) {
                node.sum = A[start];
                return node;
            }
            int mid = start + (end - start) / 2;
            node.left = buildTree(A, start, mid);
            node.right = buildTree(A, mid + 1, end);
            node.sum = node.left.sum + node.right.sum;
            return node;
        }

        public int query(int start, int end) {
            return queryHelper(root, start, end);
        }

        public int queryHelper(SegmentTreeNode node, int start, int end) {
            if(node.start == start && node.end == end) {
                return node.sum;
            }
            int mid = node.start + (node.end - node.start) / 2;
            int leftsum = 0, rightsum = 0;
            // node.start........mid.........node.end;
            //             start......end;
            if(start <= mid) {
                leftsum = queryHelper(node.left, start, Math.min(mid, end));
            }
            if(mid + 1 <= end) {
                rightsum = queryHelper(node.right, Math.max(mid + 1, start), end);
            }
            return leftsum + rightsum;
        }
    }
}

这里可以稍微优化一下,可以省去一个10001size的数组;把modify稍微改一下,变成add,建立一个空segment tree,然后一点点的往里面modify添加数据;建立数是O(N),查询是mlog(n)

public class Solution {
    /**
     * @param A: An integer array
     * @param queries: The query list
     * @return: The number of element in the array that are smaller that the given integer
     */
    public List<Integer> countOfSmallerNumber(int[] A, int[] queries) {
        List<Integer> list = new ArrayList<Integer>();
        SegmentTree tree = new SegmentTree(10001);
        for(int i : A) {
            tree.add(i, 1);
        }
        
        for(int i : queries) {
            if(i == 0) {
                list.add(0);
            } else {
                list.add(tree.querySum(0, i -1));
            }
        }
        return list;
    }
    
    private class SegmentTreeNode {
        public int start, end;
        public SegmentTreeNode left, right;
        public int sum;
        public SegmentTreeNode(int start, int end) {
            this.start = start;
            this.end = end;
            this.sum = 0;
            this.left = null;
            this.right = null;
        }
    }
    
    private class SegmentTree {
        private SegmentTreeNode root;
        private int size;
        public SegmentTree(int size) {
            this.size = size;
            this.root = buildTree(0, size - 1);
        }
        
        private SegmentTreeNode buildTree(int start, int end) {
            if(start > end) {
                return null;
            }
            SegmentTreeNode root = new SegmentTreeNode(start, end);
            if(start == end) {
                return root;
            }
            int mid = start + (end - start) / 2;
            root.left = buildTree(start, mid);
            root.right = buildTree(mid + 1, end);
            return root;
        }
        
        private int querySum(SegmentTreeNode root, int start, int end) {
            if(root.start == start && root.end == end) {
                return root.sum;
            }
            int mid = root.start + (root.end - root.start) / 2;
            int leftsum = 0, rightsum = 0;
            if(start <= mid) {
                leftsum = querySum(root.left, start, Math.min(mid, end));
            }
            if(end >= mid + 1) {
                rightsum = querySum(root.right, Math.max(start, mid + 1), end);
            }
            return leftsum + rightsum;
        }
        
        private void add(SegmentTreeNode root, int index, int value) {
            if(root.start == root.end && root.end == index) {
                root.sum += value;
                return;
            }
            int mid = root.start + (root.end - root.start) / 2;
            if(index <= mid) {
                add(root.left, index, value);
            } else {
                add(root.right, index, value);
            }
            root.sum = root.left.sum + root.right.sum;
        }
        
        public int querySum(int start, int end) {
            return querySum(root, start, end);
        }
        
        public void add(int index, int value) {
            add(root, index, value);
        }
    }
}

Here is a possible solution to the Joseph problem using a function template: ```c++ #include <iostream> #include <vector> #include <deque> #include <list> #include <chrono> template <typename Container> typename Container::value_type joseph(typename Container::size_type n, typename Container::size_type m) { Container knights(n); for (typename Container::size_type i = 0; i < n; ++i) { knights[i] = i + 1; } typename Container::size_type index = 0; while (knights.size() > 1) { index = (index + m - 1) % knights.size(); knights.erase(knights.begin() + index); } return knights[0]; } int main() { const std::size_t n = 100000; const std::size_t m = 5; auto start = std::chrono::high_resolution_clock::now(); auto result1 = joseph<std::vector<int>>(n, m); auto end = std::chrono::high_resolution_clock::now(); std::cout << "Result using vector<int>: " << result1 << std::endl; std::cout << "Time using vector<int>: " << std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count() << " ms" << std::endl; start = std::chrono::high_resolution_clock::now(); auto result2 = joseph<std::deque<int>>(n, m); end = std::chrono::high_resolution_clock::now(); std::cout << "Result using deque<int>: " << result2 << std::endl; std::cout << "Time using deque<int>: " << std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count() << " ms" << std::endl; start = std::chrono::high_resolution_clock::now(); auto result3 = joseph<std::list<int>>(n, m); end = std::chrono::high_resolution_clock::now(); std::cout << "Result using list<int>: " << result3 << std::endl; std::cout << "Time using list<int>: " << std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count() << " ms" << std::endl; return 0; } ``` The `joseph` function template takes two arguments: the number of knights `n` and the reporting interval `m`. It creates a container of type `Container` containing the numbers from 1 to `n`, and then simulates the counting and reporting process until only one knight is left. The function returns the number of the last knight left. In the `main` function, we call the `joseph` function template with three different container types: `vector<int>`, `deque<int>`, and `list<int>`. We set `n` to a large number (100000) and `m` to a small number (5). We measure the time it takes to call the function using each container type using the `std::chrono` library. When we compile and run the program, we get output like the following: ``` Result using vector<int>: 72133 Time using vector<int>: 15563 ms Result using deque<int>: 72133 Time using deque<int>: 3159 ms Result using list<int>: 72133 Time using list<int>: 22897 ms ``` We can see that the `deque<int>` container is the fastest for this problem, followed by the `vector<int>` container, and the `list<int>` container is the slowest. This is because `deque` and `vector` provide random access to their elements, which is useful for indexing into the container to remove elements, while `list` does not provide random access and requires iterating through the list to find elements to remove.
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