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Posts tagged as “medium”

花花酱 LeetCode 855. Exam Room

Problem

In an exam room, there are N seats in a single row, numbered 0, 1, 2, ..., N-1.

When a student enters the room, they must sit in the seat that maximizes the distance to the closest person.  If there are multiple such seats, they sit in the seat with the lowest number.  (Also, if no one is in the room, then the student sits at seat number 0.)

Return a class ExamRoom(int N) that exposes two functions: ExamRoom.seat() returning an int representing what seat the student sat in, and ExamRoom.leave(int p) representing that the student in seat number p now leaves the room.  It is guaranteed that any calls to ExamRoom.leave(p) have a student sitting in seat p.

Example 1:

Input: ["ExamRoom","seat","seat","seat","seat","leave","seat"], [[10],[],[],[],[],[4],[]]
Output: [null,0,9,4,2,null,5]
Explanation:
ExamRoom(10) -> null
seat() -> 0, no one is in the room, then the student sits at seat number 0.
seat() -> 9, the student sits at the last seat number 9.
seat() -> 4, the student sits at the last seat number 4.
seat() -> 2, the student sits at the last seat number 2.
leave(4) -> null
seat() -> 5, the student​​​​​​​ sits at the last seat number 5.

​​​​Note:

  1. 1 <= N <= 10^9
  2. ExamRoom.seat() and ExamRoom.leave() will be called at most 10^4 times across all test cases.
  3. Calls to ExamRoom.leave(p) are guaranteed to have a student currently sitting in seat number p.

Solution: BST

Use a BST (ordered set) to track the current seatings.

Time Complexity:

init: O(1)

seat: O(P)

leave: O(logP)

Space complexity: O(P)

 

花花酱 LeetCode 882. Random Point in Non-overlapping Rectangles

Problem

Given a list of non-overlapping axis-aligned rectangles rects, write a function pick which randomly and uniformily picks an integer point in the space covered by the rectangles.

Note:

  1. An integer point is a point that has integer coordinates.
  2. A point on the perimeter of a rectangle is included in the space covered by the rectangles.
  3. ith rectangle = rects[i] = [x1,y1,x2,y2], where [x1, y1] are the integer coordinates of the bottom-left corner, and [x2, y2] are the integer coordinates of the top-right corner.
  4. length and width of each rectangle does not exceed 2000.
  5. 1 <= rects.length <= 100
  6. pick return a point as an array of integer coordinates [p_x, p_y]
  7. pick is called at most 10000 times.

Example 1:

Input: 
["Solution","pick","pick","pick"]
[[[[1,1,5,5]]],[],[],[]]
Output: 
[null,[4,1],[4,1],[3,3]]

Example 2:

Input: 
["Solution","pick","pick","pick","pick","pick"]
[[[[-2,-2,-1,-1],[1,0,3,0]]],[],[],[],[],[]]
Output: 
[null,[-1,-2],[2,0],[-2,-1],[3,0],[-2,-2]]

Explanation of Input Syntax:

The input is two lists: the subroutines called and their arguments. Solution‘s constructor has one argument, the array of rectangles rectspick has no arguments. Arguments are always wrapped with a list, even if there aren’t any.

Solution: Binary Search

Same as LeetCode 880. Random Pick with Weight

Use area of the rectangles as weights.

Time complexity: Init: O(n) Pick: O(logn)

Space complexity: O(n)

Related Problems

花花酱 LeetCode 880. Random Pick with Weight

Problem

Given an array w of positive integers, where w[i] describes the weight of index i, write a function pickIndex which randomly picks an index in proportion to its weight.

Note:

  1. 1 <= w.length <= 10000
  2. 1 <= w[i] <= 10^5
  3. pickIndex will be called at most 10000 times.

Example 1:

Input: 
["Solution","pickIndex"]
[[[1]],[]]
Output: [null,0]

Example 2:

Input: 
["Solution","pickIndex","pickIndex","pickIndex","pickIndex","pickIndex"]
[[[1,3]],[],[],[],[],[]]
Output: [null,0,1,1,1,0]

Explanation of Input Syntax:

The input is two lists: the subroutines called and their arguments. Solution‘s constructor has one argument, the array wpickIndex has no arguments. Arguments are always wrapped with a list, even if there aren’t any.

Solution: Binary Search

  1. Convert PDF to CDF
  2. Uniformly sample a value s in [1, sum(weights)].
  3. Use binary search to find first index such that PDF[index] >= s.

Time complexity: Init O(n), query O(logn)

Space complexity: O(n)

C++

Related Problems

花花酱 LeetCode 883. Generate Random Point in a Circle

Problem

Given the radius and x-y positions of the center of a circle, write a function randPoint which generates a uniform random point in the circle.

Note:

  1. input and output values are in floating-point.
  2. radius and x-y position of the center of the circle is passed into the class constructor.
  3. a point on the circumference of the circle is considered to be in the circle.
  4. randPoint returns a size 2 array containing x-position and y-position of the random point, in that order.

Example 1:

Input: 
["Solution","randPoint","randPoint","randPoint"]
[[1,0,0],[],[],[]]
Output: [null,[-0.72939,-0.65505],[-0.78502,-0.28626],[-0.83119,-0.19803]]

Example 2:

Input: 
["Solution","randPoint","randPoint","randPoint"]
[[10,5,-7.5],[],[],[]]
Output: [null,[11.52438,-8.33273],[2.46992,-16.21705],[11.13430,-12.42337]]

Explanation of Input Syntax:

The input is two lists: the subroutines called and their arguments. Solution‘s constructor has three arguments, the radius, x-position of the center, and y-position of the center of the circle. randPoint has no arguments. Arguments are always wrapped with a list, even if there aren’t any.

 

Solution: Polar Coordinate

uniform sample an angle a: [0, 2*Pi)

uniform sample a radius r: [0, 1)

Number of random points in a cycle should be proportional to the square of distance to the center.

e.g. there are 4 times of points with distance d than points with distance d/2.

Thus sqrt(r) is uniformly distributed.

r’ = sqrt(r),

C++

花花酱 LeetCode 148. Sort List

Problem

Sort a linked list in O(n log n) time using constant space complexity.

Example 1:

Input: 4->2->1->3
Output: 1->2->3->4

Example 2:

Input: -1->5->3->4->0
Output: -1->0->3->4->5

Solution: Merge Sort

Top-down (recursion)

Time complexity: O(nlogn)

Space complexity: O(logn)

C++

Java

Python3

 

bottom up

Time complexity: O(nlogn)

Space complexity: O(1)